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Sample records for spatio-temporal point process

  1. Functional Principal Component Analysis of Spatio-Temporal Point Processes with Applications in Disease Surveillance

    PubMed Central

    Li, Yehua; Guan, Yongtao

    2014-01-01

    In disease surveillance applications, the disease events are modeled by spatio-temporal point processes. We propose a new class of semiparametric generalized linear mixed model for such data, where the event rate is related to some known risk factors and some unknown latent random effects. We model the latent spatio-temporal process as spatially correlated functional data, and propose Poisson maximum likelihood and composite likelihood methods based on spline approximations to estimate the mean and covariance functions of the latent process. By performing functional principal component analysis to the latent process, we can better understand the correlation structure in the point process. We also propose an empirical Bayes method to predict the latent spatial random effects, which can help highlight hot areas with unusually high event rates. Under an increasing domain and increasing knots asymptotic framework, we establish the asymptotic distribution for the parametric components in the model and the asymptotic convergence rates for the functional principal component estimators. We illustrate the methodology through a simulation study and an application to the Connecticut Tumor Registry data. PMID:25368436

  2. Modeling sediment transport as a spatio-temporal Markov process.

    NASA Astrophysics Data System (ADS)

    Heyman, Joris; Ancey, Christophe

    2014-05-01

    Despite a century of research about sediment transport by bedload occuring in rivers, its constitutive laws remain largely unknown. The proof being that our ability to predict mid-to-long term transported volumes within reasonable confidence interval is almost null. The intrinsic fluctuating nature of bedload transport may be one of the most important reasons why classical approaches fail. Microscopic probabilistic framework has the advantage of taking into account these fluctuations at the particle scale, to understand their effect on the macroscopic variables such as sediment flux. In this framework, bedload transport is seen as the random motion of particles (sand, gravel, pebbles...) over a two-dimensional surface (the river bed). The number of particles in motion, as well as their velocities, are random variables. In this talk, we show how a simple birth-death Markov model governing particle motion on a regular lattice accurately reproduces the spatio-temporal correlations observed at the macroscopic level. Entrainment, deposition and transport of particles by the turbulent fluid (air or water) are supposed to be independent and memoryless processes that modify the number of particles in motion. By means of the Poisson representation, we obtained a Fokker-Planck equation that is exactly equivalent to the master equation and thus valid for all cell sizes. The analysis shows that the number of moving particles evolves locally far from thermodynamic equilibrium. Several analytical results are presented and compared to experimental data. The index of dispersion (or variance over mean ratio) is proved to grow from unity at small scales to larger values at larger scales confirming the non Poisonnian behavior of bedload transport. Also, we study the one and two dimensional K-function, which gives the average number of moving particles located in a ball centered at a particle centroid function of the ball's radius.

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

    SciTech Connect

    Wikle, C.K.

    1996-12-31

    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. The Voxel-Wise Functional Connectome Can Be Efficiently Derived from Co-activations in a Sparse Spatio-Temporal Point-Process.

    PubMed

    Tagliazucchi, Enzo; Siniatchkin, Michael; Laufs, Helmut; Chialvo, Dante R

    2016-01-01

    Large efforts are currently under way to systematically map functional connectivity between all pairs of millimeter-scale brain regions based on large neuroimaging databases. The exploratory unraveling of this "functional connectome" based on functional Magnetic Resonance Imaging (fMRI) can benefit from a better understanding of the contributors to resting state functional connectivity. In this work, we introduce a sparse representation of fMRI data in the form of a discrete point-process encoding high-amplitude events in the blood oxygenation level-dependent (BOLD) signal and we show it contains sufficient information for the estimation of functional connectivity between all pairs of voxels. We validate this method by replicating results obtained with standard whole-brain voxel-wise linear correlation matrices in two datasets. In the first one (n = 71), we study the changes in node strength (a measure of network centrality) during deep sleep. The second is a large database (n = 1147) of subjects in which we look at the age-related reorganization of the voxel-wise network of functional connections. In both cases it is shown that the proposed method compares well with standard techniques, despite requiring only data on the order of 1% of the original BOLD signal time series. Furthermore, we establish that the point-process approach does not reduce (and in one case increases) classification accuracy compared to standard linear correlations. Our results show how large fMRI datasets can be drastically simplified to include only the timings of large-amplitude events, while still allowing the recovery of all pair-wise interactions between voxels. The practical importance of this dimensionality reduction is manifest in the increasing number of collaborative efforts aiming to study large cohorts of healthy subjects as well as patients suffering from brain disease. Our method also suggests that the electrophysiological signals underlying the dynamics of fMRI time series

  5. The Voxel-Wise Functional Connectome Can Be Efficiently Derived from Co-activations in a Sparse Spatio-Temporal Point-Process

    PubMed Central

    Tagliazucchi, Enzo; Siniatchkin, Michael; Laufs, Helmut; Chialvo, Dante R.

    2016-01-01

    Large efforts are currently under way to systematically map functional connectivity between all pairs of millimeter-scale brain regions based on large neuroimaging databases. The exploratory unraveling of this “functional connectome” based on functional Magnetic Resonance Imaging (fMRI) can benefit from a better understanding of the contributors to resting state functional connectivity. In this work, we introduce a sparse representation of fMRI data in the form of a discrete point-process encoding high-amplitude events in the blood oxygenation level-dependent (BOLD) signal and we show it contains sufficient information for the estimation of functional connectivity between all pairs of voxels. We validate this method by replicating results obtained with standard whole-brain voxel-wise linear correlation matrices in two datasets. In the first one (n = 71), we study the changes in node strength (a measure of network centrality) during deep sleep. The second is a large database (n = 1147) of subjects in which we look at the age-related reorganization of the voxel-wise network of functional connections. In both cases it is shown that the proposed method compares well with standard techniques, despite requiring only data on the order of 1% of the original BOLD signal time series. Furthermore, we establish that the point-process approach does not reduce (and in one case increases) classification accuracy compared to standard linear correlations. Our results show how large fMRI datasets can be drastically simplified to include only the timings of large-amplitude events, while still allowing the recovery of all pair-wise interactions between voxels. The practical importance of this dimensionality reduction is manifest in the increasing number of collaborative efforts aiming to study large cohorts of healthy subjects as well as patients suffering from brain disease. Our method also suggests that the electrophysiological signals underlying the dynamics of fMRI time series

  6. Bayesian hierarchical models for multivariate nonlinear spatio-temporal dynamical processes in the atmosphere and ocean

    NASA Astrophysics Data System (ADS)

    Leeds, W. B.; Wikle, C. K.

    2012-12-01

    Spatio-temporal statistical models, and in particular Bayesian hierarchical models (BHMs), have become increasingly popular as means of representing natural processes such as climate and weather that evolve over space and time. Hierarchical models make it possible to specify separate, conditional probability distributions that account for uncertainty in the observations, the underlying process, and parameters in situations when specifying these sources of uncertainty in a joint probability distribution may be difficult. As a result, BHMs are a natural setting for climatologists, meteorologists, and other environmental scientists to incorporate scientific information (e.g., PDEs, IDEs, etc.) a priori into a rigorous statistical framework that accounts for error in measurements, uncertainty in the understanding of the true underlying process, and uncertainty in the parameters that describe the process. While much work has been done in the development of statistical models for linear dynamic spatio-temporal processes, statistical modeling for nonlinear (and particularly, multivariate nonlinear) spatio-temporal dynamical processes is still a relatively open area of inquiry. As a result, general statistical models for environmental scientists to model complicated nonlinear processes is limited. We address this limitation in the methodology by introducing a multivariate "general quadratic nonlinear" framework for modeling multivariate, nonlinear spatio-temporal random processes inside of a BHM in a way that is especially applicable for problems in the ocean and atmospheric sciences. We show that in addition to the fact that this model addresses the previously mentioned sources of uncertainty for a wide spectrum of multivariate, nonlinear spatio-temporal processes, it is also a natural framework for data assimilation, allowing for the fusing of observations with computer models, computer model emulators, computer model output, or "mechanistically motivated" statistical

  7. STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data.

    PubMed

    Hyun, Jung Won; Li, Yimei; Huang, Chao; Styner, Martin; Lin, Weili; Zhu, Hongtu

    2016-07-01

    Longitudinal neuroimaging data plays an important role in mapping the neural developmental profile of major neuropsychiatric and neurodegenerative disorders and normal brain. The development of such developmental maps is critical for the prevention, diagnosis, and treatment of many brain-related diseases. The aim of this paper is to develop a spatio-temporal Gaussian process (STGP) framework to accurately delineate the developmental trajectories of brain structure and function, while achieving better prediction by explicitly incorporating the spatial and temporal features of longitudinal neuroimaging data. Our STGP integrates a functional principal component model (FPCA) and a partition parametric space-time covariance model to capture the medium-to-large and small-to-medium spatio-temporal dependence structures, respectively. We develop a three-stage efficient estimation procedure as well as a predictive method based on a kriging technique. Two key novelties of STGP are that it can efficiently use a small number of parameters to capture complex non-stationary and non-separable spatio-temporal dependence structures and that it can accurately predict spatio-temporal changes. We illustrate STGP using simulated data sets and two real data analyses including longitudinal positron emission tomography data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and longitudinal lateral ventricle surface data from a longitudinal study of early brain development. PMID:27103140

  8. Power law in random multiplicative processes with spatio-temporal correlated multipliers

    NASA Astrophysics Data System (ADS)

    Morita, Satoru

    2016-02-01

    It is well known that random multiplicative processes generate power-law probability distributions. We study how the spatio-temporal correlation of the multipliers influences the power-law exponent. We investigate two sources of the time correlation: the local environment and the global environment. In addition, we introduce two simple models through which we analytically and numerically show that the local and global environments yield different trends in the power-law exponent.

  9. Coupled map model for spatio-temporal processing in the olfactory bulb

    NASA Astrophysics Data System (ADS)

    de Almeida, L.; Idiart, M.; Quillfeldt, J. A.

    2007-02-01

    Odor processing in the animal olfactory system is still an open problem in modern neuroscience. It is a common understanding that the spatial code provided by the activity distribution of the olfactory receptor cells (ORC) due the presence of an odorant is transformed into a spatio-temporal code in the mitral cell (MC) layer in the case of mammals, or the projection neurons (PN) in the case of insects, that is decoded later along the neural path. The putative role of the spatio-temporal coding is to disambiguate the stimulus putting it in a more robust representation that allows odor separation, categorization, and recognition. Oscillations due to lateral inhibition among MC's (or PN's) may play an important part in the code as well as neural adaptation. To shed some light on their possible role in the olfaction processing, we study the properties of a simple network model. Upon the presentation of a random distributed input it respond with a rich spatio-temporal structure where two distinct phases are observed. We discuss their properties and implications in information processing.

  10. Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system

    NASA Astrophysics Data System (ADS)

    Huang, Ronghui; Chen, Jilong; Wang, Lin; Lin, Zhongda

    2012-09-01

    Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon (EAM) system are reviewed in this paper. The understanding of the EAM system has improved in many aspects: the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon (EASM) system and the East Asian winter monsoon (EAWM) system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific (EAP) teleconnection over East Asia and the North Pacific, the "Silk Road" teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.

  11. Processing discontinuous displacement fields by a spatio-temporal derivative technique

    NASA Astrophysics Data System (ADS)

    Sousa, A. M. R.; Xavier, J.; Morais, J. J. L.; Filipe, V. M. J.; Vaz, M.

    2011-12-01

    In this paper, a digital image correlation (DIC) method coupling cross-correlation with spatio-temporal differential techniques was proposed for assessing discontinuous displacement fields. The accuracy and robustness of the algorithm was assessed on a set of numerical tests by processing computer generated speckled-pattern images. Fracture mechanical tests in mode I were considered, in which both in-plane and out-of-plane rigid-body movements were taken into account. The ability for recovering the analytical asymptotic displacement field in mode I was analysed, and stress intensity factor, crack opening displacement and crack tip location were used as quantitative parameters for validation purposes. Throughout these tests, the results obtained with the proposed method were systematically compared to the ones from Aramis DIC-2D commercial code. Globally, the results computed from both methods are in good agreement with reference values. However, due to the high spatial resolution (point-wise characteristic), a better matching of the displacements in the neighbour of discontinuities could be obtained by the proposed method.

  12. Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging.

    PubMed

    Gorzolka, Karin; Kölling, Jan; Nattkemper, Tim W; Niehaus, Karsten

    2016-01-01

    MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals' germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest. PMID:26938880

  13. Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging

    PubMed Central

    Gorzolka, Karin; Kölling, Jan; Nattkemper, Tim W.; Niehaus, Karsten

    2016-01-01

    MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals’ germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest. PMID:26938880

  14. A spatio-temporal process data model for characterizing marine disasters

    NASA Astrophysics Data System (ADS)

    Jiang, B.; Zhang, X.; Huang, X.; Gao, T.

    2014-02-01

    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.

  15. Spatio-temporal evolution of biogeochemical processes at a landfill site

    NASA Astrophysics Data System (ADS)

    Arora, B.; Mohanty, B. P.; McGuire, J. T.

    2011-12-01

    Predictions of fate and transport of contaminants are strongly dependent on spatio-temporal variability of soil hydraulic and geochemical properties. This study focuses on time-series signatures of hydrological and geochemical properties at different locations within the Norman landfill site. Norman Landfill is a closed municipal landfill site with prevalent organic contamination. Monthly data at the site include specific conductance, δ18O, δ2H, dissolved organic carbon (DOC) and anions (chloride, sulfate, nitrate) from 1998-2006. Column scale data on chemical concentrations, redox gradients, and flow parameters are also available on daily and hydrological event (infiltration, drainage, etc.) scales. Since high-resolution datasets of contaminant concentrations are usually unavailable, Wavelet and Fourier analyses were used to infer the dominance of different biogeochemical processes at different spatio-temporal scales and to extract linkages between transport and reaction processes. Results indicate that time variability controls the progression of reactions affecting biodegradation of contaminants. Wavelet analysis suggests that iron-sulfide reduction reactions had high seasonal variability at the site, while fermentation processes dominated at the annual time scale. Findings also suggest the dominance of small spatial features such as layered interfaces and clay lenses in driving biogeochemical reactions at both column and landfill scales. A conceptual model that caters to increased understanding and remediating structurally heterogeneous variably-saturated media is developed from the study.

  16. OFDM Radar Space-Time Adaptive Processing by Exploiting Spatio-Temporal Sparsity

    SciTech Connect

    Sen, Satyabrata

    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 processing of massive glottic images from high-speed videoendoscopy

    NASA Astrophysics Data System (ADS)

    Yan, Yuling; Izdebski, Krzysztof; Marriott, Emma

    2011-03-01

    We present here development and application of new approaches for quantitative spatio-temporal analyses of vocal fold (VF) vibrations derived from high-speed digital imaging (HSDI) data of the glottis. We develop image processing methods to track the motion of the VF and target the analysis of HSDI-derived glottal area waveform (GAW), glottal width function (GWF) and displacements of the VF tissues for the characterization of the VF dynamic properties. In particular, a combined threshold and region growing method is used for the glottis segmentation, and an analytic signal approach and the Nyquist plot and associated parameters are used to represent and to characterize the VF vibratory behaviors in normal and specific pathologic voice productions.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and

  19. Evaluating Projected Changes in Mean Processes, Extreme Events, and their Spatio-Temporal Dependence Structures

    NASA Astrophysics Data System (ADS)

    Ganguly, A. R.; Steinhaeuser, K.; Kodra, E. A.; Kao, S.

    2010-12-01

    Observational datasets - both raw measurements and derived data products such as reanalysis data - are used to evaluate climate simulations run in forecast and hindcast modes. Bias and uncertainty in mean processes is quantified using statistical comparisons between observations and model-generated outputs. Weather and hydrological extremes under climate change are characterized using both event definitions and extreme value theory (EVT), and their aggregate statistics (intensity, duration and frequency) are likewise compared. The geographic variability and topographical biases are examined at continental to regional scales, and dependence structures (both spatio-temporal autocorrelation and long-range dependence) are assessed using statistical and nonlinear dynamical methods. These tools were developed primarily using the CMIP3/IPCC-AR4 archived model outputs, and are being additional tested with simulations from regional climate models which dynamically downscale the AR4 archives. This combination of traditional and novel tools is thus geared towards evaluation of multiple climate models which may handle processes or generate outputs at different spatial and temporal scales. The tools are expected to be immediately applicable to the CMIP5 data when it becomes available. The anticipated space-time resolutions will pose algorithmic challenges and computational demands, which will be addressed using analytic solutions and implementations thereof on high-performance scientific computing platforms.

  20. The Voronoi spatio-temporal data structure

    NASA Astrophysics Data System (ADS)

    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

  1. Spatio-temporal change modeling with array data

    NASA Astrophysics Data System (ADS)

    Lu, Meng; Pebesma, Edzer

    2015-04-01

    Spatio-temporal change modeling of our ecosystems is critical for environmental conservation. Open access to remote sensing satellite image archives provides new opportunities for change modeling, such as near real-time change monitoring with long term image time series. Newly developed time series analysis methods allow the detection of quantitative changes in trend and seasonality for each pixel of the image. A drawback of pure time series analysis is that spatial dependence is neglected. There are several spatio-temporal statistical approaches to incorporate spatial context. One method is to build hierarchical models with spatial effects for time series parameters. Other methods include representing regression parameters as spatially correlated random fields, or integrating spatial autoregressive models to time series analysis. Apart from spatio-temporal statistical modeling, the results can be further improved by qualification of detected change points with their spatio-temporal neighbors. Spatio-temporal modeling approaches are typically complex and large in scale, and call for new data management and analysis tools. Remote sensing satellite images, which are continuous and regular in space and time, can naturally be represented as three- or four-dimensional arrays for spatio-temporal data management and analysis. The developed spatio-temporal statistical algorithms can be flexibly applied within array partitions that span the relevant array-based dimensions. This study investigates the potential of array-based Data Data Management and Analytic Software (DMAS) for fast data access, data integration and large-scale complex spatio-temporal analysis. A study case is developed in near-real time deforestation monitoring in Amazonian rainforest with long-term 250 m, 8-day resolution MODIS image time series. A novel spatio-temporal change modeling process is being developed and implemented in DMAS to realize rapid and automated analysis of satellite image time series

  2. Time-Resolved and Spatio-Temporal Analysis of Complex Cognitive Processes and their Role in Disorders like Developmental Dyscalculia

    PubMed Central

    Mórocz, István Akos; Janoos, Firdaus; van Gelderen, Peter; Manor, David; Karni, Avi; Breznitz, Zvia; von Aster, Michael; Kushnir, Tammar; Shalev, Ruth

    2012-01-01

    The aim of this article is to report on the importance and challenges of a time-resolved and spatio-temporal analysis of fMRI data from complex cognitive processes and associated disorders using a study on developmental dyscalculia (DD). Participants underwent fMRI while judging the incorrectness of multiplication results, and the data were analyzed using a sequence of methods, each of which progressively provided more a detailed picture of the spatio-temporal aspect of this disease. Healthy subjects and subjects with DD performed alike behaviorally though they exhibited parietal disparities using traditional voxel-based group analyses. Further and more detailed differences, however, surfaced with a time-resolved examination of the neural responses during the experiment. While performing inter-group comparisons, a third group of subjects with dyslexia (DL) but with no arithmetic difficulties was included to test the specificity of the analysis and strengthen the statistical base with overall fifty-eight subjects. Surprisingly, the analysis showed a functional dissimilarity during an initial reading phase for the group of dyslexic but otherwise normal subjects, with respect to controls, even though only numerical digits and no alphabetic characters were presented. Thus our results suggest that time-resolved multi-variate analysis of complex experimental paradigms has the ability to yield powerful new clinical insights about abnormal brain function. Similarly, a detailed compilation of aberrations in the functional cascade may have much greater potential to delineate the core processing problems in mental disorders. PMID:22368322

  3. Processing of facial emotional expression: spatio-temporal data as assessed by scalp event-related potentials.

    PubMed

    Krolak-Salmon, P; Fischer, C; Vighetto, A; Mauguière, F

    2001-03-01

    Event-related potentials (ERPs) were recorded in 10 adult volunteers, who were asked to view pictures of faces with different emotional expressions, i.e. fear, happiness, disgust, surprise and neutral expression [Ekman, P. & Friesen, W.V. (1975). Pictures of Facial Affect. Consulting Psychologist Press, Palo Alto, CA]. ERPs were recorded during two different tasks with the same stimuli. Firstly, subjects were instructed to pay attention to the gender of the faces by counting males or females. Secondly, they had to focus on facial expressions by counting faces who looked surprised. The classical scalp 'face-related potentials', i.e. a vertex-positive potential and a bilateral temporal negativity, were recorded 150 ms after the stimulus onset. Significant differences were found, firstly between late-latency ERPs to emotional faces and to neutral faces, between 250 and 550 ms of latency and, secondly, among the ERPs to the different facial expressions between 550 and 750 ms of latency. These differences appeared only during the expression discrimination task, not during the gender discrimination task. Topographic maps of these differences showed a specific right temporal activity related to each emotional expression, some particularities being observed for each expression. This study provides new data concerning the spatio-temporal features of facial expression processing, particularly a late-latency activity related to specific attention to facial expressions. PMID:11264671

  4. Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar

    PubMed Central

    Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

    2015-01-01

    A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results. PMID:26694385

  5. Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar.

    PubMed

    Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

    2015-01-01

    A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters' outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results. PMID:26694385

  6. Spatio-temporal dynamics of automatic processing of phonological information in visual words.

    PubMed

    Wang, Xiao-Dong; Wu, Yin-Yuan; A-Ping Liu; Wang, Peng

    2013-01-01

    Sensory-specific cortices appear to be sensitive to information from another modality. Here we investigate whether the human brain automatically extracts the phonological information in visual words in early visual processing. We continuously presented native Chinese speakers peripherally with Chinese homophone characters in an oddball paradigm, while they performed a visual detection task presented in the centre of the visual field. We found the lexical tone phonology embedded in the characters is processed automatically by the brain of native speakers, as revealed by whole-head electrical recordings of the mismatch negativity (MMN). Source solution further revealed the MMN involved the neural activations from the visual cortex to the auditory cortex (130-460 ms). The spatial-temporal dynamics indicate a visual-auditory interaction in the early, automatic processing of phonological information in visual words. PMID:24336606

  7. Synthesis of neural networks for spatio-temporal spike pattern recognition and processing

    PubMed Central

    Tapson, Jonathan C.; Cohen, Greg K.; Afshar, Saeed; Stiefel, Klaus M.; Buskila, Yossi; Wang, Runchun Mark; Hamilton, Tara J.; van Schaik, André

    2013-01-01

    The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework (NEF) offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify—arbitrarily—neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times. PMID:24009550

  8. Spatio-temporal learning with the online finite and infinite echo-state Gaussian processes.

    PubMed

    Soh, Harold; Demiris, Yiannis

    2015-03-01

    Successful biological systems adapt to change. In this paper, we are principally concerned with adaptive systems that operate in environments where data arrives sequentially and is multivariate in nature, for example, sensory streams in robotic systems. We contribute two reservoir inspired methods: 1) the online echostate Gaussian process (OESGP) and 2) its infinite variant, the online infinite echostate Gaussian process (OIESGP) Both algorithms are iterative fixed-budget methods that learn from noisy time series. In particular, the OESGP combines the echo-state network with Bayesian online learning for Gaussian processes. Extending this to infinite reservoirs yields the OIESGP, which uses a novel recursive kernel with automatic relevance determination that enables spatial and temporal feature weighting. When fused with stochastic natural gradient descent, the kernel hyperparameters are iteratively adapted to better model the target system. Furthermore, insights into the underlying system can be gleamed from inspection of the resulting hyperparameters. Experiments on noisy benchmark problems (one-step prediction and system identification) demonstrate that our methods yield high accuracies relative to state-of-the-art methods, and standard kernels with sliding windows, particularly on problems with irrelevant dimensions. In addition, we describe two case studies in robotic learning-by-demonstration involving the Nao humanoid robot and the Assistive Robot Transport for Youngsters (ARTY) smart wheelchair. PMID:25720008

  9. Advanced spatio-temporal filtering techniques for photogrammetric image sequence analysis in civil engineering material testing

    NASA Astrophysics Data System (ADS)

    Liebold, F.; Maas, H.-G.

    2016-01-01

    The paper shows advanced spatial, temporal and spatio-temporal filtering techniques which may be used to reduce noise effects in photogrammetric image sequence analysis tasks and tools. As a practical example, the techniques are validated in a photogrammetric spatio-temporal crack detection and analysis tool applied in load tests in civil engineering material testing. The load test technique is based on monocular image sequences of a test object under varying load conditions. The first image of a sequence is defined as a reference image under zero load, wherein interest points are determined and connected in a triangular irregular network structure. For each epoch, these triangles are compared to the reference image triangles to search for deformations. The result of the feature point tracking and triangle comparison process is a spatio-temporally resolved strain value field, wherein cracks can be detected, located and measured via local discrepancies. The strains can be visualized as a color-coded map. In order to improve the measuring system and to reduce noise, the strain values of each triangle must be treated in a filtering process. The paper shows the results of various filter techniques in the spatial and in the temporal domain as well as spatio-temporal filtering techniques applied to these data. The best results were obtained by a bilateral filter in the spatial domain and by a spatio-temporal EOF (empirical orthogonal function) filtering technique.

  10. Analysing the spatio-temporal organization of sediment dynamics at the hillslope scale using a process based erosion model

    NASA Astrophysics Data System (ADS)

    Scherer, U.; Zehe, E.; Ehret, U.; Kleidon, A.

    2012-04-01

    The morphology of soil covered hillslopes tends to a characteristic convex-concave shape. In hilly landscapes, where erosion rates do not exceed the weathering rates of bedrock material, the form of hillslopes is convex near the hilltop and becomes increasingly planar further downslope with the steepest descent in the middle of the slope. This typical shape is the result of long term erosion and sediment redistribution processes driven by a topographic gradient and climatic forcing. Erosion rates depend on slope, soil properties, vegetation cover and rainfall/runoff rates. The morphology of hillslopes is thus the result of a trade-off between all these parameters controlling the relation of detachment, transport and deposition rates of sediments as well as feedback mechanisms on the driving gradient. Sediment flux increases with increasing slope but higher sediment transport rates deplete the driving gradient and thus reduce sediment export. We hypothesize that sediment export is maximized under the condition of maintaining the driving gradient and that this trade-off implies a typical shape and steepness of slopes. We used the process based model CATFLOW-SED to verify this hypothesis and to better understand the spatio-temporal organisation of sediment dynamics at the hillslope scale. CATFLOW-SED is a continuous, dynamic, spatially distributed model. Soil water dynamics is described by the Richards equation, including an effective approach for preferential flow that is numerically solved by an implicit mass conservative Picard iteration. Evaporation and transpiration is simulated, using an advanced approach based on the Penman-Monteith equation. The model simulates overland flow as sheet flow using the diffusion wave equation. Soil detachment is related to the attacking forces of rainfall and overland flow. The detachment rate further depends on the model parameter erosion resistance, which is characterized by soil properties, land use and management practice

  11. Estimating global natural wetland methane emissions using process modelling: spatio-temporal patterns and contributions to atmospheric methane fluctuations

    USGS Publications Warehouse

    Zhu, Qiuan; Peng, Changhui; Chen, Huai; Fang, Xiuqin; Liu, Jinxun; Jiang, Hong; Yang, Yanzheng; Yang, Gang

    2015-01-01

    Aim The fluctuations of atmospheric methane (CH4) that have occurred in recent decades are not fully understood, particularly with regard to the contribution from wetlands. The application of spatially explicit parameters has been suggested as an effective method for reducing uncertainties in bottom-up approaches to wetland CH4 emissions, but has not been included in recent studies. Our goal was to estimate spatio-temporal patterns of global wetland CH4 emissions using a process model and then to identify the contribution of wetland emissions to atmospheric CH4fluctuations. Location Global. Methods A process-based model integrated with full descriptions of methanogenesis (TRIPLEX-GHG) was used to simulate global wetland CH4emissions. Results Global annual wetland CH4 emissions ranged from 209 to 245 Tg CH4 year−1 between 1901 and 2012, with peaks occurring in 1991 and 2012. There is a decreasing trend between 1990 and 2010 with a rate of approximately 0.48 Tg CH4 year−1, which was largely caused by emissions from tropical wetlands showing a decreasing trend of 0.44 Tg CH4 year−1 since the 1970s. Emissions from tropical, temperate and high-latitude wetlands comprised 59, 26 and 15% of global emissions, respectively. Main conclusion Global wetland CH4 emissions, the interannual variability of which was primary controlled by tropical wetlands, partially drive the atmosphericCH4 burden. The stable to decreasing trend in wetland CH4 emissions, a result of a balance of emissions from tropical and extratropical wetlands, was a particular factor in slowing the atmospheric CH4 growth rate during the 1990s. The rapid decrease in tropical wetland CH4emissions that began in 2000 was supposed to offset the increase in anthropogenic emissions and resulted in a relatively stable level of atmospheric CH4 from 2000 to 2006. Increasing wetland CH4 emissions, particularly after 2010, should be an important contributor to the growth in

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  14. Modeling spatio-temporal field evolution

    NASA Astrophysics Data System (ADS)

    Borštnik Bračič, A.; Grabec, I.; Govekar, E.

    2009-06-01

    Prediction of spatio-temporal field evolution is based on the extraction of a physical law from joint experimental data. This extraction is usually described by a set of differential equations. If the only source of information is a field record, a method of field generators based on nonparametric modeling by conditional average can successfully replace differential equations. In this article we apply the method of field generators to a two-dimensional chaotic field record that describes the asynchronous motion of high-amplitude striations. We show how to choose the model structure in order to optimize the quality of the prediction process.

  15. Spatio-temporal action localization for human action recognition in large dataset

    NASA Astrophysics Data System (ADS)

    Megrhi, Sameh; Jmal, Marwa; Beghdadi, Azeddine; Mseddi, Wided

    2015-03-01

    Human action recognition has drawn much attention in the field of video analysis. In this paper, we develop a human action detection and recognition process based on the tracking of Interest Points (IP) trajectory. A pre-processing step that performs spatio-temporal action detection is proposed. This step uses optical flow along with dense speed-up-robust-features (SURF) in order to detect and track moving humans in moving fields of view. The video description step is based on a fusion process that combines displacement and spatio-temporal descriptors. Experiments are carried out on the big data-set UCF-101. Experimental results reveal that the proposed techniques achieve better performances compared to many existing state-of-the-art action recognition approaches.

  16. Nonlinear wave interactions between short pulses of different spatio-temporal extents

    PubMed Central

    Sivan, Y.; Rozenberg, S.; Halstuch, A.; Ishaaya, A. A.

    2016-01-01

    We study the nonlinear wave interactions between short pulses of different spatio-temporal extents. Unlike the well-understood mixing of quasi-monochromatic waves, this configuration is highly non-intuitive due to the complex coupling between the spatial and temporal degrees of freedom of the interacting pulses. We illustrate the process intuitively with transitions between different branches of the dispersion curves and interpret it in terms of spectral exchange between the interacting pulses. We verify our interpretation with an example whereby a spectrally-narrow pulse “inherits” the wide spectrum of a pump pulse centered at a different wavelength, using exact numerical simulations, as well as a simplified coupled mode analysis and an asymptotic analytical solution. The latter also provides a simple and intuitive quantitative interpretation. The complex wave mixing process studied here may enable flexible spatio-temporal shaping of short pulses and is the starting point of the study of more complicated systems. PMID:27381552

  17. Art, Science and Architecture: Architecture as a Dynamic Process of Structuring Matter-Energy in the Spatio-Temporal World.

    ERIC Educational Resources Information Center

    Minai, Asghar Talaye

    Developed were methods of coordinating art and science in relation to the creation of the physical form of the environment. Such an approach has been directed towards a theory of form based on point theory or field theory in architecture and deals with the problem of potentiality or dispositional properties. Part I, Towards a Sociology of…

  18. The effect of spatio-temporal distance between visual stimuli on information processing in children with Specific Language Impairment.

    PubMed

    Dispaldro, Marco; Corradi, Nicola

    2015-01-01

    The purpose of this study is to evaluate whether children with Specific Language Impairment (SLI) have a deficit in processing a sequence of two visual stimuli (S1 and S2) presented at different inter-stimulus intervals and in different spatial locations. In particular, the core of this study is to investigate whether S1 identification is disrupted due to a retroactive interference of S2. To this aim, two experiments were planned in which children with SLI and children with typical development (TD), matched by age and non-verbal IQ, were compared (Experiment 1: SLI n=19; TD n=19; Experiment 2: SLI n=16; TD n=16). Results show group differences in the ability to identify a single stimulus surrounded by flankers (Baseline level). Moreover, children with SLI show a stronger negative interference of S2, both for temporal and spatial modulation. These results are discussed in the light of an attentional processing limitation in children with SLI. PMID:26277740

  19. A multivariate statistical approach to identify the spatio-temporal variation of geochemical process in a hard rock aquifer.

    PubMed

    Thivya, C; Chidambaram, S; Thilagavathi, R; Prasanna, M V; Singaraja, C; Adithya, V S; Nepolian, M

    2015-09-01

    A study has been carried out in crystalline hard rock aquifers of Madurai district, Tamil Nadu, to identify the spatial and temporal variations and to understand sources responsible for hydrogeochemical processes in the region. Totally, 216 samples were collected for four seasons [premonsoon (PRM), southwest monsoon (SWM), northeast monsoon (NWM), and postmonsoon (POM)]. The Na and K ions are attributed from weathering of feldspars in charnockite and fissile hornblende gneiss. The results also indicate that monsoon leaches the U ions in the groundwater and later it is reflected in the (222)Rn levels also. The statistical relationship on the temporal data reflects the fact that Ca, Mg, Na, Cl, HCO3, and SO4 form the spinal species, which are the chief ions playing the significant role in the geochemistry of the region. The factor loadings of the temporal data reveal the fact that the predominant factor is anthropogenic process and followed by natural weathering and U dissolution. The spatial analysis of the temporal data reveals that weathering is prominent in the NW part and that of distribution of U and (222)Rn along the NE part of the study area. This is also reflected in the cluster analysis, and it is understood that lithology, land use pattern, lineaments, and groundwater flow direction determine the spatial variation of these ions with respect to season. PMID:26239570

  20. Spatio-temporal modelling of electrical supply systems to optimize the site planning process for the "power to mobility" technology

    NASA Astrophysics Data System (ADS)

    Karl, Florian; Zink, Roland

    2016-04-01

    The transformation of the energy sector towards decentralized renewable energies (RE) requires also storage systems to ensure security of supply. The new "Power to Mobility" (PtM) technology is one potential solution to use electrical overproduction to produce methane for i.e. gas vehicles. Motivated by these fact, the paper presents a methodology for a GIS-based temporal modelling of the power grid, to optimize the site planning process for the new PtM-technology. The modelling approach is based on a combination of the software QuantumGIS for the geographical and topological energy supply structure and OpenDSS for the net modelling. For a case study (work in progress) of the city of Straubing (Lower Bavaria) the parameters of the model are quantified. The presentation will discuss the methodology as well as the first results with a view to the application on a regional scale.

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

    PubMed Central

    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

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

    PubMed

    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

  3. A semiparametric spatio-temporal model for solar irradiance data

    DOE PAGESBeta

    Patrick, Joshua D.; Harvill, Jane L.; Hansen, Clifford W.

    2016-03-01

    Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance atmore » high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.« less

  4. a Spatio-Temporal Framework for Modeling Active Layer Thickness

    NASA Astrophysics Data System (ADS)

    Touyz, J.; Streletskiy, D. A.; Nelson, F. E.; Apanasovich, T. V.

    2015-07-01

    The Arctic is experiencing an unprecedented rate of environmental and climate change. The active layer (the uppermost layer of soil between the atmosphere and permafrost that freezes in winter and thaws in summer) is sensitive to both climatic and environmental changes, and plays an important role in the functioning, planning, and economic activities of Arctic human and natural ecosystems. This study develops a methodology for modeling and estimating spatial-temporal variations in active layer thickness (ALT) using data from several sites of the Circumpolar Active Layer Monitoring network, and demonstrates its use in spatial-temporal interpolation. The simplest model's stochastic component exhibits no spatial or spatio-temporal dependency and is referred to as the naïve model, against which we evaluate the performance of the other models, which assume that the stochastic component exhibits either spatial or spatio-temporal dependency. The methods used to fit the models are then discussed, along with point forecasting. We compare the predicted fit of the various models at key study sites located in the North Slope of Alaska and demonstrate the advantages of space-time models through a series of error statistics such as mean squared error, mean absolute and percent deviance from observed data. We find the difference in performance between the spatio-temporal and remaining models is significant for all three error statistics. The best stochastic spatio-temporal model increases predictive accuracy, compared to the naïve model, of 33.3%, 36.2% and 32.5% on average across the three error metrics at the key sites for a one-year hold out period.

  5. Inverse hydrological modelling of spatio-temporal rainfall patterns

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

    Distributed hydrological models are commonly used for simulating the non-linear response of a watershed to rainfall events for addressing different hydrological properties of the landscape. Such models are driven by spatial rainfall patterns for consecutive time steps, which are normally generated from point measurements using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall patterns especially in data scarce regions with poorly gauged catchments or for highly dynamic, small scaled rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties are associated with poorly identified spatio-temporal rainfall distribution in distributed rainfall-runoff-modelling since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves are underestimated. For addressing these challenges a novel methodology for inverse hydrological modelling is proposed using a Markov-Chain-Monte-Carlo framework. Thereby, potential candidates of spatio-temporal rainfall patterns are generated and selected according their ability to reproduce the observed surface runoff at the catchment outlet for a given transfer function in a best way. The Methodology combines the concept of random mixing of random spatial fields with a grid-based spatial distributed rainfall runoff model. The conditional target rainfall field is obtained as a linear combination of unconditional spatial random fields. The corresponding weights of the linear combination are selected such that the spatial variability of the rainfall amounts as well as the actual observed rainfall values are reproduced. The functionality of the methodology is demonstrated on a synthetic example. Thereby, the known spatio-temporal distribution of rainfall is reproduced for a given number of point observations of rainfall and the integral catchment response at the catchment outlet for a synthetic catchment

  6. Spatio-temporal variation of erosion-type non-point source pollution in a small watershed of hilly and gully region, Chinese Loess Plateau.

    PubMed

    Wu, Lei; Liu, Xia; Ma, Xiao-Yi

    2016-06-01

    Loss of nitrogen and phosphorus in the hilly and gully region of Chinese Loess Plateau not only decreases the utilization rate of fertilizer but also is a potential threat to aquatic environments. In order to explore the process of erosion-type non-point source (NPS) pollution in Majiagou watershed of Loess Plateau, a distributed, dynamic, and integrated NPS pollution model was established to investigate impacts of returning farmland on erosion-type NPS pollution load from 1995 to 2012. Results indicate that (1) the integrated model proposed in this study was verified to be reasonable; the general methodology is universal and can be applicable to the hilly and gully region, Loess Plateau; (2) the erosion-type NPS total nitrogen (TN) and total phosphorus (TP) load showed an overall decreasing trend; the average nitrogen and phosphorus load modulus in the last four years (2009-2012) were 1.23 and 1.63 t/km(2) · a, respectively, which were both decreased by about 35.4 % compared with the initial treatment period (1995-1998); and (3) The spatial variations of NPS pollution are closely related to spatial characteristics of rainfall, topography, and soil and land use types; the peak regions of TN and TP loss mainly occurred along the main river banks of the Yanhe River watershed from northeast to southeast, and gradually decreased with the increase of distance to the left and right river banks, respectively. Results may provide scientific basis for the watershed-scale NPS pollution control of the Loess Plateau. PMID:26898934

  7. Chaotic itinerancy, temporal segmentation and spatio-temporal combinatorial codes

    NASA Astrophysics Data System (ADS)

    Dias, Juliana R.; Oliveira, Rodrigo F.; Kinouchi, Osame

    2008-01-01

    We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors (“patterns”) we add a slow coupling dynamics that makes the visited patterns lose stability, leading to an itinerant behavior in the form of punctuated equilibria. One finds that the transition frequency matrix for transitions between patterns shows non-trivial statistical properties in the chaotic itinerant regime. We show that mixture input patterns can be temporally segmented by the itinerant dynamics. The viability of a combinatorial spatio-temporal neural code is also demonstrated.

  8. Mapping spatio-temporal filtering algorithms used in fluoroscopy to single core and multicore DSP architectures

    NASA Astrophysics Data System (ADS)

    Dasgupta, Udayan; Ali, Murtaza

    2011-03-01

    Low dose X-ray image sequences, as obtained in fluoroscopy, exhibit high levels of noise that must be suppressed in real-time, while preserving diagnostic structures. Multi-step adaptive filtering approaches, often involving spatio-temporal filters, are typically used to achieve this goal. In this work typical fluoroscopic image sequences, corrupted with Poisson noise, were processed using various filtering schemes. The noise suppression of the schemes was evaluated using objective image quality measures. Two adaptive spatio-temporal schemes, the first one using object detection and the second one using unsharp masking, were chosen as representative approaches for different fluoroscopy procedures and mapped on to Texas Instrument's (TI) high performance digital signal processors (DSP). The paper explains the fixed point design of these algorithms and evaluates its impact on overall system performance. The fixed point versions of these algorithms are mapped onto the C64x+TM core using instruction-level parallelism to effectively use its VLIW architecture. The overall data flow was carefully planned to reduce cache and data movement overhead, while working with large medical data sets. Apart from mapping these algorithms on to TI's single core DSP architecture, this work also distributes the operations to leverage multi-core DSP architectures. The data arrangement and flow were optimized to minimize inter-processor messaging and data movement overhead.

  9. Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

    2014-12-01

    Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

  10. Spatio-temporal dynamics in the origin of genetic information

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Jeong, Hawoong

    2005-04-01

    We study evolutionary processes induced by spatio-temporal dynamics in prebiotic evolution. Using numerical simulations, we demonstrate that hypercycles emerge from complex interaction structures in multispecies systems. In this work, we also find that ‘hypercycle hybrid’ protects the hypercycle from its environment during the growth process. There is little selective advantage for one hypercycle to maintain coexistence with others. This brings the possibility of the outcompetition between hypercycles resulting in the negative effect on information diversity. To enrich the information in hypercycles, symbiosis with parasites is suggested. It is shown that symbiosis with parasites can play an important role in the prebiotic immunology.

  11. Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations

    SciTech Connect

    Schüler, D.; Alonso, S.; Bär, M.; Torcini, A.

    2014-12-15

    Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexisting static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed Central

    Caucci, Luca; Barrett, Harrison H.; Rodríguez, Jeffrey J.

    2010-01-01

    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. PMID:19550494

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

    PubMed

    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. PMID:19550494

  15. Proposal for a Non-Interceptive Spatio-Temporal Correlation Monitor

    SciTech Connect

    Maxwell, T.; Piot, P.; /Northern Illinois U. /Fermilab

    2009-05-01

    Designs toward TeV-range electron-positron linear colliders include a non-zero crossing angle colliding scheme at the interaction point to mitigate instabilities and possible background. Maximizing the luminosity when operating with non-zero crossing angles requires the use of 'crab' cavities to impart a well-defined spatio-temporal correlation. In this paper we propose a novel noninterceptive diagnostic capable of measuring and monitoring the spatio-temporal correlation, i.e. the transverse position of sub-picosecond time slices, within bunch. An analysis of the proposed scheme, its spatio-temporal resolution and its limitations are quantified. Finally, the design of a proof-of-principle experiment in preparation for the Fermilab's A0 photoinjector is presented.

  16. Standards-Based Services for Big Spatio-Temporal Data

    NASA Astrophysics Data System (ADS)

    Baumann, P.; Merticariu, V.; Dumitru, A.; Misev, D.

    2016-06-01

    With the unprecedented availability of continuously updated measured and generated data there is an immense potential for getting new and timely insights - yet, the value is not fully leveraged as of today. The quest is up for high-level service interfaces for dissecting datasets and rejoining them with other datasets - ultimately, to allow users to ask "any question, anytime, on any size" enabling them to "build their own product on the go". With OGC Coverages, a concrete, interoperable data model has been established which unifies n-D spatio-temporal regular and irregular grids, point clouds, and meshes. The Web Coverage Service (WCS) suite provides versatile streamlined coverage functionality ranging from simple access to flexible spatio-temporal analytics. Flexibility and scalability of the WCS suite has been demonstrated in practice through massive services run by large-scale data centers. We present the current status in OGC Coverage data and service models, contrast them to related work, and describe a scalable implementation based on the rasdaman array engine.

  17. Multiscale recurrence analysis of spatio-temporal data

    NASA Astrophysics Data System (ADS)

    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.

  18. Spatio-Temporal Oscillations in Predator-Prey Systems

    NASA Astrophysics Data System (ADS)

    Tomé, T.; de Carvalho, K. Cristina

    2005-10-01

    In recent years a particularly great effort has been made to understand the role of space given by a spatial structure and local interactions in the characterization of the dynamics of competing biological species. Irreversible stochastic lattice models have been studied to mimic predator-prey systems with Markovian local rules based in the Lotka-Volterra model. One of the problems being studied is the stability of the temporal oscillations of the population of two-species systems-whether they are synchronized. Here we study the temporal oscillations of a two-species system by considering two probabilistic cellular automata defined in regular lattices where each site can be in three states: empty, occupied by a prey, or occupied by a predator. One of them, the isotropic model, has local rules similar to those of the contact process and try to mimic the Lotka-Volterra model mechanisms. The other automaton, the anisotropic model, is based in rules that are similar to the isotropic model, but a anisotropic neighborhood is considered. This model was introduced to explore the effect of spatial anisotropy in temporal oscillations. In fact, it has been pointed out that temporally periodic states can be stable in spatial anisotropic irreversible systems whose anisotropy is exploited conveniently. We show Monte Carlo simulations performed on square lattices for both automata. Our results indicate that, in the thermodynamic limit, oscillations can occur only at a local level, even in the anisotropic model. We observe that for given sets of control parameters a spatio-temporal oscillation occurs in the system. These structures are analyzed.

  19. Spatio-temporal aggregation of European air quality observations in the Sensor Web

    NASA Astrophysics Data System (ADS)

    Stasch, Christoph; Foerster, Theodor; Autermann, Christian; Pebesma, Edzer

    2012-10-01

    An increasing amount of observations from different applications such as long-term environmental monitoring or disaster management is published in the Web using Sensor Web technologies. The standardization of these technologies eases the integration of heterogeneous observations into several applications. However, as observations differ in spatio-temporal coverage and resolution, aggregation of observations in space and time is needed. We present an approach for spatio-temporal aggregation in the Sensor Web using the Geoprocessing Web. In particular, we define a tailored observation model for different aggregation levels, a process model for aggregation processes and a Spatio-Temporal Aggregation Service. The presented approach is demonstrated by a case study of delivering aggregated air quality observations on-demand in the Sensor Web.

  20. A hierarchical spatio-temporal data model for dynamic monitoring of land use

    NASA Astrophysics Data System (ADS)

    Wang, Hao; Liu, Yaolin

    2007-06-01

    Dynamic monitoring of land use is a perennial and persistent process now in Shanghai. Therefore, the cumulated amount of monitoring data will be very large. It is an exigent problem how to manage and use this data effectively. The key issue is finding a suitable spatio-temporal data model that must take into account space, time and attribute factor adequately. In dynamic monitoring of land use, it is change that is of direct interest. With analyzing the feature of land use dynamic monitoring and the shortage of some spatio-temporal data models when they are used in the field, this paper proposes a Hierarchical Spatio-Temporal Data Model (HSDM) that stores elements of change and makes these available for direct query and analysis.

  1. Plant diversity increases spatio-temporal niche complementarity in plant-pollinator interactions.

    PubMed

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

    2016-04-01

    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 pollinator functional groups (honeybees, bumblebees, solitary bees, and hoverflies) in experimental plots at three different vegetation strata between sunrise and sunset. Visits were modified by plant species richness interacting with time and space. Furthermore, the complementarity of pollinator functional groups in space and time was stronger in species-rich mixtures. We conclude that high plant diversity should ensure stable pollination services, mediated via spatio-temporal niche complementarity in flower visitation. PMID:27069585

  2. The Relationship between Filling-in Induction and Spatio-Temporal Frequency of Sorrounding Dynamic Textures

    NASA Astrophysics Data System (ADS)

    Yokota, Masae; Yokota, Yasunari

    To elucidate perceptual filling-in mechanisms in peripheral vision, we investigated dependency of filling-in occurrence on spatio-temporal frequency of dynamic textures surrounding the filling-in target. We first measured spatial frequency sensitivity of the filling-in target in static texture. Then, the time to filling-in, when dynamic textures which have variously limited spatio-temporal frequency are surrounding the filling-in target, were measured. According to the hypothesis of filling-in process which has already proposed by the authors, the tendency of inducing filling-in, i.e., the attenuation factor of perceptual power for filling-in target in dynamic textures, is estimated as a function of spatio-temporal frequency. It was suggested that surrounding texture with stronger perception promotes filling-in more intensively.

  3. Stochastic spatio-temporal modelling with PCRaster Python

    NASA Astrophysics Data System (ADS)

    Karssenberg, D.; Schmitz, O.; de Jong, K.

    2012-04-01

    PCRaster Python is a software framework for building spatio-temporal models of land surface processes (Karssenberg, Schmitz, Salamon, De Jong, & Bierkens, 2010; PCRaster, 2012). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations, developed in C++, are available to model builders as Python functions. Users create models by combining these functions in a Python script. As construction of large iterative models is often difficult and time consuming for non-specialists in programming, the software comes with a set of Python framework classes that provide control flow for static modelling, temporal modelling, stochastic modelling using Monte Carlo simulation, and data assimilation techniques including the Ensemble Kalman filter and the Particle Filter. A framework for integrating model components with different time steps and spatial discretization is currently available as a prototype (Schmitz, de Jong, & Karssenberg, in review). The software includes routines for visualisation of stochastic spatio-temporal data for prompt, interactive, visualisation of model inputs and outputs. Visualisation techniques include animated maps, time series, probability distributions, and animated maps with exceedance probabilities. The PCRaster Python software is used by researchers from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows and Linux operating systems, and OS X (under development).

  4. In-situ measurements of pore water stable isotope composition in a semi-arid environment with implications for spatio-temporal variability of unsaturated zone processes.

    NASA Astrophysics Data System (ADS)

    Gaj, Marcel; Beyer, Matthias; Koeniger, Paul; Hamutoko, Yosefina; Himmelsbach, Thomas

    2015-04-01

    Northern Namibia is a region with high population growth, limited water resources and a transboundary aquifer system where groundwater recharge and groundwater flow processes are not yet well understood. Our study is an interdisciplinary approach to improve the understanding of links between hydrological, geochemical and ecological processes to estimate areas that contribute to recharge a shallow aquifer system. To determine the spatial variability of infiltration and evapotranspiration processes within the critical interface and between the atmosphere and the groundwater nine plots in an area of 9,000 m2 were investigated. Stable isotopes (deuterium, δ2H, and oxygen-18, δ18O) of soil pore water were measured directly in the field using a LGR-DLT100 and commercially available soil gas probes (BGL-30, UMS). Additionally, soil moisture and temperature were recorded. After drift correction of the isotope data the long term precision using a quality check standard for 221 measurement points of a two week period was between 6.3 - 7.4 o for δ2H and 1.3 - 3.6 o for δ18O. Each point was measured with six repetitions were the mean standard deviation for all quality check standards was 1.3 - 1.6 o for δ2H and 0.23 - 0.30 o for δ18O. It could be observed that the quality of the measurements decreased with increasing number of measurements due to a memory effect of the probes enhanced by organic contamination of the membrane pores. However, results support the applicability of an in-situ system for the determination of stable isotopes in soil pore water. Spatially and temporal variability affected by intermitted light rainfall events can be deduced with the observed data.

  5. Spatio-Temporal Detection of the Thiomonas Population and the Thiomonas Arsenite Oxidase Involved in Natural Arsenite Attenuation Processes in the Carnoulès Acid Mine Drainage.

    PubMed

    Hovasse, Agnès; Bruneel, Odile; Casiot, Corinne; Desoeuvre, Angélique; Farasin, Julien; Hery, Marina; Van Dorsselaer, Alain; Carapito, Christine; Arsène-Ploetze, Florence

    2016-01-01

    The acid mine drainage (AMD) impacted creek of the Carnoulès mine (Southern France) is characterized by acid waters with a high heavy metal content. The microbial community inhabiting this AMD was extensively studied using isolation, metagenomic and metaproteomic methods, and the results showed that a natural arsenic (and iron) attenuation process involving the arsenite oxidase activity of several Thiomonas strains occurs at this site. A sensitive quantitative Selected Reaction Monitoring (SRM)-based proteomic approach was developed for detecting and quantifying the two subunits of the arsenite oxidase and RpoA of two different Thiomonas groups. Using this approach combined with FISH and pyrosequencing-based 16S rRNA gene sequence analysis, it was established here for the first time that these Thiomonas strains are ubiquitously present in minor proportions in this AMD and that they express the key enzymes involved in natural remediation processes at various locations and time points. In addition to these findings, this study also confirms that targeted proteomics applied at the community level can be used to detect weakly abundant proteins in situ. PMID:26870729

  6. Spatio-Temporal Detection of the Thiomonas Population and the Thiomonas Arsenite Oxidase Involved in Natural Arsenite Attenuation Processes in the Carnoulès Acid Mine Drainage

    PubMed Central

    Hovasse, Agnès; Bruneel, Odile; Casiot, Corinne; Desoeuvre, Angélique; Farasin, Julien; Hery, Marina; Van Dorsselaer, Alain; Carapito, Christine; Arsène-Ploetze, Florence

    2016-01-01

    The acid mine drainage (AMD) impacted creek of the Carnoulès mine (Southern France) is characterized by acid waters with a high heavy metal content. The microbial community inhabiting this AMD was extensively studied using isolation, metagenomic and metaproteomic methods, and the results showed that a natural arsenic (and iron) attenuation process involving the arsenite oxidase activity of several Thiomonas strains occurs at this site. A sensitive quantitative Selected Reaction Monitoring (SRM)-based proteomic approach was developed for detecting and quantifying the two subunits of the arsenite oxidase and RpoA of two different Thiomonas groups. Using this approach combined with FISH and pyrosequencing-based 16S rRNA gene sequence analysis, it was established here for the first time that these Thiomonas strains are ubiquitously present in minor proportions in this AMD and that they express the key enzymes involved in natural remediation processes at various locations and time points. In addition to these findings, this study also confirms that targeted proteomics applied at the community level can be used to detect weakly abundant proteins in situ. PMID:26870729

  7. Risk management in spatio-temporally varying field by true slime mold

    NASA Astrophysics Data System (ADS)

    Ito, Kentaro; Sumpter, David; Nakagaki, Toshiyuki

    Revealing how lower organisms solve complicated problems is a challenging research area, which could reveal the evolutionary origin of biological information processing. Here we report on the ability of a single-celled organism, true slime mold, to find a smart solution of risk management under spatio-temporally varying conditions. We designed test conditions under which there were three food-locations at vertices of equilateral triangle and a toxic light illuminated the organism on alternating halves of the triangle. We found that the organism behavior depended on the period of the repeated illumination, even though the total exposure time was kept the same . A simple mathematical model for the experimental results is proposed from a dynamical system point of view. We discuss our results in the context of a strategy of risk management by Physarum.

  8. Spatio-temporal properties of letter crowding

    PubMed Central

    Chung, Susana T. L.

    2016-01-01

    Crowding between adjacent letters has been investigated primarily as a spatial effect. The purpose of this study was to investigate the spatio-temporal properties of letter crowding. Specifically, we examined the systematic changes in the degradation effects in letter identification performance when adjacent letters were presented with a temporal asynchrony, as a function of letter separation and between the fovea and the periphery. We measured proportion-correct performance for identifying the middle target letter in strings of three lowercase letters at the fovea and 10° in the inferior visual field, for a range of center-to-center letter separations and a range of stimulus onset asynchronies (SOA) between the target and flanking letters (positive SOAs: target preceded flankers). As expected, the accuracy for identifying the target letters reduces with decreases in letter separation. This crowding effect shows a strong dependency on SOAs, such that crowding is maximal between 0 and ∼100 ms (depending on conditions) and diminishes for larger SOAs (positive or negative). Maximal crowding does not require the target and flanking letters to physically coexist for the entire presentation duration. Most importantly, crowding can be minimized even for closely spaced letters if there is a large temporal asynchrony between the target and flankers. The reliance of letter identification performance on SOAs and how it changes with letter separations imply that the crowding effect can be traded between space and time. Our findings are consistent with the notion that crowding should be considered as a spatio-temporal, and not simply a spatial, effect. PMID:27088895

  9. Spatio-temporal properties of letter crowding.

    PubMed

    Chung, Susana T L

    2016-04-01

    Crowding between adjacent letters has been investigated primarily as a spatial effect. The purpose of this study was to investigate the spatio-temporal properties of letter crowding. Specifically, we examined the systematic changes in the degradation effects in letter identification performance when adjacent letters were presented with a temporal asynchrony, as a function of letter separation and between the fovea and the periphery. We measured proportion-correct performance for identifying the middle target letter in strings of three lowercase letters at the fovea and 10° in the inferior visual field, for a range of center-to-center letter separations and a range of stimulus onset asynchronies (SOA) between the target and flanking letters (positive SOAs: target preceded flankers). As expected, the accuracy for identifying the target letters reduces with decreases in letter separation. This crowding effect shows a strong dependency on SOAs, such that crowding is maximal between 0 and ∼100 ms (depending on conditions) and diminishes for larger SOAs (positive or negative). Maximal crowding does not require the target and flanking letters to physically coexist for the entire presentation duration. Most importantly, crowding can be minimized even for closely spaced letters if there is a large temporal asynchrony between the target and flankers. The reliance of letter identification performance on SOAs and how it changes with letter separations imply that the crowding effect can be traded between space and time. Our findings are consistent with the notion that crowding should be considered as a spatio-temporal, and not simply a spatial, effect. PMID:27088895

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

    PubMed Central

    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 implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NOx in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy. PMID:25264424

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

    PubMed

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

    2014-09-01

    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 implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NOx in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R (2) of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy. PMID:25264424

  12. Spatio-Temporal Clustering of Monitoring Network

    NASA Astrophysics Data System (ADS)

    Hussain, I.; Pilz, J.

    2009-04-01

    Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters

  13. Cortical Spatio-Temporal Dynamics Underlying Phonological Target Detection in Humans

    ERIC Educational Resources Information Center

    Chang, Edward F.; Edwards, Erik; Nagarajan, Srikantan S.; Fogelson, Noa; Dalal, Sarang S.; Canolty, Ryan T.; Kirsch, Heidi E.; Barbaro, Nicholas M.; Knight, Robert T.

    2011-01-01

    Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential…

  14. A Spatio-Temporal Downscaler for Output From Numerical Models

    PubMed Central

    Berrocal, Veronica J.; Gelfand, Alan E.; Holland, David M.

    2010-01-01

    Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characterized by full spatial coverage of the region of interest, high temporal resolution, no missing data but consequential calibration concerns. The second tends to be sparsely collected in space with coarser temporal resolution, often with missing data but, where recorded, provides, essentially, the true value. Accommodating the spatial misalignment between the two types of data is of fundamental importance for both improved predictions of exposure as well as for evaluation and calibration of the numerical model. In this article we propose a simple, fully model-based strategy to downscale the output from numerical models to point level. The static spatial model, specified within a Bayesian framework, regresses the observed data on the numerical model output using spatially-varying coefficients which are specified through a correlated spatial Gaussian process. As an example, we apply our method to ozone concentration data for the eastern U.S. and compare it to Bayesian melding (Fuentes and Raftery 2005) and ordinary kriging (Cressie 1993; Chilès and Delfiner 1999). Our results show that our method outperforms Bayesian melding in terms of computing speed and it is superior to both Bayesian melding and ordinary kriging in terms of predictive performance; predictions obtained with our method are better calibrated and predictive intervals have empirical coverage closer to the nominal values. Moreover, our model can be easily extended to accommodate for the temporal dimension. In this regard, we consider several spatio-temporal versions of the static model. We compare them using out-of-sample predictions of ozone concentration for the eastern U.S. for the period May 1–October 15, 2001. For the best choice, we present a

  15. Automatic calibration of a parsimonious ecohydrological model in a sparse basin using the spatio-temporal variation of the NDVI

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Drylands are extensive, covering 30% of the Earth's land surface and 50% of Africa. In these water-controlled areas, vegetation plays a key role in the water cycle. Ecohydrological models provide a tool to investigate the relationships between vegetation and water resources. However, studies in Africa often face the problem that many ecohydrological models have quite extensive parametrical requirements, while available data are scarce. Therefore, there is a need for searching new sources of information such as satellite data. The advantages of the use of satellite data in dry regions has been deeply demonstrated and studied. But, the use of this kind of data forces to introduce the concept of spatio-temporal information. In this context, we have to deal with the fact that there is a lack in terms of statistics and methodologies to incorporate the spatio-temporal data during the calibration and validation processes. This research wants to be a contribution in that sense. The used ecohydrological model was calibrated in the Upper Ewaso river basin in Kenya only using NDVI (Normalized Difference Vegetation Index) data from MODIS. An automatic calibration methodology based on Singular Value Decomposition techniques was proposed in order to calibrate the model taking into account the temporal variation and, also, the spatial pattern of the observed NDVI and the simulated LAI. The obtained results have demonstrated: (1) the satellite data is an extraordinary useful tool of information and it can be used to implement ecohydrological models in dry regions; (2) the proposed model calibrated only using satellite data is able to reproduce the vegetation dynamics (in time and in space) and, also, the observed discharge at the outlet point; and (3) the proposed automatic calibration methodology works satisfactorily and it includes spatio-temporal data, in other words, it takes into account the temporal variation and the spatial pattern of the analyzed data.

  16. Research on spatio-temporal ontology based on description logic

    NASA Astrophysics Data System (ADS)

    Huang, Yongqi; Ding, Zhimin; Zhao, Zhui; Ouyang, Fucheng

    2008-10-01

    DL, short for Description Logic, is aimed at getting a balance between describing ability and reasoning complexity. Users can adopt DL to write clear and formalized concept description for domain model, which makes ontology description possess well-defined syntax and semantics and helps to resolve the problem of spatio-temporal reasoning based on ontology. This paper studies on basic theory of DL and relationship between DL and OWL at first. By analyzing spatio-temporal concepts and relationship of spatio-temporal GIS, the purpose of this paper is adopting ontology language based on DL to express spatio-temporal ontology, and employing suitable ontology-building tool to build spatio-temporal ontology. With regard to existing spatio-temporal ontology based on first-order predicate logic, we need to transform it into spatio-temporal ontology based on DL so as to make the best of existing research fruits. This paper also makes a research on translating relationships between DL and first-order predicate logic.

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Target tracking based on spatio-temporal fractal error

    NASA Astrophysics Data System (ADS)

    Allen, Brian S.

    2007-04-01

    This paper presents a novel approach to target tracking using a measurement process based on spatio-temporal fractal error. Moving targets are automatically detected using one-dimensional temporal fractal error. A template derived from the two-dimensional spatial fractal error is then extracted for a designated target to allow for correlation-based template matching in subsequent frames. The outputs of both the spatial and temporal fractal error components are combined and presented as input to a kinematic tracking filter. It is shown that combining the two outputs provides improved tracking performance in the presence of noise, occlusion, other moving objects, and when the target of interest stops moving. Furthermore, reconciliation of the spatial and temporal components also provides a useful mechanism for detecting occlusion and avoiding template drift, a problem typically present in correlation-based trackers. Results are demonstrated using airborne MWIR sequences from the DARPA VIVID dataset.

  19. Spatio-temporal characteristics of Trichel pulse at low pressure

    SciTech Connect

    He, Shoujie; Jing, Ha

    2014-01-15

    Trichel pulses are investigated using a needle-to-plane electrode geometry at low pressure. The evolution of current and voltage, the spatio-temporal discharge images of Trichel pulse are measured. The rising time and duration time in a pulse are about 10 μs and several tens of microseconds, respectively. One period of pulse can be divided into three stages: the stage preceding cathode breakdown, cathode glow formation, and discharge decaying process. Besides a cathode glow and a dark space, an anode glow is also observed. The emission spectra mainly originate from the C{sup 3}Π{sub u} → B{sup 3}Π{sub g} transition for nitrogen. In addition, the capacitances in parallel connected with the discharge cell have important influence on the pulsing frequency.

  20. Numerical spatio-temporal characterization of Listeria monocytogenes biofilms.

    PubMed

    Mosquera-Fernández, M; Rodríguez-López, P; Cabo, M L; Balsa-Canto, E

    2014-07-16

    As the structure of biofilms plays a key role in their resistance and persistence, this work presents for the first time the numerical characterization of the temporal evolution of biofilm structures formed by three Listeria monocytogenes strains on two types of stainless-steel supports, AISI 304 SS No. 2B and AISI 316 SS No. 2R. Counting methods, motility tests, fluorescence microscopy and image analysis were combined to study the dynamic evolution of biofilm formation and structure. Image analysis was performed with several well-known parameters as well as a newly defined parameter to quantify spatio-temporal distribution. The results confirm the interstrain variability of L. monocytogenes species regarding biofilm structure and structure evolution. Two types of biofilm were observed: homogeneous or flat and heterogeneous or clustered. Differences in clusters and in attachment and detachment processes were due mainly to the topography and composition of the two surfaces although an effect due to motility was also found. PMID:24858448

  1. Spatio-temporal characteristics of Trichel pulse at low pressure

    NASA Astrophysics Data System (ADS)

    He, Shoujie; Jing, Ha

    2014-01-01

    Trichel pulses are investigated using a needle-to-plane electrode geometry at low pressure. The evolution of current and voltage, the spatio-temporal discharge images of Trichel pulse are measured. The rising time and duration time in a pulse are about 10 μs and several tens of microseconds, respectively. One period of pulse can be divided into three stages: the stage preceding cathode breakdown, cathode glow formation, and discharge decaying process. Besides a cathode glow and a dark space, an anode glow is also observed. The emission spectra mainly originate from the C3Пu → B3Пg transition for nitrogen. In addition, the capacitances in parallel connected with the discharge cell have important influence on the pulsing frequency.

  2. Evaluation of Bayesian spatio-temporal latent models in small area health data.

    PubMed

    Choi, Jungsoon; Lawson, Andrew B; Cai, Bo; Hossain, Md Monir

    2011-12-01

    Health outcomes are linked to air pollution, demographic, or socioeconomic factors which vary across space and time. Thus, it is often found that relative risks in space-time health data have locally different temporal patterns. In such cases, latent modeling is useful in the disaggregation of risk profiles. In particular, spatio-temporal mixture models can help to isolate spatial clusters each of which has a homogeneous temporal pattern in relative risks. In mixture modeling, various weight structures can be used and two situations can be considered: the number of underlying components is known or unknown. In this paper, we compare spatio-temporal mixture models with different weight structures in both situations. In addition, spatio-temporal Dirichlet process mixture models are compared to them when the number of components is unknown. For comparison, we propose a set of spatial cluster detection diagnostics based on the posterior distribution of the weights. We also develop new accuracy measures to assess the recovery of true relative risks. Based on the simulation study, we examine the performance of various spatio-temporal mixture models in terms of proposed methods and goodness-of-fit measures. We apply our models to a county-level chronic obstructive pulmonary disease data set from the state of Georgia. PMID:22184483

  3. Spatio-temporal fluctuations in immiscible polymeric binary mixtures: towards the realization of a signal/information processing device with hierarchical instabilities

    NASA Astrophysics Data System (ADS)

    Maruyama, Ryota; Asakawa, Naoki

    2014-09-01

    A design of a bio-inspired signal/information processing device and the fabrication of a stochastic delay-derivative element (SDDE) using an immiscible polymer binary mixture of poly(L-lactic acid) with poly(ɛ-caprolactone) are described. A functional aspect of bio-inspired signal/information processing using both analogue electric circuits and numerical simulations are shown. Nano-thin films of polymeric binary mixtures were explored to realize the SDDE.

  4. Sensor Web for Spatio-Temporal Monitoring of a Hydrological Environment

    NASA Technical Reports Server (NTRS)

    Delin, K. A.; Jackson, S. P.; Johnson, D. W.; Burleigh, S. C.; Woodrow, R. R.; McAuley, M.; Britton, J. T.; Dohm, J. M.; Ferre, T. P. A.; Ip, Felipe

    2004-01-01

    The Sensor Web is a macroinstrument concept that allows for the spatio-temporal understanding of an environment through coordinated efforts between multiple numbers and types of sensing platforms, including, in its most general form, both orbital and terrestrial and both fixed and mobile. Each of these platforms, or pods, communicates within its local neighborhood and thus distributes information to the instrument as a whole. The result of sharing and continual processing of this information among all the Sensor Web elements will result in an information flow and a global perception of and reactive capability to the environment. As illustrated, the Sensor Web concept also allows for the recursive notion of a web of webs with individual distributed instruments possibly playing the role of a single node point on a larger Sensor Web instrument. In particular, the fusion of inexpensive, yet sophisticated, commercial technology from both the computation and telecommunication revolutions has enabled the development of practical, fielded, and embedded in situ systems that have been the focus of the NASA/JPL Sensor Webs Project (http://sensorwebs.jpl.nasa.gov/). These Sensor Webs are complete systems consisting of not only the pod elements that wirelessly communicate among themselves, but also interfacing and archiving software that allows for easy use by the end-user. Previous successful deployments have included environments as diverse as coastal regions, Antarctica, and desert areas. The Sensor Web has broad implications for Earth and planetary science and will revolutionize the way experiments and missions are conceived and performed. As part of our current efforts to develop a macrointelligence within the system, we have deployed a Sensor Web at the Central Avra Valley Storage and Recovery Project (CAVSARP) facility located west of Tucson, AZ. This particular site was selected because it is ideal for studying spatio-temporal phenomena and for providing a test site for

  5. Hirarchical Bayesian Spatio-Temporal Interpolation including Covariates

    NASA Astrophysics Data System (ADS)

    Hussain, Ijaz; Mohsin, Muhammad; Spoeck, Gunter; Pilz, Juergen

    2010-05-01

    The space-time interpolation of precipitation has significant contribution to river control,reservoir operations, forestry interest and flash flood watches etc. The changes in environmental covariates and spatial covariates make space-time estimation of precipitation a challenging task. In our earlier paper [1], we used transformed hirarchical Bayesian sapce-time interpolation method for predicting the amount of precipiation. In present paper, we modified the [2] method to include covarites which varaies with respect to space-time. The proposed method is applied to estimating space-time monthly precipitation in the monsoon periods during 1974 - 2000. The 27-years monthly average data of precipitation, temperature, humidity and wind speed are obtained from 51 monitoring stations in Pakistan. The average monthly precipitation is used response variable and temperature, humidity and wind speed are used as time varying covariates. Moreovere the spatial covarites elevation, latitude and longitude of same monitoring stations are also included. The cross-validation method is used to compare the results of transformed hierarchical Bayesian spatio-temporal interpolation with and without including environmental and spatial covariates. The software of [3] is modified to incorprate enviornmental covariates and spatil covarites. It is observed that the transformed hierarchical Bayesian method including covarites provides more accuracy than the transformed hierarchical Bayesian method without including covarites. Moreover, the five potential monitoring cites are selected based on maximum entropy sampaling design approach. References [1] I.Hussain, J.Pilz,G. Spoeck and H.L.Yu. Spatio-Temporal Interpolation of Precipitation during Monsoon Periods in Pakistan. submitted in Advances in water Resources,2009. [2] N.D. Le, W. Sun, and J.V. Zidek, Bayesian multivariate spatial interpolation with data missing by design. Journal of the Royal Statistical Society. Series B (Methodological

  6. Spatio-temporal population estimates for risk management

    NASA Astrophysics Data System (ADS)

    Cockings, Samantha; Martin, David; Smith, Alan; Martin, Rebecca

    2013-04-01

    . Unusual patterns associated with special events can also be modelled and the framework is fully volume preserving. Outputs from the model are gridded population surfaces for the specified time slice, either for total population or by sub-groups (e.g. age). Software to implement the models (SurfaceBuilder247) has been developed and pre-processed layers for typical time slices for England and Wales in 2001 and 2006 are available for UK academic purposes. The outputs and modelling framework from the Pop24/7 programme provide significant opportunities for risk management applications. For estimates of mid- to long-term cumulative population exposure to hazards, such as in flood risk mapping, populations can be produced for numerous time slices and integrated with flood models. For applications in emergency response/ management, time-specific population models can be used as seeds for agent-based models or other response/behaviour models. Estimates for sub-groups of the population also permit exploration of vulnerability through space and time. This paper outlines the requirements for effective spatio-temporal population models for risk management. It then describes the Pop24/7 framework and illustrates its potential for risk management through presentation of examples from natural and anthropogenic hazard applications. The paper concludes by highlighting key challenges for future research in this area.

  7. Unavoidable Errors: A Spatio-Temporal Analysis of Time-Course and Neural Sources of Evoked Potentials Associated with Error Processing in a Speeded Task

    ERIC Educational Resources Information Center

    Vocat, Roland; Pourtois, Gilles; Vuilleumier, Patrik

    2008-01-01

    The detection of errors is known to be associated with two successive neurophysiological components in EEG, with an early time-course following motor execution: the error-related negativity (ERN/Ne) and late positivity (Pe). The exact cognitive and physiological processes contributing to these two EEG components, as well as their functional…

  8. Spatio-temporal correlations in Coulomb clusters

    NASA Astrophysics Data System (ADS)

    Ghosal, Amit; Ash, Biswarup; Chakrabarti, Jaydeb

    Dynamical response of Coulomb-particles in nanoclusters are investigated at different temperatures characterizing their solid-like (Wigner molecule) and liquid-like behavior. The density correlations probe spatio-temporal relaxation, uncovering distinct behavior at multiple time scales in these systems. They show a stretched-Gaussian or stretched-exponential spatial decay at long times in circular and irregular traps. Interplay of confinement and long-range nature of interactions yields spatially correlated motion of the particles in string-like paths, leaving the system heterogeneous even at long times. While particles in a `solid' flow producing dynamic heterogeneities, their random motion in `liquid' defies central limit theorem. Distinguishing the two confinements, temperature dependent motional signatures serve as a criterion for the crossover between `solid' and `liquid'. The irregular Wigner molecule turns into a nearly homogeneous liquid over a much wider temperature window compared to the circular case. The temperature dependence of different relaxation time scales builds crucial insights. A phenomenological model, relating the unusual dynamics to the heterogeneous nature of the diffusivities in the system, captures much of the subtleties of our numerical simulations.

  9. Spatio-temporal registration of multiple trajectories.

    PubMed

    Padoy, Nicolas; Hager, Gregory D

    2011-01-01

    A growing number of medical datasets now contain both a spatial and a temporal dimension. Trajectories, from tools or body features, are thus becoming increasingly important for their analysis. In this paper, we are interested in recovering the spatial and temporal differences between trajectories coming from different datasets. In particular, we address the case of surgical gestures, where trajectories contain both spatial transformations and speed differences in the execution. We first define the spatio-temporal registration problem between multiple trajectories. We then propose an optimization method to jointly recover both the rigid spatial motions and the non-linear time warpings. The optimization generates also a generic trajectory template, in which spatial and temporal differences have been factored out. This approach can be potentially used to register and compare gestures side-by-side for training sessions, to build gesture trajectory models for automation by a robot, or to register the trajectories of natural or artificial markers which follow similar motions. We demonstrate its usefulness with synthetic and real experiments. In particular, we register and analyze complex surgical gestures performed by tele-manipulation using the da Vinci robot. PMID:22003611

  10. From upright to upside-down presentation: A spatio-temporal ERP study of the parametric effect of rotation on face and house processing

    PubMed Central

    Jemel, Boutheina; Coutya, Julie; Langer, Caroline; Roy, Sylvain

    2009-01-01

    Background While there is a general agreement that picture-plane inversion is more detrimental to face processing than to other seemingly complex visual objects, the origin of this effect is still largely debatable. Here, we address the question of whether face inversion reflects a quantitative or a qualitative change in processing mode by investigating the pattern of event-related potential (ERP) response changes with picture plane rotation of face and house pictures. Thorough analyses of topographical (Scalp Current Density maps, SCD) and dipole source modeling were also conducted. Results We find that whilst stimulus orientation affected in a similar fashion participants' response latencies to make face and house decisions, only the ERPs in the N170 latency range were modulated by picture plane rotation of faces. The pattern of N170 amplitude and latency enhancement to misrotated faces displayed a curvilinear shape with an almost linear increase for rotations from 0° to 90° and a dip at 112.5° up to 180° rotations. A similar discontinuity function was also described for SCD occipito-temporal and temporal current foci with no topographic distribution changes, suggesting that upright and misrotated faces activated similar brain sources. This was confirmed by dipole source analyses showing the involvement of bilateral sources in the fusiform and middle occipital gyri, the activity of which was differentially affected by face rotation. Conclusion Our N170 findings provide support for both the quantitative and qualitative accounts for face rotation effects. Although the qualitative explanation predicted the curvilinear shape of N170 modulations by face misrotations, topographical and source modeling findings suggest that the same brain regions, and thus the same mechanisms, are probably at work when processing upright and rotated faces. Taken collectively, our results indicate that the same processing mechanisms may be involved across the whole range of face

  11. SuperFly: a comparative database for quantified spatio-temporal gene expression patterns in early dipteran embryos.

    PubMed

    Cicin-Sain, Damjan; Pulido, Antonio Hermoso; Crombach, Anton; Wotton, Karl R; Jiménez-Guri, Eva; Taly, Jean-François; Roma, Guglielmo; Jaeger, Johannes

    2015-01-01

    We present SuperFly (http://superfly.crg.eu), a relational database for quantified spatio-temporal expression data of segmentation genes during early development in different species of dipteran insects (flies, midges and mosquitoes). SuperFly has a special focus on emerging non-drosophilid model systems. The database currently includes data of high spatio-temporal resolution for three species: the vinegar fly Drosophila melanogaster, the scuttle fly Megaselia abdita and the moth midge Clogmia albipunctata. At this point, SuperFly covers up to 9 genes and 16 time points per species, with a total of 1823 individual embryos. It provides an intuitive web interface, enabling the user to query and access original embryo images, quantified expression profiles, extracted positions of expression boundaries and integrated datasets, plus metadata and intermediate processing steps. SuperFly is a valuable new resource for the quantitative comparative study of gene expression patterns across dipteran species. Moreover, it provides an interesting test set for systems biologists interested in fitting mathematical gene network models to data. Both of these aspects are essential ingredients for progress toward a more quantitative and mechanistic understanding of developmental evolution. PMID:25404137

  12. Spatio-temporal characteristics of metabotropic glutamate receptor 5 traffic at or near the plasma membrane in astrocytes.

    PubMed

    Lee, William; Parpura, Vladimir

    2016-06-01

    Astrocytes can sense extracellular glutamate and respond to it by elevating their intracellular Ca(2+) levels via the activation of G-protein coupled receptors, such as metabotropic glutamate receptor 5 (mGluR5), which, during early postnatal development, is the primary receptor responsible for glutamatergic signaling in astrocytes. However, the detailed spatio-temporal characteristics of mGluR5 traffic at or near the plasma membrane of astrocytes are not well understood. To address this issue, we expressed recombinant fluorescent protein chimera of mGluR5 and used total internal reflection fluorescence microscopy on rat visual cortical astrocytes in culture. We used astrocytes lacking major processes, otherwise posing as a diffusion barrier, to infer into the general dynamics of this receptor. We found that plasmalemmal mGluR5 clusters in distinct areas, the size, and initial spatio-temporal level of occupancy of which dictated mGluR5 trafficking characteristics upon glutamate stimulation. These findings will be valuable in the interpretation of point-to-point information transfer and volume transmission between astrocytes and neurons, as well as that of paracrine signaling within astrocytic networks. PMID:27014856

  13. SuperFly: a comparative database for quantified spatio-temporal gene expression patterns in early dipteran embryos

    PubMed Central

    Cicin-Sain, Damjan; Pulido, Antonio Hermoso; Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Taly, Jean-François; Roma, Guglielmo; Jaeger, Johannes

    2015-01-01

    We present SuperFly (http://superfly.crg.eu), a relational database for quantified spatio-temporal expression data of segmentation genes during early development in different species of dipteran insects (flies, midges and mosquitoes). SuperFly has a special focus on emerging non-drosophilid model systems. The database currently includes data of high spatio-temporal resolution for three species: the vinegar fly Drosophila melanogaster, the scuttle fly Megaselia abdita and the moth midge Clogmia albipunctata. At this point, SuperFly covers up to 9 genes and 16 time points per species, with a total of 1823 individual embryos. It provides an intuitive web interface, enabling the user to query and access original embryo images, quantified expression profiles, extracted positions of expression boundaries and integrated datasets, plus metadata and intermediate processing steps. SuperFly is a valuable new resource for the quantitative comparative study of gene expression patterns across dipteran species. Moreover, it provides an interesting test set for systems biologists interested in fitting mathematical gene network models to data. Both of these aspects are essential ingredients for progress toward a more quantitative and mechanistic understanding of developmental evolution. PMID:25404137

  14. A LANGUAGE FOR MODULAR SPATIO-TEMPORAL SIMULATION (R824766)

    EPA Science Inventory

    Creating an effective environment for collaborative spatio-temporal model development will require computational systems that provide support for the user in three key areas: (1) Support for modular, hierarchical model construction and archiving/linking of simulation modules; (2)...

  15. Spatio-temporal dynamics of biogeochemical processes and air-sea CO2 fluxes in the Western English Channel based on two years of FerryBox deployment

    NASA Astrophysics Data System (ADS)

    Marrec, P.; Cariou, T.; Latimier, M.; Macé, E.; Morin, P.; Vernet, M.; Bozec, Y.

    2014-12-01

    From January 2011 to January 2013, a FerryBox system was installed on a Voluntary Observing Ship (VOS), which crossed the Western English Channel (WEC) between Roscoff (France) and Plymouth (UK) up to 3 times a day. The FerryBox continuously measured sea surface temperature (SST), sea surface salinity (SSS), dissolved oxygen (DO), fluorescence and partial pressure of CO2 (from April 2012) along the ferry track. Sensors were calibrated based on 714 bimonthly surface samplings with precisions of 0.016 for SSS, 3.3 μM for DO, 0.40 μg L- 1 for Chlorophyll-a (Chl-a) (based on fluorescence measurements) and 5.2 μatm for pCO2. Over the 2 years of deployment (900 crossings), we reported 9% of data lost due to technical issues and quality checked data was obtained to allow investigation of the dynamics of biogeochemical processes related to air-sea CO2 fluxes in the WEC. Based on this unprecedented high-frequency dataset, the physical structure of the WEC was assessed using SST anomalies and the presence of a thermal front was observed around the latitude 49.5°N, which divided the WEC in two main provinces: the seasonally stratified northern WEC (nWEC) and the all-year well-mixed southern WEC (sWEC). These hydrographical properties strongly influenced the spatial and inter-annual distributions of phytoplankton blooms, which were mainly limited by nutrients and light availability in the nWEC and the sWEC, respectively. Air-sea CO2 fluxes were also highly related to hydrographical properties of the WEC between late April and early September 2012, with the sWEC a weak source of CO2 to the atmosphere of 0.9 mmol m- 2 d- 1, whereas the nWEC acted as a sink for atmospheric CO2 of 6.9 mmol m- 2 d- 1. The study of short time-scale dynamics of air-sea CO2 fluxes revealed that an intense and short (less than 10 days) summer bloom in the nWEC contributed to 29% of the CO2 sink during the productive period, highlighting the necessity for high frequency observations in coastal

  16. Parallel indexing technique for spatio-temporal data

    NASA Astrophysics Data System (ADS)

    He, Zhenwen; Kraak, Menno-Jan; Huisman, Otto; Ma, Xiaogang; Xiao, Jing

    2013-04-01

    The requirements for efficient access and management of massive multi-dimensional spatio-temporal data in geographical information system and its applications are well recognized and researched. The most popular spatio-temporal access method is the R-Tree and its variants. However, it is difficult to use them for parallel access to multi-dimensional spatio-temporal data because R-Trees, and variants thereof, are in hierarchical structures which have severe overlapping problems in high dimensional space. We extended a two-dimensional interval space representation of intervals to a multi-dimensional parallel space, and present a set of formulae to transform spatio-temporal queries into parallel interval set operations. This transformation reduces problems of multi-dimensional object relationships to simpler two-dimensional spatial intersection problems. Experimental results show that the new parallel approach presented in this paper has superior range query performance than R*-trees for handling multi-dimensional spatio-temporal data and multi-dimensional interval data. When the number of CPU cores is larger than that of the space dimensions, the insertion performance of this new approach is also superior to R*-trees. The proposed approach provides a potential parallel indexing solution for fast data retrieval of massive four-dimensional or higher dimensional spatio-temporal data.

  17. Spatio-Temporal Variability of Water Vapor in the Free Troposphere Investigated by Dial and Ftir Vertical Soundings

    NASA Astrophysics Data System (ADS)

    Vogelmann, H.; Sussmann, R.; Trickl, T.; Reichert, A.

    2016-06-01

    We report on the free tropospheric spatio-temporal variability of water vapor investigated by the analysis of a five-year period of water vapor vertical soundings above Mt. Zugspitze (2962 m a.s.l., Germany). Our results are obtained from a combination of measurements of vertically integrated water vapor (IWV), recorded with a solar Fourier Transform InfraRed (FTIR) spectrometer and of water vapor profiles recorded with the nearby differential absorption lidar (DIAL). The special geometrical arrangement of one zenith-viewing and one sun-pointing instrument and the temporal resolution of both optical instruments allow for an investigation of the spatio-temporal variability of IWV on a spatial scale of less than one kilometer and on a time scale of less than one hour. We investigated the short-term variability of both IWV and water vapor profiles from statistical analyses. The latter was also examined by case studies with a clear assignment to certain atmospheric processes as local convection or long-range transport. This study is described in great detail in our recent publication [1].

  18. Out of equilibrium spatio-temporal correlations in the Bose-Hubbard model

    NASA Astrophysics Data System (ADS)

    Kennett, Malcolm; Fitzpatrick, Matthew

    2016-05-01

    The Bose-Hubbard model (BHM) provides a model system to study quench dynamics across a quantum phase transition. Theoretically, it has proven challenging to study spatio-temporal correlations in the BHM in dimensions higher than one. We use the Schwinger-Keldysh technique and a strong-coupling expansion to develop a two-particle irreducible formalism to allow us to study spatio-temporal correlations in both the superfluid (SF) and Mott-insulating (MI) regimes during a quantum quench for dimensions higher than one. We obtain equations of motion for both the superfluid order parameter and two-point correlation functions and present numerical results for the evolution of two-time correlation functions. We relate our results to experiments on cold atoms in optical lattices. Supported by NSERC.

  19. Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

    USGS Publications Warehouse

    Wikle, C.K.; Royle, J. Andrew

    2005-01-01

    Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

  20. Analysis of non-ergodic behaviour in spatio-temporal coherence properties of speckle light

    NASA Astrophysics Data System (ADS)

    Réfrégier, Philippe

    Spatio-temporal coherence properties of light scattered by rough surfaces that leads to speckle fluctuations are analysed. It is demonstrated that the scattered light is non-ergodic with the disorder due to the scattering process. Although the mutual coherence matrix vanishes with isotropic polarization fluctuations, it is shown that spatio-temporal coherence properties can be described with interference experiments that can be obtained between different speckles of the scattered light. For non-singular scattering processes, the maximal value of the modulus of the Wolf degree of coherence is analysed in the spatial time domain. This approach is also applied to totally unpolarized incident light with an isotropic and spatially independent scattering process. The mean value and the standard deviation of the Wolf degree of coherence are then determined from the coherence properties of the incident light.

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

    PubMed Central

    Musolesi, Mirco

    2016-01-01

    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. PMID:27429776

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

    PubMed

    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. PMID:27429776

  3. Methods for detecting saddle-type objects from spatio-temporal data: A comparative analysis

    NASA Astrophysics Data System (ADS)

    Donner, S.; Padberg, K.; Donner, R.; Kurths, J.

    2009-04-01

    The positions of saddle points and their associated invariant manifolds are known to play a crucial role in understanding transport processes in two-dimensional steady flows. Since the relevant data are often only coarsely gridded, a reliable detection of fixed points in spatio-temporal discretised vector fields is a problem of contemporary interest. Unsteady flows may additionally exhibit distinguished hyperbolic trajectories and associated manifolds - often only defined on a finite-time span - that continue to organise particle transport. As these objects are known to be Lagrangian their exact position can typically not be deduced from analysing single velocity fields. In the literature, several methods are described for approximating hyperbolic objects in steady and unsteady flows, but it is usually not clear how well they perform for a specific data set. This contribution presents a comparative analysis of the performance of three common methods (finite-time Lyapunov exponents, hyperbolicity time, leaking). In addition, a simple statistic approach based on a gradient approximation of the velocity fields is used to approximate instantaneous stagnation points. The results are evaluated with respect to the errors in the total number and location of analytically known saddle points for two different two-dimensional steady velocity fields. The reliability is statistically tested by applying multiplicative Gaussian white noise to the original data and repeating all procedures. In a second step of analysis, the different methods are applied to time-dependent versions of these velocity fields, where candidates for hyperbolic trajectories are detected and compared.

  4. Spatio-temporal correlation-based fast coding unit depth decision for high efficiency video coding

    NASA Astrophysics Data System (ADS)

    Zhou, Chengtao; Zhou, Fan; Chen, Yaowu

    2013-10-01

    The exhaustive block partition search process in high efficiency video coding (HEVC) imposes a very high computational complexity on test module of HEVC encoder (HM). A fast coding unit (CU) depth algorithm using the spatio-temporal correlation of the depth information to fasten the search process is proposed. The depth of the coding tree unit (CTU) is predicted first by using the depth information of the spatio-temporal neighbor CTUs. Then, the depth information of the adjacent CU is incorporated to skip some specific depths when encoding the sub-CTU. As compared with the original HM encoder, experimental results show that the proposed algorithm can save more than 20% encoding time on average for intra-only, low-delay, low-delay P slices, and random access cases with almost the same rate-distortion performance.

  5. Spatio-temporally smoothed coherence factor for ultrasound imaging.

    PubMed

    Xu, Mengling; Yang, Xin; Ding, Mingyue; Yuchi, Ming

    2014-01-01

    Coherence-factor-like beamforming methods, such as the coherence factor (CF), the phase coherence factor (PCF), or the sign coherence factor (SCF), have been applied to suppress side and/or grating lobes and clutter in ultrasound imaging. These adaptive weighting factors can be implemented effectively with low computational complexity to improve image contrast properties. However, because of low SNR, the resulting images may suffer from deficiencies, including reduced overall image brightness, increased speckle variance, black-region artifacts surrounding hyperechoic objects, and underestimated magnitudes of point targets. To overcome these artifacts, a new spatio-temporal smoothing procedure is introduced to the CF method. It results in a smoothed coherence factor which measures the signal coherence among the beamsums of the divided subarrays over the duration of a transmit pulse. In addition, the procedure is extended to the SCF using the sign bits of the received signals. Simulated and real experimental data sets demonstrate that the proposed methods can improve the robustness of the CF and SCF with reduced speckle variance and significant removal of black-region artifacts, while preserving the ability to suppress clutter. Consequently, image contrast can be enhanced, especially for anechoic cysts. PMID:24402905

  6. Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

    NASA Astrophysics Data System (ADS)

    Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

    2015-04-01

    Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems

  7. Reaction diffusion equation with spatio-temporal delay

    NASA Astrophysics Data System (ADS)

    Zhao, Zhihong; Rong, Erhua

    2014-07-01

    We investigate reaction-diffusion equation with spatio-temporal delays, the global existence, uniqueness and asymptotic behavior of solutions for which in relation to constant steady-state solution, included in the region of attraction of a stable steady solution. It is shown that if the delay reaction function satisfies some conditions and the system possesses a pair of upper and lower solutions then there exists a unique global solution. In terms of the maximal and minimal constant solutions of the corresponding steady-state problem, we get the asymptotic stability of reaction-diffusion equation with spatio-temporal delay. Applying this theory to Lotka-Volterra model with spatio-temporal delay, we get the global solution asymptotically tend to the steady-state problem's steady-state solution.

  8. Diverse spatio-temporal dynamical patterns of p53 and cell fate decisions

    NASA Astrophysics Data System (ADS)

    Clairambault, Jean; Eliaš, Ján

    2016-06-01

    The protein p53 as a tumour suppressor protein accumulates in cells in response to DNA damage and transactivates a large variety of genes involved in apoptosis, cell cycle regulation and numerous other processes. Recent biological observations suggest that specific spatio-temporal dynamical patterns of p53 may be associated with specific cellular response, and thus the spatio-temporal heterogeneity of the p53 dynamics contributes to the overall complexity of p53 signalling. Reaction-diffusion equations taking into account spatial representation of the cell and motion of the species inside the cell can be used to model p53 protein network and could be thus of some help to biologists and pharmacologists in anticancer treatment.

  9. A spatio-temporal model of housing prices based on individual sales transactions over time

    NASA Astrophysics Data System (ADS)

    Smith, Tony E.; Wu, Peggy

    2009-12-01

    A spatio-temporal model of housing price trends is developed that focuses on individual housing sales over time. The model allows for both the spatio-temporal lag effects of previous sales in the vicinity of each housing sale, and for general autocorrelation effects over time. A key feature of this model is the recognition of the unequal spacing between individual housing sales over time. Hence the residuals are modeled as a first-order autoregressive process with unequally spaced events. The maximum-likelihood estimation of this model is developed in detail, and tested in terms of simulations based on selected data. In addition, the model is applied to a small data set in the Philadelphia area.

  10. Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    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.

  11. Time reversal and the spatio-temporal matched filter

    SciTech Connect

    Lehman, S K; Poggio, A J; Kallman, J S; Meyer, A W; Candy, J V

    2004-03-08

    It is known that focusing of an acoustic field by a time-reversal mirror (TRM) is equivalent to a spatio-temporal matched filter under conditions where the Green's function of the field satisfies reciprocity and is time invariant, i.e. the Green's function is independent of the choice of time origin. In this letter, it is shown that both reciprocity and time invariance can be replaced by a more general constraint on the Green's function that allows a TRM to implement the spatio-temporal matched filter even when conditions are time varying.

  12. Ontology Driven Analysis of Spatio-temporal Phenomena, Aimed At Spatial Planning And Environmental Forecasting

    NASA Astrophysics Data System (ADS)

    Iwaniak, A.; Łukowicz, J.; Strzelecki, M.; Kaczmarek, I.

    2013-10-01

    Spatial planning is a crucial area for balancing civilization development with environmental protection. Spatial planning has a multidisciplinary nature. It must take into account the dynamics of the processes, which could affect the integrity of the environmental system. That is why we need a new approach to modelling phenomena occurring in space. Such approach is offered by ontologies, based on Description Logic (DL) and related to inference systems. Ontology is a system for the knowledge representation, including conceptual scheme and based on this scheme representation of reality. Ontologies can be enriched with additional logical systems. The authors present a way of building domain ontologies for spatial planning, including the representation of spatio-temporal phenomena. Description Logic is supplemented by structures of temporal logic. As a result, the analysis for exploring the topological relations between spatial objects will be extended to include temporal relationships: coincidence, precedence and succession, cause and effect relationship. Spatio-temporal models with temporal logic structures, encoded in ontologies, could be a subject of inference process, performed by semantic reasoners (reasoner engines). Spatio-temporal representations are offered, by so-called upper ontologies, such as GFO, BFO, OCHRE and others. Temporal structures provided in such ontologies, are useful for the analysis of data obtained from environmental and development monitoring systems and for description and representation of historical phenomena. They allow creating the models and scenarios of expected spatial transformation. They will support analysis for spatial development design, decision-making in spatial planning and forecasting of environmental impact.

  13. Real-Time Spatio-Temporal Twice Whitening for MIMO Energy Detector

    SciTech Connect

    Humble, Travis S; Mitra, Pramita; Barhen, Jacob; Schleck, Bryan

    2010-01-01

    While many techniques exist for local spectrum sensing of a primary user, each represents a computationally demanding task to secondary user receivers. In software-defined radio, computational complexity lengthens the time for a cognitive radio to recognize changes in the transmission environment. This complexity is even more significant for spatially multiplexed receivers, e.g., in SIMO and MIMO, where the spatio-temporal data sets grow in size with the number of antennae. Limits on power and space for the processor hardware further constrain SDR performance. In this report, we discuss improvements in spatio-temporal twice whitening (STTW) for real-time local spectrum sensing by demonstrating a form of STTW well suited for MIMO environments. We implement STTW on the Coherent Logix hx3100 processor, a multicore processor intended for low-power, high-throughput software-defined signal processing. These results demonstrate how coupling the novel capabilities of emerging multicore processors with algorithmic advances can enable real-time, software-defined processing of large spatio-temporal data sets.

  14. Impaired Spatio-Temporal Predictive Motor Timing Associated with Spinocerebellar Ataxia Type 6.

    PubMed

    Broersen, Robin; Onuki, Yoshiyuki; Abdelgabar, Abdel R; Owens, Cullen B; Picard, Samuel; Willems, Jessica; Boele, Henk-Jan; Gazzola, Valeria; Van der Werf, Ysbrand D; De Zeeuw, Chris I

    2016-01-01

    Many daily life activities demand precise integration of spatial and temporal information of sensory inputs followed by appropriate motor actions. This type of integration is carried out in part by the cerebellum, which has been postulated to play a central role in learning and timing of movements. Cerebellar damage due to atrophy or lesions may compromise forward-model processing, in which both spatial and temporal cues are used to achieve prediction for future motor states. In the present study we sought to further investigate the cerebellar contribution to predictive and reactive motor timing, as well as to learning of sequential order and temporal intervals in these tasks. We tested patients with spinocerebellar ataxia type 6 (SCA6) and healthy controls for two related motor tasks; one requiring spatio-temporal prediction of dynamic visual stimuli and another one requiring reactive timing only. We found that healthy controls established spatio-temporal prediction in their responses with high temporal precision, which was absent in the cerebellar patients. SCA6 patients showed lower predictive motor timing, coinciding with a reduced number of correct responses during the 'anticipatory' period on the task. Moreover, on the task utilizing reactive motor timing functions, control participants showed both sequence order and temporal interval learning, whereas patients only showed sequence order learning. These results suggest that SCA6 affects predictive motor timing and temporal interval learning. Our results support and highlight cerebellar contribution to timing and argue for cerebellar engagement during spatio-temporal prediction of upcoming events. PMID:27571363

  15. Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

    NASA Astrophysics Data System (ADS)

    Bhattacharjee, S.; Ghosh, S. K.

    2015-07-01

    Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

  16. Impaired Spatio-Temporal Predictive Motor Timing Associated with Spinocerebellar Ataxia Type 6

    PubMed Central

    Onuki, Yoshiyuki; Abdelgabar, Abdel R.; Owens, Cullen B.; Picard, Samuel; Willems, Jessica; Boele, Henk-Jan; Gazzola, Valeria; Van der Werf, Ysbrand D.; De Zeeuw, Chris I.

    2016-01-01

    Many daily life activities demand precise integration of spatial and temporal information of sensory inputs followed by appropriate motor actions. This type of integration is carried out in part by the cerebellum, which has been postulated to play a central role in learning and timing of movements. Cerebellar damage due to atrophy or lesions may compromise forward-model processing, in which both spatial and temporal cues are used to achieve prediction for future motor states. In the present study we sought to further investigate the cerebellar contribution to predictive and reactive motor timing, as well as to learning of sequential order and temporal intervals in these tasks. We tested patients with spinocerebellar ataxia type 6 (SCA6) and healthy controls for two related motor tasks; one requiring spatio-temporal prediction of dynamic visual stimuli and another one requiring reactive timing only. We found that healthy controls established spatio-temporal prediction in their responses with high temporal precision, which was absent in the cerebellar patients. SCA6 patients showed lower predictive motor timing, coinciding with a reduced number of correct responses during the ‘anticipatory’ period on the task. Moreover, on the task utilizing reactive motor timing functions, control participants showed both sequence order and temporal interval learning, whereas patients only showed sequence order learning. These results suggest that SCA6 affects predictive motor timing and temporal interval learning. Our results support and highlight cerebellar contribution to timing and argue for cerebellar engagement during spatio-temporal prediction of upcoming events. PMID:27571363

  17. Studies on spatio-temporal filtering of GNSS-derived coordinates

    NASA Astrophysics Data System (ADS)

    Gruszczynski, Maciej; Bogusz, Janusz; Kłos, Anna; Figurski, Mariusz

    2015-04-01

    The information about lithospheric deformations may be obtained nowadays by analysis of velocity field derived from permanent GNSS (Global Navigation Satellite System) observations. Despite developing more and more reliable models, the permanent stations residuals must still be considered as coloured noise. Meeting the GGOS (Global Geodetic Observing System) requirements, we are obliged to investigate the correlations between residuals, which are the result of common mode error (CME). This type of error may arise from mismodelling of: satellite orbits, the Earth Orientation Parameters, satellite antenna phase centre variations or unmodelling of large scale atmospheric effects. The above described together cause correlations between stochastic parts of coordinate time series obtained at stations located of even few thousands kilometres from each other. Permanent stations that meet the aforementioned terms form the regional (EPN - EUREF Permanent Network) or local sub-networks of global (IGS - International GNSS Service) network. Other authors (Wdowinski et al., 1997; Dong et al., 2006) dealt with spatio-temporal filtering and indicated three major regional filtering approaches: the stacking, the Principal Component Analysis (PCA) based on the empirical orthogonal function and the Karhunen-Loeve expansion. The need for spatio-temporal filtering is evident today, but the question whether the size of the network affects the accuracy of station's position and its velocity still remains unanswered. With the aim to determine the network's size, for which the assumption of spatial uniform distribution of CME is retained, we used stacking approach. We analyzed time series of IGS stations with daily network solutions processed by the Military University of Technology EPN Local Analysis Centre in Bernese 5.0 software and compared it with the JPL (Jet Propulsion Laboratory) PPP (Precice Point Positioning). The method we propose is based on the division of local GNSS networks

  18. Visual Experience Modulates Spatio-Temporal Dynamics of Circuit Activation

    PubMed Central

    Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

    2011-01-01

    Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its input layer (Layer 4) is reduced, as is the activation of L2/3 – the main recipient of the output from L4. Our data suggest that the decrease in spatio-temporal activation of L2/3 depends on reduced L4 output, and is not intrinsically generated within L2/3. The data shown here suggest that changes in the synaptic components of the visual cortical circuit result not only in alteration of local integration of excitatory and inhibitory inputs, but also in a significant decrease in overall circuit activation. Furthermore, our data indicate a differential effect of visual deprivation on L4 and L2/3, suggesting that while feedforward activation of L2/3 is reduced, its activation by long range, within layer inputs is unaltered. Thus, brief visual deprivation induces experience-dependent circuit re-organization by modulating not only circuit excitability, but also the spatio-temporal patterns of cortical activation within and between layers. PMID:21743804

  19. Spatio-temporal analysis of environmental radiation in Korea

    SciTech Connect

    Kim, J.Y.; Lee, B.C.; Shin, H.K.

    2007-07-01

    Geostatistical visualization of environmental radiation is a very powerful approach to explore and understand spatio-temporal variabilities of environmental radiation data. Spatial patterns of environmental radiation can be described quantitatively in terms of variogram and kriging, which are based on the idea that statistical variation of data are functions of distance. (authors)

  20. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovič, Dušan; Stopar, Bojan

    2011-02-01

    The global geospatial community is investing substantial effort in providing tools for geospatial data-quality information analysis and systematizing the criteria for geospatial data quality. The importance of these activities is increasing, especially in the last decade, which has witnessed an enormous expansion of geospatial data use in general and especially among mass users. Although geospatial data producers are striving to define and present data-quality standards to users and users increasingly need to assess the fitness for use of the data, the success of these activities is still far from what is expected or required. As a consequence, neglect or misunderstanding of data quality among users results in misuse or risks. This paper presents an aid in spatio-temporal quality evaluation through the use of spatio-temporal evaluation matrices (STEM) and the index of spatio-temporal anticipations (INSTANT) matrices. With the help of these two simple tools, geospatial data producers can systematically categorize and visualize the granularity of their spatio-temporal data, and users can present their requirements in the same way using business intelligence principles and a Web 2.0 approach. The basic principles and some examples are presented in the paper, and potential further applied research activities are briefly described.

  1. Robust visual tracking with dual spatio-temporal context trackers

    NASA Astrophysics Data System (ADS)

    Sun, Shiyan; Zhang, Hong; Yuan, Ding

    2015-12-01

    Visual tracking is a challenging problem in computer vision. Recent years, significant numbers of trackers have been proposed. Among these trackers, tracking with dense spatio-temporal context has been proved to be an efficient and accurate method. Other than trackers with online trained classifier that struggle to meet the requirement of real-time tracking task, a tracker with spatio-temporal context can run at hundreds of frames per second with Fast Fourier Transform (FFT). Nevertheless, the performance of the tracker with Spatio-temporal context relies heavily on the learning rate of the context, which restricts the robustness of the tracker. In this paper, we proposed a tracking method with dual spatio-temporal context trackers that hold different learning rate during tracking. The tracker with high learning rate could track the target smoothly when the appearance of target changes, while the tracker with low learning rate could percepts the occlusion occurring and continues to track when the target starts to emerge again. To find the target among the candidates from these two trackers, we adopt Normalized Correlation Coefficient (NCC) to evaluate the confidence of each sample. Experimental results show that the proposed algorithm performs robustly against several state-of-the-art tracking methods.

  2. Fast Spatio-Temporal Data Mining from Large Geophysical Datasets

    NASA Technical Reports Server (NTRS)

    Stolorz, P.; Mesrobian, E.; Muntz, R.; Santos, J. R.; Shek, E.; Yi, J.; Mechoso, C.; Farrara, J.

    1995-01-01

    Use of the UCLA CONQUEST (CONtent-based Querying in Space and Time) is reviewed for performance of automatic cyclone extraction and detection of spatio-temporal blocking conditions on MPP. CONQUEST is a data analysis environment for knowledge and data mining to aid in high-resolution modeling of climate modeling.

  3. Cubic map algebra functions for spatio-temporal analysis

    USGS Publications Warehouse

    Mennis, J.; Viger, R.; Tomlin, C.D.

    2005-01-01

    We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

  4. Finding Spatio-Temporal Patterns in Large Sensor Datasets

    ERIC Educational Resources Information Center

    McGuire, Michael Patrick

    2010-01-01

    Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

  5. Kernel Averaged Predictors for Spatio-Temporal Regression Models.

    PubMed

    Heaton, Matthew J; Gelfand, Alan E

    2012-12-01

    In applications where covariates and responses are observed across space and time, a common goal is to quantify the effect of a change in the covariates on the response while adequately accounting for the spatio-temporal structure of the observations. The most common approach for building such a model is to confine the relationship between a covariate and response variable to a single spatio-temporal location. However, oftentimes the relationship between the response and predictors may extend across space and time. In other words, the response may be affected by levels of predictors in spatio-temporal proximity to the response location. Here, a flexible modeling framework is proposed to capture such spatial and temporal lagged effects between a predictor and a response. Specifically, kernel functions are used to weight a spatio-temporal covariate surface in a regression model for the response. The kernels are assumed to be parametric and non-stationary with the data informing the parameter values of the kernel. The methodology is illustrated on simulated data as well as a physical data set of ozone concentrations to be explained by temperature. PMID:24010051

  6. Spatio-Temporal Signal Twice-Whitening Algorithms on the hx3100 Ultra-Low Power Multicore Processor

    SciTech Connect

    Humble, Travis S; Mitra, Pramita; Barhen, Jacob; Schleck, Bryan; Polcari, John; Traweek, Michael

    2010-01-01

    While modern signal detection theory fully accounts for spatially distributed sensors, exploiting these techniques for real-time sensing using large, underwater acoustic arrays requires advances in the spatio-temporal signal processing algorithms. In particular, the computational complexity of many spatio-temporal processing techniques is so large that conventional computer processors lack sufficient throughput to provide real-time processing of large spatio-temporal data sets. These limits are exacerbated when constraints, such as power consumption or footprint, reduce the available computational resources. In this report, we demonstrate an implementation of a signal twice-whitening algorithm that is better suited for processing spatio-temporal data in real time. We emphasize these advances by implementing data whitening on the Coherent Logix hx3100 processor, a programmable multicore processor intended for low-power and high-throughput signal processing. These results serve as an example of how the novel capabilities available from emerging multicore processor platforms can provide real-time, software-defined processing of large data sets acquired by spatially distributed sensing.

  7. An Accessible Method for Implementing Hierarchical Models with Spatio-Temporal Abundance Data

    PubMed Central

    Ross, Beth E.; Hooten, Mevin B.; Koons, David N.

    2012-01-01

    A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time. PMID:23166658

  8. An Accessible Method for Implementing Hierarchical Models with Spatio-Temporal Abundance Data

    USGS Publications Warehouse

    Ross, Beth E.; Hooten, Melvin B.; Koons, David N.

    2012-01-01

    A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.

  9. Inferring social network structure in ecological systems from spatio-temporal data streams

    PubMed Central

    Psorakis, Ioannis; Roberts, Stephen J.; Rezek, Iead; Sheldon, Ben C.

    2012-01-01

    We propose a methodology for extracting social network structure from spatio-temporal datasets that describe timestamped occurrences of individuals. Our approach identifies temporal regions of dense agent activity and links are drawn between individuals based on their co-occurrences across these ‘gathering events’. The statistical significance of these connections is then tested against an appropriate null model. Such a framework allows us to exploit the wealth of analytical and computational tools of network analysis in settings where the underlying connectivity pattern between interacting agents (commonly termed the adjacency matrix) is not given a priori. We perform experiments on two large-scale datasets (greater than 106 points) of great tit Parus major wild bird foraging records and illustrate the use of this approach by examining the temporal dynamics of pairing behaviour, a process that was previously very hard to observe. We show that established pair bonds are maintained continuously, whereas new pair bonds form at variable times before breeding, but are characterized by a rapid development of network proximity. The method proposed here is general, and can be applied to any system with information about the temporal co-occurrence of interacting agents. PMID:22696481

  10. Spatio-temporal properties and evolution of the 2013 Aigion earthquake swarm (Corinth Gulf, Greece)

    NASA Astrophysics Data System (ADS)

    Mesimeri, M.; Karakostas, V.; Papadimitriou, E.; Schaff, D.; Tsaklidis, G.

    2016-04-01

    The 2013 Aigion earthquake swarm that took place in the west part of Corinth Gulf is investigated for revealing faulting and seismicity properties of the activated area. The activity started on May 21 and was appreciably intense in the next 3 months. The recordings of the Hellenic Unified Seismological Network (HUSN), which is adequately dense around the affected area, were used to accurately locate 1501 events. The double difference ( hypoDD) technique was employed for the manually picked P and S phases along with differential times derived from waveform cross-correlation for improving location accuracy. The activated area with dimensions 6 × 2 km is located approximately 5 km SE of Aigion. Focal mechanisms of 77 events with M ≥ 2.0 were determined from P wave first motions and used for the geometry identification of the ruptured segments. Spatio-temporal distribution of earthquakes revealed an eastward and westward hypocentral migration from the starting point suggesting the division of the seismic swarm into four major clusters. The hypocentral migration was corroborated by the Coulomb stress change calculation, indicating that four fault segments involved in the rupture process successively failed by stress change encouragement. Examination of fluid flow brought out that it cannot be unambiguously considered as the driving mechanism for the successive failures.

  11. Identifying spatio-temporal patterns of transboundary disease spread: examples using avian influenza H5N1 outbreaks

    PubMed Central

    Farnsworth, Matthew L.; Ward, Michael P.

    2009-01-01

    Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic avian influenza H5N1 outbreaks in village poultry in Romania, 2005–2006, spatio-temporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported. PMID:19210952

  12. High spatio-temporal resolution observations of crater lake temperatures at Kawah Ijen volcano, East Java, Indonesia

    NASA Astrophysics Data System (ADS)

    Lewicki, Jennifer L.; Caudron, Corentin; van Hinsberg, Vincent J.; Hilley, George E.

    2016-08-01

    The crater lake of Kawah Ijen volcano, East Java, Indonesia, has displayed large and rapid changes in temperature at point locations during periods of unrest, but measurement techniques employed to date have not resolved how the lake's thermal regime has evolved over both space and time. We applied a novel approach for mapping and monitoring variations in crater lake apparent surface ("skin") temperatures at high spatial (˜32 cm) and temporal (every 2 min) resolution at Kawah Ijen on 18 September 2014. We used a ground-based FLIR T650sc camera with digital and thermal infrared (TIR) sensors from the crater rim to collect (1) a set of visible imagery around the crater during the daytime and (2) a time series of co-located visible and TIR imagery at one location from pre-dawn to daytime. We processed daytime visible imagery with the Structure-from-Motion photogrammetric method to create a digital elevation model onto which the time series of TIR imagery was orthorectified and georeferenced. Lake apparent skin temperatures typically ranged from ˜21 to 33 °C. At two locations, apparent skin temperatures were ˜4 and 7 °C less than in situ lake temperature measurements at 1.5 and 5-m depth, respectively. These differences, as well as the large spatio-temporal variations observed in skin temperatures, were likely largely associated with atmospheric effects such as the evaporative cooling of the lake surface and infrared absorption by water vapor and SO2. Calculations based on orthorectified TIR imagery thus yielded underestimates of volcanic heat fluxes into the lake, whereas volcanic heat fluxes estimated based on in situ temperature measurements (68 to 111 MW) were likely more representative of Kawah Ijen in a quiescent state. The ground-based imaging technique should provide a valuable tool to continuously monitor crater lake temperatures and contribute insight into the spatio-temporal evolution of these temperatures associated with volcanic activity.

  13. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    NASA Astrophysics Data System (ADS)

    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.

  14. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    NASA Astrophysics Data System (ADS)

    Schöll, Eckehard

    2001-02-01

    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.

  15. A Bayesian spatio-temporal method for disease outbreak detection

    PubMed Central

    Cooper, Gregory F

    2010-01-01

    A system that monitors a region for a disease outbreak is called a disease outbreak surveillance system. A spatial surveillance system searches for patterns of disease outbreak in spatial subregions of the monitored region. A temporal surveillance system looks for emerging patterns of outbreak disease by analyzing how patterns have changed during recent periods of time. If a non-spatial, non-temporal system could be converted to a spatio-temporal one, the performance of the system might be improved in terms of early detection, accuracy, and reliability. A Bayesian network framework is proposed for a class of space-time surveillance systems called BNST. The framework is applied to a non-spatial, non-temporal disease outbreak detection system called PC in order to create the spatio-temporal system called PCTS. Differences in the detection performance of PC and PCTS are examined. The results show that the spatio-temporal Bayesian approach performs well, relative to the non-spatial, non-temporal approach. PMID:20595315

  16. Low-rank matrix decomposition and spatio-temporal sparse recovery for STAP radar

    DOE PAGESBeta

    Sen, Satyabrata

    2015-08-04

    We develop space-time adaptive processing (STAP) methods by leveraging the advantages of sparse signal processing techniques in order to detect a slowly-moving target. We observe that the inherent sparse characteristics of a STAP problem can be formulated as the low-rankness of clutter covariance matrix when compared to the total adaptive degrees-of-freedom, and also as the sparse interference spectrum on the spatio-temporal domain. By exploiting these sparse properties, we propose two approaches for estimating the interference covariance matrix. In the first approach, we consider a constrained matrix rank minimization problem (RMP) to decompose the sample covariance matrix into a low-rank positivemore » semidefinite and a diagonal matrix. The solution of RMP is obtained by applying the trace minimization technique and the singular value decomposition with matrix shrinkage operator. Our second approach deals with the atomic norm minimization problem to recover the clutter response-vector that has a sparse support on the spatio-temporal plane. We use convex relaxation based standard sparse-recovery techniques to find the solutions. With extensive numerical examples, we demonstrate the performances of proposed STAP approaches with respect to both the ideal and practical scenarios, involving Doppler-ambiguous clutter ridges, spatial and temporal decorrelation effects. As a result, the low-rank matrix decomposition based solution requires secondary measurements as many as twice the clutter rank to attain a near-ideal STAP performance; whereas the spatio-temporal sparsity based approach needs a considerably small number of secondary data.« less

  17. Low-rank matrix decomposition and spatio-temporal sparse recovery for STAP radar

    SciTech Connect

    Sen, Satyabrata

    2015-08-04

    We develop space-time adaptive processing (STAP) methods by leveraging the advantages of sparse signal processing techniques in order to detect a slowly-moving target. We observe that the inherent sparse characteristics of a STAP problem can be formulated as the low-rankness of clutter covariance matrix when compared to the total adaptive degrees-of-freedom, and also as the sparse interference spectrum on the spatio-temporal domain. By exploiting these sparse properties, we propose two approaches for estimating the interference covariance matrix. In the first approach, we consider a constrained matrix rank minimization problem (RMP) to decompose the sample covariance matrix into a low-rank positive semidefinite and a diagonal matrix. The solution of RMP is obtained by applying the trace minimization technique and the singular value decomposition with matrix shrinkage operator. Our second approach deals with the atomic norm minimization problem to recover the clutter response-vector that has a sparse support on the spatio-temporal plane. We use convex relaxation based standard sparse-recovery techniques to find the solutions. With extensive numerical examples, we demonstrate the performances of proposed STAP approaches with respect to both the ideal and practical scenarios, involving Doppler-ambiguous clutter ridges, spatial and temporal decorrelation effects. As a result, the low-rank matrix decomposition based solution requires secondary measurements as many as twice the clutter rank to attain a near-ideal STAP performance; whereas the spatio-temporal sparsity based approach needs a considerably small number of secondary data.

  18. Spatio-temporal filtration of dynamic CT data using diffusion filters

    NASA Astrophysics Data System (ADS)

    Bruder, H.; Raupach, R.; Klotz, E.; Stierstorfer, K.; Flohr, T.

    2009-02-01

    We present a method for spatio-temporal filtration of dynamic CT data, to increase the signal-to-noise ratio (SNR) of image data at the same time maintaining image quality, in particular spatial and temporal sharpness of the images. Alternatively, the radiation dose applied to the patient can be reduced at the same time maintaining the noise level and the image sharpness. In contrast to classical methods, which generally operate on the three spatial dimensions of image data, noise statistics is improved by extending the filtration to the temporal dimension. Our approach is based on nonlinear and anisotropic diffusion filters, which are based on a model of heat diffusion adapted to medical CT data. Bilateral filters are a special class of diffusion filters, which do not need iteration to reach a convergence image, but represent the fixed point of a dedicated diffusion filter. Spatio-temporal, anisotropic bilateral filters are developed and applied to dynamic CT image data. The potential was evaluated using data from perfusion CT and cardiac dual source CT (DSCT) data, respectively. It was shown, that in perfusion CT, SNR can be improved by a factor of 4 at the same radiation dose. On basis of clinical data it was shown, that alternatively the radiation dose to the patient can be reduced by a factor of at least 2. A more accurate evaluation of the perfusion parameters blood flow, blood volume and time-to-peak is supported. In DSCT noise statistics can be improved using more projection data than needed for image reconstruction, however, as a consequence the temporal resolution is significantly impaired. Due to the anisotropy of the spatio-temporal bilateral filter temporal contrast edges between adjacent time samples are preserved, at the same time substantially smoothing image data in homogeneous regions. Also temporal contrast edges are preserved, maintaining the very high temporal resolution of DSCT acquisitions (~ 80 ms). CT examinations of the heart require

  19. A Hierarchical Bayesian Approach for Learning Sparse Spatio-Temporal Decomposition of Multichannel EEG

    PubMed Central

    Wu, Wei; Chen, Zhe; Gao, Shangkai; Brown, Emery N.

    2011-01-01

    Multichannel electroencephalography (EEG) offers a non-invasive tool to explore spatio-temporal dynamics of brain activity. With EEG recordings consisting of multiple trials, traditional signal processing approaches that ignore inter-trial variability in the data may fail to accurately estimate the underlying spatio-temporal brain patterns. Moreover, precise characterization of such inter-trial variability per se can be of high scientific value in establishing the relationship between brain activity and behavior. In this paper, a statistical modeling framework is introduced for learning spatiotemporal decomposition of multiple-trial EEG data recorded under two contrasting experimental conditions. By modeling the variance of source signals as random variables varying across trials, the proposed two-stage hierarchical Bayesian model is able to capture inter-trial amplitude variability in the data in a sparse way where a parsimonious representation of the data can be obtained. A variational Bayesian (VB) algorithm is developed for statistical inference of the hierarchical model. The efficacy of the proposed modeling framework is validated with the analysis of both synthetic and real EEG data. In the simulation study we show that even at low signal-to-noise ratios our approach is able to recover with high precision the underlying spatiotemporal patterns and the evolution of source amplitude across trials; on two brain-computer interface (BCI) data sets we show that our VB algorithm can extract physiologically meaningful spatio-temporal patterns and make more accurate predictions than other two widely used algorithms: the common spatial patterns (CSP) algorithm and the Infomax algorithm for independent component analysis (ICA). The results demonstrate that our statistical modeling framework can serve as a powerful tool for extracting brain patterns, characterizing trial-to-trial brain dynamics, and decoding brain states by exploiting useful structures in the data. PMID

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

    USGS Publications Warehouse

    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

  1. Working with Spatio-Temporal Data Type

    NASA Astrophysics Data System (ADS)

    Raza, A.

    2012-07-01

    Several aspects of spatiotemporal databases have been explored in past decades, ranging from basic data structure to query processing and indexing. But today, operational temporal GIS does not exist. The key impediments have been the complexity of integrating space and time and the lack of standards. OpenGIS standards for simple feature access (spatial type) do exist, but unlike the spatial type, standards for spatiotemporal data type do not exist. This paper explores a new approach to modeling space and time to provide the basis for implementing a temporal GIS. This approach is based on the concept of data types in databases. A data type provides constructors, accessors, and operators. Most commercial and open source databases provide data types to deal with the spatial component of a GIS, called spatial type. Oracle Spatial, DB2 Spatial Extender and Informix Spatial DataBlade, ST_Geometry for PostgreSQL and Oracle from Esri, PostGIS for PostgreSQL, etc., are some examples. This new spatiotemporal data type is called spatiotemporal type (STT). This STT is implemented in PostgreSQL, an open source relational database management system. The STT is an extension of Esri's ST_Geometry type for PostgreSQL, in which each spatial object has a life span. Constructors, accessors, and relational functions are provided to create STT and support spatial, spatiotemporal, and temporal queries. Some functions are extended based on OpenGIS standards for the spatial type. Examples are provided to demonstrate the application of these functions. The paper concludes with limitations and challenges of implementing STT.

  2. Macroscopic hotspots identification: A Bayesian spatio-temporal interaction approach.

    PubMed

    Dong, Ni; Huang, Helai; Lee, Jaeyoung; Gao, Mingyun; Abdel-Aty, Mohamed

    2016-07-01

    This study proposes a Bayesian spatio-temporal interaction approach for hotspot identification by applying the full Bayesian (FB) technique in the context of macroscopic safety analysis. Compared with the emerging Bayesian spatial and temporal approach, the Bayesian spatio-temporal interaction model contributes to a detailed understanding of differential trends through analyzing and mapping probabilities of area-specific crash trends as differing from the mean trend and highlights specific locations where crash occurrence is deteriorating or improving over time. With traffic analysis zones (TAZs) crash data collected in Florida, an empirical analysis was conducted to evaluate the following three approaches for hotspot identification: FB ranking using a Poisson-lognormal (PLN) model, FB ranking using a Bayesian spatial and temporal (B-ST) model and FB ranking using a Bayesian spatio-temporal interaction (B-ST-I) model. The results show that (a) the models accounting for space-time effects perform better in safety ranking than does the PLN model, and (b) the FB approach using the B-ST-I model significantly outperforms the B-ST approach in correctly identifying hotspots by explicitly accounting for the space-time variation in addition to the stable spatial/temporal patterns of crash occurrence. In practice, the B-ST-I approach plays key roles in addressing two issues: (a) how the identified hotspots have evolved over time and (b) the identification of areas that, whilst not yet hotspots, show a tendency to become hotspots. Finally, it can provide guidance to policy decision makers to efficiently improve zonal-level safety. PMID:27110645

  3. Clifford algebra-based spatio-temporal modelling and analysis for complex geo-simulation data

    NASA Astrophysics Data System (ADS)

    Luo, Wen; Yu, Zhaoyuan; Hu, Yong; Yuan, Linwang

    2013-10-01

    The spatio-temporal data simulating Ice-Land-Ocean interaction of Antarctic are used to demonstrate the Clifford algebra-based data model construction, spatio-temporal query and data analysis. The results suggest that Clifford algebra provides a powerful mathematical tool for the whole modelling and analysis chains for complex geo-simulation data. It can also help implement spatio-temporal analysis algorithms more clearly and simply.

  4. Spontaneous bursting: From temporal to spatio-temporal intermittency

    SciTech Connect

    Platt, N.; Hammel, S.M.

    1996-06-01

    A simple model for temporal bursting is introduced. This model invokes either dynamic or random forcing of a bifurcation parameter of some simple dynamical system in a way that makes the bifurcation parameter spend suitable amounts of time below and above the bifurcation threshold. This model is extended to coupled map lattices to produce spontaneous spatio-temporal burstings. It models physical systems which are embedded in a random background that is statistically homogeneous in space and time. An application of this model to optical turbulence is discussed. {copyright} {ital 1996 American Institute of Physics.}

  5. Spatio-Temporal Regularization for Longitudinal Registration to Subject-Specific 3d Template

    PubMed Central

    Guizard, Nicolas; Fonov, Vladimir S.; García-Lorenzo, Daniel; Nakamura, Kunio; Aubert-Broche, Bérengère; Collins, D. Louis

    2015-01-01

    Neurodegenerative diseases such as Alzheimer's disease present subtle anatomical brain changes before the appearance of clinical symptoms. Manual structure segmentation is long and tedious and although automatic methods exist, they are often performed in a cross-sectional manner where each time-point is analyzed independently. With such analysis methods, bias, error and longitudinal noise may be introduced. Noise due to MR scanners and other physiological effects may also introduce variability in the measurement. We propose to use 4D non-linear registration with spatio-temporal regularization to correct for potential longitudinal inconsistencies in the context of structure segmentation. The major contribution of this article is the use of individual template creation with spatio-temporal regularization of the deformation fields for each subject. We validate our method with different sets of real MRI data, compare it to available longitudinal methods such as FreeSurfer, SPM12, QUARC, TBM, and KNBSI, and demonstrate that spatially local temporal regularization yields more consistent rates of change of global structures resulting in better statistical power to detect significant changes over time and between populations. PMID:26301716

  6. Spatio-Temporal Equalizer for a Receiving-Antenna Feed Array

    NASA Technical Reports Server (NTRS)

    Mukai, Ryan; Lee, Dennis; Vilnrotter, Victor

    2010-01-01

    A spatio-temporal equalizer has been conceived as an improved means of suppressing multipath effects in the reception of aeronautical telemetry signals, and may be adaptable to radar and aeronautical communication applications as well. This equalizer would be an integral part of a system that would also include a seven-element planar array of receiving feed horns centered at the focal point of a paraboloidal antenna that would be nominally aimed at or near the aircraft that would be the source of the signal that one seeks to receive (see Figure 1). This spatio-temporal equalizer would consist mostly of a bank of seven adaptive finite-impulse-response (FIR) filters one for each element in the array - and the outputs of the filters would be summed (see Figure 2). The combination of the spatial diversity of the feedhorn array and the temporal diversity of the filter bank would afford better multipath-suppression performance than is achievable by means of temporal equalization alone. The seven-element feed array would supplant the single feed horn used in a conventional paraboloidal ground telemetry-receiving antenna. The radio-frequency telemetry signals re ceiv ed by the seven elements of the array would be digitized, converted to complex baseband form, and sent to the FIR filter bank, which would adapt itself in real time to enable reception of telemetry at a low bit error rate, even in the presence of multipath of the type found at many flight test ranges.

  7. Spatio-Temporal Expression Pattern of Frizzled Receptors after Contusive Spinal Cord Injury in Adult Rats

    PubMed Central

    Arenas, Ernest; Rodriguez, Francisco Javier

    2012-01-01

    Background Wnt proteins are a large family of molecules that are critically involved in multiple central nervous system (CNS) developmental processes. Experimental evidences suggest a role for this family of proteins in many CNS disorders, including spinal cord injury (SCI), which is a major neuropathology owing to its high prevalence and chronic sensorimotor functional sequelae. Interestingly, most Wnt proteins and their inhibitors are expressed in the uninjured spinal cord, and their temporal expression patterns are dramatically altered after injury. However, little is known regarding the expression of their better-known receptors, the Frizzled family, after SCI. Thus, the aim of the present study was to evaluate the expression of Frizzled receptors in the damaged spinal cord. Findings Based on the evidence that Wnts are expressed in the spinal cord and are transcriptionally regulated by SCI in adulthood, we analysed the spatio-temporal mRNA and protein expression patterns of Frizzled receptors after contusive SCI using quantitative RT-PCR and single and double immunohistochemistry, respectively. Our results show that almost all of the 10 known Frizzled receptors were expressed in specific spatial patterns in the uninjured spinal cords. Moreover, the Frizzled mRNAs and proteins were expressed after SCI, although their expression patterns were altered during the temporal progression of SCI. Finally, analysis of cellular Frizzled 5 expression pattern by double immunohistochemistry showed that, in the uninjured spinal cord, this receptor was expressed in neurons, oligodendrocytes, astrocytes, microglia and NG2+ glial precursors. After injury, Frizzled 5 was not only still expressed in oligodendrocytes, astrocytes and NG2+ glial precursors but also in axons at all evaluated time points. Moreover, Frizzled 5 was expressed in reactive microglia/macrophages from 3 to 14 days post-injury. Conclusions Our data suggest the involvement of Frizzled receptors in physiological

  8. Interesting Spatio-Temporal Region Discovery Computations Over Gpu and Mapreduce Platforms

    NASA Astrophysics Data System (ADS)

    McDermott, M.; Prasad, S. K.; Shekhar, S.; Zhou, X.

    2015-07-01

    Discovery of interesting paths and regions in spatio-temporal data sets is important to many fields such as the earth and atmospheric sciences, GIS, public safety and public health both as a goal and as a preliminary step in a larger series of computations. This discovery is usually an exhaustive procedure that quickly becomes extremely time consuming to perform using traditional paradigms and hardware and given the rapidly growing sizes of today's data sets is quickly outpacing the speed at which computational capacity is growing. In our previous work (Prasad et al., 2013a) we achieved a 50 times speedup over sequential using a single GPU. We were able to achieve near linear speedup over this result on interesting path discovery by using Apache Hadoop to distribute the workload across multiple GPU nodes. Leveraging the parallel architecture of GPUs we were able to drastically reduce the computation time of a 3-dimensional spatio-temporal interest region search on a single tile of normalized difference vegetative index for Saudi Arabia. We were further able to see an almost linear speedup in compute performance by distributing this workload across several GPUs with a simple MapReduce model. This increases the speed of processing 10 fold over the comparable sequential while simultaneously increasing the amount of data being processed by 384 fold. This allowed us to process the entirety of the selected data set instead of a constrained window.

  9. Mining fuzzy association rules in spatio-temporal databases

    NASA Astrophysics Data System (ADS)

    Shu, Hong; Dong, Lin; Zhu, Xinyan

    2008-12-01

    A huge amount of geospatial and temporal data have been collected through various networks of environment monitoring stations. For instance, daily precipitation and temperature are observed at hundreds of meteorological stations in Northeastern China. However, these massive raw data from the stations are not fully utilized for meeting the requirements of human decision-making. In nature, the discovery of geographical data mining is the computation of multivariate spatio-temporal correlations through the stages of data mining. In this paper, a procedure of mining association rules in regional climate-changing databases is introduced. The methods of Kriging interpolation, fuzzy cmeans clustering, and Apriori-based logical rules extraction are employed subsequently. Formally, we define geographical spatio-temporal transactions and fuzzy association rules. Innovatively, we make fuzzy data conceptualization by means of fuzzy c-means clustering, and transform fuzzy data items with membership grades into Boolean data items with weights by means ofλ-cut sets. When the algorithm Apriori is executed on Boolean transactions with weights, fuzzy association rules are derived. Fuzzy association rules are more nature than crisp association rules for human cognition about the reality.

  10. Gait recognition using spatio-temporal silhouette-based features

    NASA Astrophysics Data System (ADS)

    Sabir, Azhin; Al-jawad, Naseer; Jassim, Sabah

    2013-05-01

    This paper presents a new algorithm for human gait recognition based on Spatio-temporal body biometric features using wavelet transforms. The proposed algorithm extracts the Gait cycle depending on the width of boundary box from a sequence of Silhouette images. Gait recognition is based on feature level fusion of three feature vectors: the gait spatio-temporal feature represented by the distances between (feet, knees, hands, shoulders, and height); binary difference between consecutive frames of the silhouette for each leg detected separately based on hamming distance; a vector of statistical parameters captured from the wavelet low frequency domain. The fused feature vector is subjected to dimension reduction using linear discriminate analysis. The Nearest Neighbour with a certain threshold used for classification. The threshold is obtained by experiment from a set of data captured from the CASIA database. We shall demonstrate that our method provides a non-traditional identification based on certain threshold to classify the outsider members as non-classified members.

  11. The spatio-temporal spectrum of turbulent flows.

    PubMed

    Clark di Leoni, P; Cobelli, P J; Mininni, P D

    2015-12-01

    Identification and extraction of vortical structures and of waves in a disorganised flow is a mayor challenge in the study of turbulence. We present a study of the spatio-temporal behavior of turbulent flows in the presence of different restitutive forces. We show how to compute and analyse the spatio-temporal spectrum from data stemming from numerical simulations and from laboratory experiments. Four cases are considered: homogeneous and isotropic turbulence, rotating turbulence, stratified turbulence, and water wave turbulence. For homogeneous and isotropic turbulence, the spectrum allows identification of sweeping by the large-scale flow. For rotating and for stratified turbulence, the spectrum allows identification of the waves, precise quantification of the energy in the waves and in the turbulent eddies, and identification of physical mechanisms such as Doppler shift and wave absorption in critical layers. Finally, in water wave turbulence the spectrum shows a transition from gravity-capillary waves to bound waves as the amplitude of the forcing is increased. PMID:26701711

  12. Multiple dipole modeling of spatio-temporal MEG (magnetoencephalogram) data

    SciTech Connect

    Mosher, J.C. . Systems Engineering and Development Div. University of Southern California, Los Angeles, CA . Signal and Image Processing Inst.); Lewis, P.S. ); Leahy, R. . Signal and Image Processing Inst.); Singh, M. (University of Southern Californi

    1990-01-01

    An array of SQUID biomagentometers may be used to measure the spatio-temporal neuromagnetic field produced by the brain in response to a given sensory stimulus. A popular model for the neural activity that produces these fields is a set of current dipoles. We present here a common linear algebraic framework for three common spatio-temporal dipole models: moving and rotating dipoles, rotating dipoles with fixed location, and dipoles with fixed orientation and location. Our intent here is not to argue the merits of one model over another, but rather show how each model may be solved efficiently, and within the same framework as the others. In all cases, we assume that the location, orientation, and magnitude of the dipoles are unknown. We present the parameter estimation problem for these three models in a common framework, and show how, in each case, the problem may be decomposed into the estimation of the dipole locations using nonlinear minimization followed by linear estimation of the associated moment time series. Numerically efficient means of calculating the cost function are presented, and problems of model order selection and missing moments are also investigated. The methods described are demonstrated in a simulated application to a three dipole problem. 21 refs., 2 figs., 1 tab.

  13. Spatio-temporal Granger causality: a new framework

    PubMed Central

    Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

    2015-01-01

    That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

  14. Spatio-temporal Granger causality: a new framework.

    PubMed

    Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

    2013-10-01

    That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

  15. Event Detection using Twitter: A Spatio-Temporal Approach

    PubMed Central

    Cheng, Tao; Wicks, Thomas

    2014-01-01

    Background Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor. Methods This paper suggests an alternative methodology for event detection using space-time scan statistics (STSS). This technique looks for clusters within the dataset across both space and time, regardless of tweet content. It is expected that clusters of tweets will emerge during spatio-temporally relevant events, as people will tweet more than expected in order to describe the event and spread information. The special event used as a case study is the 2013 London helicopter crash. Results and Conclusion A spatio-temporally significant cluster is found relating to the London helicopter crash. Although the cluster only remains significant for a relatively short time, it is rich in information, such as important key words and photographs. The method also detects other special events such as football matches, as well as train and flight delays from Twitter data. These findings demonstrate that STSS is an effective approach to analysing Twitter data for event detection. PMID:24893168

  16. A GRASS GIS based Spatio-Temporal Algebra for Raster-, 3D Raster- and Vector Time Series Data

    NASA Astrophysics Data System (ADS)

    Leppelt, Thomas; Gebbert, Sören

    2015-04-01

    Enhancing the well known and widely used map algebra proposed by Dr. Charles Dana Tomlin [1] with the time dimension is an ongoing research topic. The efficient processing of large time series of raster, 3D raster and vector datasets, e. g. raster datasets for temperature or precipitations on continental scale, requires a sophisticated spatio-temporal algebra that is capable of handling datasets with different temporal granularities and spatio-temporal extents. With the temporal enabled GRASS GIS [2] and the GRASS GIS Temporal Framework new spatio-temporal data types are available in GRASS GIS 7, called space time datasets. These space time datasets represent time series of raster, 3D raster and vector map layers. Furthermore the temporal framework provides a wide range of functionalities to support the implementation of a temporal algebra. While spatial capabilities of GRASS GIS are used to perform the spatial processing of the time stamped map layers that are registered in a space time dataset, the temporal processing is provided by the GRASS GIS temporal framework that supports time intervals and time instances. Mixing time instance and time intervals as well as gaps, overlapping or inclusion of intervals and instances is possible. Hence this framework allows an arbitrary layout of the time dimension. We implemented two ways to process space time datasets with arbitrary temporal layout, the temporal topology and the granularity based spatio-temporal algebra. The algebra provides the functionality to define complex spatio-temporal topological operators that process time and space in a single expression. The algebra includes methods to select map layers from space time datasets based on their temporal relations, to temporally shift time stamped map layers, to create temporal buffer and to snap time instances of time stamped map layers to create a valid temporal topology. In addition spatio-temporal operations can be evaluated within conditional statements. These

  17. Spatio-temporal dynamics of fructan metabolism in developing barley grains.

    PubMed

    Peukert, Manuela; Thiel, Johannes; Peshev, Darin; Weschke, Winfriede; Van den Ende, Wim; Mock, Hans-Peter; Matros, Andrea

    2014-09-01

    Barley (Hordeum vulgare) grain development follows a series of defined morphological and physiological stages and depends on the supply of assimilates (mainly sucrose) from the mother plant. Here, spatio-temporal patterns of sugar distributions were investigated by mass spectrometric imaging, targeted metabolite analyses, and transcript profiling of microdissected grain tissues. Distinct spatio-temporal sugar balances were observed, which may relate to differentiation and grain filling processes. Notably, various types of oligofructans showed specific distribution patterns. Levan- and graminan-type oligofructans were synthesized in the cellularized endosperm prior to the commencement of starch biosynthesis, while during the storage phase, inulin-type oligofructans accumulated to a high concentration in and around the nascent endosperm cavity. In the shrunken endosperm mutant seg8, with a decreased sucrose flux toward the endosperm, fructan accumulation was impaired. The tight partitioning of oligofructan biosynthesis hints at distinct functions of the various fructan types in the young endosperm prior to starch accumulation and in the endosperm transfer cells that accomplish the assimilate supply toward the endosperm at the storage phase. PMID:25271242

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

    PubMed

    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. PMID:27100003

  19. Spatio-temporal representativeness of euphotic depth in situ sampling in transitional coastal waters

    NASA Astrophysics Data System (ADS)

    Luhtala, Hanna; Tolvanen, Harri

    2016-06-01

    In dynamic coastal waters, the representativeness of spot sampling is limited to the measurement time and place due to local heterogeneity and irregular water property fluctuations. We assessed the representativeness of in situ sampling by analysing spot-sampled depth profiles of photosynthetically active radiation (PAR) in dynamic coastal archipelago waters in the south-western Finnish coast of the Baltic Sea. First, we assessed the role of spatio-temporality within the underwater light dynamics. As a part of this approach, an anomaly detection procedure was tested on a dataset including a large archipelago area and extensive temporal coverage throughout the ice-free season. The results suggest that euphotic depth variability should be treated as a spatio-temporal process rather than considering spatial and temporal dimensions separately. Second, we assessed the representativeness of spot sampling through statistical analysis of comparative data from spatially denser sampling on three test sites on two optically different occasions. The datasets revealed variability in different dimensions and scales. The suitability of a dataset to reveal wanted phenomena can usually be improved by careful planning and by clearly defining the data sampling objectives beforehand. Nonetheless, conducting a sufficient in situ sampling in dynamic coastal area is still challenging: detecting the general patterns at all the relevant dimensions is complicated by the randomness effect, which reduces the reliability of spot samples on a more detailed scale. Our results indicate that good representativeness of a euphotic depth sampling location is not a stable feature in a highly dynamic environment.

  20. Spatio-Temporal Dynamics of Fructan Metabolism in Developing Barley Grains[W

    PubMed Central

    Peukert, Manuela; Thiel, Johannes; Peshev, Darin; Weschke, Winfriede; Van den Ende, Wim; Mock, Hans-Peter; Matros, Andrea

    2014-01-01

    Barley (Hordeum vulgare) grain development follows a series of defined morphological and physiological stages and depends on the supply of assimilates (mainly sucrose) from the mother plant. Here, spatio-temporal patterns of sugar distributions were investigated by mass spectrometric imaging, targeted metabolite analyses, and transcript profiling of microdissected grain tissues. Distinct spatio-temporal sugar balances were observed, which may relate to differentiation and grain filling processes. Notably, various types of oligofructans showed specific distribution patterns. Levan- and graminan-type oligofructans were synthesized in the cellularized endosperm prior to the commencement of starch biosynthesis, while during the storage phase, inulin-type oligofructans accumulated to a high concentration in and around the nascent endosperm cavity. In the shrunken endosperm mutant seg8, with a decreased sucrose flux toward the endosperm, fructan accumulation was impaired. The tight partitioning of oligofructan biosynthesis hints at distinct functions of the various fructan types in the young endosperm prior to starch accumulation and in the endosperm transfer cells that accomplish the assimilate supply toward the endosperm at the storage phase. PMID:25271242

  1. A spatio-temporal database for diagnosing drought vulnerability in the Upper Colorado River Basin, Colorado

    NASA Astrophysics Data System (ADS)

    Sampson, K. M.; Wilhelmi, O.

    2009-12-01

    Effective drought planning and mitigation requires an understanding of water supply and demand, including historical biophysical and legal conditions that lead to water shortages among various end-users. With the goal of providing information that is useful for managing current drought risks and for adapting to changing climate, this project aims to fill the gaps in the knowledge about spatio-temporal variations in water demand patterns in the Upper Colorado River Basin (UCRB). This information will help to identify vulnerabilities in the water management structure for more targeted drought preparedness and early warning. Though monitoring of hydro-meteorological properties is important to the forecast of drought conditions, the availability of water is complicated by the administration of existing water rights. The picture is increasingly complicated by the common practice of transmountain diversion, in which water in one basin is transported to another basin for use. This presentation will discuss development of a water demand data model and a spatio-temporal database that will support topological relationships among water users and their respective sources of water supply, including transfers and exchanges. GIS processes for linking water supply to the end users and their water demands will be discussed.

  2. Mapping Spatio-Temporal Diffusion inside the Human Brain Using a Numerical Solution of the Diffusion Equation

    PubMed Central

    Zhan, Wang; Jiang, Li; Loew, Murray; Yang, Yihong

    2008-01-01

    Diffusion is an important mechanism for molecular transport in living biological tissues. Diffusion magnetic resonance imaging (dMRI) provides a unique probe to examine microscopic structures of the tissues in vivo, but current dMRI techniques usually ignore the spatio-temporal evolution process of the diffusive medium. In the present study, we demonstrate the feasibility to reveal the spatio-temporal diffusion process inside the human brain based on a numerical solution of the diffusion equation. Normal human subjects were scanned with a diffusion tensor imaging (DTI) technique on a 3-Tesla MRI scanner, and the diffusion tensor in each voxel was calculated from the DTI data. The diffusion equation, a partial-derivative description of Fick’s Law for the diffusion process, was discretized into equivalent algebraic equations. A finite-difference method was employed to obtain the numerical solution of the diffusion equation with a Crank-Nicholson iteration scheme to enhance the numerical stability. By specifying boundary and initial conditions, the spatio-temporal evolution of the diffusion process inside the brain can be virtually reconstructed. Our results exhibit similar medium profiles and diffusion coefficients as those of light fluorescence dextrans measured in integrative optical imaging experiments. The proposed method highlights the feasibility to non-invasively estimate the macroscopic diffusive transport time for a molecule in a given region of the brain. PMID:18440744

  3. Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

    PubMed

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

    2016-01-01

    The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

  4. Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

    PubMed Central

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

    2016-01-01

    The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

  5. Resolving Trends in Antarctic Ice Sheet Mass Loss and Glacio-isostatic Adjustment Through Spatio-temporal Source-separation

    NASA Astrophysics Data System (ADS)

    Bamber, J. L.; Schoen, N.; Zammit-Mangion, A.; Rougier, J.; Flament, T.; Luthcke, S. B.; Petrie, E. J.; Rémy, F.

    2013-12-01

    There remains considerable inconsistency between different methods and approaches for determining ice mass trends for Antarctica from satellite observations. There are three approaches that can provide near global coverage for mass trends: altimetry, gravimetry and mass budget calculations. All three approaches suffer from a source separation problem where other geophysical processes limit the capability of the method to resolve the origin and magnitude of a mass change. A fourth approach, GPS vertical motion, provides localised estimates of mass change due to elastic uplift and an indirect estimate of GIA. Each approach has different source separation issues and different spatio-temporal error characteristics. In principle, it should be possible to combine the data and process covariances to minimize the uncertainty in the solution and to produce robust, posterior errors for the trends. In practice, this is a challenging problem in statistics because of the large number of degrees of freedom, the variable spatial and temporal sampling between the different observations and the fact that some processes remain under-sampled, such as firn compaction. Here, we present a novel solution to this problem using the latest methods in statistical modelling of spatio-temporal processes. We use Bayesian hierarchical modelling and employ stochastic partial differential equations to capture our physical understanding of the key processes that influence our observations. Due to the huge number of observations involved (> 10^8) methods are required to reduce the dimensionality of the problem and care is required in treatment of the observations as they are not independent. Here, we focus mainly on the results rather than the full suite of methods and we present time evolving fields of surface mass balance, ice dynamic-driven mass loss, and firn compaction for the period 2003-2009, derived from a combination of ICESat, ENVISAT, GRACE, InSAR, GPS and regional climate model output

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

    NASA Astrophysics Data System (ADS)

    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

  7. [Spatio-temporal variability of habitat quality in Beijing-Tianjin-Hebei Area based on land use change].

    PubMed

    Wu, Jian-sheng; Cao, Qi-wen; Shi, Shu-qin; Huang, Xiu-lan; Lu, Zhi-qiang

    2015-11-01

    Land use change is the core content of global change. To achieve sustainable land use planning, it is necessary to evaluate the habitat quality pattern and its spatio-temporal variation resulted from land use change, which can provide basis for the formulation of land management policy. Based on the analysis of land use change from 2000 to 2010, this study investigated the spatio-temporal variation of habitat quality pattern of Beijing-Tianjin-Hebei Area. We used the watershed profile sampling points and spatial autocorrelation analysis based on watershed subdivision. The results showed that the main land use change types from 2000 to 2010 in this area included the transition from cultivated land to construction land, the transition between forest and grassland, and the transition from water bodies to cultivated land. This land use/cover change process led to the decrease of heterogeneity of landscape structure and increase of fragmentation. The overall spatial pattern of habitat quality was that southeast and south areas were relatively lower, while north and west areas were relatively higher. The analysis based on watershed profile showed that the habitat quality of each watershed presented significant difference in each part. Habitat quality of most sampling points degraded in a way, while some improved compared with 2000. In general, the habitat quality of the bottom part of Luanhe River basin, the medium part of Bai-Chaobai-Chaobaixin River basin, the medium and the bottom part of Yongding River basin and medium part of Laozhang-Fudongpai- Beipai River basin were poor and volatile, while other parts were relatively good. There was a decreasing agglomeration characteristic of distribution of habitat quality in Beijing-Tianjin-Hebei Area under the disturbance of human activities. Areas of high habitat quality in 2000 were mainly located in Luanhe River basin and top part of Baihe basin. Areas of low habitat quality were mainly located in medium and bottom part

  8. Spatio-temporal Characterization of the Motion of Beating and Fibrillating Myocardial Cells

    NASA Astrophysics Data System (ADS)

    Koss, Jordan; Coppersmith, Susan

    2000-03-01

    We discuss our spatio-temporal analysis of video images of the motion of chicken myocyte tissue cultures. These chicken myocardial cells form a standard biological model for testing the efficacy of drugs and other clinical techniques in restoring organized contraction after a simulated event of cardiac arrest. Our analysis provides a novel means for measuring the strength of regenerated contractions. Additionally, under certain circumstances, the culture of myocardial cells can be driven into a state of fibrillation. We can quantify the visually obvious fact that both the time sequence at individual points as well as the degree of synchronization of the motion at spatially separated points in normally beating tissue are quite different than those in fibrillatory tissue. We compare our work to the results of analyzing electrocardiogram (EKG) traces of fibrillations.

  9. Geostatistical Analysis of Spatio-Temporal Forest Fire Data

    NASA Astrophysics Data System (ADS)

    Vega Orozco, Carmen D.; Kanevski, Mikhail; Tonini, Marj; Conedera, Marc

    2010-05-01

    Forest fire is one of the major phenomena causing degradation of environment, landscape, natural ecosystems, human health and economy. One of the main topic in forest fire data studies deals with the detection, analysis and modelling of spatio-temporal patterns of clustering. Spatial patterns of forest fire locations, their sizes and their sequence in time are of great interest for fire prediction and for forest fire management planning and distribution in optimal way necessary resources. Currently, fires can be analyzed and monitored by using different statistical tools, for example, Ripley's k-function, fractals, Allan factor, scan statistics, etc. Some of them are adapted to temporal or spatial data and are either local or global. In the present study the main attention is paid to the application of geostatistical tools - variography and methods for the analysis of monitoring networks (MN) clustering techniques (topological, statistical and fractal measures), in order to detect and to characterize spatio-temporal forest fire patterns. The main studies performed include: a) analysis of forest fires temporal sequences; b) spatial clustering of forest fires; c) geostatistical spatial analysis of burnt areas. Variography was carried out both for temporal and spatial data. Real case study is based on the forest-fire event data from Canton of Ticino (Switzerland) for a period of 1969 to 2008. The results from temporal analysis show the presence of clustering and seasonal periodicities. Comprehensive analysis of the variograms shows an anisotropy in the direction 30° East-North where smooth changes are detected, while on the direction 30° North-West a greater variability was identified. The research was completed with an application of different MN analysis techniques including, analysis of distributions of distances between events, Morisita Index (MI), fractal dimensions (sandbox counting and box counting methods) and functional fractal dimensions, adapted and

  10. Multilevel Methodology for Simulation of Spatio-Temporal Systems with Heterogeneous Activity; Application to Spread of Valley Fever Fungus

    USGS Publications Warehouse

    Jammalamadaka, Rajanikanth

    2009-01-01

    This report consists of a dissertation submitted to the faculty of the Department of Electrical and Computer Engineering, in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Graduate College, The University of Arizona, 2008. Spatio-temporal systems with heterogeneity in their structure and behavior have two major problems associated with them. The first one is that such complex real world systems extend over very large spatial and temporal domains and consume so many computational resources to simulate that they are infeasible to study with current computational platforms. The second one is that the data available for understanding such systems is limited because they are spread over space and time making it hard to obtain micro and macro measurements. This also makes it difficult to get the data for validation of their constituent processes while simultaneously considering their global behavior. For example, the valley fever fungus considered in this dissertation is spread over a large spatial grid in the arid Southwest and typically needs to be simulated over several decades of time to obtain useful information. It is also hard to get the temperature and moisture data (which are two critical factors on which the survival of the valley fever fungus depends) at every grid point of the spatial domain over the region of study. In order to address the first problem, we develop a method based on the discrete event system specification which exploits the heterogeneity in the activity of the spatio-temporal system and which has been shown to be effective in solving relatively simple partial differential equation systems. The benefit of addressing the first problem is that it now makes it feasible to address the second problem. We address the second problem by making use of a multilevel methodology based on modeling and simulation and systems theory. This methodology helps us in the construction of models with different resolutions (base and

  11. A spatio-temporal filter approach to synchronous brain activities.

    PubMed

    Nakagawa, T; Ohashi, A

    1980-01-01

    This paper presents a mathematical mechanism for neuronal synchronization in oscillatory brain activities on the basis of the layer structures with recurrent inhibition. To begin with, a linear theory reveals that the recurrent inhibition tends to cause a synchronous uniform oscillation if the loop delay increases, and that an oscillating neuron recruits neighboring neurons by delivering synchronous inputs through the recurrent inhibition loop if the frequency is that of the selfexcitatory oscillation. Then, a quasilinearized dual wave model (DWM), employing the two-sinusoids plus bias input describing functions (TSBDF), shows the competitive relationship between the synchronous oscillation and a spatial wave that is introduced to represent normal brain activity patterns. Results of computer simulations conform well to the predictions of the DWM. Thus, synchronous brain activities are suggested to be the result of the spatio-temporal filter characteristics of the brain layer structures, modified by the neural nonlinearity. PMID:7353063

  12. Sparse cortical source localization using spatio-temporal atoms.

    PubMed

    Korats, Gundars; Ranta, Radu; Le Cam, Steven; Louis-Dorr, Valérie

    2015-08-01

    This paper addresses the problem of sparse localization of cortical sources from scalp EEG recordings. Localization algorithms use propagation model under spatial and/or temporal constraints, but their performance highly depends on the data signal-to-noise ratio (SNR). In this work we propose a dictionary based sparse localization method which uses a data driven spatio-temporal dictionary to reconstruct the measurements using Single Best Replacement (SBR) and Continuation Single Best Replacement (CSBR) algorithms. We tested and compared our methods with the well-known MUSIC and RAP-MUSIC algorithms on simulated realistic data. Tests were carried out for different noise levels. The results show that our method has a strong advantage over MUSIC-type methods in case of synchronized sources. PMID:26737185

  13. Spatio-Temporal Structure of Hooded Gull Flocks

    PubMed Central

    Yomosa, Makoto; Mizuguchi, Tsuyoshi; Hayakawa, Yoshinori

    2013-01-01

    We analyzed the spatio-temporal structure of hooded gull flocks with a portable stereo camera system. The 3-dimensional positions of individuals were reconstructed from pairs of videos. The motions of each individual were analyzed, and both gliding and flapping motions were quantified based on the velocity time series. We analyzed the distributions of the nearest neighbor’s position in terms of coordinates based on each individual’s motion. The obtained results were consistent with the aerodynamic interaction between individuals. We characterized the leader-follower relationship between individuals by a delay time to mimic the direction of a motion. A relation between the delay time and a relative position was analyzed quantitatively, which suggested the basic properties of the formation flight that maintains order in the flock. PMID:24339960

  14. High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

    NASA Astrophysics Data System (ADS)

    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.

  15. SPATIO-TEMPORAL COMPLEXITY OF THE AORTIC SINUS VORTEX

    PubMed Central

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-01-01

    The aortic sinus vortex is a classical flow structure of significant importance to aortic valve dynamics and the initiation and progression of calific aortic valve disease. We characterize the spatio-temporal characteristics of aortic sinus voxtex dynamics in relation to the viscosity of blood analog solution as well as heart rate. High resolution time-resolved (2KHz) particle image velocimetry was conducted to capture 2D particle streak videos and 2D instantaneous velocity and streamlines along the sinus midplane using a physiological but rigid aorta model fitted with a porcine bioprosthetic heart valve. Blood analog fluids used include a water-glycerin mixture and saline to elucidate the sensitivity of vortex dynamics to viscosity. Experiments were conducted to record 10 heart beats for each combination of blood analog and heart rate condition. Results show that the topological characteristics of the velocity field vary in time-scales as revealed using time bin averaged vectors and corresponding instantaneous streamlines. There exist small time-scale vortices and a large time-scale main vortex. A key flow structure observed is the counter vortex at the upstream end of the sinus adjacent to the base (lower half) of the leaflet. The spatio-temporal complexity of vortex dynamics is shown to be profoundly influenced by strong leaflet flutter during systole with a peak frequency of 200Hz and peak amplitude of 4 mm observed in the saline case. While fluid viscosity influences the length and time-scales as well as the introduction of leaflet flutter, heart rate influences the formation of counter vortex at the upstream end of the sinus. Higher heart rates are shown to reduce the strength of the counter vortex that can greatly influence the directionality and strength of shear stresses along the base of the leaflet. This study demonstrates the impact of heart rate and blood analog viscosity on aortic sinus hemodynamics. PMID:25067881

  16. Spatio-temporal activity of lightnings over Greece

    NASA Astrophysics Data System (ADS)

    Nastos, P. T.; Matsangouras, I. T.; Chronis, T. G.

    2012-04-01

    Extreme precipitation events are always associated with convective weather conditions driving to intense lightning activity: Cloud to Ground (CG), Ground to Cloud (GC) and Cloud to Cloud (CC). Thus, the study of lightnings, which typically occur during thunderstorms, gives evidence of the spatio-temporal variability of intense precipitation. Lightning is a natural phenomenon in the atmosphere, being a major cause of storm related with deaths and main trigger of forest fires during dry season. Lightning affects the many electrochemical systems of the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. An operational lightning detection network (LDN) has been established since 2007 by HNMS, consisting of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. In this study, the spatial and temporal variability of recorded lightnings (CG, GC and CC) are analyzed over Greece, during the period from January 14, 2008 to December 31, 2009, for the first time. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS). In addition to the analysis of spatio-temporal activity over Greece, the HNMS-LDN characteristics are also presented. The results of the performed analysis reveal the specific geographical sub-regions associated with lightnings incidence. Lightning activity occurs mainly during the autumn season, followed by summer and spring. Higher frequencies of flashes appear over Ionian and Aegean Sea than over land during winter period against continental mountainous regions during summer period.

  17. Spatio-temporal clustering of wildfires in Portugal

    NASA Astrophysics Data System (ADS)

    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.

  18. A Spatio-temporal Model of African Animal Trypanosomosis Risk

    PubMed Central

    Dicko, Ahmadou H.; Percoma, Lassane; Sow, Adama; Adam, Yahaya; Mahama, Charles; Sidibé, Issa; Dayo, Guiguigbaza-Kossigan; Thévenon, Sophie; Fonta, William; Sanfo, Safietou; Djiteye, Aligui; Salou, Ernest; Djohan, Vincent; Cecchi, Giuliano; Bouyer, Jérémy

    2015-01-01

    Background African animal trypanosomosis (AAT) is a major constraint to sustainable development of cattle farming in sub-Saharan Africa. The habitat of the tsetse fly vector is increasingly fragmented owing to demographic pressure and shifts in climate, which leads to heterogeneous risk of cyclical transmission both in space and time. In Burkina Faso and Ghana, the most important vectors are riverine species, namely Glossina palpalis gambiensis and G. tachinoides, which are more resilient to human-induced changes than the savannah and forest species. Although many authors studied the distribution of AAT risk both in space and time, spatio-temporal models allowing predictions of it are lacking. Methodology/Principal Findings We used datasets generated by various projects, including two baseline surveys conducted in Burkina Faso and Ghana within PATTEC (Pan African Tsetse and Trypanosomosis Eradication Campaign) national initiatives. We computed the entomological inoculation rate (EIR) or tsetse challenge using a range of environmental data. The tsetse apparent density and their infection rate were separately estimated and subsequently combined to derive the EIR using a “one layer-one model” approach. The estimated EIR was then projected into suitable habitat. This risk index was finally validated against data on bovine trypanosomosis. It allowed a good prediction of the parasitological status (r2 = 67%), showed a positive correlation but less predictive power with serological status (r2 = 22%) aggregated at the village level but was not related to the illness status (r2 = 2%). Conclusions/Significance The presented spatio-temporal model provides a fine-scale picture of the dynamics of AAT risk in sub-humid areas of West Africa. The estimated EIR was high in the proximity of rivers during the dry season and more widespread during the rainy season. The present analysis is a first step in a broader framework for an efficient risk management of climate

  19. High spatio-temporal resolution observations of crater-lake temperatures at Kawah Ijen volcano, East Java, Indonesia

    USGS Publications Warehouse

    Lewicki, Jennifer L.; Corentin Caudron; Vincent van Hinsberg; George Hilley

    2016-01-01

    The crater lake of Kawah Ijen volcano, East Java, Indonesia, has displayed large and rapid changes in temperature at point locations during periods of unrest, but measurement techniques employed to-date have not resolved how the lake’s thermal regime has evolved over both space and time. We applied a novel approach for mapping and monitoring variations in crater-lake apparent surface (“skin”) temperatures at high spatial (~32 cm) and temporal (every two minutes) resolution at Kawah Ijen on 18 September 2014. We used a ground-based FLIR T650sc camera with digital and thermal infrared (TIR) sensors from the crater rim to collect (1) a set of visible imagery around the crater during the daytime and (2) a time series of co-located visible and TIR imagery at one location from pre-dawn to daytime. We processed daytime visible imagery with the Structure-from-Motion photogrammetric method to create a digital elevation model onto which the time series of TIR imagery was orthorectified and georeferenced. Lake apparent skin temperatures typically ranged from ~21 to 33oC. At two locations, apparent skin temperatures were ~ 4 and 7 oC less than in-situ lake temperature measurements at 1.5 and 5 m depth, respectively. These differences, as well as the large spatio-temporal variations observed in skin temperatures, were likely largely associated with atmospheric effects such as evaporative cooling of the lake surface and infrared absorption by water vapor and SO2. Calculations based on orthorectified TIR imagery thus yielded underestimates of volcanic heat fluxes into the lake, whereas volcanic heat fluxes estimated based on in-situ temperature measurements (68 to 111 MW) were likely more representative of Kawah Ijen in a quiescent state. The ground-based imaging technique should provide a valuable tool to continuously monitor crater-lake temperatures and contribute insight into the spatio-temporal evolution of these temperatures associated with volcanic activity.

  20. Spatio-Temporal Transmission Patterns of Black-Band Disease in a Coral Community

    PubMed Central

    Zvuloni, Assaf; Artzy-Randrup, Yael; Stone, Lewi; Kramarsky-Winter, Esti; Barkan, Roy; Loya, Yossi

    2009-01-01

    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 10×10 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 out that

  1. A probe array for the investigation of spatio-temporal structures in drift wave turbulence

    SciTech Connect

    Latten, A.; Klinger, T.; Piel, A.; Pierre, T.

    1995-05-01

    A probe array with 64 azimuthally arranged Langmuir probes is presented as a new diagnostic tool for the investigation of drift waves. A parallel data acquisition system provides full spatio-temporal data of azimuthally propagating waves. For both regular and turbulent states of current-driven drift waves, the information provided by such space-time patterns is compared with results obtained from conventional two-point correlation methods. The probe array allows one to directly estimate the time-averaged wave number spectrum. In a turbulent state, the spectrum yields to a power law of {ital S}({ital k}){proportional_to}{ital k}{sup {minus}3.6{plus_minus}0.1}. {copyright} {ital 1995} {ital American} {ital Institute} {ital of} {ital Physics}.

  2. Final report: spatio-temporal data mining of scientific trajectory data

    SciTech Connect

    Gaffney, S; Smyth, P

    2001-01-10

    With the increasing availability of massive observational and experimental data sets (across a wide variety of scientific disciplines) there is an increasing need to provide scientists with efficient computational tools to explore such data in a systematic manner. For example, techniques such as classification and clustering are now being widely used in astronomy to categorize and organize stellar objects into groups and catalogs, which in turn provide the impetus for scientific hypothesis formation and discovery (e.g., see Fayyad, Djorgovski and Weir (1996); or Cheeseman and Stutz (1996) or Fayyad and Smyth (1999) in a more general context). Data-driven exploration of massive spatio-temporal data sets is an area where there is particular need of data mining techniques. Scientists are overwhelmed by the vast quantities of data which simulations, experiments, and observational instruments can produce. Analysis of spatio-temporal data is inherently challenging, yet most current research in data mining is focused on algorithms based on more traditional feature-vector data representations. Scientists are often not particularly interested in raw grid-level data, but rather in the phenomena and processes which are ''driving'' the data. In particular, they are often interested in the temporal and spatial evolution of specific ''spatially local'' structures of interest, e.g., birth-death processes for vortices and interfaces in fluid-flow simulations and experiments, trajectories of extra-tropical cyclones from sea-level pressure data over the Atlantic and Pacific oceans, and sunspot shape and size evolution over time from daily chromospheric images of the Sun. The ability to automatically detect, cluster, and catalog such objects in principle provides an important ''data reduction front-end'' which can convert 4-d data sets (3 spatial and 1 temporal dimension) on a massive grid to a much more abstract representation of local structures and their evolution. In turn, these

  3. A single glance at natural face images generate larger and qualitatively different category-selective spatio-temporal signatures than other ecologically-relevant categories in the human brain.

    PubMed

    Jacques, Corentin; Retter, Talia L; Rossion, Bruno

    2016-08-15

    Although humans discriminate natural images of faces from other categories at a single glance, clarifying the neural specificity and spatio-temporal dynamics of this process without low-level visual confounds remains a challenge. We recorded high-density scalp electroencephalogram while presenting natural images of various objects at a fast periodic rate (5.88images/s). In different stimulation sequences, numerous variable exemplars of three categories associated with cortical specialization in neuroimaging - faces, body parts, or houses - appeared every five images (5.88Hz/5=1.18Hz). In these fast periodic visual stimulation (FPVS) sequences, common low- and high-level visual processes between these categories and other objects are captured at the 5.88Hz frequency, while high-level category-selective responses are objectively quantified at the 1.18Hz frequency and harmonics. Category-selective responses differed quantitatively and qualitatively between faces, body parts and houses. First, they were much larger (2-4 times) for faces over the whole scalp. Second, specific and reliable scalp topographical maps of category-selective responses pointed to distinct principle neural sources for faces (ventral occipito-temporal), body parts (lateral occipito-temporal) and houses (dorso-medial occipital). Category-selective EEG responses were found at multiple time-windows from 110 to 600ms post-stimulus onset. Faces elicited the most complex spatio-temporal profile with up to four selective responses, although body parts and houses also elicited selective responses more complex than previously described. These observations indicate that a single glance at natural face images inserted in a rapid stream of natural objects generates a quantitatively and qualitatively unique category-selective spatio-temporal signature in occipito-temporal cortical areas of the human brain. PMID:27138205

  4. Big Data Standards in Action: Spatio-Temporal Analytics with EarthServer

    NASA Astrophysics Data System (ADS)

    Baumann, Peter

    2014-05-01

    In the transatlantic EarthServer initiative, a set of value-adding services on massive spatio-temporal data are being established for all Earth Sciences. Already at a volume exceeding 10 Terabyte in total, several of the services will break the 100 TB barrier this summer. The common EarthServer platform rigorously relies on the open OGC standards only. At the heart is the core OGC Big Geo Data standard, Web Coverage Service (WCS), together with its analytics extension Web Coverage Processing Service (WCPS). We present OGC's coverage data and processing model. On the example of the WCS Core Reference Implementation, rasdaman, we discuss how scalable implementations are supported. Time and Internet permitting a live demo will be included.

  5. Spatio-temporal characteristics of self-pulse in hollow cathode discharge

    NASA Astrophysics Data System (ADS)

    Jing, Ha; He, Shoujie

    2015-02-01

    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.

  6. Spatio-temporal characteristics of self-pulse in hollow cathode discharge

    SciTech Connect

    Jing, Ha; He, Shoujie

    2015-02-15

    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.

  7. Spatio-temporal interpolation of soil moisture in 3D+T using automated sensor network data

    NASA Astrophysics Data System (ADS)

    Gasch, C.; Hengl, T.; Magney, T. S.; Brown, D. J.; Gräler, B.

    2014-12-01

    Soil sensor networks provide frequent in situ measurements of dynamic soil properties at fixed locations, producing data in 2- or 3-dimensions and through time (2D+T and 3D+T). Spatio-temporal interpolation of 3D+T point data produces continuous estimates that can then be used for prediction at unsampled times and locations, as input for process models, and can simply aid in visualization of properties through space and time. Regression-kriging with 3D and 2D+T data has successfully been implemented, but currently the field of geostatistics lacks an analytical framework for modeling 3D+T data. Our objective is to develop robust 3D+T models for mapping dynamic soil data that has been collected with high spatial and temporal resolution. For this analysis, we use data collected from a sensor network installed on the R.J. Cook Agronomy Farm (CAF), a 37-ha Long-Term Agro-Ecosystem Research (LTAR) site in Pullman, WA. For five years, the sensors have collected hourly measurements of soil volumetric water content at 42 locations and five depths. The CAF dataset also includes a digital elevation model and derivatives, a soil unit description map, crop rotations, electromagnetic induction surveys, daily meteorological data, and seasonal satellite imagery. The soil-water sensor data, combined with the spatial and temporal covariates, provide an ideal dataset for developing 3D+T models. The presentation will include preliminary results and address main implementation strategies.

  8. Predicting gross primary production with high spatio-temporal resolution remote sensing datasets at regional scale

    NASA Astrophysics Data System (ADS)

    Fu, D.; Chen, B.

    2012-04-01

    resolution; (ii) the estimated GPP is produced by GR model using available reflectance data with high spatial resolution; (iii) the GR model's calibration process is done combined with SAFE model's pure footprint result and the observations of flux sites; (iv) the spatio-temporal distribution of GPP values at regional scale are predicted with specific parameters correspond to different ecosystem.

  9. Correlation analysis of spatio-temporal images for estimating two-dimensional flow velocity field in a rotating flow condition

    NASA Astrophysics Data System (ADS)

    Yu, Kwonkyu; Kim, Seojun; Kim, Dongsu

    2015-10-01

    Flow velocity estimation in actual rivers using image processing technique has been highlighted for hydrometric communities in the last decades, and this technique is called Large Scale Particle Image Velocimetry (LSPIV). Although LSPIV has been successfully tested in many flow conditions, it has addressed several limitations estimating mean flow field because of difficult flow conditions such as rotating, lack of light and seeds, and noisy flow conditions. Recently, an alternative technique named STIV to use spatio-temporal images based on successively recorded images has been introduced to overcome the limitations of LSPIV. The STIV was successfully applied to obtain one-dimensional flow component in the river for estimating streamflow discharge, where the main flow direction is known. Using the 5th order of central difference scheme, the STIV directly calculated the mean angle of slopes which appeared as strips in the spatio-temporal images and has been proved to be more reliable and efficient for the discharge estimation as compared with the conventional LSPIV. However, yet it has not been sufficiently qualified to derive two-dimensional flow field in the complex flow, such as rotating or locally unsteady flow conditions. We deemed that it was because the strips in the given spatio-temporal images from not properly oriented for main flow direction are not narrow enough or clearly visible, thus the direct estimating strip slope could give erroneous results. Thereby, the STIV has been mainly applied for obtaining one-dimensional flow component. In this regard, we proposed an alternative algorithm to estimate the mean slope angle for enhancing the capability of the STIV, which used correlation coefficient between odd and even image splits from the given spatio-temporal image. This method was named CASTI (Correlation Analysis of Spatio-Temporal Image). This paper described the step-by-step procedure of the CASTI and validated its capability for estimating two

  10. How geomorphology and groundwater level affect the spatio-temporal variability of riverine cold water patches?

    NASA Astrophysics Data System (ADS)

    Wawrzyniak, Vincent; Piégay, Hervé; Allemand, Pascal; Vaudor, Lise; Goma, Régis; Grandjean, Philippe

    2016-04-01

    Temperature is a key factor for river ecosystems. In summer, patches of cold water are formed in the river by groundwater seepage. These patches have strong ecological significance and extend to the surface water in a well-mixed riverine system. These patches can serve as thermal refuges for some fish species during summer. In this study, the temporal variability and spatial distribution of cold water patches were explored along a 50 km river reach (the lower Ain River, France) using thermal infrared airborne remote sensing. This study examines a new range of processes acting on cold water patches at different scales that have not previously been touched upon in the literature. Three airborne campaigns were conducted during the summers of 2010, 2011 and 2014. Based on these images, a large number of cold water patches were identified using an automated method. Four types of patches were observed: tributary plumes, cold side channels (former channels or point-bar backwater channels), side seeps (located directly in the river channel) and gravel bar seeps (occurring at the downstream end of gravel bars). Logistic regression was used to analyse the longitudinal distribution of cold water patches according to geomorphologic indicators reflecting current or past fluvial process. Side seeps were found to be related to the local geology. Cold side channels were correlated to contemporary and past lateral river mobility. Gravel bar seeps were related to the current development of bars and are more prevalent in wandering reaches than in single-bed incised and paved reaches. The logistic model was subsequently used to evaluate gravel bar seep variability in the past. The model suggests larger numbers of seeps in the mid-20th century when bar surface area was higher. Interannual variability in the occurrence and spatial extent of side seeps and gravel bar seeps appear to be related to groundwater level fluctuations. Cold side channels exhibited greater interannual stability

  11. Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales

    NASA Astrophysics Data System (ADS)

    Feigin, Alexander; Mukhin, Dmitry; Gavrilov, Andrey; Volodin, Evgeny; Loskutov, Evgeny

    2014-05-01

    Natural systems are in general space-distributed, and their evolution represents a broad spectrum of temporal scales. The multiscale nature may be resulted from multiplicity of mechanisms governing the system behaviour, and a large number of feedbacks and nonlinearities. A way to reveal and understand the underlying mechanisms as well as to model corresponding sub-systems is decomposition of the full (complex) system into well separated spatio-temporal patterns ("modes") that evolve with essentially different time scales. In the report a new method of a similar decomposition is discussed. The method is based on generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding space-distributed time series in basis of spatio-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points. The method is applied to decomposition of the Earth's climate system: on the base of 156 years time series of SST anomalies distributed over the globe [2] two climatic modes possessing by noticeably different time scales (3-5 and 9-11 years) are separated. For more accurate exclusion of "too slow" (and thus not represented correctly) processes from real data the numerically produced STEOF basis is used. For doing this the time series generated by the INM RAS Coupled Climate Model [3] is utilized. Relations of separated modes to ENSO and PDO are investigated. Possible development of the suggested approach in order to the separation of the modes that are nonlinearly uncorrelated is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/ 3. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm

  12. Mass Spectrometric Analysis of Spatio-Temporal Dynamics of Crustacean Neuropeptides

    PubMed Central

    OuYang, Chuanzi; Liang, Zhidan; Li, Lingjun

    2014-01-01

    Neuropeptides represent one of the largest classes of signaling molecules used by nervous systems to regulate a wide range of physiological processes. Over the past several years, mass spectrometry (MS)-based strategies have revolutionized the discovery of neuropeptides in numerous model organisms, especially in decapod crustaceans. Here, we focus our discussion on recent advances in the use of MS-based techniques to map neuropeptides in spatial domain and monitoring their dynamic changes in temporal domain. These MS-enabled investigations provide valuable information about the distribution, secretion and potential function of neuropeptides with high molecular specificity and sensitivity. In situ MS imaging and in vivo microdialysis are highlighted as key technologies for probing spatio-temporal dynamics of neuropeptides in the crustacean nervous system. This review summarizes the latest advancement in MS-based methodologies for neuropeptide analysis including typical workflow and sample preparation strategies as well as major neuropeptide families discovered in decapod crustaceans. PMID:25448012

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

    PubMed

    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. PMID:27338846

  14. Spatio-temporal generation regimes in quasi-CW Raman fiber lasers.

    PubMed

    Tarasov, Nikita; Sugavanam, Srikanth; Churkin, Dmitry

    2015-09-21

    We present experimental measurements of intensity spatio-temporal dynamics in quasi-CW Raman fiber laser. Depending on the power, the laser operates in different spatio-temporal regimes varying from partial mode-locking near the generation threshold to almost stochastic radiation and a generation of short-lived pulses at high power. The transitions between the generation regimes are evident in intensity spatio-temporal dynamics. Two-dimensional auto-correlation functions provide an additional insight into temporal and spatial properties of the observed regimes. PMID:26406625

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

    PubMed Central

    2011-01-01

    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 of the STSE design and

  16. Spatial Distribution of Tree Species Governs the Spatio-Temporal Interaction of Leaf Area Index and Soil Moisture across a Forested Landscape

    PubMed Central

    Naithani, Kusum J.; Baldwin, Doug C.; Gaines, Katie P.; Lin, Henry; Eissenstat, David M.

    2013-01-01

    Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests. PMID:23554915

  17. Spontaneous switching among multiple spatio-temporal patterns in three-oscillator systems constructed with oscillatory cells of true slime mold

    NASA Astrophysics Data System (ADS)

    Takamatsu, Atsuko

    2006-11-01

    Three-oscillator systems with plasmodia of true slime mold, Physarum polycephalum, which is an oscillatory amoeba-like unicellular organism, were experimentally constructed and their spatio-temporal patterns were investigated. Three typical spatio-temporal patterns were found: rotation ( R), partial in-phase ( PI), and partial anti-phase with double frequency ( PA). In pattern R, phase differences between adjacent oscillators were almost 120 ∘. In pattern PI, two oscillators were in-phase and the third oscillator showed anti-phase against the two oscillators. In pattern PA, two oscillators showed anti-phase and the third oscillator showed frequency doubling oscillation with small amplitude. Actually each pattern is not perfectly stable but quasi-stable. Interestingly, the system shows spontaneous switching among the multiple quasi-stable patterns. Statistical analyses revealed a characteristic in the residence time of each pattern: the histograms seem to have Gamma-like distribution form but with a sharp peak and a tail on the side of long period. That suggests the attractor of this system has complex structure composed of at least three types of sub-attractors: a “Gamma attractor”-involved with several Poisson processes, a “deterministic attractor”-the residence time is deterministic, and a “stable attractor”-each pattern is stable. When the coupling strength was small, only the Gamma attractor was observed and switching behavior among patterns R, PI, and PA almost always via an asynchronous pattern named O. A conjecture is as follows: Internal/external noise exposes each pattern of R, PI, and PA coexisting around bifurcation points: That is observed as the Gamma attractor. As coupling strength increases, the deterministic attractor appears then followed by the stable attractor, always accompanied with the Gamma attractor. Switching behavior could be caused by regular existence of the Gamma attractor.

  18. Adaptive OFDM waveform design for spatio-temporal-sparsity exploited STAP radar

    NASA Astrophysics Data System (ADS)

    Sen, Satyabrata; Barhen, Jacob

    2015-05-01

    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. 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 propose 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 propose to 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.

  19. Spatio-temporal soil moisture patterns across gradients of vegetation and topography

    NASA Astrophysics Data System (ADS)

    Hassler, Sibylle; Weiler, Markus; Blume, Theresa

    2014-05-01

    Soil moisture dynamics control hydrological processes on various scales: changes in local water storage and potential activation of preferential flow paths influence connectivity and runoff from hillslopes and ultimately the discharge response of the stream. The spatio-temporal patterns of soil moisture, however, are dependent on a combination of local parameters such as soil type, vegetation and topography as well as meteorological conditions, antecedent moisture and seasonality. In an integrative monitoring study carried out within the CAOS observatory in Luxemburg (http://www.caos-project.de/), soil moisture was measured at 21 sites with 3 soil moisture profiles each. These sites include grassland as well as forest on the one hand and cover different hillslope positions on the other hand. This setup allows us to study both vegetation and topographic effects. The spatio-temporal patterns of soil moisture were analysed using two approaches: 1) we examined temporal persistence of soil moisture patterns with rank stability plots and addressed the variability within and between sites for contrasting meteorological conditions. 2) In a next step we focused on specific hydrologic events: two periods during summer recession were distinguished, first the drying out of the soils during a period of no precipitation, but also the continuing decline even after summer rains have started. Furthermore, the soil moisture response to three different rainfall events was examined, varying in intensity and antecedent moisture conditions. The emerging contrasts in patterns were put into context of site-specific characteristics such as vegetation and topographical position to identify controls on soil moisture dynamics for our range of sites. Ultimately, linking similarity in soil moisture response in landscapes to these controls can elucidate the hydrological functioning of landscape units and thus facilitate modelling efforts.

  20. Response-mode decomposition of spatio-temporal haemodynamics.

    PubMed

    Pang, J C; Robinson, P A; Aquino, K M

    2016-05-01

    The blood oxygen-level dependent (BOLD) response to a neural stimulus is analysed using the transfer function derived from a physiologically based poroelastic model of cortical tissue. The transfer function is decomposed into components that correspond to distinct poles, each related to a response mode with a natural frequency and dispersion relation; together these yield the total BOLD response. The properties of the decomposed components provide a deeper understanding of the nature of the BOLD response, via the components' frequency dependences, spatial and temporal power spectra, and resonances. The transfer function components are then used to separate the BOLD response to a localized impulse stimulus, termed the Green function or spatio-temporal haemodynamic response function, into component responses that are explicitly related to underlying physiological quantities. The analytical results also provide a quantitative tool to calculate the linear BOLD response to an arbitrary neural drive, which is faster to implement than direct Fourier transform methods. The results of this study can be used to interpret functional magnetic resonance imaging data in new ways based on physiology, to enhance deconvolution methods and to design experimental protocols that can selectively enhance or suppress particular responses, to probe specific physiological phenomena. PMID:27170653

  1. Workload induced spatio-temporal distortions and safety of flight

    SciTech Connect

    Barrett, C.L.; Weisgerber, S.A.; Naval Weapons Center, China Lake, CA )

    1989-01-01

    A theoretical analysis of the relationship between cognitive complexity and the perception of time and distance is presented and experimentally verified. Complex tasks produce high rates of mental representation which affect the subjective sense of duration and, through the subjective time scale, the percept of distance derived from dynamic visual cues (i.e., visual cues requiring rate integration). The analysis of the interrelationship of subjective time and subjective distance yields the prediction that, as a function of cognitive complexity, distance estimates derived from dynamic visual cues will be longer than the actual distance whereas estimates based on perceived temporal duration will be shorter than the actual distance. This prediction was confirmed in an experiment in which subjects (both pilots and non-pilots) estimated distances using either temporal cues or dynamic visual cues. The distance estimation task was also combined with secondary loading tasks in order to vary the overall task complexity. The results indicated that distance estimates based on temporal cues were underestimated while estimates based on visual cues were overestimated. This spatio-temporal distortion effect increased with increases in overall task complexity. 30 refs., 6 figs., 1 tab.

  2. Spatio-temporal self-organization in mudstones.

    SciTech Connect

    Dewers, Thomas A.

    2010-12-01

    Shales and other mudstones are the most abundant rock types in sedimentary basins, yet have received comparatively little attention. Common as hydrocarbon seals, these are increasingly being targeted as unconventional gas reservoirs, caprocks for CO2 sequestration, and storage repositories for waste. The small pore and grain size, large specific surface areas, and clay mineral structures lend themselves to rapid reaction rates, high capillary pressures, and semi-permeable membrane behavior accompanying changes in stress, pressure, temperature and chemical conditions. Under far from equilibrium conditions, mudrocks display a variety of spatio-temporal self-organized phenomena arising from nonlinear thermo-mechano-chemo-hydro coupling. Beginning with a detailed examination of nano-scale pore network structures in mudstones, we discuss the dynamics behind such self-organized phenomena as pressure solitons in unconsolidated muds, chemically-induced flow self focusing and permeability transients, localized compaction, time dependent well-bore failure, and oscillatory osmotic fluxes as they occur in clay-bearing sediments. Examples are draw from experiments, numerical simulation, and the field. These phenomena bear on the ability of these rocks to serve as containment barriers.

  3. Research of spatio-temporal analysis of agricultural pest

    NASA Astrophysics Data System (ADS)

    Wang, Changwei; Li, Deren; Hu, Yueming; Wu, Xiaofang; Qi, Yu

    2009-10-01

    The increase of agricultural pest disasters in recent years has become one of major problems in agriculture harvest; how to predict and control the disasters of agricultural pest has thus attracted great research interest. Although a series of works have been done and some achievements have been attained, the knowledge in this area remains limited. The migration of agricultural pest is not only related to the time variation, but also the space; consequently, the population of agricultural pest has complex spatio-temporal characteristics. The space factor and the temporal factor must be considered at the same time in the research of dynamics changes of the pest population. Using plant hoppers as an object of study, this study employed the biological analogy deviation model to study the distribution of pest population in different periods of time in Guangdong Province. It is demonstrated that the population distribution of plant hoppers is not only related to the space location, but also has a certain direction. The result reported here offers help to the monitor, prevention and control of plant hoppers in Guangdong Provinces.

  4. Spatio-Temporal Self-Organization in Mudstones (Invited)

    NASA Astrophysics Data System (ADS)

    Dewers, T. A.

    2010-12-01

    Shales and other mudstones are the most abundant rock types in sedimentary basins, yet have received comparatively little attention. Common as hydrocarbon seals, these are increasingly being targeted as unconventional gas reservoirs, caprocks for CO2 sequestration, and storage repositories for waste. The small pore and grain size, large specific surface areas, and clay mineral structures lend themselves to rapid reaction rates, high capillary pressures, and semi-permeable membrane behavior accompanying changes in stress, pressure, temperature and chemical conditions. Under far from equilibrium conditions, mudrocks display a variety of spatio-temporal self-organized phenomena arising from nonlinear thermo-mechano-chemo-hydro coupling. Beginning with a detailed examination of nano-scale pore network structures in mudstones, we discuss the dynamics behind such self-organized phenomena as pressure solitons in unconsolidated muds, chemically-induced flow self focusing and permeability transients, localized compaction, time dependent well-bore failure, and oscillatory osmotic fluxes as they occur in clay-bearing sediments. Examples are draw from experiments, numerical simulation, and the field. These phenomena bear on the ability of these rocks to serve as containment barriers. This work is funded by the US Department of Energy, Office of Basic Energy Sciences. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000

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

    PubMed Central

    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. PMID:26442094

  6. Spatio-Temporal Multiscale Denoising of Fluoroscopic Sequence.

    PubMed

    Amiot, Carole; Girard, Catherine; Chanussot, Jocelyn; Pescatore, Jeremie; Desvignes, Michel

    2016-06-01

    In the past 20 years, a wide range of complex fluoroscopically guided procedures have shown considerable growth. Biologic effects of the exposure (radiation induced burn, cancer) lead to reduce the dose during the intervention, for the safety of patients and medical staff. However, when the dose is reduced, image quality decreases, with a high level of noise and a very low contrast. Efficient restoration and denoising algorithms should overcome this drawback. We propose a spatio-temporal filter operating in a multi-scales space. This filter relies on a first order, motion compensated, recursive temporal denoising. Temporal high frequency content is first detected and then matched over time to allow for a strong denoising in the temporal axis. We study this filter in the curvelet domain and in the dual-tree complex wavelet domain, and compare those results to state of the art methods. Quantitative and qualitative analysis on both synthetic and real fluoroscopic sequences demonstrate that the proposed filter allows a great dose reduction. PMID:26812705

  7. Spatio-temporal patterns in inclined layer convection

    NASA Astrophysics Data System (ADS)

    Subramanian, Priya; Brausch, Oliver; Daniels, Karen E.; Bodenschatz, Eberhard; Schneider, Tobias M.; Pesch, Werner

    2016-05-01

    This paper reports on a theoretical analysis of the rich variety of spatio-temporal patterns observed recently in inclined layer convection at medium Prandtl number when varying the inclination angle $\\gamma$ and the Rayleigh number $R$. The present numerical investigation of the inclined layer convection system is based on the standard Oberbeck-Boussinesq equations. The patterns are shown to originate from a complicated competition of buoyancy-driven and shear-flow driven pattern forming mechanisms. The former are expressed as \\rm{longitudinal} convection rolls with their axes oriented parallel to the incline, the latter as perpendicular \\rm{transverse} rolls. Along with conventional methods to study roll patterns and their stability, we employ direct numerical simulations in large spatial domains, comparable with the experimental ones. As a result, we determine the phase diagram of the characteristic complex 3D convection patterns above onset of convection in the $\\gamma-R$ plane, and find that it compares very well with the experiments. In particular we demonstrate that interactions of specific Fourier modes, characterized by a resonant interaction of their wavevectors in the layer plane, are key to understanding the pattern morphologies.

  8. Efficient Segmentation of Spatio-Temporal Data from Simulations

    SciTech Connect

    Fodor, I K; Kamath, C

    2003-01-15

    Detecting and tracking objects in spatio-temporal datasets is an active research area with applications in many domains. A common approach is to segment the 2D frames in order to separate the objects of interest from the background, then estimate the motion of the objects and track them over time. Most existing algorithms assume that the objects to be tracked are rigid. In many scientific simulations, however, the objects of interest evolve over time and thus pose additional challenges for the segmentation and tracking tasks. We investigate efficient segmentation methods in the context of scientific simulation data. Instead of segmenting each frame separately, we propose an incremental approach which incorporates the segmentation result from the previous time frame when segmenting the data at the current time frame. We start with the simple K-means method, then we study more complicated segmentation techniques based on Markov random fields. We compare the incremental methods to the corresponding sequential ones both in terms of the quality of the results, as well as computational complexity.

  9. Spatio-Temporal Matching for Human Pose Estimation in Video.

    PubMed

    Zhou, Feng; Torre, Fernando De la

    2016-08-01

    Detection and tracking humans in videos have been long-standing problems in computer vision. Most successful approaches (e.g., deformable parts models) heavily rely on discriminative models to build appearance detectors for body joints and generative models to constrain possible body configurations (e.g., trees). While these 2D models have been successfully applied to images (and with less success to videos), a major challenge is to generalize these models to cope with camera views. In order to achieve view-invariance, these 2D models typically require a large amount of training data across views that is difficult to gather and time-consuming to label. Unlike existing 2D models, this paper formulates the problem of human detection in videos as spatio-temporal matching (STM) between a 3D motion capture model and trajectories in videos. Our algorithm estimates the camera view and selects a subset of tracked trajectories that matches the motion of the 3D model. The STM is efficiently solved with linear programming, and it is robust to tracking mismatches, occlusions and outliers. To the best of our knowledge this is the first paper that solves the correspondence between video and 3D motion capture data for human pose detection. Experiments on the CMU motion capture, Human3.6M, Berkeley MHAD and CMU MAD databases illustrate the benefits of our method over state-of-the-art approaches. PMID:26863647

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

    USGS Publications Warehouse

    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.

  11. Spatio-temporal distribution of human lifespan in China

    PubMed Central

    Wang, Shaobin; Luo, Kunli; Liu, Yonglin

    2015-01-01

    Based on the data of latest three Chinese population censuses (1990–2010), four lifespan indicators were calculated: centenarians per one hundred thousand inhabitants (CH); longevity index (LI); the percentage of the population aged at least 80 years (ultra-octogenarian index, UOI) and life expectancy at birth (LEB). The spatio-temporal distributions of data at Chinese county level show that high-longevity areas (high values of CH and LI) and low-longevity areas (low CH and LI values) both exhibit clear non-uniformity of spatial distribution and relative immobility through time. Contrarily, the distribution of UOI and LEB shows a decline from the east to the west. The spatial autocorrelation analyses indicate less spatial dependency and several discontinuous clusters regions of high-CH and LI areas. The factors of temperature, topography and wet/dry climate lack of significant influence on CH and LI. It can be inferred that, in addition to genetic factor and living custom, some unique and long-term environmental effects may be related with high or low values of CH and LI. PMID:26346713

  12. Spatio-Temporal Measurements of Short Wind Water Waves

    NASA Astrophysics Data System (ADS)

    Rocholz, Roland; Jähne, Bernd

    2010-05-01

    Spatio-temporal measurements of wind-driven short-gravity capillary waves are reported for a wide range of experimental conditions, including wind, rain and surface slicks. The experiments were conducted in the Hamburg linear wind/wave flume in cooperation with the Institute of Oceanography at the University of Hamburg, Germany. Both components of the slope field were measured optically at a fetch of 14.4 m using a color imaging slope gauge (CISG) with a footprint of 223 x 104 mm and a resolution of 0.7 mm. The instrument was improved versus earlier versions (Jähne and Riemer (1990), Klinke (1992)) to achieve a sampling rate of 312.5 Hz, which now allows for the computation of 3D wavenumber-frequency spectra (see Rocholz (2008)). This made it possible to distinguish waves traveling in and against wind direction, which proved useful to distinguish wind waves from ring waves caused by rain drop impacts. Using a new calibration method it was possible to correct for the intrinsic nonlinearities of the instrument in the slope range up to ±1. In addition, the Modulation Transfer Function (MTF) was measured and employed for the restoration of the spectral amplitudes for wavenumbers in the range from 60 to 2300 rad/m. The spectra for pure wind conditions are generally consistent with previous measurements. But, the shape of the saturation spectra in the vicinity of k~1000 rad/m (i.e. pure capillary waves) stands in contradiction to former investigations where a sharp spectral cutoff (k^(-2) or k^(-3)) is commonly reported (e.g. Jähne and Riemer (1990)). This cutoff is reproduced by almost all semi-empirical models of the energy flux in the capillary range (e.g. Kudryavtsev et al. (1999), Apel (1994)). However, the new MTF corrected spectra show only a gentle decrease (between k^(-0.5) and k^(-1)) for k > 1000 rad/m. Therefore the question for the relative importance of different dissipation mechanisms might need a new assessment. References: J. R. Apel. An improved

  13. Spatio-temporal coupling of EEG signals in epilepsy

    NASA Astrophysics Data System (ADS)

    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.

  14. Ultrashort relativistic electron bunches and spatio-temporal radiation biology

    NASA Astrophysics Data System (ADS)

    Gauduel, Y. A.; Faure, J.; Malka, V.

    2008-08-01

    The intensive developments of terawatt Ti:Sa lasers permit to extend laser-plasma interactions into the relativistic regime, providing very-short electron or proton bunches. Experimental researches developed at the interface of laser physics and radiation biology, using the combination of sub-picosecond electron beams in the energy range 2-15 MeV with femtosecond near-IR optical pulses might conjecture the real-time investigation of penetrating radiation effects. A perfect synchronization between the particle beam (pump) and optical beam at 820 nm (probe) allows subpicosecond time resolution. This emerging domain involves high-energy radiation femtochemistry (HERF) for which the early spatial energy deposition is decisive for the prediction of cellular and tissular radiation damages. With vacuum-focused intensities of 2.7 x 1019 W cm-2 and a high energy electron total charge of 2.5 nC, radiation events have been investigated in the temporal range 10-13 - 10-10s. The early radiation effects of secondary electron on biomolecular sensors may be investigated inside sub-micrometric ionisation, considering the radial direction of Gaussian electron bunches. It is shown that short range electron-biosensor interactions lower than 10 A take place in nascent track structures triggered by penetrating radiation bunches. The very high dose delivery 1013 Gy s-1 performed with laser plasma accelerator may challenge our understanding of nanodosimetry on the time scale of molecular target motions. High-quality ultrashort penetrating radiation beams open promising opportunities for the development of spatio-temporal radiation biology, a crucial domain of cancer therapy, and would favor novating applications in nanomedicine such as highly-selective shortrange pro-drug activation.

  15. Spatio-Temporal Dynamics of Hypoxia during Radiotherapy.

    PubMed

    Kempf, Harald; Bleicher, Marcus; Meyer-Hermann, Michael

    2015-01-01

    Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment. PMID:26273841

  16. Spatio-temporal microseismicity clustering in the Cretan region

    NASA Astrophysics Data System (ADS)

    Becker, Dirk; Meier, Thomas; Rische, Martina; Bohnhoff, Marco; Harjes, Hans-Peter

    2006-09-01

    Spatio-temporal clustering of microseismicity in the central forearc of the Hellenic Subduction Zone in the area of Crete is investigated. Data for this study were gathered by temporary short period networks which were installed on the islands of Crete and Gavdos between 1996 and 2004. The similarity of waveforms is quantified systematically to identify clusters of microseismicity. Waveform similarities are calculated using an adaptive time window containing both the P- and S-wave onsets. The cluster detection is performed by applying a single linkage approach. Clusters are found in the interplate seismicity as well as in the intraplate seismicity of the continental crust in the region of the transtensional Ptolemy structure. The majority of the clusters are off the southern coast of Crete, in a region of elevated intraplate microseismic activity within the Aegean plate. Clusters in the Gavdos region are located at depths compatible with the plate interface while cluster activity in the region of the Ptolemy trench is distributed along a nearly vertical structure throughout the crust extending down to the plate interface. Most clusters show swarm-like behaviour with seismic activity confined to only a few hours or days, without a dominant earthquake and with a power law distribution of the interevent times. For the largest cluster, precise relocations of the events using travel time differences of P- and S-waves derived from waveform cross correlations reveal migration of the hypocenters. This cluster is located in the region of the Ptolemy trench and migration occurs along the strike of the trench at ˜ 500 m/day. Relocated hypocenters as well as subtle differences in the waveforms suggest an offset between the hypocenters and thus the activation of distinct patches on the rupture surface. The observed microseismicity patterns may be related to fluids being transported along the plate interface and escaping towards the surface in zones of crustal weakness (Ptolemy

  17. Spatio-Temporal Dynamics of Hypoxia during Radiotherapy

    PubMed Central

    Kempf, Harald; Bleicher, Marcus; Meyer-Hermann, Michael

    2015-01-01

    Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment. PMID:26273841

  18. Spatio-Temporal Patterns of Surface Irradiance in the Himalaya

    NASA Astrophysics Data System (ADS)

    Dobreva, I. D.; Bishop, M. P.

    2014-12-01

    Climate-glacier dynamics in the Himalaya are complex. Research indicates extreme local variability in glacier fluctuations and the presence of regional trends. The glaciers in the Karakoram Himalaya depart from world trends of glacier recession, as many are advancing or surging. Nevertheless, glacier sensitivity to climate change has yet to be quantitatively assessed given numerous controlling factors. We attempt to address part of the problem by evaluating the role of topography in explaining variations in surface irradiance. Specifically, we developed a spectral-based topographic solar radiation model that accounts for multi-scale topographic effects. We evaluate surface irradiance simulations over a multitude of glaciers across the Karakoram and Nepalese Himalaya and examine spatio-temporal patterns to determine which alpine glaciers are more susceptible to radiation forcing. Simulation results reveal that many Nepalese glaciers characterized by rapid downwasting, retreat and expanding proglacial lakes, exhibit relatively high-magnitude daily irradiance patterns spatially focused over the terminus region, while other glacier surface areas received less short-wave irradiance. These results were found to be associated with basin-scale relief conditions and topographic shielding. Altitudinal variation in glacier surface irradiance was found to increase during the later portion of the ablation season, as changes in solar geometry produce more cast shadows that protect glaciers given extreme relief. Topographic effects on surface irradiance vary significantly from glacier to glacier, demonstrating the important role of glacier and mountain geodynamics on glacier sensitivity to climate change. Spatial and altitudinal patterns, coupled with information regarding supraglacial debris distribution, depth and ice-flow velocities, may potentially explain glacier sensitivity to climate change and the local variability of glacier fluctuations in the Himalaya.

  19. Spatio-temporal representativeness of aerosol remote sensing observations

    NASA Astrophysics Data System (ADS)

    Schutgens, Nick; Gryspeerdt, Edward; Tsyro, Svetlana; Goto, Daisuke; Watson-Parris, Duncan; Weigum, Natalie; Schulz, Michael; Stier, Philip

    2016-04-01

    One characteristic of remote sensing observations is the strong intermittency with which they observe the same scene. Due to unfavourable conditions (due to e.g. low visible light, cloudiness or high surface albedo), sampling constraints (due to e.g. polar orbits) or instrument malfunction or maintenance, gaps in the observing record of hours to months exist. At the same time, satellite L3 products often are spatial aggregates over considerable distances (e.g. 1 by 1 degree). We study the impact of spatio-temporal sampling of observations on their representativeness: i.e. how well can satellite products represent the large scale (~ 100 by 100 km) aerosol field over periods of days, months, or years. This study was conducted by using diverse global and regional aerosol models as a truth and sub-sample them according to actual observations. In this way, we have been able to study the representativeness of different observing systems like MODIS, CALIOP and AERONET. Monthly and yearly averages allow serious sampling errors, that may still be present in multi-year climatologies due to recurring observing patterns. Even daily averages are affected as diurnal cycles can often not be observed. We discuss the implications these representativeness errors have for e.g. model evaluation or the construction of climatologies. We also assess similar representativeness issues in ground site in-situ observations from e.g. EMEP or IMPROVE and show that satellite datasets have distinct advantages due to their better spatial coverage provided temporal sampling is dealt with properly (i.e. through collocation of datasets). Finally, we briefly introduce a software tool (the Community Intercomparison Suite or CIS) that is designed to improve representativeness of datasets in intercomparion studies through aggregation and collocation of data.

  20. SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data

    NASA Astrophysics Data System (ADS)

    Rivest, Sonia; Bédard, Yvan; Proulx, Marie-Josée; Nadeau, Martin; Hubert, Frederic; Pastor, Julien

    To support their analytical processes, today's organizations deploy data warehouses and client tools such as OLAP (On-Line Analytical Processing) to access, visualize, and analyze their integrated, aggregated and summarized data. Since a large part of these data have a spatial component, better client tools are required to take full advantage of the geometry of the spatial phenomena or objects being analyzed. With this regard, Spatial OLAP (SOLAP) technology offers promising possibilities. A SOLAP tool can be defined as "a type of software that allows rapid and easy navigation within spatial databases and that offers many levels of information granularity, many themes, many epochs and many display modes synchronized or not: maps, tables and diagrams" [Bédard, Y., Proulx, M.J., Rivest, S., 2005. Enrichissement du OLAP pour l'analyse géographique: exemples de réalisation et différentes possibilités technologiques. In: Bentayeb, F., Boussaid, O., Darmont, J., Rabaseda, S. (Eds.), Entrepôts de Données et Analyse en ligne, RNTI B_1. Paris: Cépaduès, pp. 1-20]. SOLAP tools offer a new user interface and are meant to be client applications sitting on top of multi-scale spatial data warehouses or datacubes. As they are based on the multidimensional paradigm, they facilitate the interactive spatio-temporal exploration of data. The purpose of this paper is to discuss how SOLAP concepts support spatio-temporal exploration of data and then to present the geovisualization, interactivity, and animation features of the SOLAP software developed by our research group. This paper first reviews the general concepts behind OLAP and SOLAP systems. This is followed by a discussion of how these SOLAP concepts support spatio-temporal exploration of data. In the subsequent section, SOLAP software is introduced along with features that enable geovisualization, interactivity and animation.

  1. Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements

    PubMed Central

    Riehle, Alexa; Wirtssohn, Sarah; Grün, Sonja; Brochier, Thomas

    2013-01-01

    Grasping an object involves shaping the hand and fingers in relation to the object’s physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation. PMID:23543888

  2. A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollution

    NASA Astrophysics Data System (ADS)

    Akbari, Mohammad; Samadzadegan, Farhad; Weibel, Robert

    2015-07-01

    Spatio-temporal co-occurrence patterns represent subsets of object types which are located together in both space and time. Existing algorithms for co-occurrence pattern mining cannot handle complex applications such as air pollution in several ways. First, the existing models assume that spatial relationships between objects are explicitly represented in the input data, while the new method allows extracting implicitly contained spatial relationships algorithmically. Second, instead of extracting co-occurrence patterns of only point data, the proposed method deals with different feature types that is with point, line and polygon data. Thus, it becomes relevant for a wider range of real applications. Third, it also allows mining a spatio-temporal co-occurrence pattern simultaneously in space and time so that it illustrates the evolution of patterns over space and time. Furthermore, the proposed algorithm uses a Voronoi tessellation to improve efficiency. To evaluate the proposed method, it was applied on a real case study for air pollution where the objective is to find correspondences of air pollution with other parameters which affect this phenomenon. The results of evaluation confirm not only the capability of this method for co-occurrence pattern mining of complex applications, but also it exhibits an efficient computational performance.

  3. Characterizing the spatio-temporal and energy-dependent response of riometer absorption to particle precipitation

    NASA Astrophysics Data System (ADS)

    Kellerman, Adam; Makarevich, Roman; Spanswick, Emma; Donovan, Eric; Shprits, Yuri

    2016-07-01

    Energetic electrons in the 10's of keV range precipitate to the upper D- and lower E-region ionosphere, and are responsible for enhanced ionization. The same particles are important in the inner magnetosphere, as they provide a source of energy for waves, and thus relate to relativistic electron enhancements in Earth's radiation belts.In situ observations of plasma populations and waves are usually limited to a single point, which complicates temporal and spatial analysis. Also, the lifespan of satellite missions is often limited to several years which does not allow one to infer long-term climatology of particle precipitation, important for affecting ionospheric conditions at high latitudes. Multi-point remote sensing of the ionospheric plasma conditions can provide a global view of both ionospheric and magnetospheric conditions, and the coupling between magnetospheric and ionospheric phenomena can be examined on time-scales that allow comprehensive statistical analysis. In this study we utilize multi-point riometer measurements in conjunction with in situ satellite data, and physics-based modeling to investigate the spatio-temporal and energy-dependent response of riometer absorption. Quantifying this relationship may be a key to future advancements in our understanding of the complex D-region ionosphere, and may lead to enhanced specification of auroral precipitation both during individual events and over climatological time-scales.

  4. Spatio-temporal resolution of primary processes of photosynthesis.

    PubMed

    Junge, Wolfgang

    2015-01-01

    Technical progress in laser-sources and detectors has allowed the temporal and spatial resolution of chemical reactions down to femtoseconds and Å-units. In photon-excitable systems the key to chemical kinetics, trajectories across the vibrational saddle landscape, are experimentally accessible. Simple and thus well-defined chemical compounds are preferred objects for calibrating new methodologies and carving out paradigms of chemical dynamics, as shown in several contributions to this Faraday Discussion. Aerobic life on earth is powered by solar energy, which is captured by microorganisms and plants. Oxygenic photosynthesis relies on a three billion year old molecular machinery which is as well defined as simpler chemical constructs. It has been analysed to a very high precision. The transfer of excitation between pigments in antennae proteins, of electrons between redox-cofactors in reaction centres, and the oxidation of water by a Mn4Ca-cluster are solid state reactions. ATP, the general energy currency of the cell, is synthesized by a most agile, rotary molecular machine. While the efficiency of photosynthesis competes well with photovoltaics at the time scale of nanoseconds, it is lower by an order of magnitude for crops and again lower for bio-fuels. The enormous energy demand of mankind calls for engineered (bio-mimetic or bio-inspired) solar-electric and solar-fuel devices. PMID:25824647

  5. Automated Spatio-Temporal Analysis of Remotely Sensed Imagery for Water Resources Management

    NASA Astrophysics Data System (ADS)

    Bahr, Thomas

    2016-04-01

    Since 2012, the state of California faces an extreme drought, which impacts water supply in many ways. Advanced remote sensing is an important technology to better assess water resources, monitor drought conditions and water supplies, plan for drought response and mitigation, and measure drought impacts. In the present case study latest time series analysis capabilities are used to examine surface water in reservoirs located along the western flank of the Sierra Nevada region of California. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. A time series from Landsat images (L-5 TM, L-7 ETM+, L-8 OLI) of the AOI was obtained for 1999 to 2015 (October acquisitions). Downloaded from the USGS EarthExplorer web site, they already were georeferenced to a UTM Zone 10N (WGS-84) coordinate system. ENVITasks were used to pre-process the Landsat images as follows: • Triangulation based gap-filling for the SLC-off Landsat-7 ETM+ images. • Spatial subsetting to the same geographic extent. • Radiometric correction to top-of-atmosphere (TOA) reflectance. • Atmospheric correction using QUAC®, which determines atmospheric correction parameters directly from the observed pixel spectra in a scene, without ancillary information. Spatio-temporal analysis was executed with the following tasks: • Creation of Modified Normalized Difference Water Index images (MNDWI, Xu 2006) to enhance open water features while suppressing noise from built-up land, vegetation, and soil. • Threshold based classification of the water index images to extract the water features. • Classification aggregation as a post-classification cleanup process. • Export of the respective water classes to vector layers for further evaluation in a GIS. • Animation of the classification series and export to

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

    NASA Astrophysics Data System (ADS)

    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

  7. Hydrograph transposition to ungauged basin accounting for spatio-temporal rainfall variability

    NASA Astrophysics Data System (ADS)

    de Lavenne, Alban; Cudennec, Christophe

    2013-04-01

    Lack of measurements is one of the main issues in hydrological modelling. However, neighbours and nested gauged catchment are precious sources of information to understand the catchment behaviours within one region. Extracting the maximum of information from those points of measurements, that could be then transposed to ungauged catchment, is still a great challenge. We propose a methodology to transpose hydrological information from gauged catchments to ungauged ones, in order to simulate streamflow hydrographs. It uses geomorphology-based hydrological modelling, which is particularly well adapted to ungauged basins thanks to its robustness, generality and flexibility. We develop a geomorphology-based model on the gauged catchment which has been built in order to capture the main behaviour of the basin. Its transfer function considers the different dynamics of the catchment through the combination of velocities and width functions. Moreover, the explicit structure of the model enables to easily create a map of isochrone areas describing the time to the outlet. Therefore, spatially distributed rainfall can then be split into those isochrone areas, permitting the transfer function to deal with spatio-temporal variability of rainfall. Once the model calibrated, using a particle swarm optimisation algorithm, its transfer function is inversed to assess the net rainfall time series. In this way, we obtained a standardized variable which is used to estimate discharge in ungauged basin. Therefore, net rainfall time series is transposed and convoluted on the ungauged catchment using its own transfer function. Spatio-temporal rainfall variability between basins is considered through a correction of this net rainfall time series. This correction is based on differences between mean gross rainfall observation among those two catchments. This methodology is applied on pairs of basins among 6 gauged basins (from 5km² to 316km²) located in Brittany, France. For the benefit of

  8. Fast prototyping of wavelet spatio-temporal RS fusion with Raingauge time series with GDAL and Python-DWT

    NASA Astrophysics Data System (ADS)

    Chemin, Yann

    2013-04-01

    Availability of rainfall time-series is limited in many parts of the World, and the continuity of such records is variable. This research endeavors to extend actual daily rainfall observations to ungauged areas using vegetation response as witnessed by remote sensing data and taking into account rainfall event histograms as well as cumulative total daily rainfall, over a period of 11 years. Open Source code development permitted to gain on several aspects. The first one pertains to space, Python and its numerical part (NumPy) are scientifically concise, as a bonus to be expressive. The second is the availability of the Discrete Wavelet Transform (DWT) in Python already, which permitted to reduce the Wavelet Transform to a small set of instructions, clarifying and simplifying the understanding of the code once it reaches the Public Domain. GDAL interface permitted to load satellite imagery and write fused rainfall time-series in spatio-temporal dimensions. Other scientific tool from Numerical Python were also used in the process of developing the algorithm (scipy.stats.stats and scipy.interpolate.griddata). Due to the large amount of days (4019) and the kilometer based resolution of the vegetation RS data, it takes about a week for the code to resolve the fusion problem. An attempt at using an multicore interpolation implementation in Python (hpgl) which unfortunately was not an active project anymore, though certainly deserving interest. Results show that rainfall events histograms can be reconstructed, and that total cumulative rainfall is estimated with 85% accuracy, using a surrounding network of rain gauges at 30-50 km of distance from the point of study. This research can strengthen various types of research and applications such as ungauged basins research, regional climate modeling, agricultural insurance systems, etc. Further development aims at porting the code to distributed computing.

  9. A spatio-temporal detective quantum efficiency and its application to fluoroscopic systems

    SciTech Connect

    Friedman, S. N.; Cunningham, I. A.

    2010-11-15

    Purpose: Fluoroscopic x-ray imaging systems are used extensively in spatio-temporal detection tasks and require a spatio-temporal description of system performance. No accepted metric exists that describes spatio-temporal fluoroscopic performance. The detective quantum efficiency (DQE) is a metric widely used in radiography to quantify system performance and as a surrogate measure of patient ''dose efficiency.'' It has been applied previously to fluoroscopic systems with the introduction of a temporal correction factor. However, the use of a temporally-corrected DQE does not provide system temporal information and it is only valid under specific conditions, many of which are not likely to be satisfied by suboptimal systems. The authors propose a spatio-temporal DQE that describes performance in both space and time and is applicable to all spatio-temporal quantum-based imaging systems. Methods: The authors define a spatio-temporal DQE (two spatial-frequency axes and one temporal-frequency axis) in terms of a small-signal spatio-temporal modulation transfer function (MTF) and spatio-temporal noise power spectrum (NPS). Measurements were made on an x-ray image intensifier-based bench-top system using continuous fluoroscopy with an RQA-5 beam at 3.9 {mu}R/frame and hardened 50 kVp beam (0.8 mm Cu filtration added) at 1.9 {mu}R/frame. Results: A zero-frequency DQE value of 0.64 was measured under both conditions. Nonideal performance was noted at both larger spatial and temporal frequencies; DQE values decreased by {approx}50% at the cutoff temporal frequency of 15 Hz. Conclusions: The spatio-temporal DQE enables measurements of decreased temporal system performance at larger temporal frequencies analogous to previous measurements of decreased (spatial) performance. This marks the first time that system performance and dose efficiency in both space and time have been measured on a fluoroscopic system using DQE and is the first step toward the generalized use of DQE on

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

    PubMed

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

    2014-01-01

    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. PMID:24992684

  11. An Adaptive Organization Method of Geovideo Data for Spatio-Temporal Association Analysis

    NASA Astrophysics Data System (ADS)

    Wu, C.; Zhu, Q.; Zhang, Y. T.; Du, Z. Q.; Zhou, Y.; Xie, X.; He, F.

    2015-07-01

    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.

  12. Bayesian Spatio-Temporal Analysis and Geospatial Risk Factors of Human Monocytic Ehrlichiosis

    PubMed Central

    Raghavan, Ram K.; Neises, Daniel; Goodin, Douglas G.; Andresen, Daniel A.; Ganta, Roman R.

    2014-01-01

    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. PMID:24992684

  13. A Spatio-Temporally Explicit Random Encounter Model for Large-Scale Population Surveys.

    PubMed

    Jousimo, Jussi; Ovaskainen, Otso

    2016-01-01

    Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov-Malyshev-Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density. We also introduce a weighting scheme to estimate density on habitats that are not covered by survey transects, assuming that movement data on a subset of individuals is available. We test the performance of spatio-temporal and temporal approaches by a simulation study mimicking the Finnish winter track count survey. The results illustrate how the spatio-temporal modelling approach is able to borrow information from observations made on neighboring locations and times when estimating population density, and that spatio-temporal and temporal smoothing models can provide improved estimates of total population size compared to the FMP method. PMID:27611683

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

    NASA Astrophysics Data System (ADS)

    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

  15. Spatio-Temporal Evolution and Scaling Properties of Human Settlements (Invited)

    NASA Astrophysics Data System (ADS)

    Small, C.; Milesi, C.; Elvidge, C.; Baugh, K.; Henebry, G. M.; Nghiem, S. V.

    2013-12-01

    Growth and evolution of cities and smaller settlements is usually studied in the context of population and other socioeconomic variables. While this is logical in the sense that settlements are groups of humans engaged in socioeconomic processes, our means of collecting information about spatio-temporal distributions of population and socioeconomic variables often lack the spatial and temporal resolution to represent the processes at scales which they are known to occur. Furthermore, metrics and definitions often vary with country and through time. However, remote sensing provides globally consistent, synoptic observations of several proxies for human settlement at spatial and temporal resolutions sufficient to represent the evolution of settlements over the past 40 years. We use several independent but complementary proxies for anthropogenic land cover to quantify spatio-temporal (ST) evolution and scaling properties of human settlements globally. In this study we begin by comparing land cover and night lights in 8 diverse settings - each spanning gradients of population density and degree of land surface modification. Stable anthropogenic night light is derived from multi-temporal composites of emitted luminance measured by the VIIRS and DMSP-OLS sensors. Land cover is represented as mixtures of sub-pixel fractions of rock, soil and impervious Substrates, Vegetation and Dark surfaces (shadow, water and absorptive materials) estimated from Landsat imagery with > 94% accuracy. Multi-season stability and variability of land cover fractions effectively distinguishes between spectrally similar land covers that corrupt thematic classifications based on single images. We find that temporal stability of impervious substrates combined with persistent shadow cast between buildings results in temporally stable aggregate reflectance across seasons at the 30 m scale of a Landsat pixel. Comparison of night light brightness with land cover composition, stability and variability

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

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    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

  18. Mapping the spatio-temporal risk of lead exposure in apex species for more effective mitigation.

    PubMed

    Mateo-Tomás, Patricia; Olea, Pedro P; Jiménez-Moreno, María; Camarero, Pablo R; Sánchez-Barbudo, Inés S; Rodríguez Martín-Doimeadios, Rosa C; Mateo, Rafael

    2016-07-27

    Effective mitigation of the risks posed by environmental contaminants for ecosystem integrity and human health requires knowing their sources and spatio-temporal distribution. We analysed the exposure to lead (Pb) in griffon vulture Gyps fulvus-an apex species valuable as biomonitoring sentinel. We determined vultures' lead exposure and its main sources by combining isotope signatures and modelling analyses of 691 bird blood samples collected over 5 years. We made yearlong spatially explicit predictions of the species risk of lead exposure. Our results highlight elevated lead exposure of griffon vultures (i.e. 44.9% of the studied population, approximately 15% of the European, showed lead blood levels more than 200 ng ml(-1)) partly owing to environmental lead (e.g. geological sources). These exposures to environmental lead of geological sources increased in those vultures exposed to point sources (e.g. lead-based ammunition). These spatial models and pollutant risk maps are powerful tools that identify areas of wildlife exposure to potentially harmful sources of lead that could affect ecosystem and human health. PMID:27466455

  19. Minimal Spatio-Temporal Extent of Events, Neutrinos, and the Cosmological Constant Problem

    NASA Astrophysics Data System (ADS)

    Ahluwalia-Khalilova, D. V.

    Chryssomalakos and Okon, through a uniqueness analysis, have strengthened the Vilela Mendes suggestion that the immunity to infinitesimal perturbations in the structure constants of a physically-relevant Lie algebra should be raised to the status of a physical principle. Since the Poincaré-Heisenberg algebra does not carry the indicated immunity, it is suggested that the Lie algebra for the interface of the gravitational and quantum realms (IGQR) is its stabilized form. It carries three additional parameters: a length scale pertaining to the Planck/unification scale, a second length scale associated with cosmos, and a new dimensionless constant. Here, we show that the adoption of the stabilized Poincaré-Heisenberg algebra (SPHA) for the IGQR has the immediate implication that a "point particle" ceases to be a viable physical notion. It must be replaced by objects which carry a well-defined, representation space-dependent, minimal spatio-temporal extent. The ensuing implications have the potential, without spoiling any of the successes of the Standard Model of particle physics, to resolve the cosmological constant problem while concurrently offering a first-principle hint as to why there exists a coincidence between cosmic vacuum energy density and neutrino masses. The main theses which the essay presents is the following: an extension of the present-day physics to a framework which respects SPHA should be seen as the most natural and systematic path towards gaining a deeper understanding of outstanding questions, if not providing answers to them.

  20. Modeling self-organized spatio-temporal patterns of PIP3 and PTEN during spontaneous cell polarization

    NASA Astrophysics Data System (ADS)

    Knoch, Fabian; Tarantola, Marco; Bodenschatz, Eberhard; Rappel, Wouter-Jan

    2014-08-01

    During spontaneous cell polarization of Dictyostelium discoideum cells, phosphatidylinositol (3,4,5)-triphoshpate (PIP3) and PTEN (phosphatase tensin homolog) have been identified as key signaling molecules which govern the process of polarization in a self-organized manner. Recent experiments have quantified the spatio-temporal dynamics of these signaling components. Surprisingly, it was found that membrane-bound PTEN can be either in a high or low state, that PIP3 waves were initiated in areas lacking PTEN through an excitable mechanism, and that PIP3 was degraded even though the PTEN concentration remained low. Here we develop a reaction-diffusion model that aims to explain these experimental findings. Our model contains bistable dynamics for PTEN, excitable dynamics for PIP3, and postulates the existence of two species of PTEN with different dephosphorylation rates. We show that our model is able to produce results that are in good qualitative agreement with the experiments, suggesting that our reaction-diffusion model underlies the self-organized spatio-temporal patterns observed in experiments.

  1. New Fast Fall Detection Method Based on Spatio-Temporal Context Tracking of Head by Using Depth Images

    PubMed Central

    Yang, Lei; Ren, Yanyun; Hu, Huosheng; Tian, Bo

    2015-01-01

    In order to deal with the problem of projection occurring in fall detection with two-dimensional (2D) grey or color images, this paper proposed a robust fall detection method based on spatio-temporal context tracking over three-dimensional (3D) depth images that are captured by the Kinect sensor. In the pre-processing procedure, the parameters of the Single-Gauss-Model (SGM) are estimated and the coefficients of the floor plane equation are extracted from the background images. Once human subject appears in the scene, the silhouette is extracted by SGM and the foreground coefficient of ellipses is used to determine the head position. The dense spatio-temporal context (STC) algorithm is then applied to track the head position and the distance from the head to floor plane is calculated in every following frame of the depth image. When the distance is lower than an adaptive threshold, the centroid height of the human will be used as the second judgment criteria to decide whether a fall incident happened. Lastly, four groups of experiments with different falling directions are performed. Experimental results show that the proposed method can detect fall incidents that occurred in different orientations, and they only need a low computation complexity. PMID:26378540

  2. Spatio-Temporal Dynamics of Yeast Mitochondrial Biogenesis: Transcriptional and Post-Transcriptional mRNA Oscillatory Modules

    PubMed Central

    Lelandais, Gaëlle; Saint-Georges, Yann; Geneix, Colette; Al-Shikhley, Liza; Dujardin, Geneviève; Jacq, Claude

    2009-01-01

    Examples of metabolic rhythms have recently emerged from studies of budding yeast. High density microarray analyses have produced a remarkably detailed picture of cycling gene expression that could be clustered according to metabolic functions. We developed a model-based approach for the decomposition of expression to analyze these data and to identify functional modules which, expressed sequentially and periodically, contribute to the complex and intricate mitochondrial architecture. This approach revealed that mitochondrial spatio-temporal modules are expressed during periodic spikes and specific cellular localizations, which cover the entire oscillatory period. For instance, assembly factors (32 genes) and translation regulators (47 genes) are expressed earlier than the components of the amino-acid synthesis pathways (31 genes). In addition, we could correlate the expression modules identified with particular post-transcriptional properties. Thus, mRNAs of modules expressed “early” are mostly translated in the vicinity of mitochondria under the control of the Puf3p mRNA-binding protein. This last spatio-temporal module concerns mostly mRNAs coding for basic elements of mitochondrial construction: assembly and regulatory factors. Prediction that unknown genes from this module code for important elements of mitochondrial biogenesis is supported by experimental evidence. More generally, these observations underscore the importance of post-transcriptional processes in mitochondrial biogenesis, highlighting close connections between nuclear transcription and cytoplasmic site-specific translation. PMID:19521515

  3. The dynamics of spatio-temporal Rho GTPase signaling: formation of signaling patterns

    PubMed Central

    Fritz, Rafael Dominik; Pertz, Olivier

    2016-01-01

    Rho GTPases are crucial signaling molecules that regulate a plethora of biological functions. Traditional biochemical, cell biological, and genetic approaches have founded the basis of Rho GTPase biology. The development of biosensors then allowed measuring Rho GTPase activity with unprecedented spatio-temporal resolution. This revealed that Rho GTPase activity fluctuates on time and length scales of tens of seconds and micrometers, respectively. In this review, we describe Rho GTPase activity patterns observed in different cell systems. We then discuss the growing body of evidence that upstream regulators such as guanine nucleotide exchange factors and GTPase-activating proteins shape these patterns by precisely controlling the spatio-temporal flux of Rho GTPase activity. Finally, we comment on additional mechanisms that might feed into the regulation of these signaling patterns and on novel technologies required to dissect this spatio-temporal complexity. PMID:27158467

  4. Geovisualization Approaches for Spatio-temporal Crime Scene Analysis - Towards 4D Crime Mapping

    NASA Astrophysics Data System (ADS)

    Wolff, Markus; Asche, Hartmut

    This paper presents a set of methods and techniques for analysis and multidimensional visualisation of crime scenes in a German city. As a first step the approach implies spatio-temporal analysis of crime scenes. Against this background a GIS-based application is developed that facilitates discovering initial trends in spatio-temporal crime scene distributions even for a GIS untrained user. Based on these results further spatio-temporal analysis is conducted to detect variations of certain hotspots in space and time. In a next step these findings of crime scene analysis are integrated into a geovirtual environment. Behind this background the concept of the space-time cube is adopted to allow for visual analysis of repeat burglary victimisation. Since these procedures require incorporating temporal elements into virtual 3D environments, basic methods for 4D crime scene visualisation are outlined in this paper.

  5. Why risk managers need information about spatio-temporal variability of natural hazards. Examples from practice

    NASA Astrophysics Data System (ADS)

    Zischg, Andreas

    2013-04-01

    Integrated risk management consists of risk prevention, early warning, intervention during an event and restoration/re-construction after an event. The prevention phase consists of land use planning measures with a long-term time horizon and of structural measures that sometimes have a lifespan of more than 30-50 years. In this case, it is important to analyse the long-term evolvement of natural risks due to climate changes or land use changes. Besides of this, the spatial and temporal variability of a natural hazard process during the course of an event is also important. The shift from "static" hazard and risk assessment towards a "dynamic" assessment offers benefits for improving the intervention phase in risk management. This contribution describes some examples and points out the benefits of this shift for risk management. One example is the variable disposition of small alpine catchments for runoff and its relevance for early warning. The disposition for runoff depends on the actual status of environmental variables such as soil moisture and the snowpack characteristics. A feasibility study showed how the monitoring of soil moisture and the status of the snowpack can be incorporated into a rule base for describing the temporal variability of the disposition for high runoff in alpine catchments. The study showed that this information about the system state of alpine catchments can be used to improve the assessment of the consequences of a weather forecast for risk management. Another example is the use of snowpack and weather monitoring and traffic intensity measurements for avalanche risk management on alpine roads. Here, the information about the spatio-temporal variability of the snow avalanches and the presence of vehicles can be used for improving the procedures for road closure and re-opening. Another example is the preparation of intervention plans for fire brigades and other relief units during urban floods. The simulation of the temporal evolvement of

  6. Spatio-temporal microseismic analysis of the Woodford Shale, Canadian County, Oklahoma

    NASA Astrophysics Data System (ADS)

    Eppehimer, Jarred

    Microseismicity provides data that can be used to monitor hydraulic fracture stimulation programs as well as to characterize the resulting hydraulic fractures. This is especially important in low permeability gas and oil shales, where the creation of additional permeability through these fracture treatments is essential to production. However, many applications and analyses of these data are either qualitative in nature or include a large element of interpretational bias. This study looks at two microseismic analytical techniques: the radius of gyration (ROG) tensor, as described in Sayers & Le Calvez (2010), and the methods described in Shapiro (2008) that relate spatio-temporal microseismic signatures to hydraulic diffusivity and ultimately hydraulic permeability. The radius of gyration tensor is used to generate a characteristic ellipsoid for any set of microseismic events, and the aspect ratio of this ellipsoid can be related to local in-situ horizontal stress ratios. These methods are applied to surface microseismic data collected for six horizontal wells drilled and completed in the Woodford Shale in Canadian County, Oklahoma. Additionally, an attempt is made to bridge the gap between these methods. Specifically, the characteristic ellipsoid generation from the radius of gyration tensor in Sayers & Le Calvez (2010) is applied to Shapiro's workflow. Shapiro attempts to link the 3D anisotropic triggering front of seismicity, which is an ellipsoid that envelops time-scaled microseismic events, to reservoir permeability. The radius of gyration tensor will generate this ellipsoid and remove interpretational bias that would have been present otherwise. Lastly, an attempt is made at relating the signatures present in the characteristic ellipsoids to zones of natural fracture reactivation. This is done on a stage-by-stage basis. The hypothesis is that an ellipsoid with a significant tilt in its most vertical principal axis and a significant azimuthal rotation away

  7. Spatio-temporal Remodeling of Functional Membrane Microdomains Organizes the Signaling Networks of a Bacterium

    PubMed Central

    Schneider, Johannes; Klein, Teresa; Mielich-Süss, Benjamin; Koch, Gudrun; Franke, Christian; Kuipers, Oscar P.; Kovács, Ákos T.; Sauer, Markus; Lopez, Daniel

    2015-01-01

    Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs) that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium. PMID:25909364

  8. Spatio-temporal evolution of shoreline changes along the coast between sousse- Monastir (Eastearn of Tunisia)

    NASA Astrophysics Data System (ADS)

    Fathallah, S.; Ben Amor, R.; Gueddari, M.

    2009-04-01

    Spatio-temporal evolution of shoreline Changes along the coast between Sousse-Monastir (Eastern of Tunisia). Safa Fathallah*, Rim Ben Amor and Moncef Gueddari Unit of Research of Geochemistry and Environmental Geology. Faculty of Science of Tunis, University of Tunis El Manar, 2092. (*) Corresponding author: safa_fathallah@yahoo.fr The coast of Sousse-Monastir in eastern of Tunisia, has undergone great changes, due to natural and anthropic factors. Increasing human use, the construction of two ports and coastal urbanization (hotels and industries) has accelerated the erosion process. The coastal defense structures (breakwaters and enrockment), built to protect the most eroded zone are efficient, but eroded zones appeared in the southern part of breakwaters. Recent and historic aerial photography was used to estimate, observe, and analyze past shoreline and bathymetric positions and trends involving shore evolution for Sousse-Monastir coast. All of the photographs were calibrated and mosaicked by Arc Map Gis 9.1, the years used are 1925, 1962, 1988, 1996, and 2001 for shoreline change analysis and 1884 and 2001 for bathymetric changes. The analyze of this photographs show that the zone located at the south of breakwater are mostly eroded with high speed process (2m/year). Another zone appears as eroded at the south part of Hamdoun River, with 1,5m/year erosion speed . Keywords: Shoreline evolution, defense structures, Sousse-Monastir coast, Tunisia.

  9. Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography

    PubMed Central

    Hegde, Anant; Erdogmus, Deniz; Shiau, Deng S.; Principe, Jose C.; Sackellares, Chris J.

    2007-01-01

    Abnormal dynamical coupling between brain structures is believed to be primarily responsible for the generation of epileptic seizures and their propagation. In this study, we attempt to identify the spatio-temporal interactions of an epileptic brain using a previously proposed nonlinear dependency measure. Using a clustering model, we determine the average spatial mappings in an epileptic brain at different stages of a complex partial seizure. Results involving 8 seizures from 2 epileptic patients suggest that there may be a fixed pattern associated with regional spatio-temporal dynamics during the interictal to pre-post-ictal transition. PMID:18317515

  10. Visual Analysis of Multi-Run Spatio-Temporal Simulations Using Isocontour Similarity for Projected Views.

    PubMed

    Fofonov, Alexey; Molchanov, Vladimir; Linsen, Lars

    2016-08-01

    Multi-run simulations are widely used to investigate how simulated processes evolve depending on varying initial conditions. Frequently, such simulations model the change of spatial phenomena over time. Isocontours have proven to be effective for the visual representation and analysis of 2D and 3D spatial scalar fields. We propose a novel visualization approach for multi-run simulation data based on isocontours. By introducing a distance function for isocontours, we generate a distance matrix used for a multidimensional scaling projection. Multiple simulation runs are represented by polylines in the projected view displaying change over time. We propose a fast calculation of isocontour differences based on a quasi-Monte Carlo approach. For interactive visual analysis, we support filtering and selection mechanisms on the multi-run plot and on linked views to physical space visualizations. Our approach can be effectively used for the visual representation of ensembles, for pattern and outlier detection, for the investigation of the influence of simulation parameters, and for a detailed analysis of the features detected. The proposed method is applicable to data of any spatial dimensionality and any spatial representation (gridded or unstructured). We validate our approach by performing a user study on synthetic data and applying it to different types of multi-run spatio-temporal simulation data. PMID:26561458

  11. Spatio-Temporal Variability in Fecal Indicator Bacteria Concentrations at Huntington Beach: Connections to Physical Forcing

    NASA Astrophysics Data System (ADS)

    Rippy, M. A.; Feddersen, F.; Leichter, J.; Omand, M.; Moore, D. F.; McGee, C.; Franks, P. J.

    2007-05-01

    Two major factors determine the spatial and temporal distributions of fecal indicator bacteria (FIB) at a given beach: local circulation & mixing patterns, and bacterial inactivation rates. High frequency and spatial resolution bacterial sampling combined with measurements of physical processes can be used to infer inactivation rates, enabling differentiation between dilution & mortality as factors driving variability in nearshore FIB abundance. A FIB sampling experiment (HB06) took place on 16 October 2006, at Huntington State Beach, a site selected due to its persistent problems with FIB pollution. Water samples were taken at 20-minute intervals (from 6:50am to 11:50am) at ten locations; four in an alongshore transect spanning 1 km at the shoreline, and the remainder in a 300-m long cross-shore transect. All samples were analyzed for FIB concentration (Total Coliforms, E. coli & Enterococci) and, for a subset, species level Enterococcus composition was determined. As part of the HB06 experiment, currents, temperature, waves, and chlorophyll fluorescence were measured simultaneously in the cross-shore direction with rapid CTD casts 300 m offshore. Results indicate that E. coli and Enterococcus concentrations exhibit exponential decreases with time, with smaller decay rates associated with depth and with sites in the Talbert Marsh and Santa Ana River. FIB concentrations are also noticeably lower farther offshore (300 m). Spatio-temporal patterns in FIB concentration will be presented in conjunction with the nearshore physical data allowing the relationship between physical dynamics and biological variability to be addressed.

  12. Disentangling multidimensional spatio-temporal data into their common and aberrant responses.

    PubMed

    Chang, Young Hwan; Korkola, James; Amin, Dhara N; Moasser, Mark M; Carmena, Jose M; Gray, Joe W; Tomlin, Claire J

    2015-01-01

    With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures and how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data. PMID:25901353

  13. Disentangling multidimensional spatio-temporal data into their common and aberrant responses

    SciTech Connect

    Chang, Young Hwan; Korkola, James; Amin, Dhara N.; Moasser, Mark M.; Carmena, Jose M.; Gray, Joe W.; Tomlin, Claire J.; Lisacek, Frederique

    2015-04-22

    With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures and how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data.

  14. Spatio-temporal evolution of interfacial instabilities in vertical gas-liquid flows

    NASA Astrophysics Data System (ADS)

    Schmidt, Patrick; Valluri, Prashant; Ó Náraigh, Lennon; Lucquiaud, Mathieu

    2014-11-01

    Vertical gas-liquid flows are characteristic for process engineering and widely employed in various technical applications. However, the dynamic behaviour of the liquid interface in such flows is still not fully understood. We focus in our work on characterising the interfacial instability as well as associated interfacial waves in vertical laminar-laminar gas-liquid flows over a wide range of parameters covering different flow regimes, i.e. counter-current, zero-interface velocity (loading) and partial-to-full liquid flow reversal (flooding). High-resolution direct numerical simulations using the TPLS flow solver (http://sourceforge.net/projects/tpls/) reveal the existence of weakly nonlinear interfacial waves, which are in good agreement with Stuart-Landau theory. These waves travel down- or upstream, depending on the flow regime. Furthermore, spatio-temporal linear stability analysis indicates the occurrence of absolute instability within the investigated parameter range. DNS is used to analyse this feature in more detail whereby agreement with linear theory has been established.

  15. Spatio-temporal Kinetics of Nontypeable Haemophilus influenzae(NTHi) Biofilms

    NASA Astrophysics Data System (ADS)

    Dhanji, Aleya; Rosas, Lucia; Ray, William; Jayaprakash, Ciriyam; Bakaletz, Lauren; Das, Jayajit

    2014-03-01

    Bacteria can form complex spatial structures known as biofilms. Biofilm formation is frequently associated with chronic infections due to the greatly enhanced antibiotic resistance of resident bacteria. However, our understanding of the role of basic processes, such as bacteria replication and resource consumption, in controlling the development and temporal change of the spatial structure remains rudimentary. Here, we examine the growth of cultured biofilms by the opportunistic pathogen NTHi. Through spatial information extracted from confocal microscopy images, we quantitatively characterize the biofilm structure as it evolves over time. We find that the equal-time height-height pair correlation function decreases with distance and scales with time for small length scales. Furthermore, both the surface roughness and the correlation length perpendicular to the surface growth direction increase with time initially and then decrease. We construct a spatially resolved agent based model beginning with the simplest possible case of a single bacteria species Fisher-Kolmogorov-Petrovsky-Piscounov equation. We show that it cannot describe the observed spatio-temporal behavior and suggest an improved two-species model that better captures the dynamics of the NTHi system. Supported by The Research Institute at Nationwide Children's Hospital.

  16. Spatio-temporal behavior of microwave sheath-voltage combination plasma source

    NASA Astrophysics Data System (ADS)

    Kar, Satyananda; Kousaka, Hiroyuki; Raja, Laxminarayan L.

    2015-05-01

    Microwave sheath-Voltage combination Plasma (MVP) is a high density plasma source and can be used as a suitable plasma processing device (e.g., ionized physical vapor deposition). In the present report, the spatio-temporal behavior of an argon MVP sustained along a direct-current biased Ti rod is investigated. Two plasma modes are observed, one is an "oxidized state" (OS) at the early time of the microwave plasma and the other is "ionized sputter state" (ISS) at the later times. Transition of the plasma from OS to ISS results a prominent change in the visible color of the plasma, resulting from a significant increase in the plasma density, as measured by a Langmuir probe. In the OS, plasma is dominated by Ar ions, and the density is in amplitude order of 1011 cm-3. In the ISS, metal ions from the Ti rod contribute significantly to the ion composition, and higher density plasma (1012 cm-3) is produced. Nearly uniform high density plasma along the length of the Ti rod is produced at very low input microwave powers (around 30 W). Optical emission spectroscopy measurements confirm the presence of sputtered Ti ions and Ti neutrals in the ISS.

  17. Fine tuning the correlation limit of spatio-temporal signal space separation for magnetoencephalography.

    PubMed

    Medvedovsky, Mordekhay; Taulu, Samu; Bikmullina, Rozaliya; Ahonen, Antti; Paetau, Ritva

    2009-02-15

    Head, jaw and tongue movements contribute to speech artifacts in magnetoencephalography (MEG). Their sources lay close to MEG sensors, therefore, the spatio-temporal signal space separation method (tSSS), specifically suppressing nearby artifacts, can be used for speech artifact suppression. After data reconstruction by signal space separation (referred as SSS), tSSS identifies artifacts by their correlated temporal behavior inside and outside the sensor helmet. The artifacts to be eliminated are thresholded by the quantitative level of this correlation determined by correlation limit (CL). Unnecessarily high CL value may result in suboptimal interference suppression. We evaluated the performance of tSSS with different CLs on MEG data containing speech artifacts. MEG was recorded with 204 planar gradiometers and 102 magnetometers in two subjects counting aloud. The recorded data were processed by tSSS using CLs 0.98, 0.8 and 0.6, and traces were compared. The speech artifact was increasingly suppressed with decreasing CL, but sufficient suppression was achieved at different CL in each subject. Alpha rhythm was not suppressed with CL 0.98 or 0.8; some amplitude reduction with CL 0.6 occurred in one subject. The tSSS is a robust tool suppressing MEG artifacts. It can be fine tuned for challenging artifacts which, after insufficient rejection might resemble brain signals. PMID:18996412

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

    NASA Astrophysics Data System (ADS)

    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.

  19. Insight into others’ minds: spatio-temporal representations by intrinsic frame of reference

    PubMed Central

    Sun, Yanlong; Wang, Hongbin

    2014-01-01

    Recent research has seen a growing interest in connections between domains of spatial and social cognition. Much evidence indicates that processes of representing space in distinct frames of reference (FOR) contribute to basic spatial abilities as well as sophisticated social abilities such as tracking other’s intention and belief. Argument remains, however, that belief reasoning in social domain requires an innately dedicated system and cannot be reduced to low-level encoding of spatial relationships. Here we offer an integrated account advocating the critical roles of spatial representations in intrinsic frame of reference. By re-examining the results from a spatial task (Tamborello etal., 2012) and a false-belief task (Onishi and Baillargeon, 2005), we argue that spatial and social abilities share a common origin at the level of spatio-temporal association and predictive learning, where multiple FOR-based representations provide the basic building blocks for efficient and flexible partitioning of the environmental statistics. We also discuss neuroscience evidence supporting these mechanisms. We conclude that FOR-based representations may bridge the conceptual as well as the implementation gaps between the burgeoning fields of social and spatial cognition. PMID:24592226

  20. A Bayesian Hierarchical Model for Spatio-Temporal Prediction and Uncertainty Assessment Using Repeat LiDAR Acquisitions for the Kenai Peninsula, AK, USA

    NASA Astrophysics Data System (ADS)

    Babcock, C. R.; Andersen, H. E.; Finley, A. O.; Cook, B.; Morton, D. C.

    2015-12-01

    Models using repeat LiDAR and field campaigns may be one mechanism to monitor carbon storage and flux in forested regions. Considering the ability of multi-temporal LiDAR to estimate growth, it is not surprising that there is great interest in developing forest carbon monitoring strategies that rely on repeated LiDAR acquisitions. Allowing for sparser field campaigns, LiDAR stands to make monitoring forest carbon cheaper and more efficient than field-only sampling procedures. Here, we look to the spatio-temporally data-rich Kenai Peninsula in Alaska to examine the potential for Bayesian spatio-temporal mapping of forest carbon storage and uncertainty. The framework explored here can predict forest carbon through space and time, while formally propagating uncertainty through to prediction. Bayesian spatio-temporal models are flexible frameworks allowing for forest growth processes to be formally integrated into the model. By incorporating a mechanism for growth---using temporally repeated field and LiDAR data---we can more fully exploit the information-rich inventory network to improve prediction accuracy. LiDAR data for the Kenai Peninsula has been collected on four different occasions---spatially coincident LiDAR strip samples in 2004, 09 and 14, along with a wall-to-wall collection in 2008. There were 436 plots measured twice between 2002 and 2014. LiDAR was acquired at least once over most inventory plots with many having LiDAR collected during 2, 3 or 4 different campaigns. Results from this research will impact how forests are inventoried. It is too expensive to monitor terrestrial carbon using field-only sampling strategies and currently proposed LiDAR model-based techniques lack the ability to properly utilize temporally repeated and misaligned data. Bayesian hierarchical spatio-temporal models offer a solution to these shortcomings and allow for formal predictive error assessment, which is useful for policy development and decision making.

  1. Spatio-temporal optimization of agricultural practices to achieve a sustainable development at basin level; framework of a case study in Colombia

    NASA Astrophysics Data System (ADS)

    Uribe, Natalia; corzo, Gerald; Solomatine, Dimitri

    2016-04-01

    The flood events present during the last years in different basins of the Colombian territory have raised questions on the sensitivity of the regions and if this regions have common features. From previous studies it seems important features in the sensitivity of the flood process were: land cover change, precipitation anomalies and these related to impacts of agriculture management and water management deficiencies, among others. A significant government investment in the outreach activities for adopting and promoting the Colombia National Action Plan on Climate Change (NAPCC) is being carried out in different sectors and regions, having as a priority the agriculture sector. However, more information is still needed in the local environment in order to assess were the regions have this sensitivity. Also the continuous change in one region with seasonal agricultural practices have been pointed out as a critical information for optimal sustainable development. This combined spatio-temporal dynamics of crops cycle in relation to climate change (or variations) has an important impact on flooding events at basin areas. This research will develop on the assessment and optimization of the aggregated impact of flood events due to determinate the spatio-temporal dynamic of changes in agricultural management practices. A number of common best agricultural practices have been identified to explore their effect in a spatial hydrological model that will evaluate overall changes. The optimization process consists on the evaluation of best performance in the agricultural production, without having to change crops activities or move to other regions. To achieve this objectives a deep analysis of different models combined with current and future climate scenarios have been planned. An algorithm have been formulated to cover the parametric updates such that the optimal temporal identification will be evaluated in different region on the case study area. Different hydroinformatics

  2. Impacts of cattle grazing on spatio-temporal variability of soil moisture and above-ground live plant biomass in mixed grasslands

    NASA Astrophysics Data System (ADS)

    Virk, Ravinder

    Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB

  3. Using Unmanned Aerial Vehicle (UAV) for spatio-temporal monitoring of soil erosion and roughness in Chania, Crete, Greece

    NASA Astrophysics Data System (ADS)

    Alexakis, Dimitrios; Seiradakis, Kostas; Tsanis, Ioannis

    2016-04-01

    This article presents a remote sensing approach for spatio-temporal monitoring of both soil erosion and roughness using an Unmanned Aerial Vehicle (UAV). Soil erosion by water is commonly known as one of the main reasons for land degradation. Gully erosion causes considerable soil loss and soil degradation. Furthermore, quantification of soil roughness (irregularities of the soil surface due to soil texture) is important and affects surface storage and infiltration. Soil roughness is one of the most susceptible to variation in time and space characteristics and depends on different parameters such as cultivation practices and soil aggregation. A UAV equipped with a digital camera was employed to monitor soil in terms of erosion and roughness in two different study areas in Chania, Crete, Greece. The UAV followed predicted flight paths computed by the relevant flight planning software. The photogrammetric image processing enabled the development of sophisticated Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimeter level. The DTMs were developed using photogrammetric processing of more than 500 images acquired with the UAV from different heights above the ground level. As the geomorphic formations can be observed from above using UAVs, shadowing effects do not generally occur and the generated point clouds have very homogeneous and high point densities. The DTMs generated from UAV were compared in terms of vertical absolute accuracies with a Global Navigation Satellite System (GNSS) survey. The developed data products were used for quantifying gully erosion and soil roughness in 3D as well as for the analysis of the surrounding areas. The significant elevation changes from multi-temporal UAV elevation data were used for estimating diachronically soil loss and sediment delivery without installing sediment traps. Concerning roughness, statistical indicators of surface elevation point measurements were estimated and various

  4. The Impact of Spatio-Temporal Constraints on Cursive Letter Handwriting in Children

    ERIC Educational Resources Information Center

    Chartrel, Estelle; Vinter, Annie

    2008-01-01

    The study assessed the impact of spatial and temporal constraints on handwriting movements in young children. One hundred children of 5-7 years of age of both genders were given the task of copying isolated cursive letters under four conditions: normal, with temporal, spatial, or spatio-temporal constraints. The results showed that imposing…

  5. a Framework for Online Spatio-Temporal Data Visualization Based on HTML5

    NASA Astrophysics Data System (ADS)

    Mao, B.; Wu, Z.; Cao, J.

    2012-07-01

    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.

  6. Statistical Analysis of Spatio-temporal Variations of Sea Surface Height Observed by Topex Altimeter

    NASA Technical Reports Server (NTRS)

    Fabrikant, A.; Glazman, R. E.; Greysukh, A.

    1994-01-01

    Using non-gridded Topex altimeter data, high resolution 2-d power spectra and spatio-temporal autocorrelation functions of sea surface height (SSH) variations are estimated and employed for studying anisotropic SSH fields varying in a broad range of scales.

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

    NASA Technical Reports Server (NTRS)

    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.

  8. On the spatio-temporal dynamics of soil moisture at the field scale

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, we review the state of the art of characterizing and analyzing spatio-temporal dynamics of soil moisture content at the field scale. We discuss measurement techniques that have become available in recent years and that provide unique opportunities to characterize field scale soil mois...

  9. Mapping the spatio-temporal distribution of threatened batoids to improve conservation in a subtropical estuary.

    PubMed

    Possatto, F E; Broadhurst, M K; Spach, H L; Winemiller, K O; Millar, R B; Santos, K M; Lamour, M R

    2016-07-01

    The spatio-temporal distributions of four batoid species were examined in a subtropical estuary. Fluvial gradient was the most important factor explaining abundances, reflecting positive relationships with either salinity or distance from urbanised areas that were consistent across seasons and depths. The results support existing protected areas. PMID:27108671

  10. Construction of an Unbiased Spatio-temporal Atlas of the Tongue During Speech

    PubMed Central

    Woo, Jonghye; Xing, Fangxu; Lee, Junghoon; Stone, Maureen; Prince, Jerry L.

    2016-01-01

    Quantitative characterization and comparison of tongue motion during speech and swallowing present fundamental challenges because of striking variations in tongue structure and motion across subjects. A reliable and objective description of the dynamics tongue motion requires the consistent integration of inter-subject variability to detect the subtle changes in populations. To this end, in this work, we present an approach to constructing an unbiased spatio-temporal atlas of the tongue during speech for the first time, based on cine-MRI from twenty two normal subjects. First, we create a common spatial space using images from the reference time frame, a neutral position, in which the unbiased spatio-temporal atlas can be created. Second, we transport images from all time frames of all subjects into this common space via the single transformation. Third, we construct atlases for each time frame via groupwise diffeomorphic registration, which serves as the initial spatio-temporal atlas. Fourth, we update the spatio-temporal atlas by realigning each time sequence based on the Lipschitz norm on diffeomorphisms between each subject and the initial atlas. We evaluate and compare different configurations such as similarity measures to build the atlas. Our proposed method permits to accurately and objectively explain the main pattern of tongue surface motion. PMID:26221715

  11. Model term selection for spatio-temporal system identification using mutual information

    NASA Astrophysics Data System (ADS)

    Wang, Shu; Wei, Hua-Liang; Coca, Daniel; Billings, Stephen A.

    2013-02-01

    A new mutual information based algorithm is introduced for term selection in spatio-temporal models. A generalised cross validation procedure is also introduced for model length determination and examples based on cellular automata, coupled map lattice and partial differential equations are described.

  12. Analysis and Modeling of spatio-temporal Patterns of Carbon and Water Fluxes in Production Fields of Winter Wheat and Sugar Beet

    NASA Astrophysics Data System (ADS)

    Kupisch, M.; Langensiepen, M.; van Wijk, M.; Stadler, A.; Ewert, F.

    2011-12-01

    Gas exchange of CO2 and water vapour are important processes that determine crop growth and yield. Understanding their spatio-temporal variability at field level is necessary for accurate simulation of crop growth in fields with heterogeneous growing conditions and for parameterizing soil-vegetation-atmosphere transfer (SVAT) models. Accordingly, relationships between the spatio-temporal patterns of assimilation and transpiration rates and environmental (e.g. soil) heterogeneity are of specific interest. A particular challenge refers then to the appropriate method of up-scaling of these relationships from the leaf to the canopy and field level. Therefore, gas-exchange (CO2 and water vapour) was measured at different points in winter wheat and sugar beet fieldsboth at leaf and at canopy level in a nearly biweekly cycle during the growing seasons 2010 and 2011. The measurements comprised also C/N-content of leaf, leaf area index, soil water content and soil nitrogen content. The results revealed a strong spatial heterogeneity of carbon and water canopy fluxes across the fields. While canopy measurements had a temporal variability with distinct diurnal and seasonal patterns, the temporal (and spatial) variability of leaf level photosynthesisand transpirationwas comparably small.Further analysis suggests that the observed spatial and seasonal variability of canopy measurements was mainly caused by field heterogeneity in LAI and less by gas exchange rates per unit leaf area. However, both crops differed in their response to drought stress: while wheat responded mainly through irreversible reduction in green leaf area, the canopy assimilation rate of sugar beets decreases only temporarily with no observed effects in LAI. The obtained datasets from both years are the basis for parameterizing a crop growth model with canopy assimilation and transpiration components and for developing appropriate up-scaling methods from leaf to field. Our results indicate that it is

  13. Spatio-temporal structure of the wave packets generated by the solar terminator

    NASA Astrophysics Data System (ADS)

    Afraimovich, E. L.; Edemskiy, I. K.; Voeykov, S. V.; Yasyukevich, Yu. V.; Zhivetiev, I. V.

    2009-10-01

    Using long-term (1998--2009) total electron content (TEC) measurements from the GPS global network including dense network of GPS sites in USA and Japan, we have obtained the first data regarding the spatio-temporal structure and the statistics of medium-scale traveling wave packets (MS TWPs) excited by the solar terminator (ST). Total amount of the detected TWPs exceeds 565,000. There is no correlation between TWPs occurrence and geomagnetic and solar activity. We found that the diurnal, seasonal and spectral MS TWPs characteristics are specified by the solar terminator (ST) dynamics. MS TWPs are the chains of narrow-band TEC oscillations with single packet's duration of about 1-2 h and oscillation periods of 10-20 min. The total duration of chain is about 4-6 h. The MS TWPs spatial structure is characterized by a high degree of anisotropy and coherence at the distance of more than 10 wavelengths. Occurrence rate of daytime MS TWPs is high in winter and during equinoxes. Occurrence rate of nighttime MS TWPs has its peak in summer. These features are consistent with previous MS travelling ionosphere disturbance (TID) statistics obtained from 630-nm airglow imaging observations in Japan. In winter, MS TWPs in the northern hemisphere are observed 3-4 h after the morning ST passage. In summer, MS TWPs are detected 1.5-2 h before the evening ST appearance at the point of observations, but at the moment of the evening ST passage in the magneto-conjugate point. The obtained results are the first experimental evidence for the hypothesis of the ST-generated ion sound waves.

  14. Spatio-temporal variation in European starling reproductive success at multiple small spatial scales

    PubMed Central

    Brickhill, Daisy; Evans, Peter GH; Reid, Jane M

    2015-01-01

    Understanding population dynamics requires spatio-temporal variation in demography to be measured across appropriate spatial and temporal scales. However, the most appropriate spatial scale(s) may not be obvious, few datasets cover sufficient time periods, and key demographic rates are often incompletely measured. Consequently, it is often assumed that demography will be spatially homogeneous within populations that lack obvious subdivision. Here, we quantify small-scale spatial and temporal variation in a key demographic rate, reproductive success (RS), within an apparently contiguous population of European starlings. We used hierarchical cluster analysis to define spatial clusters of nest sites at multiple small spatial scales and long-term data to test the hypothesis that small-scale spatio-temporal variation in RS occurred. RS was measured as the number of chicks alive ca. 12 days posthatch either per first brood or per nest site per breeding season (thereby incorporating multiple breeding attempts). First brood RS varied substantially among spatial clusters and years. Furthermore, the pattern of spatial variation was stable across years; some nest clusters consistently produced more chicks than others. Total seasonal RS also varied substantially among spatial clusters and years. However, the magnitude of variation was much larger and the pattern of spatial variation was no longer temporally consistent. Furthermore, the estimated magnitude of spatial variation in RS was greater at smaller spatial scales. We thereby demonstrate substantial spatial, temporal, and spatio-temporal variation in RS occurring at very small spatial scales. We show that the estimated magnitude of this variation depended on spatial scale and that spatio-temporal variation would not have been detected if season-long RS had not been measured. Such small-scale spatio-temporal variation should be incorporated into empirical and theoretical treatments of population dynamics. PMID:26380670

  15. An Expectation-Maximization Method for Spatio-Temporal Blind Source Separation Using an AR-MOG Source Model

    PubMed Central

    Hild, Kenneth E.; Attias, Hagai T.; Nagarajan, Srikantan S.

    2009-01-01

    In this paper, we develop a maximum-likelihood (ML) spatio-temporal blind source separation (BSS) algorithm, where the temporal dependencies are explained by assuming that each source is an autoregressive (AR) process and the distribution of the associated independent identically distributed (i.i.d.) inovations process is described using a mixture of Gaussians. Unlike most ML methods, the proposed algorithm takes into account both spatial and temporal information, optimization is performed using the expectation-maximization (EM) method, the source model is adapted to maximize the likelihood, and the update equations have a simple, analytical form. The proposed method, which we refer to as autoregressive mixture of Gaussians (AR-MOG), outperforms nine other methods for artificial mixtures of real audio. We also show results for using AR-MOG to extract the fetal cardiac signal from real magnetocardiographic (MCG) data. PMID:18334368

  16. Multivariate spatio-temporal modelling for assessing Antarctica's present-day contribution to sea-level rise

    PubMed Central

    Zammit-Mangion, Andrew; Rougier, Jonathan; Schön, Nana; Lindgren, Finn; Bamber, Jonathan

    2015-01-01

    Antarctica is the world's largest fresh-water reservoir, with the potential to raise sea levels by about 60 m. An ice sheet contributes to sea-level rise (SLR) when its rate of ice discharge and/or surface melting exceeds accumulation through snowfall. Constraining the contribution of the ice sheets to present-day SLR is vital both for coastal development and planning, and climate projections. Information on various ice sheet processes is available from several remote sensing data sets, as well as in situ data such as global positioning system data. These data have differing coverage, spatial support, temporal sampling and sensing characteristics, and thus, it is advantageous to combine them all in a single framework for estimation of the SLR contribution and the assessment of processes controlling mass exchange with the ocean. In this paper, we predict the rate of height change due to salient geophysical processes in Antarctica and use these to provide estimates of SLR contribution with associated uncertainties. We employ a multivariate spatio-temporal model, approximated as a Gaussian Markov random field, to take advantage of differing spatio-temporal properties of the processes to separate the causes of the observed change. The process parameters are estimated from geophysical models, while the remaining parameters are estimated using a Markov chain Monte Carlo scheme, designed to operate in a high-performance computing environment across multiple nodes. We validate our methods against a separate data set and compare the results to those from studies that invariably employ numerical model outputs directly. We conclude that it is possible, and insightful, to assess Antarctica's contribution without explicit use of numerical models. Further, the results obtained here can be used to test the geophysical numerical models for which in situ data are hard to obtain. © 2015 The Authors. Environmetrics published by John Wiley & Sons Ltd. PMID:25937792

  17. Coupling observable data to the spatio-temporal properties of natural hazards, An application to the volcanic field of Harrat Rahat, Saudi Arabia

    NASA Astrophysics Data System (ADS)

    Runge, M.; Bebbington, M. S.; Cronin, S. J.; Lindsay, J. M.; Moufti, R.

    2013-12-01

    The volcanic field of Harrat Rahat in Saudi Arabia is a highly complex volcanic system with 950+ volcanic cones or craters distributed over 20,000 km2 and with evidence of volcanic activity spanning from 10 Ma to present with two historical eruptions in 641 AD and 1256 AD. This record, the proximity of Harrat Rahat to the city of Al-Madinah, and a possible stalled eruption in 1999 AD, drives a need to quantify the likelihood and magnitude of future eruptions. For volcanic fields, as is common for the majority of natural hazards, we cannot yet directly observe the underlying geophysical processes, nor do we understand them sufficiently to create reliable, predictive models. However, technological advancements and novel monitoring techniques facilitate the collection of a vast range of data types from satellite based to subsurface measurements for a region of interest. Observable data for Harrat Rahat include: vent locations, volumes and spatial distributions of past eruptive products, aeromagnetic and seismic interpretations of sub-surface structure, and regional tectonic models. We present here a bootstrap method whereby observed data values at the locations and times of an eruption are compared to values sampled at random points in space-time. This allows direct determination of the relationship (if any) between each observable data set and the spatio-temporal recurrence rates of volcanism in Harrat Rahat.

  18. Modeling spatio-temporal variations of seismicity in the San Jacinto Fault Zone

    NASA Astrophysics Data System (ADS)

    Zöller, G.; Ben-Zion, Y.

    2012-04-01

    We investigate spatio-temporal properties of earthquake patterns in the San Jacinto fault zone (SJFZ), California, between Cajon Pass and the Superstition Hill Fault, using long records of simulated seismicity constrained by available data. The model provides an effective realization (e.g. Ben-Zion 1996; Zöller et al. 2007) of a large segmented strike-slip fault zone in 3D elastic half space, with heterogeneous distributions of static/kinetic friction and creep properties, and boundary conditions consisting of constant velocity motion around the fault. The computational section of the fault contains small brittle slip patches which fail during earthquakes and may undergo some creep deformation between events. The creep rates increase to the end points of the computational section and with depth. Two significant offsets of the SJFZ at San Jacinto Valley and Coyote Ridge are modeled by strength heterogeneities. The simulated catalogs are compared to the seismicity recorded at the SJFZ since 1932 and to recently reported results on paleoearthquakes at sites along the SJFZ at Hog Lake (HL) and Mystic Lake (ML) in the last 1500 years (e.g. Onderdonk et al., 2012; Rockwell et al., 2012). We address several questions including the following intriguing issue raised by the available paleoseismological data: are large earthquakes with signatures in ML and HL typically correlated? In particular: is a typical paleoevent in HL an incomplete rupture that is continued later in ML, and vice versa? The simulation results provide insights on the statistical significance of these and other patterns, and the ability of the SJFZ to produce large earthquakes which have not been observed in recent decades.

  19. Assimilation of Spatio-Temporal Cosmic-Ray Neutron Data to Improve Hydrological Model Performance

    NASA Astrophysics Data System (ADS)

    Samaniego, L. E.; Schrön, M.; Kumar, R.; Zink, M.; Rosolem, R.; Rakovec, O.; Baroni, G.; Oswald, S. E.; Reinstorf, F.; Zacharias, S.

    2015-12-01

    Mesoscale hydrological models like mHM (Samaniego et al., 2010, WRR) are usually evaluated with observed discharge, which is a spatially integrated signal of the watershed. However, an accurate prediction of spatially distributed soil water content often is of higher interest for hydrologic prediction. For hydrologic models operating at intermediate to regional scales, Cosmic-Ray Neutron Sensors provide unrivaled soil moisture data which are much more representative than point data and of higher spatio-temporal resolution than most remote-sensing products. We are aiming to improve soil moisture calibration and evaluation in mHM with the support of the intermediate-scale data from cosmic-ray neutrons. The relationship between soil moisture profiles in the footprint and the corresponding cosmic-ray neutron counts is non-linear and not unique. Therefore we assimilate cosmic-ray neutron data directly by employing the nested forward model COSMIC (Shuttleworth et al. 2013, HESS), which calculates neutron counts from the modeled soil moisture. In optimization mode, mHM is able to calibrate parameters of both, the hydrological system and/or the neutron prediction model itself. Model performance is evaluated with independent measurements of soil moisture patterns from several catchment-wide TDR campaigns, time series of a Wireless Sensor Network and discharge in the small catchment "Schäfertal" (1.6 km2) in central Germany. One of the major challenges is to improve soil moisture and discharge performance simultaneously in the hydrologic model. This work is an important step towards the assimilation of continuous spatial data from mobile Cosmic Ray Sensing. The so-called TERENO:Rover delivers highly-resolved spatial patterns of water content in a whole catchment, which has a great potential to improve spatial performance of hydrological models.

  20. Homogeneous Geovisualization of Coastal Areas from Heterogeneous Spatio-Temporal Data

    NASA Astrophysics Data System (ADS)

    Masse, A.; Christophe, S.

    2015-08-01

    On coastal areas, recent increase in production of open-access high-quality data over large areas reflects high interests in modeling and geovisualization, especially for applications of sea level rise prediction, ship traffic security and ecological protection. Research interests are due to tricky challenges from the intrinsic nature of the coastal area, which is composed of complex geographical objects of which spatial extents vary in time, especially in the intertidal zone (tides, sands, etc.). Another interest is the complex modeling of this area based on imprecise cartographic objects (coastline, highest/lowest water level, etc.). The challenge of visualizing such specific area comes thus from 3D+t information, i.e. spatio-temporal data, and their visual integration. In this paper, we present a methodology for geovisualization issues over coastal areas. The first challenge consists in integrating multi-source heterogeneous data, i.e. raster and vector, terrestrial and hydrographic data often coming from various `paradigms', while providing a homogeneous geovisualization of the coastal area and in particular the phenomenon of the water depth. The second challenge consists in finding various possibilities to geovisualize this dynamic geographical phenomenon in controlling the level of photorealism in hybrid visualizations. Our approach is based on the use of a high-resolution Digital Terrain Model (DTM) coming from high resolution LiDAR data point cloud, tidal and topographic data. We present and discuss homogeneous hybrid visualizations, based on LiDAR and map, and on, LiDAR and orthoimagery, in order to enhance the realism while considering the water depth.

  1. Spatio-temporal variability of ionospheric Total Electron Content (TEC) over the Indian subcontinent derived from geodetic GPS network

    NASA Astrophysics Data System (ADS)

    Vijayan, M.; Kannoth, S.; Varghese, G.; Earnest, A.; Jade, S.; Bhatt, B. C.; Gupta, S. S.

    2013-12-01

    We present, for the first time, Ionospheric Total Electron Content (TEC) computed from dual frequency GPS data observed by Indian geodetic GPS network and neighboring IGS stations for more than a decade (2001-2012) (figure 1). Indian geodetic GPS network has more than 30 stations well spread across the Indian subcontinent, primarily, to study the tectonics of the Indian plate. Each station has geodetic grade dual frequency GPS receiver which are operated in continuous mode by making observations at every 30s since 2001. The ionospheric TEC presented here is computed from the code and phase GPS measurements using the software IONODETECT developed at CSIR 4PI. This decadal scale ionospheric data set covers from maxima of 23rd to maxima of 24th solar cycle with a broad spatial coverage from 35S to 56N and 38E to 134E (figure1). The GPS TEC computed at every 30 seconds over each sub-ionospheric point correlates well with International Reference Ionosphere(IRI) 2012 model in longer time scale, however, a strong spatio-temporal dependence in correlation is clearly observed. In addition a site specific, nearly systematic night time bias between GPS TEC and IRI-12 is noted. The advantage of using the systematic bias for correcting Differential Code Bias (DCB) in computing GPS TEC is discussed. We also discuss in detail the equatorial ionospheric processes and regional characteristics of Equatorial Ionization Anomaly (EIA) through latitudinal, diurnal, seasonal, and inter-annual variability of decadal scale GPS TEC computed over Indian subcontinent. EIA anomaly crust maxima during local noon on 30th November 2004 is clearly visible in the figure 1. The TEC variations associated with solar flares and solar maxima and minima during the solar cycles are also discussed to understand the impact of space weather on equatorial and mid latitude ionosphere as well as on navigation. Vertical TEC (VTEC) at each sub ionospheric pierce points (SIP) on 30th November 2004 from 0UTC to

  2. Nitrate sinks and sources as controls of spatio-temporal water quality dynamics in an agricultural headwater catchment

    NASA Astrophysics Data System (ADS)

    Schuetz, Tobias; Gascuel-Odoux, Chantal; Durand, Patrick; Weiler, Markus

    2016-02-01

    Several controls are known to affect water quality of stream networks during flow recession periods, such as solute leaching processes, surface water-groundwater interactions as well as biogeochemical in-stream turnover processes. Throughout the stream network, combinations of specific water and solute export rates and local in-stream conditions overlay the biogeochemical signals from upstream sections. Therefore, upstream sections can be considered functional units which could be distinguished and ordered regarding their relative contribution to nutrient dynamics at the catchment outlet. Based on snapshot sampling of flow and nitrate concentrations along the stream in an agricultural headwater during the summer flow recession period, we determined spatial and temporal patterns of water quality for the whole stream. A data-driven, in-stream-mixing-and-removal model was developed and applied for analysing the spatio-temporal in-stream retention processes and their effect on the spatio-temporal fluxes of nitrate from subcatchments. Thereby, we have been able to distinguish quantitatively between nitrate sinks, sources per stream reaches, and subcatchments, and thus we could disentangle the overlay of nitrate sink and source signals. For nitrate sources, we determined their permanent and temporal impact on stream water quality and for nitrate sinks, we found increasing nitrate removal efficiencies from upstream to downstream. Our results highlight the importance of distinct nitrate source locations within the watershed for in-stream concentrations and in-stream removal processes, respectively. Thus, our findings contribute to the development of a more dynamic perception of water quality in streams and rivers concerning ecological and sustainable water resource management.

  3. Nitrate sinks and sources as controls of spatio-temporal water quality dynamics in an agricultural headwater catchment

    NASA Astrophysics Data System (ADS)

    Schuetz, T.; Gascuel-Odoux, C.; Durand, P.; Weiler, M.

    2015-08-01

    Several controls are known to affect water quality of stream networks during flow recession periods such as solute leaching processes, surface water - groundwater interactions as well as biogeochemical in-stream retention processes. Throughout the stream network combinations of specific water and solute export rates and local in-stream conditions overlay the biogeochemical signals from upstream sections. Therefore, upstream sections can be considered as functional units which could be distinguished and ordered regarding their relative contribution to nutrient dynamics at the catchment outlet. Based on synoptic sampling of flow and nitrate concentrations along the stream in an agricultural headwater during the summer flow recession period, we determined spatial and temporal patterns of water quality for the whole stream. A data-driven, in-stream-mixing-and-removal model was developed and applied for analyzing the spatio-temporal in-stream retention processes and their effect on the spatio-temporal fluxes of nitrates from sub-catchments. Thereby, we have been able to distinguish between nitrate sinks and sources per stream reaches and sub-catchments. For nitrate sources we have determined their permanent and temporally impact on stream water quality and for nitrate sinks we have found increasing nitrate removal efficiencies from up- to downstream. Our results highlight the importance of distinct nitrate source locations within the watershed for in-stream concentrations and in-stream removal processes, respectively. Thus, our findings contribute to the development of a more dynamic perception of water quality in streams and rivers concerning ecological and sustainable water resources management.

  4. Disentangling multidimensional spatio-temporal data into their common and aberrant responses

    DOE PAGESBeta

    Chang, Young Hwan; Korkola, James; Amin, Dhara N.; Moasser, Mark M.; Carmena, Jose M.; Gray, Joe W.; Tomlin, Claire J.; Lisacek, Frederique

    2015-04-22

    With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures andmore » how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data.« less

  5. Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

    NASA Astrophysics Data System (ADS)

    Holton, L.; Deshayes, J.; Backeberg, B. C.; Loveday, B. R.; Hermes, J. C.; Reason, C. J. C.

    2016-05-01

    Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermohaline structure at the Good Hope line, a transect to the south west of the southern tip of Africa , is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution ({<} 1/10°) hindcast models agree on the temporal (2-4 cycles per year) and spatial (300-500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models ({<} 1/4^°/) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2° ) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

  6. Spatio-temporal image correlation (STIC): new technology for evaluation of the fetal heart.

    PubMed

    DeVore, G R; Falkensammer, P; Sklansky, M S; Platt, L D

    2003-10-01

    Spatio-temporal image correlation (STIC) is a new approach for clinical assessment of the fetal heart. It offers an easy to use technique to acquire data from the fetal heart and to aid in visualization with both two-dimensional and three-dimensional (3D) cine sequences. The acquisition is performed in two steps: first, images are acquired by a single, automatic volume sweep. Second, the system analyzes the image data according to their spatial and temporal domain and processes an online dynamic 3D image sequence that is displayed in a multiplanar reformatted cross-sectional display and/or a surface rendered display. The examiner can navigate within the heart, re-slice, and produce all of the standard image planes necessary for a comprehensive diagnosis. The advantages of STIC for use in evaluation of the fetal heart are as follows: the technique delivers a temporal resolution which corresponds to a B-mode frame rate of approximately 80 frames/s; it provides the examiner with an unlimited number of images for review; it allows for correlation between image planes that are perpendicular to the main image acquisition plane; it may shorten the evaluation time when complex heart defects are suspected; it enables the reconstruction of a 3D rendered image that contains depth and volume which may provide additional information that is not available from the thin multiplanar image slices (e.g. for pulmonary veins, septal thickness); it lends itself to storage and review of volume data by the examiner or by experts at a remote site; it provides the examiner with the ability to review all images in a looped cine sequence. PMID:14528474

  7. Spatio-Temporal Dynamics of Cholera during the First Year of the Epidemic in Haiti

    PubMed Central

    Gaudart, Jean; Rebaudet, Stanislas; Barrais, Robert; Boncy, Jacques; Faucher, Benoit; Piarroux, Martine; Magloire, Roc; Thimothe, Gabriel; Piarroux, Renaud

    2013-01-01

    Background In October 2010, cholera importation in Haiti triggered an epidemic that rapidly proved to be the world's largest epidemic of the seventh cholera pandemic. To establish effective control and elimination policies, strategies rely on the analysis of cholera dynamics. In this report, we describe the spatio-temporal dynamics of cholera and the associated environmental factors. Methodology/Principal findings Cholera-associated morbidity and mortality data were prospectively collected at the commune level according to the World Health Organization standard definition. Attack and mortality rates were estimated and mapped to assess epidemic clusters and trends. The relationships between environmental factors were assessed at the commune level using multivariate analysis. The global attack and mortality rates were 488.9 cases/10,000 inhabitants and 6.24 deaths/10,000 inhabitants, respectively. Attack rates displayed a significantly high level of spatial heterogeneity (varying from 64.7 to 3070.9 per 10,000 inhabitants), thereby suggesting disparate outbreak processes. The epidemic course exhibited two principal outbreaks. The first outbreak (October 16, 2010–January 30, 2011) displayed a centrifugal spread of a damping wave that suddenly emerged from Mirebalais. The second outbreak began at the end of May 2011, concomitant with the onset of the rainy season, and displayed a highly fragmented epidemic pattern. Environmental factors (river and rice fields: p<0.003) played a role in disease dynamics exclusively during the early phases of the epidemic. Conclusion Our findings demonstrate that the epidemic is still evolving, with a changing transmission pattern as time passes. Such an evolution could have hardly been anticipated, especially in a country struck by cholera for the first time. These results argue for the need for control measures involving intense efforts in rapid and exhaustive case tracking. PMID:23593516

  8. Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

    NASA Astrophysics Data System (ADS)

    Holton, L.; Deshayes, J.; Backeberg, B. C.; Loveday, B. R.; Hermes, J. C.; Reason, C. J. C.

    2016-05-01

    Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermohaline structure at the Good Hope line, a transect to the south west of the southern tip of Africa , is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution ({<} 1/10°) hindcast models agree on the temporal (2-4 cycles per year) and spatial (300-500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models ({<} 1/4°) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2°) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

  9. A method of estimating spatio-temporally distributed groundwater recharge using integrated surface-subsurface modelling

    NASA Astrophysics Data System (ADS)

    Chung, Il Moon; Kim, Nam Won; Lee, Jeongwoo; Sophocleous, Marios

    2010-05-01

    In general, there have been various methods of estimating groundwater recharge such as baseflow separation approaches, water budget analyses based on lumped conceptual models, and the water table fluctuation method (WTF) by using data from groundwater monitoring wells. However, groundwater recharge rates show spatial-temporal variability due to climatic conditions, land use, and hydrogeological heterogeneity, so these methods have various limitations in dealing with these characteristics. To overcome these limitations, we present a novel application of estimating recharge based on water balance components from the combined SWAT-MODFLOW model, which is an integrated surface-ground water model. During the process of computing recharge, the time delay is very important factor. SWAT model uses single linear reservoir storage module with an exponential decay weighting function for accounting time delay through vadose zone. However, single reservoir module has limitation on the long delay time. So we suggest a multi-reservoir storage routing module instead of single one, which represents a more realistic time delay through the vadose zone. By using this module, the parameter related to the delay time could be optimized by checking the correlation between simulated recharge and observed groundwater levels. The final step of this procedure is to compare simulated groundwater levels as well as simulated watershed runoff with observed ones. This method is applied to several watersheds in Korea for the purpose of testing the procedure for proper estimation of spatio-temporal groundwater recharge distribution. As this application procedure of estimating recharge has the advantages of the effectiveness of a watershed model as well as the accuracy of the WTF method, the estimated daily recharge rate could be thought as an improved estimate reflecting the heterogeneity of hydrogeology, climatic conditions, land use, as well as the physical behavior of water in soil layers and

  10. Spatio-temporal variation of drought in China during 1961-2012: A climatic perspective

    NASA Astrophysics Data System (ADS)

    Xu, Kai; Yang, Dawen; Yang, Hanbo; Li, Zhe; Qin, Yue; Shen, Yan

    2015-07-01

    Understanding the spatial and temporal variation of drought is essentially important in drought assessment. In most previous studies, drought event is usually identified in space and time separately, ignoring the nature of the dynamic processes. In order to better understand how drought changes have taken place in China during the past half-century, we carried out a comprehensive analysis of their spatio-temporal variation based on multiple drought indices from a climatic perspective. A 3-dimensional clustering method is developed to identify drought events in China from 1961 to 2012 based on the 0.25° gridded indices of SPI3 (3 months Standardized Precipitation Index), RDI3 (3 months Reconnaissance Drought Index) and SPEI3 (3 months Standardized Precipitation Evapotranspiration Index). Drought events are further characterized by five parameters: duration, affected area, severity, intensity, and centroid. Remotely sensed soil moisture data were used to validate the rationality of identified drought events. The results show that the two most severe drought events in the past half century which occurred in the periods 1962-1963 and 2010-2011 swept more than half of the non-arid regions in China. Large magnitude droughts were usually centered in the region from North China Plain to the downstream of Yangtze River. The western part of North China Plain, Loess Plateau, Sichuan Basin and Yunnan-Guizhou Plateau had a significant drying trend, which is mainly caused by the significant decrease of precipitation. The three drought indices have almost the same performance in the humid regions, while SPI and RDI were found to be more appropriate than SPEI in the arid regions.

  11. Automated classification of LV regional wall motion based on spatio-temporal profiles from cardiac cine magnetic resonance imaging

    NASA Astrophysics Data System (ADS)

    Mantilla, Juan; Garreau, Mireille; Bellanger, Jean-Jacques; Paredes, José Luis

    2013-11-01

    Assessment of the cardiac Left Ventricle (LV) wall motion is generally based on visual inspection or quantitative analysis of 2D+t sequences acquired in short-axis cardiac cine-Magnetic Resonance Imaging (MRI). Most often, cardiac dynamic is globally analized from two particular phases of the cardiac cycle. In this paper, we propose an automated method to classify regional wall motion in LV function based on spatio-temporal pro les and Support Vector Machines (SVM). This approach allows to obtain a binary classi cation between normal and abnormal motion, without the need of pre-processing and by exploiting all the images of the cardiac cycle. In each short- axis MRI slice level (basal, median, and apical), the spatio-temporal pro les are extracted from the selection of a subset of diametrical lines crossing opposites LV segments. Initialized at end-diastole phase, the pro les are concatenated with their corresponding projections into the succesive temporal phases of the cardiac cycle. These pro les are associated to di erent types of information that derive from the image (gray levels), Fourier, Wavelet or Curvelet domains. The approach has been tested on a set of 14 abnormal and 6 healthy patients by using a leave-one-out cross validation and two kernel functions for SVM classi er. The best classi cation performance is yielded by using four-level db4 wavelet transform and SVM with a linear kernel. At each slice level the results provided a classi cation rate of 87.14% in apical level, 95.48% in median level and 93.65% in basal level.

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

    PubMed Central

    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

  13. Salmonella enterica Serovar Napoli Infection in Italy from 2000 to 2013: Spatial and Spatio-Temporal Analysis of Cases Distribution and the Effect of Human and Animal Density on the Risk of Infection

    PubMed Central

    Graziani, Caterina; Luzzi, Ida; Owczarek, Slawomir; Dionisi, Anna Maria; Busani, Luca

    2015-01-01

    Background Salmonella Napoli is uncommon in Europe. In Italy however, it has been growing in importance since 2000. To date, no risk factors have been identified to account for its rise. This study aims at describing the epidemiology, spatial and spatio-temporal patterns of S. Napoli in Italy from 2000 to 2013, and to explore the role of several environmental correlates, namely urbanization, altitude and number of livestock farms, on the risk of S. Napoli infection among humans. Method Data were obtained from Enter-Net Italy, a network of diagnostic laboratories. The data were aggregated at the municipality level. Descriptive epidemiology, multivariate regression models, spatial and spatio-temporal analyses were performed on the number of cases and incidence rates. Results S. Napoli showed an expanding trend at the national level, and an increasing number of cases. Compared to the other main serovars in Italy, the risk of S. Napoli infection was higher in the age group <1 year, and lower in the other age groups. Although urbanization and the number of farms were associated with the risk of S. Napoli infection to some extent, their role in the epidemiology of the disease remains inconclusive. S. Napoli cases showed a positive global spatial autocorrelation as well as a significant spatio-temporal interaction. Twenty-four spatial and spatio-temporal clusters were identified, seven purely spatial and 17 spatio-temporal, mainly in north-western Italy. Most of the clusters were in areas characterized by urban and industrial settlements surrounded by agricultural land and an abundance of freshwater bodies. Conclusions Our results point to the presence, in a number of areas in Italy, of a Salmonella of public health concern originating in the environment. This highlights the increasing relevance of environmental, non-food-related sources of human exposure to enteric pathogens. PMID:26558381

  14. Spatial and Spatio-Temporal Models for Modeling Epidemiological Data with Excess Zeros

    PubMed Central

    Arab, Ali

    2015-01-01

    Epidemiological data often include excess zeros. This is particularly the case for data on rare conditions, diseases that are not common in specific areas or specific time periods, and conditions and diseases that are hard to detect or on the rise. In this paper, we provide a review of methods for modeling data with excess zeros with focus on count data, namely hurdle and zero-inflated models, and discuss extensions of these models to data with spatial and spatio-temporal dependence structures. We consider a Bayesian hierarchical framework to implement spatial and spatio-temporal models for data with excess zeros. We further review current implementation methods and computational tools. Finally, we provide a case study on five-year counts of confirmed cases of Lyme disease in Illinois at the county level. PMID:26343696

  15. Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

    PubMed Central

    Baratchi, Mitra; Meratnia, Nirvana; Havinga, Paul J. M.; Skidmore, Andrew K.; Toxopeus, Bert A. G.

    2013-01-01

    Movement ecology is a field which places movement as a basis for understanding animal behavior. To realize this concept, ecologists rely on data collection technologies providing spatio-temporal data in order to analyze movement. Recently, wireless sensor networks have offered new opportunities for data collection from remote places through multi-hop communication and collaborative capability of the nodes. Several technologies can be used in such networks for sensing purposes and for collecting spatio-temporal data from animals. In this paper, we investigate and review technological solutions which can be used for collecting data for wildlife monitoring. Our aim is to provide an overview of different sensing technologies used for wildlife monitoring and to review their capabilities in terms of data they provide for modeling movement behavior of animals. PMID:23666132

  16. DSTiPE Algorithm for Fuzzy Spatio-Temporal Risk Calculation in Wireless Environments

    SciTech Connect

    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.

  17. Identifying causal gateways and mediators in complex spatio-temporal systems.

    PubMed

    Runge, Jakob; Petoukhov, Vladimir; Donges, Jonathan F; Hlinka, Jaroslav; Jajcay, Nikola; Vejmelka, Martin; Hartman, David; Marwan, Norbert; Paluš, Milan; Kurths, Jürgen

    2015-01-01

    Identifying regions important for spreading and mediating perturbations is crucial to assess the susceptibilities of spatio-temporal complex systems such as the Earth's climate to volcanic eruptions, extreme events or geoengineering. Here a data-driven approach is introduced based on a dimension reduction, causal reconstruction, and novel network measures based on causal effect theory that go beyond standard complex network tools by distinguishing direct from indirect pathways. Applied to a data set of atmospheric dynamics, the method identifies several strongly uplifting regions acting as major gateways of perturbations spreading in the atmosphere. Additionally, the method provides a stricter statistical approach to pathways of atmospheric teleconnections, yielding insights into the Pacific-Indian Ocean interaction relevant for monsoonal dynamics. Also for neuroscience or power grids, the novel causal interaction perspective provides a complementary approach to simulations or experiments for understanding the functioning of complex spatio-temporal systems with potential applications in increasing their resilience to shocks or extreme events. PMID:26443010

  18. Spatio-Temporal Dynamics in Collective Frog Choruses Examined by Mathematical Modeling and Field Observations

    NASA Astrophysics Data System (ADS)

    Aihara, Ikkyu; Mizumoto, Takeshi; Otsuka, Takuma; Awano, Hiromitsu; Nagira, Kohei; Okuno, Hiroshi G.; Aihara, Kazuyuki

    2014-01-01

    This paper reports theoretical and experimental studies on spatio-temporal dynamics in the choruses of male Japanese tree frogs. First, we theoretically model their calling times and positions as a system of coupled mobile oscillators. Numerical simulation of the model as well as calculation of the order parameters show that the spatio-temporal dynamics exhibits bistability between two-cluster antisynchronization and wavy antisynchronization, by assuming that the frogs are attracted to the edge of a simple circular breeding site. Second, we change the shape of the breeding site from the circle to rectangles including a straight line, and evaluate the stability of two-cluster and wavy antisynchronization. Numerical simulation shows that two-cluster antisynchronization is more frequently observed than wavy antisynchronization. Finally, we recorded frog choruses at an actual paddy field using our sound-imaging method. Analysis of the video demonstrated a consistent result with the aforementioned simulation: namely, two-cluster antisynchronization was more frequently realized.

  19. Kronecker PCA based spatio-temporal modeling of video for dismount classification

    NASA Astrophysics Data System (ADS)

    Greenewald, Kristjan H.; Hero, Alfred O.

    2014-06-01

    We consider the application of KronPCA spatio-temporal modeling techniques1, 2 to the extraction of spatiotemporal features for video dismount classification. KronPCA performs a low-rank type of dimensionality reduction that is adapted to spatio-temporal data and is characterized by the T frame multiframe mean μ and covariance ∑ of p spatial features. For further regularization and improved inverse estimation, we also use the diagonally corrected KronPCA shrinkage methods we presented in.1 We apply this very general method to the modeling of the multivariate temporal behavior of HOG features extracted from pedestrian bounding boxes in video, with gender classification in a challenging dataset chosen as a specific application. The learned covariances for each class are used to extract spatiotemporal features which are then classified, achieving competitive classification performance.

  20. A model for optimizing file access patterns using spatio-temporal parallelism

    SciTech Connect

    Boonthanome, Nouanesengsy; Patchett, John; Geveci, Berk; Ahrens, James; Bauer, Andy; Chaudhary, Aashish; Miller, Ross G.; Shipman, Galen M.; Williams, Dean N.

    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.

  1. Identifying causal gateways and mediators in complex spatio-temporal systems

    PubMed Central

    Runge, Jakob; Petoukhov, Vladimir; Donges, Jonathan F.; Hlinka, Jaroslav; Jajcay, Nikola; Vejmelka, Martin; Hartman, David; Marwan, Norbert; Paluš, Milan; Kurths, Jürgen

    2015-01-01

    Identifying regions important for spreading and mediating perturbations is crucial to assess the susceptibilities of spatio-temporal complex systems such as the Earth's climate to volcanic eruptions, extreme events or geoengineering. Here a data-driven approach is introduced based on a dimension reduction, causal reconstruction, and novel network measures based on causal effect theory that go beyond standard complex network tools by distinguishing direct from indirect pathways. Applied to a data set of atmospheric dynamics, the method identifies several strongly uplifting regions acting as major gateways of perturbations spreading in the atmosphere. Additionally, the method provides a stricter statistical approach to pathways of atmospheric teleconnections, yielding insights into the Pacific–Indian Ocean interaction relevant for monsoonal dynamics. Also for neuroscience or power grids, the novel causal interaction perspective provides a complementary approach to simulations or experiments for understanding the functioning of complex spatio-temporal systems with potential applications in increasing their resilience to shocks or extreme events. PMID:26443010

  2. Spatio-temporal dynamics of a three interacting species mathematical model inspired in physics

    NASA Astrophysics Data System (ADS)

    Sánchez-Garduño, Faustino; Breña-Medina, Víctor F.

    2008-02-01

    In this paper we study both, analytically and numerically, the spatio-temporal dynamics of a three interacting species mathematical model. The populations take the form of pollinators, a plant and herbivores; the model consists of three nonlinear reaction-diffusion-advection equations. In view of considering the full model, as a previous step we firstly analyze a mutualistic interaction (pollinator-plant), later on a predator-prey (plant-herbivore) interaction model is studied and finally, we consider the full model. In all cases, the purely temporal dynamics is given; meanwhile for the spatio-temporal dynamics, we use numerical simulations, corresponding to those parameter values for which we obtain interesting temporal dynamics.

  3. Spatio-temporal registration in multiplane MRI acquisitions for 3D colon motiliy analysis

    NASA Astrophysics Data System (ADS)

    Kutter, Oliver; Kirchhoff, Sonja; Berkovich, Marina; Reiser, Maximilian; Navab, Nassir

    2008-03-01

    In this paper we present a novel method for analyzing and visualizing dynamic peristaltic motion of the colon in 3D from two series of differently oriented 2D MRI images. To this end, we have defined an MRI examination protocol, and introduced methods for spatio-temporal alignment of the two MRI image series into a common reference. This represents the main contribution of this paper, which enables the 3D analysis of peristaltic motion. The objective is to provide a detailed insight into this complex motion, aiding in the diagnosis and characterization of colon motion disorders. We have applied the proposed spatio-temporal method on Cine MRI data sets of healthy volunteers. The results have been inspected and validated by an expert radiologist. Segmentation and cylindrical approximation of the colon results in a 4D visualization of the peristaltic motion.

  4. Effects of climate change adaptation scenarios on perceived spatio-temporal characteristics of drought events

    NASA Astrophysics Data System (ADS)

    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

  5. Identifying causal gateways and mediators in complex spatio-temporal systems

    NASA Astrophysics Data System (ADS)

    Runge, Jakob; Petoukhov, Vladimir; Donges, Jonathan F.; Hlinka, Jaroslav; Jajcay, Nikola; Vejmelka, Martin; Hartman, David; Marwan, Norbert; Paluš, Milan; Kurths, Jürgen

    2015-10-01

    Identifying regions important for spreading and mediating perturbations is crucial to assess the susceptibilities of spatio-temporal complex systems such as the Earth's climate to volcanic eruptions, extreme events or geoengineering. Here a data-driven approach is introduced based on a dimension reduction, causal reconstruction, and novel network measures based on causal effect theory that go beyond standard complex network tools by distinguishing direct from indirect pathways. Applied to a data set of atmospheric dynamics, the method identifies several strongly uplifting regions acting as major gateways of perturbations spreading in the atmosphere. Additionally, the method provides a stricter statistical approach to pathways of atmospheric teleconnections, yielding insights into the Pacific-Indian Ocean interaction relevant for monsoonal dynamics. Also for neuroscience or power grids, the novel causal interaction perspective provides a complementary approach to simulations or experiments for understanding the functioning of complex spatio-temporal systems with potential applications in increasing their resilience to shocks or extreme events.

  6. Spatio-temporal pattern of viral meningitis in Michigan, 1993-2001

    NASA Astrophysics Data System (ADS)

    Greene, Sharon K.; Schmidt, Mark A.; Stobierski, Mary Grace; Wilson, Mark L.

    2005-05-01

    To characterize Michigan's high viral meningitis incidence rates, 8,803 cases from 1993-2001 were analyzed for standard epidemiological indices, geographic distribution, and spatio-temporal clusters. Blacks and infants were found to be high-risk groups. Annual seasonality and interannual variability in epidemic magnitude were apparent. Cases were concentrated in southern Michigan, and cumulative incidence was correlated with population density at the county level (r=0.45, p<0.001). Kulldorff's Scan test identified the occurrence of spatio-temporal clusters in Lower Michigan during July-October 1998 and 2001 (p=0.01). More extensive data on cases, laboratory isolates, sociodemographics, and environmental exposures should improve detection and enhance the effectiveness of a Space-Time Information System aimed at prevention.

  7. Synchronization and control in time-delayed complex networks and spatio-temporal patterns

    NASA Astrophysics Data System (ADS)

    Banerjee, S.; Kurths, J.; Schöll, E.

    2016-02-01

    This special topics issue is a collection of contributions on the recent developments of control and synchronization in time delayed systems and space time chaos. The various articles report interesting results on time delayed complex networks; fractional order delayed models; dynamics of spatio-temporal patterns; stochastic models etc. Experimental analysis on synchronization, dynamics and control of chaos are also well investigated using Field Programmable Gate Array (FPGA), circuit realizations and chemical reactions.

  8. Combined optical solitons with parabolic law nonlinearity and spatio-temporal dispersion

    NASA Astrophysics Data System (ADS)

    Zhou, Qin; Zhu, Qiuping

    2015-03-01

    In this work, combined optical solitons are constructed in a weakly nonlocal nonlinear medium. The spatio-temporal dispersion (STD), parabolic law nonlinearity, detuning, nonlinear dispersion as well as inter-modal dispersion are taken into account. The integration tool that is applied is the complex envelope function ansatz. The influences of different parameters on dynamical behavior of combined optical solitons are discussed. The results are useful in describing the propagation of combined optical solitons with STD and parabolic law nonlinearity.

  9. Spatio-temporal Transmission and Environmental Determinants of Schistosomiasis Japonica in Anhui Province, China

    PubMed Central

    Hu, Yi; Li, Rui; Bergquist, Robert; Lynn, Henry; Gao, Fenghua; Wang, Qizhi; Zhang, Shiqing; Sun, Liqian; Zhang, Zhijie; Jiang, Qingwu

    2015-01-01

    Background Schistosomiasis japonica still remains of public health and economic significance in China, especially in the lake and marshland areas along the Yangtze River Basin, where the control of transmission has proven difficult. In the study, we investigated spatio-temporal variations of S. japonicum infection risk in Anhui Province and assessed the associations of the disease with key environmental factors with the aim of understanding the mechanism of the disease and seeking clues to effective and sustainable schistosomiasis control. Methodology/Principal Findings Infection data of schistosomiasis from annual conventional surveys were obtained at the village level in Anhui Province, China, from 2000 to 2010 and used in combination with environmental data. The spatio-temporal kriging model was used to assess how these environmental factors affected the spatio-temporal pattern of schistosomiasis risk. Our results suggested that seasonal variation of the normalized difference vegetation index (NDVI), seasonal variation of land surface temperature at daytime (LSTD), and distance to the Yangtze River were negatively significantly associated with risk of schistosomiasis. Predictive maps showed that schistosomiasis prevalence remained at a low level and schistosomiasis risk mainly evolved along the Yangtze River. Schistosomiasis risk also followed a focal spatial pattern, fluctuating temporally with a peak (the largest spatial extent) in 2005 and then contracting gradually but with a scattered distribution until 2010. Conclusion The fitted spatio-temporal kriging model can capture variations of schistosomiasis risk over space and time. Combined with techniques of geographic information system (GIS) and remote sensing (RS), this approach facilitates and enriches risk modeling of schistosomiasis, which in turn helps to identify prior areas for effective and sustainable control of schistosomiasis in Anhui Province and perhaps elsewhere in China. PMID:25659112

  10. Projecting low and extensive dimensional chaos from spatio-temporal dynamics

    NASA Astrophysics Data System (ADS)

    Ananthakrishna, G.; Sarmah, R.

    2013-07-01

    We review the spatio-temporal dynamical features of the Ananthakrishna model for the Portevin-Le Chatelier effect, a kind of plastic instability observed under constant strain rate deformation conditions. We then establish a qualitative correspondence between the spatio-temporal structures that evolve continuously in the instability domain and the nature of the irregularity of the scalar stress signal. Rest of the study is on quantifying the dynamical information contained in the stress signals about the spatio-temporal dynamics of the model. We show that at low applied strain rates, there is a one-to-one correspondence with the randomly nucleated isolated bursts of mobile dislocation density and the stress drops. We then show that the model equations are spatio-temporally chaotic by demonstrating the number of positive Lyapunov exponents and Lyapunov dimension scale with the system size at low and high strain rates. Using a modified algorithm for calculating correlation dimension density, we show that the stress-strain signals at low applied strain rates corresponding to spatially uncorrelated dislocation bands exhibit features of low dimensional chaos. This is made quantitative by demonstrating that the model equations can be approximately reduced to space independent model equations for the average dislocation densities, which is known to be low-dimensionally chaotic. However, the scaling regime for the correlation dimension shrinks with increasing applied strain rate due to increasing propensity for propagation of the dislocation bands. The stress signals in the partially propagating to fully propagating bands turn to have features of extensive chaos.

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

    NASA Astrophysics Data System (ADS)

    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. Robust segmentation of 4D cardiac MRI-tagged images via spatio-temporal propagation

    NASA Astrophysics Data System (ADS)

    Qian, Zhen; Huang, Xiaolei; Metaxas, Dimitris N.; Axel, Leon

    2005-04-01

    In this paper we present a robust method for segmenting and tracking cardiac contours and tags in 4D cardiac MRI tagged images via spatio-temporal propagation. Our method is based on two main techniques: the Metamorphs Segmentation for robust boundary estimation, and the tunable Gabor filter bank for tagging lines enhancement, removal and myocardium tracking. We have developed a prototype system based on the integration of these two techniques, and achieved efficient, robust segmentation and tracking with minimal human interaction.

  13. The impact of seasonal signals on spatio-temporal filtering

    NASA Astrophysics Data System (ADS)

    Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

    2016-04-01

    Existence of Common Mode Errors (CMEs) in permanent GNSS networks contribute to spatial and temporal correlation in residual time series. Time series from permanently observing GNSS stations of distance less than 2 000 km are similarly influenced by such CME sources as: mismodelling (Earth Orientation Parameters - EOP, satellite orbits or antenna phase center variations) during the process of the reference frame realization, large-scale atmospheric and hydrospheric effects as well as small scale crust deformations. Residuals obtained as a result of detrending and deseasonalising of topocentric GNSS time series arranged epoch-by-epoch form an observation matrix independently for each component (North, East, Up). CME is treated as internal structure of the data. Assuming a uniform temporal function across the network it is possible to filter CME out using PCA (Principal Component Analysis) approach. Some of above described CME sources may be reflected as a wide range of frequencies in GPS residual time series. In order to determine an impact of seasonal signals modeling to existence of spatial correlation in network and consequently the results of CME filtration, we chose two ways of modeling. The first approach was commonly presented by previous authors, who modeled with the Least-Squares Estimation (LSE) only annual and semi-annual oscillations. In the second one the set of residuals was a result of modeling of deterministic part that included fortnightly periods plus up to 9th harmonics of Chandlerian, tropical and draconitic oscillations. Correlation coefficients for residuals in parallel with KMO (Kaiser-Meyer-Olkin) statistic and Bartlett's test of sphericity were determined. For this research we used time series expressed in ITRF2008 provided by JPL (Jet Propulsion Laboratory). GPS processing was made using GIPSY-OASIS software in a PPP (Precise Point Positioning) mode. In order to form GPS station network that meet demands of uniform spatial response to the

  14. Integration of spatio-temporal contrast sensitivity with a multi-slice channelized Hotelling observer

    NASA Astrophysics Data System (ADS)

    Avanaki, Ali N.; Espig, Kathryn S.; Marchessoux, Cedric; Krupinski, Elizabeth A.; Bakic, Predrag R.; Kimpe, Tom R. L.; Maidment, Andrew D. A.

    2013-03-01

    Barten's model of spatio-temporal contrast sensitivity function of human visual system is embedded in a multi-slice channelized Hotelling observer. This is done by 3D filtering of the stack of images with the spatio-temporal contrast sensitivity function and feeding the result (i.e., the perceived image stack) to the multi-slice channelized Hotelling observer. The proposed procedure of considering spatio-temporal contrast sensitivity function is generic in the sense that it can be used with observers other than multi-slice channelized Hotelling observer. Detection performance of the new observer in digital breast tomosynthesis is measured in a variety of browsing speeds, at two spatial sampling rates, using computer simulations. Our results show a peak in detection performance in mid browsing speeds. We compare our results to those of a human observer study reported earlier (I. Diaz et al. SPIE MI 2011). The effects of display luminance, contrast and spatial sampling rate, with and without considering foveal vision, are also studied. Reported simulations are conducted with real digital breast tomosynthesis image stacks, as well as stacks from an anthropomorphic software breast phantom (P. Bakic et al. Med Phys. 2011). Lesion cases are simulated by inserting single micro-calcifications or masses. Limitations of our methods and ways to improve them are discussed.

  15. Oversaturated part-based visual tracking via spatio-temporal context learning.

    PubMed

    Liu, Wei; Li, Jicheng; Shi, Zhiguang; Chen, Xiaotian; Chen, Xiao

    2016-09-01

    Partial occlusion is one of the key challenging factors in a robust visual tracking method. To solve this issue, part-based trackers are widely explored; most of them are computationally expensive and therefore infeasible for real-time applications. Context information around the target has been used in tracking, which was recently renewed by a spatio-temporal context (STC) tracker. The fast Fourier transform adopted in STC equips it with high efficiency. However, the global context used in STC alleviates the performance when dealing with occlusion. In this paper, we propose an oversaturated part-based tracker based on spatio-temporal context learning, which tracks objects based on selected parts with spatio-temporal context learning. Furthermore, a structural layout constraint and a novel model update strategy are utilized to enhance the tracker's anti-occlusion ability and to deal with other appearance changes effectively. Extensive experimental results demonstrate our tracker's superior robustness against the original STC and other state-of-art methods. PMID:27607271

  16. Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies

    PubMed Central

    Mitchell, Richard

    2014-01-01

    Estimating the long-term health impact of air pollution using an ecological spatio-temporal study design is a challenging task, due to the presence of residual spatio-temporal autocorrelation in the health counts after adjusting for the covariate effects. This autocorrelation is commonly modelled by a set of random effects represented by a Gaussian Markov random field (GMRF) prior distribution, as part of a hierarchical Bayesian model. However, GMRF models typically assume the random effects are globally smooth in space and time, and thus are likely to be collinear to any spatially and temporally smooth covariates such as air pollution. Such collinearity leads to poor estimation performance of the estimated fixed effects, and motivated by this epidemiological problem, this paper proposes new GMRF methodology to allow for localised spatio-temporal smoothing. This means random effects that are either geographically or temporally adjacent are allowed to be autocorrelated or conditionally independent, which allows more flexible autocorrelation structures to be represented. This increased flexibility results in improved fixed effects estimation compared with global smoothing models, which is evidenced by our simulation study. The methodology is then applied to the motivating study investigating the long-term effects of air pollution on respiratory ill health in Greater Glasgow, Scotland between 2007 and 2011. PMID:24648100

  17. Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

    NASA Astrophysics Data System (ADS)

    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.

  18. Effects on orientation perception of manipulating the spatio-temporal prior probability of stimuli.

    PubMed

    Guo, Kun; Nevado, Angel; Robertson, Robert G; Pulgarin, Maribel; Thiele, Alexander; Young, Malcolm P

    2004-01-01

    Spatial and temporal regularities commonly exist in natural visual scenes. The knowledge of the probability structure of these regularities is likely to be informative for an efficient visual system. Here we explored how manipulating the spatio-temporal prior probability of stimuli affects human orientation perception. Stimulus sequences comprised four collinear bars (predictors) which appeared successively towards the foveal region, followed by a target bar with the same or different orientation. Subjects' orientation perception of the foveal target was biased towards the orientation of the predictors when presented in a highly ordered and predictable sequence. The discrimination thresholds were significantly elevated in proportion to increasing prior probabilities of the predictors. Breaking this sequence, by randomising presentation order or presentation duration, decreased the thresholds. These psychophysical observations are consistent with a Bayesian model, suggesting that a predictable spatio-temporal stimulus structure and an increased probability of collinear trials are associated with the increasing prior expectation of collinear events. Our results suggest that statistical spatio-temporal stimulus regularities are effectively integrated by human visual cortex over a range of spatial and temporal positions, thereby systematically affecting perception. PMID:15246751

  19. Evaluating the Spatio-Temporal Factors that Structure Network Parameters of Plant-Herbivore Interactions

    PubMed Central

    López-Carretero, Antonio; Díaz-Castelazo, Cecilia; Boege, Karina; Rico-Gray, Víctor

    2014-01-01

    Despite the dynamic nature of ecological interactions, most studies on species networks offer static representations of their structure, constraining our understanding of the ecological mechanisms involved in their spatio-temporal stability. This is the first study to evaluate plant-herbivore interaction networks on a small spatio-temporal scale. Specifically, we simultaneously assessed the effect of host plant availability, habitat complexity and seasonality on the structure of plant-herbivore networks in a coastal tropical ecosystem. Our results revealed that changes in the host plant community resulting from seasonality and habitat structure are reflected not only in the herbivore community, but also in the emergent properties (network parameters) of the plant-herbivore interaction network such as connectance, selectiveness and modularity. Habitat conditions and periods that are most stressful favored the presence of less selective and susceptible herbivore species, resulting in increased connectance within networks. In contrast, the high degree of selectivennes (i.e. interaction specialization) and modularity of the networks under less stressful conditions was promoted by the diversification in resource use by herbivores. By analyzing networks at a small spatio-temporal scale we identified the ecological factors structuring this network such as habitat complexity and seasonality. Our research offers new evidence on the role of abiotic and biotic factors in the variation of the properties of species interaction networks. PMID:25340790

  20. Identifying causal gateways and mediators in complex spatio-temporal systems

    NASA Astrophysics Data System (ADS)

    Runge, Jakob; Petoukhov, Vladimir; Donges, Jonathan; Hlinka, Jaroslav; Jajcay, Nikola; Vejmelka, Martin; Hartman, David; Marwan, Norbert; Palus, Milan; Kurths, Jürgen

    2016-04-01

    Identifying regions important for spreading and mediating perturbations is crucial to assess the susceptibilities of spatio-temporal complex systems such as the Earth's climate to volcanic eruptions, extreme events or geoengineering. Here a data-driven approach is introduced based on a dimension reduction, causal reconstruction, and novel network measures based on causal effect theory that go beyond standard complex network tools by distinguishing direct from indirect pathways. Applied to a data set of atmospheric dynamics, the method identifies several strongly uplifting regions acting as major gateways of perturbations spreading in the atmosphere. Additionally, the method provides a stricter statistical approach to pathways of atmospheric teleconnections, yielding insights into the Pacific-Indian Ocean interaction relevant for monsoonal dynamics. The novel causal interaction perspective provides a complementary approach to simulations or experiments for understanding the functioning of complex spatio-temporal systems with potential applications in increasing their resilience to shocks or extreme events. Reference: Runge, J., Petoukhov, V., Donges, J. F., Hlinka, J., Jajcay, N., Vejmelka, M., Hartman, D., Marwan, M., Paluš, M., Kurths, J. (2015). Identifying causal gateways and mediators in complex spatio-temporal systems. Nature Communications, 6, 8502. doi:10.1038/ncomms9502

  1. Spatio-temporal microseismic analysis of the Woodford Shale, Canadian County, Oklahoma

    NASA Astrophysics Data System (ADS)

    Eppehimer, Jarred

    Microseismicity provides data that can be used to monitor hydraulic fracture stimulation programs as well as to characterize the resulting hydraulic fractures. This is especially important in low permeability gas and oil shales, where the creation of additional permeability through these fracture treatments is essential to production. However, many applications and analyses of these data are either qualitative in nature or include a large element of interpretational bias. This study looks at two microseismic analytical techniques: the radius of gyration (ROG) tensor, as described in Sayers & Le Calvez (2010), and the methods described in Shapiro (2008) that relate spatio-temporal microseismic signatures to hydraulic diffusivity and ultimately hydraulic permeability. The radius of gyration tensor is used to generate a characteristic ellipsoid for any set of microseismic events, and the aspect ratio of this ellipsoid can be related to local in-situ horizontal stress ratios. These methods are applied to surface microseismic data collected for six horizontal wells drilled and completed in the Woodford Shale in Canadian County, Oklahoma. Additionally, an attempt is made to bridge the gap between these methods. Specifically, the characteristic ellipsoid generation from the radius of gyration tensor in Sayers & Le Calvez (2010) is applied to Shapiro's workflow. Shapiro attempts to link the 3D anisotropic triggering front of seismicity, which is an ellipsoid that envelops time-scaled microseismic events, to reservoir permeability. The radius of gyration tensor will generate this ellipsoid and remove interpretational bias that would have been present otherwise. Lastly, an attempt is made at relating the signatures present in the characteristic ellipsoids to zones of natural fracture reactivation. This is done on a stage-by-stage basis. The hypothesis is that an ellipsoid with a significant tilt in its most vertical principal axis and a significant azimuthal rotation away

  2. A SPATIO-TEMPORAL DOWNSCALER FOR OUTPUT FROM NUMERICAL MODELS

    EPA Science Inventory

    Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characterized by full spatial cove...

  3. Spatio-temporal soil moisture patterns - A meta-analysis using plot to catchment scale data

    NASA Astrophysics Data System (ADS)

    Korres, W.; Reichenau, T. G.; Fiener, P.; Koyama, C. N.; Bogena, H. R.; Cornelissen, T.; Baatz, R.; Herbst, M.; Diekkrüger, B.; Vereecken, H.; Schneider, K.

    2015-01-01

    Soil moisture is a key variable in hydrology, meteorology and agriculture. It is influenced by many factors, such as topography, soil properties, vegetation type, management, and meteorological conditions. The role of these factors in controlling the spatial patterns and temporal dynamics is often not well known. The aim of the current study is to analyze spatio-temporal soil moisture patterns acquired across a variety of land use types, on different spatial scales (plot to meso-scale catchment) and with different methods (point measurements, remote sensing, and modeling). We apply a uniform set of tools to determine method specific effects, as well as site and scale specific controlling factors. Spatial patterns of soil moisture and their temporal development were analyzed using nine different datasets from the Rur catchment in Western Germany. For all datasets we found negative linear relationships between the coefficient of variation and the mean soil moisture, indicating lower spatial variability at higher mean soil moisture. For a forest sub-catchment compared to cropped areas, the offset of this relationship was larger, with generally larger variability at similar mean soil moisture values. Using a geostatistical analysis of the soil moisture patterns we identified three groups of datasets with similar values for sill and range of the theoretical variogram: (i) modeled and measured datasets from the forest sub-catchment (patterns mainly influenced by soil properties and topography), (ii) remotely sensed datasets from the cropped part of the Rur catchment (patterns mainly influenced by the land-use structure of the cropped area), and (iii) modeled datasets from the cropped part of the Rur catchment (patterns mainly influenced by large scale variability of soil properties). A fractal analysis revealed that all analyzed soil moisture patterns showed a multifractal behavior, with at least one scale break and generally high fractal dimensions. Corresponding scale

  4. Spatio-Temporal Pattern and Socio-Economic Factors of Bacillary Dysentery at County Level in Sichuan Province, China.

    PubMed

    Ma, Yue; Zhang, Tao; Liu, Lei; Lv, Qiang; Yin, Fei

    2015-01-01

    Bacillary dysentery (BD) remains a big public health problem in China. Effective spatio-temporal monitoring of BD incidence is important for successful implementation of control and prevention measures. This study aimed to examine the spatio-temporal pattern of BD and analyze socio-economic factors that may affect BD incidence in Sichuan province, China. Firstly, we used space-time scan statistic to detect the high risk spatio-temporal clusters in each year. Then, bivariate spatial correlation and Bayesian spatio-temporal model were utilized to examine the associations between the socio-economic factors and BD incidence. Spatio-temporal clusters of BD were mainly located in the northern-southern belt of the midwest area of Sichuan province. The proportion of primary industry, the proportion of rural population and the rates of BD incidence show statistically significant positive correlation. The proportion of secondary industry, proportion of tertiary Industry, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons, per capital GDP and the rate of BD incidence show statistically significant negative correlation. The best fitting spatio-temporal model showed that medical and technical personnel per thousand persons and per capital GDP were significantly negative related to the risk of BD. PMID:26469274

  5. Spatio-Temporal Pattern and Socio-Economic Factors of Bacillary Dysentery at County Level in Sichuan Province, China

    PubMed Central

    Ma, Yue; Zhang, Tao; Liu, Lei; Lv, Qiang; Yin, Fei

    2015-01-01

    Bacillary dysentery (BD) remains a big public health problem in China. Effective spatio-temporal monitoring of BD incidence is important for successful implementation of control and prevention measures. This study aimed to examine the spatio-temporal pattern of BD and analyze socio-economic factors that may affect BD incidence in Sichuan province, China. Firstly, we used space-time scan statistic to detect the high risk spatio-temporal clusters in each year. Then, bivariate spatial correlation and Bayesian spatio-temporal model were utilized to examine the associations between the socio-economic factors and BD incidence. Spatio-temporal clusters of BD were mainly located in the northern-southern belt of the midwest area of Sichuan province. The proportion of primary industry, the proportion of rural population and the rates of BD incidence show statistically significant positive correlation. The proportion of secondary industry, proportion of tertiary Industry, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons, per capital GDP and the rate of BD incidence show statistically significant negative correlation. The best fitting spatio-temporal model showed that medical and technical personnel per thousand persons and per capital GDP were significantly negative related to the risk of BD. PMID:26469274

  6. An interactive spatio-temporal knowledge-discovery environment for solid Earth Science education

    NASA Astrophysics Data System (ADS)

    Landgrebe, T. C.; Müller, R. D.; EathByte Group

    2011-12-01

    prototyping of analysis work-flows without requiring programming expertise. A plug-in framework allows for the construction of new spatio-temporal data processing components, which is seeing the functionality and flexibility of this environment increasing rapidly, aided by an open-source model. The resultant ensemble of technologies lends itself to becoming a frontier teaching and research tool, providing the necessary abstraction of complexity required to better understand how the various complex Earth processes acted through time resulting in the familiar spatial configuration we observe today.

  7. A spatio-temporal screening tool for outlier detection in long term / large scale air quality observation time series and monitoring networks

    NASA Astrophysics Data System (ADS)

    Kracht, Oliver; Reuter, Hannes I.; Gerboles, Michel

    2013-04-01

    the attribute values of neighbours have a relationship due to the emission, transport and reaction of air pollutants, abnormal values can be detected by extreme values of their attributes compared to the attribute values of their neighbours. This comparison basically requires a spatio-temporal smoothing, i.e. a specific rule by which data points are averaged within a neighbourhood. The calculation of such reference basis has the effect of a low pass filter, meaning that high frequencies of the signal are removed from the data while preserving low frequencies. In this context, the choice of an appropriate kernel smoother function (e.g., nearest neighbour smoother, weighted kernel average smoother, etc.) is of particular importance. Our presentation will emphasize the effects bound to the selection of the corresponding weighting functions, like inverse squared normalized Euclidean distance or inverse squared Mahalanobis distance etc., and discuss the appropriateness and shortcomings of the different approaches. Corresponding parameter selections related to the extent of the spatio-temporal domain and the final test statistics for outlier thresholding are evaluated by sensitivity analysis. [1] R Development Core Team (2012): R: A language and environment for statistical computing. http://www.R-project.org/ [2] Shekhar S., Lu C. T. and Zhang P. (2003): A Unified Approach to Spatial Outliers Detection. GeoInformatica, 7(2).

  8. Spatio-temporal Interplay of RWTs and Cyclones in the North Atlantic

    NASA Astrophysics Data System (ADS)

    Schuster, M.; Ulbrich, U.

    2014-12-01

    We examine the relation of Rossby-Wave-Trains (RWTs) and cyclones in the North Atlantic. Extra-tropical cyclones are known to have high socioeconomic impacts (high windspeed and large amounts of precipitation). Long lived RWTs have been shown to be precursors for extreme events. Therefore they may impact the predictability of mid-latitude (extreme) weather systems. Current results point at the following relationship: The weakening or dissolving of a long lived RWT that was prevalent over the U.S. and the eastern Pacific for up to 5 days facilitates the genesis of a cyclone downstream - in the whole North Atlantic. In turn, the temporal and spacial coincidence of a newly developing or rather reinforcing RWT off the western coast of Europe and these pre-existing cyclone leads to a strengthening of the cyclone and triggers an explosive development just off the European coast. We apply automated schemes for the identification and tracking of RWTs and cyclones, respectively and relate their characteristics, with a focus on the impact for European climate. By evaluating reanalysis and model data of historical/uninitialized hindcast simulations, we aim to identify spatio-temporal connections between these objectively identified RWTs and cyclones. We then evaluate the interplay of RWT and cyclones in initialized hindcasts and a two way nested (TWN) model simulation. All named simulations are part of the MiKlip project (decadal climate prediction; funded by the German Ministry of Education and Research - BMBF). We also evaluate the decadal variability of cyclones and RWTs in the MiKlip simulations. For our TWN model setup, the regional climate model COSMO-CLM (CCLM) is nested into the atmosphere- ocean general circulation model ECHAM6/MPI-OM (MPI-ESM) in order to investigate the feedback of the meso-scales on the large scales and vice versa. Focus is laid on the development and propagation of synoptic systems (e.g. Rossby Wave Trains and cyclones) that are affecting Europe

  9. Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale

    NASA Astrophysics Data System (ADS)

    Ibrahim, Hesham M.; Huggins, David R.

    2011-07-01

    SummarySpatio-temporal patterns of soil water are major determinants of crop yield potential in dryland agriculture and can serve as the basis for delineating precision management zones. Soil water patterns can vary significantly due to differences in seasonal precipitation, soil properties and topographic features. In this study we used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water at the Washington State University Cook Agronomy Farm (CAF) near Pullman, WA. During the period 1999-2006, the CAF was divided into three roughly equal blocks (A, B, and C), and soil water at 0.3 m intervals to a depth of 1.5 m measured gravimetrically at approximately one third of the 369 geo-referenced points on the 37-ha watershed. These data were combined with terrain attributes, soil bulk density and apparent soil conductivity (EC a). The first EOF generated from the three blocks explained 73-76% of the soil water variability. Field patterns of soil water based on EOF interpolation varied between wet and dry conditions during spring and fall seasons. Under wet conditions, elevation and wetness index were the dominant factors regulating the spatial patterns of soil water. As soil dries out during summer and fall, soil properties (EC a and bulk density) become more important in explaining the spatial patterns of soil water. The EOFs generated from block B, which represents average topographic and soil properties, provided better estimates of soil water over the entire watershed with larger Nash-Sutcliffe Coefficient of Efficiency (NSCE) values, especially when the first two EOFs were retained. Including more than the first two EOFs did not significantly increase the NSCE of soil water estimate. The EOF interpolation method to estimate soil water variability worked slightly better during spring than during fall, with average NSCE values of 0.23 and 0.20, respectively. The predictable patterns of stored soil water in the spring could

  10. Spatio-temporal patterns and factors controlling the hydrogeochemistry of the river Jhelum basin, Kashmir Himalaya.

    PubMed

    Mir, Riyaz Ahmad; Jeelani, Gh; Dar, Farooq Ahmad

    2016-07-01

    River Jhelum is a major source of water for growing population and irrigation in the Kashmir Himalaya. The region is trending towards water scarcity as well as quality deterioration stage due to its highly unregulated development. The existence of few literature on various aspects of the basin prompts us to study the spatio-temporal variability of its physicochemical parameters and thereby to understand the regulating hydrogeochemical mechanisms based on 50 samples collected during high flow (June 2008) and low flow (January 2009) periods. The water chemistry exhibited significant spatial variability reflecting the mixing processes in the basin. The seasonal effect does change the concentration of ions significantly with modest variability in the order of ionic abundance. The Ca(2+) ion among cations and HCO3 (-) ion among anions dominate the ionic budget and correlates significantly with the diverse lithology of the basin. Three major water types, i.e., Ca-Mg-HCO3 (72 %), Ca-HCO3 (12 %), and Mg-Ca-HCO3 (16 %), suggest that the chemical composition of water is dominantly controlled by carbonate lithology, besides a significant contribution from silicates. However, at certain sites, the biological processes and anthropogenic activities play a major role. Relatively, the lower ionic concentration during high flow period (summer season) suggested the significant influence of higher discharge via dilution effect. The higher discharge due to higher rainfall and snow melting in response to rising temperature in this period leads to strong flushing of human and agricultural wastes into the river. The factor analysis also reflected the dominant control of varied lithology and anthropogenic sources on the water quality based on the four significant factors explaining collectively about 70-81 % of the total data variance. A two-member chloride mixing model used to estimate the discharge contribution of tributaries to the main river channel showed reliable results. It may

  11. A spatio-temporal model of wrinkling in photopolymerised networks

    NASA Astrophysics Data System (ADS)

    Hennessy, Matthew; Vitale, Alessandra; Stavrinou, Paul; Matar, Omar; Cabral, Joao

    2015-03-01

    Photopolymerisation is a common solidification process whereby crosslinked polymer networks are created by illuminating a monomer-rich bath with collimated light. In addition, photopolymerisation is extensively employed industrially and shows exceptional promise for advanced three-dimensional patterning of functional surfaces. Under conditions of strong optical attenuation and limited mass and thermal diffusion, polymerisation occurs in a localised region which propagates from the illuminated surface into the bulk as a travelling wave with a planar wavefront. Under specific conditions that we set out to map, this planar wavefront may become unstable and the surface of the resulting gel can acquire a wrinkled morphology. We believe this instability is mechanical in nature and arises from compressive stresses that are generated during frontal photopolymerization. In this talk, we will present a novel mathematical model that captures both the photopolymerisation with wrinkling processes. We show that by coupling photopolymerisation with wrinkling in a controlled manner, a number of interesting and industrially relevant patterns can be achieved.

  12. Spatio-temporal changes of seismic anisotropy in seismogenic zones

    NASA Astrophysics Data System (ADS)

    Saade, M.; Montagner, J.; Roux, P.; Paul, C.; Brenguier, F.; Enescu, B.; Shiomi, K.

    2013-12-01

    Seismic anisotropy plays a key role in the study of stress and strain fields in the earth. Potential temporal change of seismic anisotropy can be interpreted as change of the orientation of cracks in seismogenic zones and thus change of the stress field. Such temporal changes have been observed in seismogenic zones before and after earthquakes (Durand et al. , 2011) but are still not well understood. In this study, from a numerical point of view, we investigate the variations of the polarization of surface waves in anisotropic media. These variations are related to the elastic properties of the medium, in particular to anisotropy. The technique used is based on the calculation of the whole cross-correlation tensor (CCT) of ambient seismic noise. If the sources are randomly distributed in homogeneous medium, it allows us to reconstruct the Green's tensor between two stations continuously and to monitor the region through the use of its fluctuations. Therefore, the temporal change of the Green's cross-correlation tensor enables the monitoring of stress and strain fields. This technique is applied to synthetic seismograms computed in a transversally isotropic medium with horizontal symmetry axis (hereafter referred to an HTI medium) using a code RegSEM (Cupillard et al. , 2012) based on the spectral element method. We designed an experiment in order to investigate the influence of anisotropy on the CCT. In homogeneous, isotropic medium the off-diagonal terms of the Green's tensor are null. The CCT is computed between each pair of stations and then rotated in order to approximate the Green's tensor by minimizing the off-diagonal components. This procedure permits the calculation of the polarization angle of quasi-Rayleigh and quasi-Love waves, and to observe the azimuthal variation of their polarization. The results show that even a small variation of the azimuth of seismic anisotropy with respect to a certain pair of stations can induce, in some cases, a large

  13. Spatio-temporal Visualization for Environmental Decision Support

    SciTech Connect

    Bhaduri, Budhendra L.; Shankar, Mallikarjun; Sorokine, Alexandre; Ganguly, Auroop R.

    2009-01-01

    Traditional visualization of earth surface features has been addressed through visual exploration, analysis, synthesis, and presentation of observable geospatial data. However, characterizing the changes in their observable and unobservable properties of geospatial features is critical for planning and policy formulation. Recent approaches are addressing modeling and visualization of the temporal dynamics that describe observed and/or predicted physical and socioeconomic processes using vast volumes of earth observation (imagery and other geophysical) data from remote sensor networks. This paper provides an overview of selected geospatial modeling and simulation, exploratory analysis of earth observation data, and high performance visualization research at Oak Ridge National Laboratory for developing novel data driven approaches for geospatial knowledge discovery and visualization relevant to environmental decision support.

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

    PubMed Central

    Ohshima, Daisuke; Arimoto-Matsuzaki, Kyoko; Tomida, Taichiro; Takekawa, Mutsuhiro; Ichikawa, Kazuhisa

    2015-01-01

    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. PMID:26115353

  15. Spatio-temporal dynamics of pneumonia in bighorn sheep

    USGS Publications Warehouse

    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

  16. A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)

    NASA Astrophysics Data System (ADS)

    Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng

    2016-05-01

    Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a

  17. Spatio-temporal evaluation of cattle trade in Sweden: description of a grid network visualization technique.

    PubMed

    Widgren, Stefan; Frössling, Jenny

    2010-11-01

    Understanding the intensity and spatial patterns of animal transfers is of prime importance as geographical moves play an important part in the spread and potential control of contagious animal diseases of veterinary importance. For the purpose of visualizing all registered between-herd animal movements in Sweden between 1 July 2005 and 31 December 2008 by map animation, a grid network technique based on the Bresenham line algorithm was developed. Potential spatio-temporal clustering of animals registered as sold or purchased based on location and month of trade was also detected and tested using a spatial scan statistic. Calculations were based on data from 31,375 holdings and 3,487,426 head of cattle. In total, 988,167 between-herd movements of individual bovines were displayed in a sequence of maps covering three and a half years by 2-week intervals. The maps showed that several cattle movements, both short- and long-distance, take place in Sweden each week of the year. However, most animals (75%) were only registered at one single holding during the study period and 23% were sold to a different holding once. Spatial scan statistics based on data from the year 2008 indicated uneven distributions of purchased or sold animals in space and time. During each autumn, there was an increase in cattle movements and October and November showed significantly more cases of sold or purchased animals (relative risk ~1.7, p = 0.001). Based on the results, we conclude that cattle trade is constantly active at a considerable level. This, in combination with possibly insufficient biosecurity routines applied on many farms, constitutes a risk that contagious diseases are spread in the population. The grid network maps were generated through the use of open-source tools and software in order to decrease software costs and facilitate sharing of programme code. In addition, the technique was based on scripts that allow for the inclusion of iterative processes and that comprise all

  18. Spatio-Temporal Patterns of Demyelination and Remyelination in the Cuprizone Mouse Model.

    PubMed

    Tagge, Ian; O'Connor, Audrey; Chaudhary, Priya; Pollaro, Jim; Berlow, Yosef; Chalupsky, Megan; Bourdette, Dennis; Woltjer, Randy; Johnson, Mac; Rooney, William

    2016-01-01

    Cuprizone administration in mice provides a reproducible model of demyelination and spontaneous remyelination, and has been useful in understanding important aspects of human disease, including multiple sclerosis. In this study, we apply high spatial resolution quantitative MRI techniques to establish the spatio-temporal patterns of acute demyelination in C57BL/6 mice after 6 weeks of cuprizone administration, and subsequent remyelination after 6 weeks of post-cuprizone recovery. MRI measurements were complemented with Black Gold II stain for myelin and immunohistochemical stains for associated tissue changes. Gene expression was evaluated using the Allen Gene Expression Atlas. Twenty-five C57BL/6 male mice were split into control and cuprizone groups; MRI data were obtained at baseline, after 6 weeks of cuprizone, and 6 weeks post-cuprizone. High-resolution (100 μm isotropic) whole-brain coverage magnetization transfer ratio (MTR) parametric maps demonstrated concurrent caudal-to-rostral and medial-to-lateral gradients of MTR decrease within corpus callosum (CC) that correlated well with demyelination assessed histologically. Our results show that demyelination was not limited to the midsagittal line of the corpus callosum, and also that opposing gradients of demyelination occur in the lateral and medial CC. T2-weighted MRI gray/white matter contrast was strong at baseline, weak after 6 weeks of cuprizone treatment, and returned to a limited extent after recovery. MTR decreases during demyelination were observed throughout the brain, most clearly in callosal white matter. Myelin damage and repair appear to be influenced by proximity to oligodendrocyte progenitor cell populations and exhibit an inverse correlation with myelin basic protein gene expression. These findings suggest that susceptibility to injury and ability to repair vary across the brain, and whole-brain analysis is necessary to accurately characterize this model. Whole-brain parametric mapping

  19. Spatio-Temporal Patterns of Demyelination and Remyelination in the Cuprizone Mouse Model

    PubMed Central

    Tagge, Ian; O’Connor, Audrey; Chaudhary, Priya; Pollaro, Jim; Berlow, Yosef; Chalupsky, Megan; Bourdette, Dennis; Woltjer, Randy; Johnson, Mac; Rooney, William

    2016-01-01

    Cuprizone administration in mice provides a reproducible model of demyelination and spontaneous remyelination, and has been useful in understanding important aspects of human disease, including multiple sclerosis. In this study, we apply high spatial resolution quantitative MRI techniques to establish the spatio-temporal patterns of acute demyelination in C57BL/6 mice after 6 weeks of cuprizone administration, and subsequent remyelination after 6 weeks of post-cuprizone recovery. MRI measurements were complemented with Black Gold II stain for myelin and immunohistochemical stains for associated tissue changes. Gene expression was evaluated using the Allen Gene Expression Atlas. Twenty-five C57BL/6 male mice were split into control and cuprizone groups; MRI data were obtained at baseline, after 6 weeks of cuprizone, and 6 weeks post-cuprizone. High-resolution (100μm isotropic) whole-brain coverage magnetization transfer ratio (MTR) parametric maps demonstrated concurrent caudal-to-rostral and medial-to-lateral gradients of MTR decrease within corpus callosum (CC) that correlated well with demyelination assessed histologically. Our results show that demyelination was not limited to the midsagittal line of the corpus callosum, and also that opposing gradients of demyelination occur in the lateral and medial CC. T2-weighted MRI gray/white matter contrast was strong at baseline, weak after 6 weeks of cuprizone treatment, and returned to a limited extent after recovery. MTR decreases during demyelination were observed throughout the brain, most clearly in callosal white matter. Myelin damage and repair appear to be influenced by proximity to oligodendrocyte progenitor cell populations and exhibit an inverse correlation with myelin basic protein gene expression. These findings suggest that susceptibility to injury and ability to repair vary across the brain, and whole-brain analysis is necessary to accurately characterize this model. Whole-brain parametric mapping across

  20. Numerical investigations of triggering mechanisms of shallow landslides due to heterogeneous spatio-temporal hydrological patterns.

    NASA Astrophysics Data System (ADS)

    Schwarz, Massimiliano; Cohen, Denis

    2016-04-01

    Rainfall is one of the major triggering factor of shallow landslide around the world. The increase of soil moisture in the soil influences the stability of a slope through the increase of soil bulk density, the reduction of soil apparent cohesion (due to suction stress), and the increase in pore water pressure.The spatio-temporal transformations of such properties of soil are know to be heterogeneous and under constant change. For instance, there may be a condition where, in cracked clay-soil, water, during a rain event, produces a rapid increase of pore water pressure along preferential flow-paths (crack or roots), while soil moisture and suction within the soil matrix change minimally. An another site in a sandy soil, the situation might be very different where the increase of soil moisture and pore water pressure, and the decrease of soil suction take place more or less simultaneously across the entire soil profile. In both of these cases topography plays a major role in determining the accumulation of water along the slope through different subsurface flows intensities and directions. In many documented cases in the Alps, shallow landslides may also be triggered by the punctual exfiltration of water from bedrock or weathered geological strata. The hydro-geological characteristics of the catchment control this mechanism. These different situations aim to give an idea of the large spectrum of hydrological triggering conditions of shallow landslides. The heterogeneities of these hydrological conditions represent a difficult issue in modeling shallow landslide triggering mechanisms. In the simplest models, hydrology is assumed to influence changes in pore water pressure only, mostly using one dimensional vertical infiltration models. More advanced models consider changes in apparent cohesion due to changes in soil moisture or include more complex hydrological models to simulate water flow and distribution during a rainfall event. However, most models at the

  1. Spatio-Temporal Analysis of Forest Edge Dynamics in South Western Amazonia

    NASA Astrophysics Data System (ADS)

    Numata, I.; Cochrane, M. A.; Roberts, D. A.; Soares, J. V.

    2008-12-01

    Beyond removing forest, deforestation in the Amazon creates a lot of forest edges. These edges change the microclimate and ecosystem dynamics of the remaining tropical rain forests, contributing directly to forest degradation in the Amazon. Edge-induced changes such as tree mortality and fire vulnerability occur as a function of distance from edges and time since forest fragmentation. New edges are created and older edges are eliminated constantly as deforestation advances. However, Amazon forest edge dynamics over time and space are not well understood. We need to improve our knowledge about forest edge dynamics in order to estimate the actual amount of forest degradation caused by forest fragmentation. In this study, we performed deep spatio-temporal analyses of forest fragmentation for Rondônia, in the southwestern Amazon, using a multitemporal Landsat dataset (1984-2005). Our goals were to: 1) calculate erosion/persistence of forest edges; 2) detect edge age-composition of all forest edges and; 3) estimate total degraded forest area due to forest edge effects. Two counties of different stages of deforestation were selected. Campo Novo de Rondônia (early stage) and Ouro Preto (final stage). Overall, more than 50% of forest edges were eliminated in the first four years, while only 20% of edges survived more than 10 years after edge creation. The composition of edge-ages differs according to the stage of deforestation. Between 2001 and 2005, nearly 60% of forest edges in recently developed Campo Novo de Rondônia were 0-4 years old, with only 20% > 10 years old. Conversely, in the old frontier Ouro Preto region, only 23% of forest edges were 0-4 years old and 50% were > 10 years old. These results suggest that high edge erosion rates in the years following edge creation may cause many edges disappear before they experience the complete process of edge-induced changes such as biomass collapse, potentially reducing the estimated impact of existing forest edges on

  2. Spatio-Temporal Modelling of Dust Transport over Surface Mining Areas and Neighbouring Residential Zones

    PubMed Central

    Matejicek, Lubos; Janour, Zbynek; Benes, Ludek; Bodnar, Tomas; Gulikova, Eva

    2008-01-01

    Projects focusing on spatio-temporal modelling of the living environment need to manage a wide range of terrain measurements, existing spatial data, time series, results of spatial analysis and inputs/outputs from numerical simulations. Thus, GISs are often used to manage data from remote sensors, to provide advanced spatial analysis and to integrate numerical models. In order to demonstrate the integration of spatial data, time series and methods in the framework of the GIS, we present a case study focused on the modelling of dust transport over a surface coal mining area, exploring spatial data from 3D laser scanners, GPS measurements, aerial images, time series of meteorological observations, inputs/outputs form numerical models and existing geographic resources. To achieve this, digital terrain models, layers including GPS thematic mapping, and scenes with simulation of wind flows are created to visualize and interpret coal dust transport over the mine area and a neighbouring residential zone. A temporary coal storage and sorting site, located near the residential zone, is one of the dominant sources of emissions. Using numerical simulations, the possible effects of wind flows are observed over the surface, modified by natural objects and man-made obstacles. The coal dust drifts with the wind in the direction of the residential zone and is partially deposited in this area. The simultaneous display of the digital map layers together with the location of the dominant emission source, wind flows and protected areas enables a risk assessment of the dust deposition in the area of interest to be performed. In order to obtain a more accurate simulation of wind flows over the temporary storage and sorting site, 3D laser scanning and GPS thematic mapping are used to create a more detailed digital terrain model. Thus, visualization of wind flows over the area of interest combined with 3D map layers enables the exploration of the processes of coal dust deposition at a

  3. Sensitivity Analysis of a Spatio-Temporal Avalanche Forecasting Model Based on Support Vector Machines

    NASA Astrophysics Data System (ADS)

    Matasci, G.; Pozdnoukhov, A.; Kanevski, M.

    2009-04-01

    The recent progress in environmental monitoring technologies allows capturing extensive amount of data that can be used to assist in avalanche forecasting. While it is not straightforward to directly obtain the stability factors with the available technologies, the snow-pack profiles and especially meteorological parameters are becoming more and more available at finer spatial and temporal scales. Being very useful for improving physical modelling, these data are also of particular interest regarding their use involving the contemporary data-driven techniques of machine learning. Such, the use of support vector machine classifier opens ways to discriminate the ``safe'' and ``dangerous'' conditions in the feature space of factors related to avalanche activity based on historical observations. The input space of factors is constructed from the number of direct and indirect snowpack and weather observations pre-processed with heuristic and physical models into a high-dimensional spatially varying vector of input parameters. The particular system presented in this work is implemented for the avalanche-prone site of Ben Nevis, Lochaber region in Scotland. A data-driven model for spatio-temporal avalanche danger forecasting provides an avalanche danger map for this local (5x5 km) region at the resolution of 10m based on weather and avalanche observations made by forecasters on a daily basis at the site. We present the further work aimed at overcoming the ``black-box'' type modelling, a disadvantage the machine learning methods are often criticized for. It explores what the data-driven method of support vector machine has to offer to improve the interpretability of the forecast, uncovers the properties of the developed system with respect to highlighting which are the important features that led to the particular prediction (both in time and space), and presents the analysis of sensitivity of the prediction with respect to the varying input parameters. The purpose of the

  4. Whole-animal imaging with high spatio-temporal resolution

    NASA Astrophysics Data System (ADS)

    Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

    2016-03-01

    We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

  5. An algebra for spatio-temporal information generation

    NASA Astrophysics Data System (ADS)

    Pebesma, Edzer; Scheider, Simon; Gräler, Benedikt; Stasch, Christoph; Hinz, Matthias

    2016-04-01

    When we accept the premises of James Frew's laws of metadata (Frew's first law: scientists don't write metadata; Frew's second law: any scientist can be forced to write bad metadata), but also assume that scientists try to maximise the impact of their research findings, can we develop our information infrastructures such that useful metadata is generated automatically? Currently, sharing of data and software to completely reproduce research findings is becoming standard, e.g. in the Journal of Statistical Software [1]. The reproduction (e.g. R) scripts however convey correct syntax, but still limited semantics. We propose [2] a new, platform-neutral way to algebraically describe how data is generated, e.g. by observation, and how data is derived, e.g. by processing observations. It starts with forming functions composed of four reference system types (space, time, quality, entity), which express for instance continuity of objects over time, and continuity of fields over space and time. Data, which is discrete by definition, is generated by evaluating such functions at discrete space and time instances, or by evaluating a convolution (aggregation) over them. Derived data is obtained by inputting data to data derivation functions, which for instance interpolate, estimate, aggregate, or convert fields into objects and vice versa. As opposed to the traditional when, where and what semantics of data sets, our algebra focuses on describing how a data set was generated. We argue that it can be used to discover data sets that were derived from a particular source x, or derived by a particular procedure y. It may also form the basis for inferring meaningfulness of derivation procedures [3]. Current research focuses on automatically generating provenance documentation from R scripts. [1] http://www.jstatsoft.org/ (open access) [2] http://www.meaningfulspatialstatistics.org has the full paper (in review) [3] Stasch, C., S. Scheider, E. Pebesma, W. Kuhn, 2014. Meaningful

  6. Spatio-temporal course of macrophage-like cell accumulation after experimental embolic stroke depending on treatment with tissue plasminogen activator and its combination with hyperbaric oxygenation

    PubMed Central

    Michalski, D.; Heindl, M.; Kacza, J.; Laignel, F.; Küppers-Tiedt, L.; Schneider, D.; Grosche, J.; Boltze, J.; Löhr, M.; Hobohm, C.; Härtig, W.

    2012-01-01

    Inflammation following ischaemic stroke attracts high priority in current research, particularly using human-like models and long-term observation periods considering translational aspects. The present study aimed on the spatio-temporal course of macrophage-like cell accumulation after experimental thromboembolic stroke and addressed microglial and astroglial reactions in the ischaemic border zone. Further, effects of tissue plasminogen activator (tPA) as currently best treatment for stroke and the potentially neuroprotective co-administration of hyperbaric oxygen (HBO) were investigated. Rats underwent middle cerebral artery occlusion and were assigned to control, tPA or tPA+HBO. Twenty-four hours, 7, 14 and 28 days were determined as observation time points. The accumulation of macrophage-like cells was semiquantitatively assessed by CD68 staining in the ischaemic area and ischaemic border zone, and linked to the clinical course. CD11b, ionized calcium binding adaptor molecule 1 (Iba), glial fibrillary acidic protein (GFAP) and Neuronal Nuclei (NeuN) were applied to reveal delayed glial and neuronal alterations. In all groups, the accumulation of macrophage-like cells increased distinctly from 24 hours to 7 days post ischaemia. tPA+HBO tended to decrease macrophage-like cell accumulation at day 14 and 28. Overall, a trend towards an association of increased accumulation and pronounced reduction of the neurological deficit was found. Concerning delayed inflammatory reactions, an activation of microglia and astrocytes with co-occurring neuronal loss was observed on day 28. Thereby, astrogliosis was found circularly in contrast to microglial activation directly in the ischaemic area. This study supports previous data on long-lasting inflammatory processes following experimental stroke, and additionally provides region-specific details on glial reactions. The tendency towards a decreasing macrophage-like cell accumulation after tPA+HBO needs to be discussed

  7. Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets.

    PubMed

    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. PMID:26953173

  8. China's water resources vulnerability: A spatio-temporal analysis during 2003-2013

    NASA Astrophysics Data System (ADS)

    Cai, J.; Varis, O.; Yin, H.

    2015-12-01

    The present highly serious situation of China's water environment and aquatic ecosystems has occurred in the context of its stunning socioeconomic development over the past several decades. Therefore, an analysis with a high spatio-temporal resolution of the vulnerability assessment of water resources (VAWR) in China is burningly needed. However, to our knowledge, the temporal analysis of VAWR has been not yet addressed. Consequently, we performed, for the first time, a comprehensive spatio-temporal analysis of China's water resources vulnerability (WRV), using a composite index approach with an array of aspects highlighting key challenges that China's water resources system is nowadays facing. During our study period of 2003-2013, the political weight of China's integrated water resources management has been increasing continuously. Hence, it is essential and significant, based on the historical socioeconomic changes influenced by water-environment policy making and implementation, to reveal China's WRV for pinpointing key challenges to the healthy functionality of its water resources system. The water resources system in North and Central Coast appeared more vulnerable than that in Western China. China's water use efficiency has grown substantially over the study period, and so is water supply and sanitation coverage. In contrast, water pollution has been worsening remarkably in most parts of China, and so have water scarcity and shortage in the most stressed parts of the country. This spatio-temporal analysis implies that the key challenges to China's water resources system not only root in the geographical mismatch between socioeconomic development (e.g. water demand) and water resources endowments (e.g. water resources availability), but also stem from the intertwinement between socioeconomic development and national strategic policy making.

  9. Field scale spatio-temporal soil moisture variability for trafficability and crop water availability

    NASA Astrophysics Data System (ADS)

    Carranza, Coleen; van der Ploeg, Martine; Ritsema, Coen

    2016-04-01

    Spatio-temporal patterns of soil moisture have been studied mostly for inputs in land surface models for weather and climate predictions. Remote sensing techniques for estimation of soil moisture have been explored because of the good spatial coverage at different scales. Current available satellite data provide surface soil moisture as microwave systems only measure soil moisture content up to 5cm soil depth. The OWAS1S project will focus on estimation of soil moisture from freely available Sentinel-1 datasets for operational water management in agricultural areas. As part of the project, it is essential to develop spatio-temporal methods to estimate root zone soil moisture from surface soil moisture. This will be used for crop water availability and trafficability in selected agricultural fields in the Netherlands. A network of single capacitance sensors installed per field will provide continuous measurements of soil moisture in the study area. Ground penetrating radar will be used to measure soil moisture variability within a single field for different time periods. During wetter months, optimal conditions for traffic will be assessed using simultaneous soil strength and soil moisture measurements. Towards water deficit periods, focus is on the relation (or the lack thereof) between surface soil moisture and root zone soil moisture to determine the amount of water for crops. Spatio-temporal distribution will determine important physical controls for surface and root zone soil moisture and provide insights for root-zone soil moisture. Existing models for field scale soil-water balance and data assimilation methods (e.g. Kalman filter) will be combined to estimate root zone soil moisture. Furthermore, effects of root development on soil structure and soil hydraulic properties and subsequent effects on trafficability and crop water availability will be investigated. This research project has recently started, therefore we want to present methods and framework of

  10. Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets

    PubMed Central

    Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min

    2016-01-01

    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. PMID:26953173

  11. Spatio-temporal foraging patterns of a giant zooplanktivore, the leatherback turtle

    NASA Astrophysics Data System (ADS)

    Fossette, Sabrina; Hobson, Victoria J.; Girard, Charlotte; Calmettes, Beatriz; Gaspar, Philippe; Georges, Jean-Yves; Hays, Graeme C.

    2010-05-01

    Understanding food web functioning through the study of natural bio-indicators may constitute a valuable and original approach. In the context of jellyfish proliferation in many overexploited marine ecosystems studying the spatio-temporal foraging patterns of the giant "jellyvore" leatherback turtle turns out to be particularly relevant. Here we analyzed long-term tracking data to assess spatio-temporal foraging patterns in 21 leatherback turtles during their pluri-annual migration in the Northern Atlantic. Through an analytical approach based on the animal's own motion (independent of currents) and diving behavior distinct zones of high and low foraging success were identified. High foraging success occurred in a sub-equatorial zone spanning the width of the Atlantic and at high (>30°N) latitudes. Between these zones in the centre of North Atlantic gyre there was low foraging success. This "ocean desert" area was traversed at high speed by leatherbacks on their way to more productive areas at higher latitudes. Animals traveled slowly in high foraging success areas and dived shallower (17.2 ± 8.0 km day - 1 and 53.6 ± 33.1 m mean ± SD respectively) than in low foraging success areas (51.0 ± 13.1 km day - 1 and 81.8 ± 56.2 m mean ± SD respectively). These spatio-temporal foraging patterns seem to relatively closely match the main features of the integrated meso-zooplankton distribution in the North Atlantic. Our method of defining high foraging success areas is intuitive and relatively easy to implement but also takes into account the impact of oceanic currents on animal's behavior.

  12. A bio-inspired system for spatio-temporal recognition in static and video imagery

    NASA Astrophysics Data System (ADS)

    Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

    2007-04-01

    This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

  13. Spatio-temporal patterns of dengue in Malaysia: combining address and sub-district level.

    PubMed

    Ling, Cheong Y; Gruebner, Oliver; Krämer, Alexander; Lakes, Tobia

    2014-11-01

    Spatio-temporal patterns of dengue risk in Malaysia were studied both at the address and the sub-district level in the province of Selangor and the Federal Territory of Kuala Lumpur. We geocoded laboratory-confirmed dengue cases from the years 2008 to 2010 at the address level and further aggregated the cases in proportion to the population at risk at the sub-district level. Kulldorff's spatial scan statistic was applied for the investigation that identified changing spatial patterns of dengue cases at both levels. At the address level, spatio-temporal clusters of dengue cases were concentrated at the central and south-eastern part of the study area in the early part of the years studied. Analyses at the sub-district level revealed a consistent spatial clustering of a high number of cases proportional to the population at risk. Linking both levels assisted in the identification of differences and confirmed the presence of areas at high risk for dengue infection. Our results suggest that the observed dengue cases had both a spatial and a temporal epidemiological component, which needs to be acknowledged and addressed to develop efficient control measures, including spatially explicit vector control. Our findings highlight the importance of detailed geographical analysis of disease cases in heterogeneous environments with a focus on clustered populations at different spatial and temporal scales. We conclude that bringing together information on the spatio-temporal distribution of dengue cases with a deeper insight of linkages between dengue risk, climate factors and land use constitutes an important step towards the development of an effective risk management strategy. PMID:25545931

  14. Spatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland

    NASA Astrophysics Data System (ADS)

    Poggio, Laura; Gimona, Alessandro; Brown, Iain

    2012-08-01

    Time series of satellite data have an important role in the monitoring of regional and global ecosystem properties. Satellite images often present missing data due to atmospheric aerosol, clouds or other atmospheric conditions. Most methods proposed to minimise the effects of degradation and to restore signal values do not take into account the spatial and temporal correlation of the values in the pixels. The aim of this study was to propose and test a spatio-temporal interpolation method to reconstruct pixel values in MODIS data time series that are missing due to cloud cover or other image noise. The method presented and tested is an example of a hybrid Generalised Additive Model (GAM)-geostatistical space-time model, including the fitting of a smoother spatio-temporal trend and a spatial component to account for local details supported by information in covariates. The method is not limited by the type of noise or degradation of pixels values, latitude, vegetation dynamics and land uses. The application of cloud masks on the target image provided the data for a quantitative validation through the comparison between the modelled EVI values and those from the MODIS product. The method was able to restore data providing very good to adequate responses in series of simulations of missing data. The comparison of distributions showed good agreement and predictive capabilities. The spatio-temporal method always performed better and the use of kriged residuals was helpful for situations with high percentages of missing data. The spatial pattern and the local features were well preserved for cloud coverage ⩽20%. For higher percentages of missing data, the results were smoother with less local detail retained, but still showing the general spatial pattern of the variable. The method has proved to be flexible and able to provide reconstructed images reproducing spatial patterns and local features of the measured product, even with substantial amounts of missing pixels.

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

    PubMed Central

    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,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland 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

  16. A Spatio-Temporal Algorithmic Procedure for Environmental Policymaking in the Municipality of Arkalochori in the Greek Island of Crete

    NASA Astrophysics Data System (ADS)

    Batzias, F. A.; Sidiras, D. K.; Giannopoulos, Ch.; Spetsidis, I.

    2009-08-01

    This work deals with a methodological framework designed/developed under the form of a spatio-temporal algorithmic procedure for environmental policymaking at local level. The procedure includes 25 activity stages and 9 decision nodes, putting emphasis on (i) mapping on GIS layers water supply/demand and modeling of aquatic pollution coming from point and non-point sources, (ii) environmental monitoring by periodically measuring the main pollutants in situ and in the laboratory, (iii) design of environmental projects, decomposition of them into sub-projects and combination of the latter to form attainable alternatives, (iv) multicriteria ranking of alternatives, according to a modified Delphi method, by using as criteria the expected environmental benefit, the attitude of inhabitants, the priority within the programme of regional development, the capital required for the investment and the operating cost, and (v) knowledge Base (KB) operation/enrichment, functioning in combination with a data mining mechanism to extract knowledge/information/data from external Bases. An implementation is presented referring to the Municipality of Arkalochori in the Greek island of Crete.

  17. Associating approximate paths and temporal sequences of noisy detections: Application to the recovery of spatio-temporal cancer cell trajectories.

    PubMed

    Dorfer, Matthias; Kazmar, Tomáš; Šmíd, Matěj; Sing, Sanchit; Kneißl, Julia; Keller, Simone; Debeir, Olivier; Luber, Birgit; Mattes, Julian

    2016-01-01

    In this paper we address the problem of recovering spatio-temporal trajectories of cancer cells in phase contrast video-microscopy where the user provides the paths on which the cells are moving. The paths are purely spatial, without temporal information. To recover the temporal information associated to a given path we propose an approach based on automatic cell detection and on a graph-based shortest path search. The nodes in the graph consist of the projections of the cell detections onto the geometrical cell path. The edges relate nodes which correspond to different frames of the sequence and potentially to the same cell and trajectory. In this directed graph we search for the shortest path and use it to define a temporal parametrization of the corresponding geometrical cell path. An evaluation based on 286 paths of 7 phase contrast microscopy videos shows that our algorithm allows to recover 92% of trajectory points with respect to the associated ground truth. We compare our method with a state-of-the-art algorithm for semi-automated cell tracking in phase contrast microscopy which requires interactively placed starting points for the cells to track. The comparison shows that supporting geometrical paths in combination with our algorithm allow us to obtain more reliable cell trajectories. PMID:25987193

  18. Spatio-temporal Dynamics of Pond Use and Recruitment in Florida Gopher Frogs (Rana Capito aesopus)

    SciTech Connect

    Greenberg, C.H.

    2000-05-16

    We examined spatio-temporal dynamics of the Florida Gopher frog breeding and juvenile recruitment. Ponds were situated in a hardwood or pine-savanna matrix of upland forest. Movement was monitored from 1994-1999. Adult pond use was low but relatively constant. Juvenile recruitment was higher in the upland savanna matrix. Body size was negatively correlated with the number of juveniles exiting the pond in only one year suggesting intraspecific competition is one of many factors. Most immigration occurred in May through August and was unrelated to rainfall.

  19. Spatio-temporal variation and prediction of ischemic heart disease hospitalizations in Shenzhen, China.

    PubMed

    Wang, Yanxia; Du, Qingyun; Ren, Fu; Liang, Shi; Lin, De-nan; Tian, Qin; Chen, Yan; Li, Jia-jia

    2014-05-01

    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 using the GM (1

  20. Spatio-Temporal Organization of Replication in Bacteria and Eukaryotes (Nucleoids and Nuclei)

    PubMed Central

    Jackson, Dean; Wang, Xindan; Rudner, David Z.

    2012-01-01

    Here we discuss the spatio-temporal organization of replication in eubacteria and eukaryotes. Although there are significant differences in how replication is organized in cells that contain nuclei from those that do not, you will see that organization of replication in all organisms is principally dictated by the structured arrangement of the chromosome. We will begin with how replication is organized in eubacteria with particular emphasis on three well studied model organisms. We will then discuss spatial and temporal organization of replication in eukaryotes highlighting the similarities and differences between these two domains of life. PMID:22855726

  1. Study of Spatio-Temporal Immunofluorescence on Bead Patterns in a Microfluidic Channel

    NASA Astrophysics Data System (ADS)

    Sivagnanam, Venkataragavalu; Yang, Hui; Gijs, Martin A. M.

    2010-12-01

    We performed a direct immunoassay inside a microfluidic channel on patterned streptavidin-coated beads, which captured fluorescently-labeled biotin target molecules from a continuous flow. We arranged the beads in a dot array at the bottom of the channel and demonstrated their position- and flow rate-dependent fluorescence. As the target analyte gets gradually depleted from the flow when passing downstream the channel, the highest fluorescence intensity was observed on the most upstream positioned dot patterns. We propose a simple analytical convection model to explain this spatio-temporal fluorescence.

  2. Spatio-temporal analysis of human electroencephalograms: Petit-mal epilepsy

    NASA Astrophysics Data System (ADS)

    Friedrich, R.; Uhl, C.

    An analysis of multigrid electroencephalograms (EEG) derived from two different persons suffering from petit-mal epilepsy is performed. Using a previously devised method for analyzing spatio-temporal patterns (Uhl, et al., Z. Phys. B 92 (1993) 211-219), we find a suitable mode decomposition of the EEG. Additionally, we are able to extract a three-dimensional dynamical system which describes the dynamics of the patterns as a kind of mode interaction. We show that the spike-wave behavior characteristic for petit-mal epilepsy arising in the dynamical system is related with Sil'nikov-type behavior of the mode dynamics.

  3. Spatio-temporal description of the cavitating flow behavior around NACA 2412 hydrofoil

    NASA Astrophysics Data System (ADS)

    Rudolf, P.; Štefan, D.; Sedlář, M.; Kozák, J.; Habán, V.; Huzlík, R.

    2015-12-01

    Spatio-temporal description of the cavitating flow around hydrofoil with 8 degrees incidence using proper orthogonal decomposition (POD) is presented. POD is a suitable tool, which provides information not only about the flow dynamics, but also about relevance of different flow structures. POD also enables to track energy transport within the domain and energy transfer among the eigenmodes of the flow field. Analysis documents change of the flow structure for decreasing cavitation number, which can be most likely attributed to sheet/cloud cavitation transition.

  4. A Fisher-gradient complexity in systems with spatio-temporal dynamics

    NASA Astrophysics Data System (ADS)

    Arbona, A.; Bona, C.; Massó, J.; Miñano, B.; Plastino, A.

    2016-04-01

    We define a benchmark for definitions of complexity in systems with spatio-temporal dynamics and employ it in the study of Collective Motion. We show that LMC's complexity displays interesting properties in such systems, while a statistical complexity model (SCM) based on autocorrelation reasonably meets our perception of complexity. However this SCM is not as general as desirable, as it does not merely depend on the system's Probability Distribution Function. Inspired by the notion of Fisher information, we develop a SCM candidate, which we call the Fisher-gradient complexity, which exhibits nice properties from the viewpoint of our benchmark.

  5. Detection of spatio-temporal gait parameters by using wearable motion sensors.

    PubMed

    Lee, Seon-Woo; Mase, Kenji; Kogure, Kiyoshi

    2005-01-01

    This paper presents a method to detect the spatio-temporal parameters of gait by using wearable motion sensors with a gyro, accelerometer, and magnetic sensor. The detected gait parameters are as follows: stance (ST), double support (DS), and gait cycle (GC) time as temporal parameters, and the stride length (SL) as spatial parameter. Four motion sensors are attached on both thighs and shanks of users, and the sensor data are collected in a portable PC. The temporal parameters are estimated by finding walking events, and then the stride length is calculated with two gait models. The estimated parameters are compared to those obtained from a motion capture system (VICON system). PMID:17281844

  6. Transient spatio-temporal dynamics of a diffusive plant-herbivore system with Neumann boundary conditions.

    PubMed

    Yu, Fang; Wang, Lin; Watmough, James

    2016-12-01

    In many existing predator-prey or plant-herbivore models, the numerical response is assumed to be proportional to the functional response. In this paper, without such an assumption, we consider a diffusive plant-herbivore system with Neumann boundary conditions. Besides stability of spatially homogeneous steady states, we also derive conditions for the occurrence of Hopf bifurcation and steady-state bifurcation and provide geometrical methods to locate the bifurcation values. We numerically explore the complex transient spatio-temporal behaviours induced by these bifurcations. A large variety of different types of transient behaviours including oscillations in one or both of space and time are observed. PMID:27572052

  7. Amplitude equations for collective spatio-temporal dynamics in arrays of coupled systems

    SciTech Connect

    Yanchuk, S.; Wolfrum, M.; Perlikowski, P.; Stefański, A.; Kapitaniak, T.

    2015-03-15

    We study the coupling induced destabilization in an array of identical oscillators coupled in a ring structure where the number of oscillators in the ring is large. The coupling structure includes different types of interactions with several next neighbors. We derive an amplitude equation of Ginzburg-Landau type, which describes the destabilization of a uniform stationary state and close-by solutions in the limit of a large number of nodes. Studying numerically an example of unidirectionally coupled Duffing oscillators, we observe a coupling induced transition to collective spatio-temporal chaos, which can be understood using the derived amplitude equations.

  8. Sustained spatio-temporal chaotic flow at onset of electroconvection in nematic liquid crystals

    NASA Astrophysics Data System (ADS)

    Gleeson, J. T.

    1997-02-01

    In the presence of a strong magnetic field parallel to the applied electric field, electrohydrodynamic convection (EHC) in nematic liquid crystals is a pattern forming system with weakly broken rotational symmetry in the plane parallel to the magnetic field. In this system, the first instability observed is to a spatio-temporally chaotic state, in qualitative agreement with recent theoretical results. We report experimental results demonstrating sustained time dependence and spatial disorder immediately above the subcritical transition from the quiescent state in this system.

  9. Spatio-temporal variability of soil respiration in a spruce-dominated headwater catchment in western Germany

    NASA Astrophysics Data System (ADS)

    Bossa, A. Y.; Diekkrüger, B.

    2014-08-01

    CO2 production and transport from forest floors is an important component of the carbon cycle and is closely related to the global atmosphere CO2 concentration. If we are to understand the feedback between soil processes and atmospheric CO2, we need to know more about the spatio-temporal variability of this soil respiration under different environmental conditions. In this study, long-term measurements were conducted in a spruce-dominated forest ecosystem in western Germany. Multivariate analysis-based similarities between different measurement sites led to the detection of site clusters along two CO2 emission axes: (1) mainly controlled by soil temperature and moisture condition, and (2) mainly controlled by root biomass and the forest floor litter. The combined effects of soil temperature and soil moisture were used as a time-dependent rating factor affecting the optimal CO2 production and transport at cluster level. High/moderate/weak time-dependent rating factors were associated with the different clusters. The process-based, most distant clusters were identified using specified pattern characteristics: the reaction rates in the soil layers, the activation energy for bio-chemical reactions, the soil moisture dependency parameter, the root biomass factor, the litter layer factor and the organic matter factor. A HYDRUS-1D model system was inversely used to compute soil hydraulic parameters from soil moisture measurements. Heat transport parameters were calibrated based on observed soil temperatures. The results were used to adjust CO2 productions by soil microorganisms and plant roots under optimal conditions for each cluster. Although the uncertainty associated with the HYDRUS-1D simulations is higher, the results were consistent with both the multivariate clustering and the time-dependent rating of site production. Finally, four clusters with significantly different environmental conditions (i.e. permanent high soil moisture condition, accumulated litter amount

  10. Spatio-temporal variability of soil respiration in a spruce-dominated headwater catchment in western Germany

    NASA Astrophysics Data System (ADS)

    Bossa, A. Y.; Diekkrüger, B.

    2014-01-01

    CO2 production and transport from forest floors is an important component of the carbon cycle and is closely related to the global atmosphere CO2 concentration. If we are to understand the feedback between soil processes and atmospheric CO2, we need to know more about the spatio-temporal variability of this soil respiration under different environmental conditions. In this study, long-term measurements were conducted in a spruce-dominated forest ecosystem in western Germany. Multivariate analysis-based similarities between different measurements sites led to the detection of site clusters along two CO2 emission axes: (1) mainly controlled by soil temperature and moisture condition, and (2) mainly controlled by root biomass and the forest floor litter. The combined effects of soil temperature and soil moisture were used as a time-dependent rating factor affecting the optimal CO2 production and transport at cluster level. High/moderate/weak time-dependent rating factors were associated with the different clusters. The process-based most distant clusters were identified using specified pattern characteristics: the reaction rates in the soil layers, the activation energy for bio-chemical reactions, the water sorption and desorption constant, the root biomass factor, the litter layer factor and the organic matter factor. A HYDRUS-1D model system was inversely used to compute soil hydraulic parameters from soil moisture measurements. Heat transport parameters were adjusted based on observed soil temperatures. The results were used to adjust CO2 production and transport characteristics such as the molecular diffusion coefficient of carbon dioxide in air and water and the CO2 production by soil microorganisms and plant roots under optimal conditions for each cluster. Although the uncertainty associated with the HYDRUS-1-D simulations is higher, the results were consistent with both the multivariate clustering and the time-dependent rating of site production

  11. Spatio-temporal effects of low severity grassland fire on soil colour

    NASA Astrophysics Data System (ADS)

    Pereira, Paulo; Cerdà, Artemi; Bolutiene, Violeta; Pranskevicius, Mantas; Úbeda, Xavier; Jordán, Antonio; Zavala, Lorena; Mataix-Solera, Jorge

    2013-04-01

    Fire changes soil properties directly, through temperature, or indirectly with ash deposition and the temporal elimination of vegetal cover. Both influences change soil colour and soil properties. The degree of changes depends on fire severity that has important implications on soil organic matter, texture, mineralogy and hydrological properties and type of ash produced. The ash colour is different according to the temperature of combustion and burned specie and this property will have implications on soil colour. In addition, ash properties have a strong spatial variability. The aim of this work is to study the spatio-temporal effects of a low severity grassland fire on soil colour occurred in Lithuania, near Vilnius city (54° 42' N, 25° 08' E, 158 m.a.s.l.). After the fire it was designed a plot of 20x20m in a burned and unburned flat area. Soil colour was analysed immediately after the fire, and 2, 5, 7 and 9 months after the fire. In each sampling 25 soil samples were collected, carried out to the laboratory, dried at room temperature (20-24° C) and sieved with the <2mm mesh. Soil colour was observed with the Munsell colour chart and the soil chroma value (CV) was observed. Since data did not respected the Gaussian distribution a neperian logarithmic (ln) transformation was applied. Differences among time and between plots were observed with the repeated measures ANOVA test, followed by a Tukey HSD test. Differences were significant at a p<0.05. The spatial variability (SV) was assessed with the coefficient of variation using non transformed data. The results showed differences among time at a p<0.001, treatment at a p<0.01 and time x treatment at a p<0.01. This means that fire during the first 9 months changed significantly soil colour. The CV of the burned plot was lower than the control plot (darker colour), that is attributed to the deposition of charred material and charcoal. This ash produced in this fire was mainly black coloured. With the time the

  12. Spatio-Temporal Transcript Profiling of Rice Roots and Shoots in Response to Phosphate Starvation and Recovery[W][OPEN

    PubMed Central

    Secco, David; Jabnoune, Mehdi; Walker, Hayden; Shou, Huixia; Wu, Ping; Poirier, Yves; Whelan, James

    2013-01-01

    Using rice (Oryza sativa) as a model crop species, we performed an in-depth temporal transcriptome analysis, covering the early and late stages of Pi deprivation as well as Pi recovery in roots and shoots, using next-generation sequencing. Analyses of 126 paired-end RNA sequencing libraries, spanning nine time points, provided a comprehensive overview of the dynamic responses of rice to Pi stress. Differentially expressed genes were grouped into eight sets based on their responses to Pi starvation and recovery, enabling the complex signaling pathways involved in Pi homeostasis to be untangled. A reference annotation-based transcript assembly was also generated, identifying 438 unannotated loci that were differentially expressed under Pi starvation. Several genes also showed induction of unannotated splice isoforms under Pi starvation. Among these, PHOSPHATE2 (PHO2), a key regulator of Pi homeostasis, displayed a Pi starvation–induced isoform, which was associated with increased translation activity. In addition, microRNA (miRNA) expression profiles after long-term Pi starvation in roots and shoots were assessed, identifying 20 miRNA families that were not previously associated with Pi starvation, such as miR6250. In this article, we present a comprehensive spatio-temporal transcriptome analysis of plant responses to Pi stress, revealing a large number of potential key regulators of Pi homeostasis in plants. PMID:24249833

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

    PubMed

    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. PMID:26147887

  14. Spatio-Temporal Analysis of Urban Heat Island and Urban Metabolism by Satellite Imagery over the Phoenix Metropolitan Area

    NASA Astrophysics Data System (ADS)

    Zhao, Q.; Zhan, S.; Kuai, X.; Zhan, Q.

    2015-12-01

    The goal of this research is to combine DMSP-OLS nighttime light data with Landsat imagery and use spatio-temporal analysis methods to evaluate the relationships between urbanization processes and temperature variation in Phoenix metropolitan area. The urbanization process is a combination of both land use change within the existing urban environment as well as urban sprawl that enlarges the urban area through the transformation of rural areas to urban structures. These transformations modify the overall urban climate environment, resulting in higher nighttime temperatures in urban areas compared to the surrounding rural environment. This is a well-known and well-studied phenomenon referred to as the urban heat island effect (UHI). What is unknown is the direct relationship between the urbanization process and the mechanisms of the UHI. To better understand this interaction, this research focuses on using nighttime light satellite imagery to delineate and detect urban extent changes and utilizing existing land use/land cover map or newly classified imagery from Landsat to analyze the internal urban land use variations. These data are combined with summer and winter land surface temperature data extracted from Landsat. We developed a time series of these combined data for Phoenix, AZ from 1992 to 2013 to analyze the relationships among land use change, land surface temperature and urban growth.

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

    PubMed Central

    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. PMID:26147887

  16. Multiple dipole modeling and localization from spatio-temporal MEG data

    SciTech Connect

    Mosher, J.C. ); Lewis, P.S. ); Leahy, R. )

    1992-06-01

    An array of biomagnetometers may be used to measure the spatio-temporal neuromagnetic field or magnetoencephalogram (MEG) produced by neural activity in the brain. A popular model for the neural activity produced in response to a given sensory stimulus is a set of current dipoles, where each dipole represents the primary current associated with the combined activation of a large number of neutrons located in a small volume of the brain. An important problem in the interpretation of MEG data from evoked response experiments is the localization of these neural current dipoles. The authors present here a linear algebraic framework for three common spatio-temporal dipole models: (i) unconstrained dipoles, (ii) dipoles with a fixed location, and (iii) dipoles with a fixed orientation and location. In all cases, they assume that the location, orientation, and magnitude of the dipoles are unknown. With a common model, they show how the parameter estimation problem may be decomposed into the estimation of the time invariant parameter using nonlinear least-squares minimization, followed by linear estimation of the associated time varying parameters. A subspace formulation is presented and used to derive a suboptimal least-squares subspace scanning method. The resulting algorithm is a special case of the well-known MUltiple SIgnal Classification (MUSIC) method, in which the solution (multiple dipole locations) is found by scanning potential locations using a simple one dipole model.

  17. Spatio-temporal dynamics in the phenology of croplands across the Indo-Gangetic Plains

    NASA Astrophysics Data System (ADS)

    Duncan, John M. A.; Dash, Jadunandan; Atkinson, Peter M.

    2014-08-01

    Spatio-temporal dynamics in land surface phenology parameters observed over croplands can inform on crop-climate interactions and, elucidate local to regional scale vulnerabilities either due to climate change or prevailing sub-optimal agricultural practices. Here, we observe spatio-temporal trends in land surface phenology parameters (cropping intensity, length of growing season and productivity) for kharif and rabi cropping seasons from satellite data across the Indo-Gangetic Plains from 1982 to 2006. The productivity of the Indo-Gangetic Plains croplands is of regional importance and is a vital component of Indian national food security efforts. Aside from local and intra-state heterogeneity in observed trends there was a clear west-to-east gradient in cropping intensity. Key observed trends include increasing cropping intensity in the eastern IGP, increasing number of growing days per year in Bihar, Uttar Pradesh and Haryana and increasing productivity in both cropping seasons across the IGP. This information is a crucial input to integrated assessments of the croplands to ensure management of the agricultural system shifts towards a trajectory of climate-resilience and environmental sustainability. To create spatially explicit time-series, at a spatial resolution of 8 km across the IGP of the following LSP parameters: (i) cropping intensity, (ii) LGS and (iii) agro-ecosystem productivity. To quantify normal conditions, inter-annual variation and long-term trends in these LSP parameters at an 8 km spatial resolution across the IGP croplands.

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

    PubMed Central

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    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. PMID:27297496

  19. Evaluation of spatio-temporal variability in Land Surface Temperature: A case study of Zonguldak, Turkey.

    PubMed

    Sekertekin, Aliihsan; Kutoglu, Senol Hakan; Kaya, Sinasi

    2016-01-01

    The aim of this study is to analyze spatio-temporal variability in Land Surface Temperature (LST) in and around the city of Zonguldak as a result of the growing urbanization and industrialization during the last decade. Three Landsat 5 data and one Landsat 8 data acquired on different dates were exploited in acquiring LST maps utilizing mono-window algorithm. The outcomes obtained from this study indicate that there exists a significant temperature rise in the region for the time period between 1986 and 2015. Some cross sections were selected in order to examine the relationship between the land use and LST changes in more detail. The mean LST difference between 1986 and 2015 in ERDEMIR iron and steel plant (6.8 °C), forestland (3 °C), city and town centers (4.2 °C), municipal rubbish tip (-3.9 °C), coal dump site (12.2 °C), and power plants' region (7 °C) were presented. In addition, the results indicated that the mean LST difference between forestland and city centers was approximately 5 °C, and the difference between forestland and industrial enterprises was almost 8 °C for all years. Spatio-temporal variability in LST in Zonguldak was examined in that study and due to the increase in LST, policy makers and urban planners should consider LST and urban heat island parameters for sustainable development. PMID:26666659

  20. GeoMesa: a distributed architecture for spatio-temporal fusion

    NASA Astrophysics Data System (ADS)

    Hughes, James N.; Annex, Andrew; Eichelberger, Christopher N.; Fox, Anthony; Hulbert, Andrew; Ronquest, Michael

    2015-05-01

    Recent advances in distributed databases and computing have transformed the landscape of spatio-temporal machine learning. This paper presents GeoMesa, a distributed spatio-temporal database built on top of Hadoop and column-family databases such as Accumulo and HBase, that includes a suite of tools for indexing, managing and analyzing both vector and raster data. The indexing techniques use space filling curves to map multi-dimensional data to the single lexicographic list managed by the underlying distributed database. In contrast to traditional non-distributed RDBMS, GeoMesa is capable of scaling horizontally by adding more resources at runtime; the index rebalances across the additional resources. In the raster domain, GeoMesa leverages Accumulo's server-side iterators and aggregators to perform raster interpolation and associative map algebra operations in parallel at query time. The paper concludes with two geo-time data fusion examples: using GeoMesa to aggregate Twitter data by keywords; and georegistration to drape full-motion video (FMV) over terrain.

  1. Hierarchical Bayesian spatio-temporal modeling and entropy-based network design

    NASA Astrophysics Data System (ADS)

    Wu, Y.; Jin, B.; Chan, E.

    2012-12-01

    Typical spatio-temporal data include temperature, precipitation, atmospheric pressure, ozone concentration, personal income, infection prevalence, mosquito populations, among others. To model such data in a given region by hierarchical Bayesian kriging is undertaken in this paper. In addition, an environmental network design problem is also explored. For demonstration, we consider the ozone concentrations in the Toronto region of Ontario, Canada. There are many missing observations in the data. To proceed, we first formulate the hierarchical spatio-temporal model in terms of observed data. We then fill in some missing observations such that the data has the staircase structure. Thus, in light of Le and Zidek (2006), we model the ozone concentrations in Toronto region by hierarchical Bayesian kriging and derive a conditional predictive distribution of the ozone concentrations over unknown locations. To decide if a new monitoring station needs to be added or an existing station can be closed down, we solve this environmental network design problem by using the principle of maximum entropy.

  2. Scaling and interleaving of subsystem Lyapunov exponents for spatio-temporal systems

    NASA Astrophysics Data System (ADS)

    Carretero-González, R.; Ørstavik, S.; Huke, J.; Broomhead, D. S.; Stark, J.

    1999-06-01

    The computation of the entire Lyapunov spectrum for extended dynamical systems is a very time consuming task. If the system is in a chaotic spatio-temporal regime it is possible to approximately reconstruct the Lyapunov spectrum from the spectrum of a subsystem by a suitable rescaling in a very cost effective way. We compute the Lyapunov spectrum for the subsystem by truncating the original Jacobian without modifying the original dynamics and thus taking into account only a portion of the information of the entire system. In doing so we notice that the Lyapunov spectra for consecutive subsystem sizes are interleaved and we discuss the possible ways in which this may arise. We also present a new rescaling method, which gives a significantly better fit to the original Lyapunov spectrum. We evaluate the performance of our rescaling method by comparing it to the conventional rescaling (dividing by the relative subsystem volume) for one- and two-dimensional lattices in spatio-temporal chaotic regimes. Finally, we use the new rescaling to approximate quantities derived from the Lyapunov spectrum (largest Lyapunov exponent, Lyapunov dimension, and Kolmogorov-Sinai entropy), finding better convergence as the subsystem size is increased than with conventional rescaling.

  3. Scaling and interleaving of subsystem Lyapunov exponents for spatio-temporal systems.

    PubMed

    Carretero-Gonzalez, R.; Orstavik, S.; Huke, J.; Broomhead, D. S.; Stark, J.

    1999-06-01

    The computation of the entire Lyapunov spectrum for extended dynamical systems is a very time consuming task. If the system is in a chaotic spatio-temporal regime it is possible to approximately reconstruct the Lyapunov spectrum from the spectrum of a subsystem by a suitable rescaling in a very cost effective way. We compute the Lyapunov spectrum for the subsystem by truncating the original Jacobian without modifying the original dynamics and thus taking into account only a portion of the information of the entire system. In doing so we notice that the Lyapunov spectra for consecutive subsystem sizes are interleaved and we discuss the possible ways in which this may arise. We also present a new rescaling method, which gives a significantly better fit to the original Lyapunov spectrum. We evaluate the performance of our rescaling method by comparing it to the conventional rescaling (dividing by the relative subsystem volume) for one- and two-dimensional lattices in spatio-temporal chaotic regimes. Finally, we use the new rescaling to approximate quantities derived from the Lyapunov spectrum (largest Lyapunov exponent, Lyapunov dimension, and Kolmogorov-Sinai entropy), finding better convergence as the subsystem size is increased than with conventional rescaling. (c) 1999 American Institute of Physics. PMID:12779843

  4. Rational spatio-temporal strategies for controlling a Chagas disease vector in urban environments

    PubMed Central

    Levy, Michael Z.; Malaga Chavez, Fernando S.; Cornejo del Carpio, Juan G.; Vilhena, Daril A.; McKenzie, F. Ellis; Plotkin, Joshua B.

    2010-01-01

    The rational design of interventions is critical to controlling communicable diseases, especially in urban environments. In the case of the Chagas disease vector Triatoma infestans, successful control is stymied by the return of the insect after the effectiveness of the insecticide wanes. Here, we adapt a genetic algorithm, originally developed for the travelling salesman problem, to improve the spatio-temporal design of insecticide campaigns against T. infestans, in a complex urban environment. We find a strategy that reduces the expected instances of vector return 34-fold compared with the current strategy of sequential insecticide application to spatially contiguous communities. The relative success of alternative control strategies depends upon the duration of the effectiveness of the insecticide, and it shows chaotic fluctuations in response to unforeseen delays in a control campaign. We use simplified models to analyse the outcomes of qualitatively different spatio-temporal strategies. Our results provide a detailed procedure to improve control efforts for an urban Chagas disease vector, as well as general guidelines for improving the design of interventions against other disease agents in complex environments. PMID:20061346

  5. Statistical study of spatio-temporal distribution of precursor solar flares associated with major flares

    NASA Astrophysics Data System (ADS)

    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.

  6. Statistical study of spatio-temporal distribution of precursor solar flares associated with major flares

    NASA Astrophysics Data System (ADS)

    Gyenge, N.; Ballai, I.; Baranyi, T.

    2016-04-01

    The aim of the present investigation is to study the spatio-temporal distribution of precursor flares during the 24-hour 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 characterised by the normalised frequency distribution of the quantity δ (the distance between the major flare and its precursor flare normalised by the sunspot group diameter) in four 6-hour 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 hours prior to the event. The precursors of M-class flares show lognormal-like distribution in each 6-hour 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.

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

    PubMed

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    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. PMID:27297496

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Visual tracking with spatio-temporal Dempster-Shafer information fusion.

    PubMed

    Li, Xi; Dick, Anthony; Shen, Chunhua; Zhang, Zhongfei; van den Hengel, Anton; Wang, Hanzi

    2013-08-01

    A key problem in visual tracking is how to effectively combine spatio-temporal visual information from throughout a video to accurately estimate the state of an object. We address this problem by incorporating Dempster-Shafer (DS) information fusion into the tracking approach. To implement this fusion task, the entire image sequence is partitioned into spatially and temporally adjacent subsequences. A support vector machine (SVM) classifier is trained for object/nonobject classification on each of these subsequences, the outputs of which act as separate data sources. To combine the discriminative information from these classifiers, we further present a spatio-temporal weighted DS (STWDS) scheme. In addition, temporally adjacent sources are likely to share discriminative information on object/nonobject classification. To use such information, an adaptive SVM learning scheme is designed to transfer discriminative information across sources. Finally, the corresponding DS belief function of the STWDS scheme is embedded into a Bayesian tracking model. Experimental results on challenging videos demonstrate the effectiveness and robustness of the proposed tracking approach. PMID:23529089

  10. Spatio-temporal dynamics of dengue 2009 outbreak in Córdoba City, Argentina.

    PubMed

    Estallo, E L; Carbajo, A E; Grech, M G; Frías-Céspedes, M; López, L; Lanfri, M A; Ludueña-Almeida, F F; Almirón, W R

    2014-08-01

    During 2009 the biggest dengue epidemic to date occurred in Argentina, affecting almost half the country. We studied the spatio-temporal dynamics of the outbreak in the second most populated city of the country, Córdoba city. Confirmed cases and the results of an Aedes aegypti monitoring during the outbreak were geolocated. The imported cases began in January, and the autochthonous in March. Thirty-three percent of the 130 confirmed cases were imported, and occurred mainly at the center of the city. The autochthonous cases were more frequent in the outskirts, specially in the NE and SE. Aedes aegypti infestation showed no difference between neighborhoods with or without autochthonous cases, neither between neighborhoods with autochthonous vs. imported cases. The neighborhoods with imported cases presented higher population densities. The majority of autochthonous cases occurred at ages between 25 and 44 years old. Cases formed a spatio-temporal cluster of up to 20 days and 12km. According to a mathematical model that estimates the required number of days needed for transmission according to daily temperature, the number of cases begun to fall when more than 15.5 days were needed. This may be a coarse estimation of mean mosquito survival in the area, provided that the study area is close to the global distribution limit of the vector, and that cases prevalence was very low. PMID:24795212

  11. Spatio-Temporal Pattern Analysis for Regional Climate Change Using Mathematical Morphology

    NASA Astrophysics Data System (ADS)

    Das, M.; Ghosh, S. K.

    2015-07-01

    Of late, significant changes in climate with their grave consequences have posed great challenges on humankind. Thus, the detection and assessment of climatic changes on a regional scale is gaining importance, since it helps to adopt adequate mitigation and adaptation measures. In this paper, we have presented a novel approach for detecting spatio-temporal pattern of regional climate change by exploiting the theory of mathematical morphology. At first, the various climatic zones in the region have been identified by using multifractal cross-correlation analysis (MF-DXA) of different climate variables of interest. Then, the directional granulometry with four different structuring elements has been studied to detect the temporal changes in spatial distribution of the identified climatic zones in the region and further insights have been drawn with respect to morphological uncertainty index and Hurst exponent. The approach has been evaluated with the daily time series data of land surface temperature (LST) and precipitation rate, collected from Microsoft Research - Fetch Climate Explorer, to analyze the spatio-temporal climatic pattern-change in the Eastern and North-Eastern regions of India throughout four quarters of the 20th century.

  12. Stochastic Spatio-Temporal Dynamic Model for Gene/Protein Interaction Network in Early Drosophila Development

    PubMed Central

    Li, Cheng-Wei; Chen, Bor-Sen

    2009-01-01

    In order to investigate the possible mechanisms for eve stripe formation of Drosophila embryo, a spatio-temporal gene/protein interaction network model is proposed to mimic dynamic behaviors of protein synthesis, protein decay, mRNA decay, protein diffusion, transcription regulations and autoregulation to analyze the interplay of genes and proteins at different compartments in early embryogenesis. In this study, we use the maximum likelihood (ML) method to identify the stochastic 3-D Embryo Space-Time (3-DEST) dynamic model for gene/protein interaction network via 3-D mRNA and protein expression data and then use the Akaike Information Criterion (AIC) to prune the gene/protein interaction network. The identified gene/protein interaction network allows us not only to analyze the dynamic interplay of genes and proteins on the border of eve stripes but also to infer that eve stripes are established and maintained by network motifs built by the cooperation between transcription regulations and diffusion mechanisms in early embryogenesis. Literature reference with the wet experiments of gene mutations provides a clue for validating the identified network. The proposed spatio-temporal dynamic model can be extended to gene/protein network construction of different biological phenotypes, which depend on compartments, e.g. postnatal stem/progenitor cell differentiation. PMID:20054403

  13. A geomatic methodology for spatio-temporal analysis of climatologic variables and water related diseases

    NASA Astrophysics Data System (ADS)

    Quentin, E.; Gómez Albores, M. A.; Díaz Delgado, C.

    2009-04-01

    The main objective of this research is to propose, by the way of geomatic developments, an integrated tool to analyze and model the spatio-temporal pattern of human diseases related to environmental conditions, in particular the ones that are linked to water resources. The geomatic developments follows four generic steps : requirement analysis, conceptual modeling, geomatic modeling and implementation (in Idrisi GIS software). A first development consists of the preprocessing of water, population and health data in order to facilitate the conversion and validation of tabular data into the required structure for spatio-temporal analysis. Three parallel developments follow : water balance, demographic state and evolution, epidemiological measures (morbidity and mortality rates, diseases burden). The new geomatic modules in their actual state have been tested on various regions of Mexico Republic (Lerma watershed, Chiapas state) focusing on diarrhea and vector borne diseases (dengue and malaria) and considering records over the last decade : a yearly as well as seasonal spreading trend can be observed in correlation with precipitation and temperature data. In an ecohealth perspective, the geomatic approach results particularly appropriate since one of its purposes is the integration of the various spatial themes implied in the study problem, environmental as anthropogenic. By the use of powerful spatial analysis functions, it permits the detection of spatial trends which, combined to the temporal evolution, can be of particularly use for example in climate change context, if sufficiently valid historical data can be obtain.

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Context aware spatio-temporal cell tracking in densely packed multilayer tissues.

    PubMed

    Chakraborty, Anirban; Roy-Chowdhury, Amit K

    2015-01-01

    Modern live imaging technique enables us to observe the internal part of a tissue over time by generating serial optical images containing spatio-temporal slices of hundreds of tightly packed cells. Automated tracking of plant and animal cells from such time lapse live-imaging datasets of a developing multicellular tissue is required for quantitative, high throughput analysis of cell division, migration and cell growth. In this paper, we present a novel cell tracking method that exploits the tight spatial topology of neighboring cells in a multicellular field as contextual information and combines it with physical features of individual cells for generating reliable cell lineages. The 2D image slices of multicellular tissues are modeled as a conditional random field and pairwise cell to cell similarities are obtained by estimating marginal probability distributions through loopy belief propagation on this CRF. These similarity scores are further used in a spatio-temporal graph labeling problem to obtain the optimal and feasible set of correspondences between individual cell slices across the 4D image dataset. We present results on (3D+t) confocal image stacks of Arabidopsis shoot meristem and show that the method is capable of handling many visual analysis challenges associated with such cell tracking problems, viz. poor feature quality of individual cells, low SNR in parts of images, variable number of cells across slices and cell division detection. PMID:25461334

  16. Correlated Spatio-Temporal Fluctuations in Chromatin Compaction States Characterize Stem Cells

    PubMed Central

    Talwar, Shefali; Kumar, Abhishek; Rao, Madan; Menon, Gautam I.; Shivashankar, G.V.

    2013-01-01

    Stem cells integrate signals from the microenvironment to generate lineage-specific gene expression programs upon differentiation. Undifferentiated cell nuclei are easily deformable, with an active transcriptome, whereas differentiated cells have stiffer nuclei and condensed chromatin. Chromatin organization in the stem cell state is known to be highly dynamic but quantitative characterizations of its plasticity are lacking. Using fluorescence imaging, we study the spatio-temporal dynamics of nuclear architecture and chromatin compaction in mouse embryonic stem (ES) cells and differentiated states. Individual ES cells exhibit a relatively narrow variation in chromatin compaction, whereas primary mouse embryonic fibroblasts (PMEF) show broad distributions. However, spatial correlations in chromatin compaction exhibit an emergent length scale in PMEFs, although they are unstructured and longer ranged in ES cells. We provide evidence for correlated fluctuations with large amplitude and long intrinsic timescales, including an oscillatory component, in both chromatin compaction and nuclear area in ES cells. Such fluctuations are largely frozen in PMEF. The role of actin and Lamin A/C in modulating these fluctuations is described. A simple theoretical formulation reproduces the observed dynamics. Our results suggest that, in addition to nuclear plasticity, correlated spatio-temporal structural fluctuations of chromatin in undifferentiated cells characterize the stem cell state. PMID:23442906

  17. A reevaluation of achromatic spatio-temporal vision: Nonoriented filters are monocular, they adapt, and can be used for decision making at high flicker speeds

    PubMed Central

    Meese, Tim S; Baker, Daniel H

    2011-01-01

    Masking, adaptation, and summation paradigms have been used to investigate the characteristics of early spatio-temporal vision. Each has been taken to provide evidence for (i) oriented and (ii) nonoriented spatial-filtering mechanisms. However, subsequent findings suggest that the evidence for nonoriented mechanisms has been misinterpreted: those experiments might have revealed the characteristics of suppression (eg, gain control), not excitation, or merely the isotropic subunits of the oriented detecting mechanisms. To shed light on this, we used all three paradigms to focus on the ‘high-speed’ corner of spatio-temporal vision (low spatial frequency, high temporal frequency), where cross-oriented achromatic effects are greatest. We used flickering Gabor patches as targets and a 2IFC procedure for monocular, binocular, and dichoptic stimulus presentations. To account for our results, we devised a simple model involving an isotropic monocular filter-stage feeding orientation-tuned binocular filters. Both filter stages are adaptable, and their outputs are available to the decision stage following nonlinear contrast transduction. However, the monocular isotropic filters (i) adapt only to high-speed stimuli—consistent with a magnocellular subcortical substrate—and (ii) benefit decision making only for high-speed stimuli (ie, isotropic monocular outputs are available only for high-speed stimuli). According to this model, the visual processes revealed by masking, adaptation, and summation are related but not identical. PMID:23145234

  18. Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

    NASA Astrophysics Data System (ADS)

    Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

    2013-10-01

    We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

  19. Linking spatio-temporal patterns in land cover dynamics with regional climate factors and recent weather: Application to the Flint Hills of Kansas and Oklahoma

    SciTech Connect

    Henebry, G.M.; Goodin, D.G.; Su, H.

    1995-06-01

    A key obstacle to developing regional models of ecosystem dynamics is representation of spatio-temporal variation in constituent patterns and processes. Simple resealing of site-specific ecological data or simulations to broader spatial scales is unlikely to capture regional spatio-temporal dynamics. Yet logistical constraints usually require synoptic weather data to be synthesized from sparse data networks. We seek a simple top-down model that links remotely-sensed vegetation cover with antecedent meteorological forcings to generate boundary conditions for site-specific fine-resolution data and simulations of tallgrass prairie. We developed several candidate models using AVHRR NDVI maximum biweekly composites of the Flint Hills from 1990-1993 and data from a network of more than 60 weather stations across the 40,000 km2 region. Models combined parameters derived from exemplary land cover trajectories, spatial structure (lacunarity and correlation length), and running weighted sums of weather data. Spectral-temporal models were easier to fit; lacunarity was more sensitive than correlation length; compositing effects were strong.

  20. Spatio-temporal groundwater recharge assessment using a lumped-parameter distributed model of the unsaturated zone (pyEARTH-2D)

    NASA Astrophysics Data System (ADS)

    Francés, Alain Pascal; Berhe, Ermias; Lubczynski, Maciek

    2010-05-01

    Numerical flow models are nowadays a powerful and widely used tool for groundwater management. Their reliability requires both an accurate physical representation of an aquifer system and appropriate boundary conditions. While the hydraulic parameters like hydraulic conductivity (K) and storativity (S) are spatially dependent and time invariant, groundwater fluxes such as recharge (R), evapotranspiration from groundwater (ETg) and groundwater inflow/outflow (Qgw) can vary in both space and time. Multiplicity of combinations between parameters and fluxes leads to a non-uniqueness of model solutions which limits their reliability and forecasting capability. We propose to constrain groundwater models at the catchment scale by the spatio-temporal assessment of fluxes in the unsaturated zone. Although the physically based models that involve the Darcy's law and the conservation of mass through the Richard's equation constitute the most appropriate tools for fluxes assessment in the unsaturated zone, they are computationally demanding and require a complex parameterization and boundary condition definition, which restricts their application to large and regional scales. We have thus chosen to develop and apply a lumped-parameter unsaturated zone model because it uses simplified representations of the physical processes and limits the number of parameters. We present in this study the development and application of a spatio-temporal recharge model (pyEARTH-2D) coupled with the numerical flow model MODFLOW at the catchment scale. pyEARTH-2D is a lumped-parameter distributed (grid-based) model that shares the same spatial discretization of the MODFLOW model for coupling purpose. pyEARTH-2D solves the water balance in the topsoil layer using linear relations between fluxes and soil moisture on a daily basis. The partitioning of rainfall is done by taking into consideration interception, evapotranspiration, percolation, soil moisture storage and surface storage and runoff

  1. User requirements for geo-collaborative work with spatio-temporal data in a web-based virtual globe environment.

    PubMed

    Yovcheva, Zornitza; van Elzakker, Corné P J M; Köbben, Barend

    2013-11-01

    Web-based tools developed in the last couple of years offer unique opportunities to effectively support scientists in their effort to collaborate. Communication among environmental researchers often involves not only work with geographical (spatial), but also with temporal data and information. Literature still provides limited documentation when it comes to user requirements for effective geo-collaborative work with spatio-temporal data. To start filling this gap, our study adopted a User-Centered Design approach and first explored the user requirements of environmental researchers working on distributed research projects for collaborative dissemination, exchange and work with spatio-temporal data. Our results show that system design will be mainly influenced by the nature and type of data users work with. From the end-users' perspective, optimal conversion of huge files of spatio-temporal data for further dissemination, accuracy of conversion, organization of content and security have a key role for effective geo-collaboration. PMID:23164199

  2. Spatio-temporal modeling and optimization of a deformable-grating compressor for short high-energy laser pulses.

    PubMed

    Qiao, J; Papa, J; Liu, X

    2015-10-01

    Monolithic large-scale diffraction gratings are desired to improve the performance of high-energy laser systems and scale them to higher energy, but the surface deformation of these diffraction gratings induce spatio-temporal coupling that is detrimental to the focusability and compressibility of the output pulse. A new deformable-grating-based pulse compressor architecture with optimized actuator positions has been designed to correct the spatial and temporal aberrations induced by grating wavefront errors. An integrated optical model has been built to analyze the effect of grating wavefront errors on the spatio-temporal performance of a compressor based on four deformable gratings. A 1.5-meter deformable grating has been optimized using an integrated finite-element-analysis and genetic-optimization model, leading to spatio-temporal performance similar to the baseline design with ideal gratings. PMID:26480107

  3. Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats.

    PubMed

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-09-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004-2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004-2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

  4. Spatio-Temporal Patterns of Schistosomiasis Japonica in Lake and Marshland Areas in China: The Effect of Snail Habitats

    PubMed Central

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-01-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004–2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004–2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

  5. Spatio-Temporal Distribution Characteristics and Trajectory Similarity Analysis of Tuberculosis in Beijing, China.

    PubMed

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-03-01

    Tuberculosis (TB) is an infectious disease with one of the highest reported incidences in China. The detection of the spatio-temporal distribution characteristics of TB is indicative of its prevention and control conditions. Trajectory similarity analysis detects variations and loopholes in prevention and provides urban public health officials and related decision makers more information for the allocation of public health resources and the formulation of prioritized health-related policies. This study analysed the spatio-temporal distribution characteristics of TB from 2009 to 2014 by utilizing spatial statistics, spatial autocorrelation analysis, and space-time scan statistics. Spatial statistics measured the TB incidence rate (TB patients per 100,000 residents) at the district level to determine its spatio-temporal distribution and to identify characteristics of change. Spatial autocorrelation analysis was used to detect global and local spatial autocorrelations across the study area. Purely spatial, purely temporal and space-time scan statistics were used to identify purely spatial, purely temporal and spatio-temporal clusters of TB at the district level. The other objective of this study was to compare the trajectory similarities between the incidence rates of TB and new smear-positive (NSP) TB patients in the resident population (NSPRP)/new smear-positive TB patients in the TB patient population (NSPTBP)/retreated smear-positive (RSP) TB patients in the resident population (RSPRP)/retreated smear-positive TB patients in the TB patient population (RSPTBP) to detect variations and loopholes in TB prevention and control among the districts in Beijing. The incidence rates in Beijing exhibited a gradual decrease from 2009 to 2014. Although global spatial autocorrelation was not detected overall across all of the districts of Beijing, individual districts did show evidence of local spatial autocorrelation: Chaoyang and Daxing were Low-Low districts over the six

  6. Spatio-Temporal Distribution Characteristics and Trajectory Similarity Analysis of Tuberculosis in Beijing, China

    PubMed Central

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-01-01

    Tuberculosis (TB) is an infectious disease with one of the highest reported incidences in China. The detection of the spatio-temporal distribution characteristics of TB is indicative of its prevention and control conditions. Trajectory similarity analysis detects variations and loopholes in prevention and provides urban public health officials and related decision makers more information for the allocation of public health resources and the formulation of prioritized health-related policies. This study analysed the spatio-temporal distribution characteristics of TB from 2009 to 2014 by utilizing spatial statistics, spatial autocorrelation analysis, and space-time scan statistics. Spatial statistics measured the TB incidence rate (TB patients per 100,000 residents) at the district level to determine its spatio-temporal distribution and to identify characteristics of change. Spatial autocorrelation analysis was used to detect global and local spatial autocorrelations across the study area. Purely spatial, purely temporal and space-time scan statistics were used to identify purely spatial, purely temporal and spatio-temporal clusters of TB at the district level. The other objective of this study was to compare the trajectory similarities between the incidence rates of TB and new smear-positive (NSP) TB patients in the resident population (NSPRP)/new smear-positive TB patients in the TB patient population (NSPTBP)/retreated smear-positive (RSP) TB patients in the resident population (RSPRP)/retreated smear-positive TB patients in the TB patient population (RSPTBP) to detect variations and loopholes in TB prevention and control among the districts in Beijing. The incidence rates in Beijing exhibited a gradual decrease from 2009 to 2014. Although global spatial autocorrelation was not detected overall across all of the districts of Beijing, individual districts did show evidence of local spatial autocorrelation: Chaoyang and Daxing were Low-Low districts over the six

  7. Whole-community DNA barcoding reveals a spatio-temporal continuum of biodiversity at species and genetic levels.

    PubMed

    Baselga, Andrés; Fujisawa, Tomochika; Crampton-Platt, Alexandra; Bergsten, Johannes; Foster, Peter G; Monaghan, Michael T; Vogler, Alfried P

    2013-01-01

    A correlation of species and genetic diversity has been proposed but not uniformly supported. Large-scale DNA barcoding provides qualitatively novel data to test for correlations across hierarchical levels (genes, genealogies and species), and may help to unveil the underlying processes. Here we analyse sequence variation in communities of aquatic beetles across Europe (>5,000 individuals) to test for self-similarity of beta diversity patterns at multiple hierarchical levels. We show that community similarity at all levels decreases exponentially with geographic distance, and initial similarity is correlated with the lineage age, consistent with a molecular clock. Log-log correlations between lineage age, number of lineages, and range sizes, reveal a fractal geometry in time and space, indicating a spatio-temporal continuum of biodiversity across scales. Simulations show that these findings mirror dispersal-constrained models of haplotype distributions. These novel macroecological patterns may be explained by neutral evolutionary processes, acting continuously over time to produce multi-scale regularities of biodiversity. PMID:23695686

  8. Spatio-temporal changes of photosynthesis in carnivorous plants in response to prey capture, retention and digestion

    PubMed Central

    2010-01-01

    Carnivorous plants have evolved modified leaves into the traps that assist in nutrient uptake from captured prey. It is known that the traps of carnivorous plants usually have lower photosynthetic rates than assimilation leaves as a result of adaptation to carnivory. However, a few recent studies have indicated that photosynthesis and respiration undergo spatio-temporal changes during prey capture and retention, especially in the genera with active trapping mechanisms. This study describes the spatio-temporal changes of effective quantum yield of photochemical energy conversion in photosystem II (ΦPSII) in response to ant-derived formic acid during its capture and digestion. PMID:20523127

  9. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    NASA Astrophysics Data System (ADS)

    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 coherence of free-electron laser radiation in the extreme ultraviolet determined by a Michelson interferometer

    SciTech Connect

    Hilbert, V.; Rödel, C.; Zastrau, U.; Brenner, G.; Düsterer, S.; Dziarzhytski, S.; Harmand, M.; Przystawik, A.; Redlin, H.; Toleikis, S.; Döppner, T.; Ma, T.; Fletcher, L.; Förster, E.; Glenzer, S. H.; Lee, H. J.; Hartley, N. J.; Kazak, L.; Komar, D.; Skruszewicz, S.; 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.

  11. Spatio-temporal visualization of air-sea CO2 flux and carbon budget using volume rendering

    NASA Astrophysics Data System (ADS)

    Du, Zhenhong; Fang, Lei; Bai, Yan; Zhang, Feng; Liu, Renyi

    2015-04-01

    This paper presents a novel visualization method to show the spatio-temporal dynamics of carbon sinks and sources, and carbon fluxes in the ocean carbon cycle. The air-sea carbon budget and its process of accumulation are demonstrated in the spatial dimension, while the distribution pattern and variation of CO2 flux are expressed by color changes. In this way, we unite spatial and temporal characteristics of satellite data through visualization. A GPU-based direct volume rendering technique using half-angle slicing is adopted to dynamically visualize the released or absorbed CO2 gas with shadow effects. A data model is designed to generate four-dimensional (4D) data from satellite-derived air-sea CO2 flux products, and an out-of-core scheduling strategy is also proposed for on-the-fly rendering of time series of satellite data. The presented 4D visualization method is implemented on graphics cards with vertex, geometry and fragment shaders. It provides a visually realistic simulation and user interaction for real-time rendering. This approach has been integrated into the Information System of Ocean Satellite Monitoring for Air-sea CO2 Flux (IssCO2) for the research and assessment of air-sea CO2 flux in the China Seas.

  12. Spatio-Temporal Analysis of Micro Economic Activities in Rome Reveals Patterns of Mixed-Use Urban Evolution.

    PubMed

    Fiasconaro, Alessandro; Strano, Emanuele; Nicosia, Vincenzo; Porta, Sergio; Latora, Vito

    2016-01-01

    Understanding urban growth is one with understanding how society evolves to satisfy the needs of its individuals in sharing a common space and adapting to the territory. We propose here a quantitative analysis of the historical development of a large urban area by investigating the spatial distribution and the age of commercial activities in the whole city of Rome. We find that the age of activities of various categories presents a very interesting double exponential trend, with a transition possibly related to the long-term economical effects determined by the oil crisis of the Seventies. The diversification of commercial categories, studied through various measures of entropy, shows, among other interesting features, a saturating behaviour with the density of activities. Moreover, different couples of commercial categories exhibit over the years a tendency to attract in space. Our results demonstrate that the spatio-temporal distribution of commercial activities can provide important insights on the urbanisation processes at work, revealing specific and non trivial socio-economical dynamics, as the presence of crisis periods and expansion trends, and contributing to the characterisation of the maturity of urban areas. PMID:26982028

  13. A novel spatio-temporal scale based on ocean currents unravels environmental drivers of reproductive timing in a marine predator

    PubMed Central

    Afán, Isabel; Chiaradia, André; Forero, Manuela G.; Dann, Peter; Ramírez, Francisco

    2015-01-01

    Life-history strategies have evolved in response to predictable patterns of environmental features. In practice, linking life-history strategies and changes in environmental conditions requires comparable space–time scales between both processes, a difficult match in most marine system studies. We propose a novel spatio-temporal and dynamic scale to explore marine productivity patterns probably driving reproductive timing in the inshore little penguin (Eudyptula minor), based on monthly data on ocean circulation in the Southern Ocean, Australia. In contrast to what occurred when considering any other fixed scales, little penguin's highly variable laying date always occurred within the annual peak of ocean productivity that emerged from our newly defined dynamic scale. Additionally, local sea surface temperature seems to have triggered the onset of reproduction, acting as an environmental cue informing on marine productivity patterns at our dynamic scale. Chlorophyll-a patterns extracted from this scale revealed that environment factors in marine ecosystems affecting breeding decisions are related to a much wider region than foraging areas that are commonly used in current studies investigating the link between animals' life history and their environment. We suggest that marine productivity patterns may be more predictable than previously thought when environmental and biological data are examined at appropriate scales. PMID:26063848

  14. Non-stationary spatio-temporal modeling of traffic-related pollutants in near-road environments.

    PubMed

    Gilani, Owais; Berrocal, Veronica J; Batterman, Stuart A

    2016-08-01

    A problem often encountered in environmental epidemiological studies assessing the health effects associated with ambient exposure to air pollution is the spatial misalignment between monitors' locations and subjects' actual residential locations. Several strategies have been adopted to circumvent this problem and estimate pollutants concentrations at unsampled sites, including spatial statistical or geostatistical models that rely on the assumption of stationarity to model the spatial dependence in pollution levels. Although computationally convenient, the assumption of stationarity is often untenable for pollutants concentration, particularly in the near-road environment. Building upon the work of Fuentes (2001) and Schmidt et al. (2011), in this paper we present a non-stationary spatio-temporal model for three traffic-related pollutants in a localized near-road environment. Modeling each pollutant separately and independently, we express each pollutant's concentration as a mixture of two independent spatial processes, each equipped with a non-stationary covariance function with covariates driving the non-stationarity and the mixture weights. PMID:27494957

  15. A novel spatio-temporal scale based on ocean currents unravels environmental drivers of reproductive timing in a marine predator.

    PubMed

    Afán, Isabel; Chiaradia, André; Forero, Manuela G; Dann, Peter; Ramírez, Francisco

    2015-07-01

    Life-history strategies have evolved in response to predictable patterns of environmental features. In practice, linking life-history strategies and changes in environmental conditions requires comparable space-time scales between both processes, a difficult match in most marine system studies. We propose a novel spatio-temporal and dynamic scale to explore marine productivity patterns probably driving reproductive timing in the inshore little penguin (Eudyptula minor), based on monthly data on ocean circulation in the Southern Ocean, Australia. In contrast to what occurred when considering any other fixed scales, little penguin's highly variable laying date always occurred within the annual peak of ocean productivity that emerged from our newly defined dynamic scale. Additionally, local sea surface temperature seems to have triggered the onset of reproduction, acting as an environmental cue informing on marine productivity patterns at our dynamic scale. Chlorophyll-a patterns extracted from this scale revealed that environment factors in marine ecosystems affecting breeding decisions are related to a much wider region than foraging areas that are commonly used in current studies investigating the link between animals' life history and their environment. We suggest that marine productivity patterns may be more predictable than previously thought when environmental and biological data are examined at appropriate scales. PMID:26063848

  16. Spatio-Temporal Analysis of Micro Economic Activities in Rome Reveals Patterns of Mixed-Use Urban Evolution

    PubMed Central

    Fiasconaro, Alessandro; Strano, Emanuele; Nicosia, Vincenzo; Porta, Sergio; Latora, Vito

    2016-01-01

    Understanding urban growth is one with understanding how society evolves to satisfy the needs of its individuals in sharing a common space and adapting to the territory. We propose here a quantitative analysis of the historical development of a large urban area by investigating the spatial distribution and the age of commercial activities in the whole city of Rome. We find that the age of activities of various categories presents a very interesting double exponential trend, with a transition possibly related to the long-term economical effects determined by the oil crisis of the Seventies. The diversification of commercial categories, studied through various measures of entropy, shows, among other interesting features, a saturating behaviour with the density of activities. Moreover, different couples of commercial categories exhibit over the years a tendency to attract in space. Our results demonstrate that the spatio-temporal distribution of commercial activities can provide important insights on the urbanisation processes at work, revealing specific and non trivial socio-economical dynamics, as the presence of crisis periods and expansion trends, and contributing to the characterisation of the maturity of urban areas. PMID:26982028

  17. Challenges for modelling spatio-temporal variations of malaria risk in Malawi

    NASA Astrophysics Data System (ADS)

    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. A Customized Light Sheet Microscope to Measure Spatio-Temporal Protein Dynamics in Small Model Organisms

    PubMed Central

    Rieckher, Matthias; Kourmoulakis, Georgios; Tavernarakis, Nektarios; Ripoll, Jorge; Zacharakis, Giannis

    2015-01-01

    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. PMID:26000610

  19. Multivariate testing of spatio-temporal consistence of daily precipitation records

    NASA Astrophysics Data System (ADS)

    Mächel, H.; Kapala, A.

    2013-06-01

    The project KLIDADIGI of the German Meteorological Service (DWD) systematically rescues historical daily climate data of Germany by keying and imaging. Up to now, daily nearly gap-free precipitation time series at 118 locations for the period 1901-2000 are collected and extended by digitalization of hand-written protocols. To screen the spatio-temporal consistence of these raw data, we apply principal component analysis (PCA) in S (spatial) mode for daily precipitation records as well as for indices such as the number of rainy days above a certain threshold, intensity and absolute daily maximum in monthly, seasonal or annual resolution. Results of this screening test indicate that the PCA is a useful tool for detection of questionable stations and data preprocessing for further quality control and homogenization.

  20. On the spatio-temporal dynamics of soil moisture at the field scale

    NASA Astrophysics Data System (ADS)

    Vereecken, H.; Huisman, J. A.; Pachepsky, Y.; Montzka, C.; van der Kruk, J.; Bogena, H.; Weihermüller, L.; Herbst, M.; Martinez, G.; Vanderborght, J.

    2014-08-01

    In this paper, we review the state of the art of characterizing and analyzing spatio-temporal dynamics of soil moisture content at the field scale. We discuss measurement techniques that have become available in recent years and that provide unique opportunities to characterize field scale soil moisture variability with high spatial and/or temporal resolution. These include soil moisture sensor networks, hydrogeophysical measurement techniques, novel remote sensing platforms, and cosmic ray probes. Techniques and methods to analyze soil moisture fields are briefly discussed and include temporal stability analysis, wavelet analysis and empirical orthogonal functions. We revisit local and non-local controls on field scale soil moisture dynamics and discuss approaches to model these dynamics at the field scale. Finally, we address the topic of optimal measurement design and provide an outlook and future research perspectives.

  1. Spatio-temporal distribution of VOC emissions in urban area based on receptor modeling

    NASA Astrophysics Data System (ADS)

    Stojić, A.; Stanišić Stojić, S.; Mijić, Z.; Šoštarić, A.; Rajšić, S.

    2015-04-01

    In the present study, the concentrations of VOC were measured using Proton Transfer Reaction Mass Spectrometer, together with NOx, NO2, NO, SO2, CO, and PM10 during winter 2014 in Belgrade, Serbia. For the purpose of source apportionment, receptor models Positive Matrix Factorization and Unmix were applied to the obtained dataset, both resolving six profiles. The reliable identification of pollutant sources, description of their characteristics, and estimation of their spatio-temporal distribution are presented through comprehensive analysis and comparison of receptor model solutions, with respect to meteorological data, planetary boundary layer height, and regional and long-range transport. For emissions from petrochemical industry and oil refinery a significant contribution of transport is observed, and hybrid receptor models were applied for identification of potential non-local source regions.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    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.

  3. Spatio-temporal propagation of cascading overload failures in spatially embedded networks.

    PubMed

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  4. Modelling spatio-temporal patterns of long-distance Culicoides dispersal into northern Australia.

    PubMed

    Eagles, D; Walker, P J; Zalucki, M P; Durr, P A

    2013-07-01

    Novel arboviruses, including new serotypes of bluetongue virus, are isolated intermittently from cattle and insects in northern Australia. These viruses are thought to be introduced via windborne dispersal of Culicoides from neighbouring land masses to the north. We used the HYSPLIT particle dispersal model to simulate the spatio-temporal patterns of Culicoides dispersal into northern Australia from nine putative source sites across Indonesia, Timor-Leste and Papua New Guinea. Simulated dispersal was found to be possible from each site, with the islands of Timor and Sumba highlighted as the likely principal sources and February the predominant month of dispersal. The results of this study define the likely spatial extent of the source and arrival regions, the relative frequency of dispersal from the putative sources and the temporal nature of seasonal winds from source sites into arrival regions. Importantly, the methodology and results may be applicable to other insect and pathogen incursions into northern Australia. PMID:23642857

  5. Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders.

    PubMed

    Wang, Xin; Pinto-Duarte, António; Behrens, M Margarita; Zhou, Xianjin; Sejnowski, Terrence J

    2015-01-01

    Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies. PMID:26459883

  6. Spatio-Temporal Analyses of CH4 and SO2 over Pakistan

    NASA Astrophysics Data System (ADS)

    Mahmood, Irfan; Imran Shahzad, Muhammad; Farooq Iqbal, Muhammad

    2016-07-01

    SO2 and associated compounds are one of main atmospheric pollutant. Moreover, methane - a potent greenhouse gas can also deteriorate the air quality of the region under certain chemical and meteorological conditions. Role of such gases in regional air quality of Pakistan have not been significantly studied. This study involves the analyses of CH4 and SO2 in terms of spatio-temporal distribution over Pakistan from the period 2004 - 2014 using space borne sensors namely Ozone Monitoring Instrument (OMI) and Advanced Infrared Sounder Instrument (AIRS) respectively. Results show an increase in SO2 concentration attributed to trans-boundary sources. Monthly Methane total column results show an increase in atmospheric concentration of methane for the period 2004-2014. Results of the study are complimented by calculating the back trajectories to identify the transport paths. The study significantly describes the regional description and convection phenomenon for SO2 and CH4.

  7. Effects of Spatio-Temporal Aliasing on Out-the-Window Visual Systems

    NASA Technical Reports Server (NTRS)

    Sweet, Barbara T.; Stone, Leland S.; Liston, Dorion B.; Hebert, Tim M.

    2014-01-01

    Designers of out-the-window visual systems face a challenge when attempting to simulate the outside world as viewed from a cockpit. Many methodologies have been developed and adopted to aid in the depiction of particular scene features, or levels of static image detail. However, because aircraft move, it is necessary to also consider the quality of the motion in the simulated visual scene. When motion is introduced in the simulated visual scene, perceptual artifacts can become apparent. A particular artifact related to image motion, spatiotemporal aliasing, will be addressed. The causes of spatio-temporal aliasing will be discussed, and current knowledge regarding the impact of these artifacts on both motion perception and simulator task performance will be reviewed. Methods of reducing the impact of this artifact are also addressed

  8. Hydrodynamic Model of Spatio-Temporal Evolution of Two-Plasmon Decay

    SciTech Connect

    Dimitrijevic, D. R.; Maluckov, A. A.

    2010-01-21

    A hydrodynamic model of two-plasmon decay in a homogeneous plasma slab near the quarter-critical density is constructed in order to gain better insight into the spatio-temporal evolution of the daughter electron plasma waves in plasma in the course of the instability. The influence of laser and plasma parameters on the evolution of the amplitudes of the participating waves is discussed. The secondary coupling of two daughter electron plasma waves with an ion-acoustic wave is assumed to be the principal mechanism of saturation of the instability. The impact of the inherently nonresonant nature of this secondary coupling on the development of TPD is investigated and it is shown to significantly influence the electron plasma wave dynamics. Its inclusion leads to nonuniformity of the spatial profile of the instability and causes the burst-like pattern of the instability development, which should result in the burst-like hot-electron production in homogeneous plasma.

  9. Shot boundary detection and label propagation for spatio-temporal video segmentation

    NASA Astrophysics Data System (ADS)

    Piramanayagam, Sankaranaryanan; Saber, Eli; Cahill, Nathan D.; Messinger, David

    2015-02-01

    This paper proposes a two stage algorithm for streaming video segmentation. In the first stage, shot boundaries are detected within a window of frames by comparing dissimilarity between 2-D segmentations of each frame. In the second stage, the 2-D segments are propagated across the window of frames in both spatial and temporal direction. The window is moved across the video to find all shot transitions and obtain spatio-temporal segments simultaneously. As opposed to techniques that operate on entire video, the proposed approach consumes significantly less memory and enables segmentation of lengthy videos. We tested our segmentation based shot detection method on the TRECVID 2007 video dataset and compared it with block-based technique. Cut detection results on the TRECVID 2007 dataset indicate that our algorithm has comparable results to the best of the block-based methods. The streaming video segmentation routine also achieves promising results on a challenging video segmentation benchmark database.

  10. Holographic frequency resolved optical gating for spatio-temporal characterization of ultrashort optical pulse

    NASA Astrophysics Data System (ADS)

    Mehta, Nikhil; Yang, Chuan; Xu, Yong; Liu, Zhiwen

    2014-09-01

    We introduce a novel method for characterizing the spatio-temporal evolution of ultrashort optical field by recording the spectral hologram of frequency resolved optical gating (FROG) trace. We show that FROG holography enables the measurement of phase (up to an overall constant) and group delay of the pulse which cannot be measured by conventional FROG method. To illustrate our method, we perform numerical simulation to generate holographic collinear FROG (cFROG) trace of a chirped optical pulse and retrieve its complex profile at multiple locations as it propagates through a hypothetical dispersive medium. Further, we experimentally demonstrate our method by retrieving a 67 fs pulse at three axial locations in the vicinity of focus of an objective lens and compute its group delay.

  11. Transition to Spatio-Temporal Chaos with Increasing Length in the Reaction-Diffusion System

    NASA Astrophysics Data System (ADS)

    Trail, Collin; Tomlin, Brett; Olsen, Thomas; Wiener, Richard J.

    2003-11-01

    Calculations based up the Reaction-Diffusion model (H. Riecke and H.-G. Paap, Europhys. Lett. 14), 1235 (1991).have proven to be suggestive for a wide variety of pattern forming systems, including Taylor-Couette flow with hourglass geometry(Richard J. Wiener et al), Phys. Rev. E 55, 5489 (1997).. Seeking insight to guide experimental investigations, we extend these calculations. Previous calculations indicated that in smaller systems, only temporal chaos, located in a small region, would be observed, while in longer systems instabilities would form over a wide region. Our simulations explore this transition from purely temporal chaos to spatio-temporal chaos as the length of the system is increased.

  12. Spatio-temporal Contrast Sensitivity in the Cardinal Directions of the Colour Space. A Review

    PubMed Central

    Díez-Ajenjo, Maria Amparo; Capilla, Pascual

    2010-01-01

    We review the psychophysics of the spatio-temporal contrast sensitivity in the cardinal directions of the colour space and their correlation with those neural characteristics of the visual system that limit the ability to perform contrast detection or pattern-resolution tasks. We focus our attention particularly on the influence of luminance level, spatial extent and spatial location of the stimuli - factors that determine the characteristics of the physiological mechanisms underlying detection. Optical factors do obviously play a role, but we will refer to them only briefly. Contrast sensitivity measurements are often used in clinical practice as a method to detect, at their early stages, a variety of pathologies affecting the visual system, but their usefulness is very limited due to several reasons. We suggest some considerations about stimuli characteristics that should be taken into account in order to improve the performance of this kind of measurement.

  13. Spatio-temporal imaging of light transport in scattering media using white light illumination (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Badon, Amaury; Li, Dayan; Lerosey, Geoffroy; Boccara, Claude; Fink, Mathias; Aubry, Alexandre

    2016-03-01

    We recently showed how the correlations of a broadband and incoherent wave-field can directly yield the time-dependent Green's functions between scatterers of a complex medium [Badon et al., Phys. Rev. Lett., 2015]. In this study, we apply this approach to the imaging of optical transport properties in complex media. A parallel measurement of millions of Green's functions at the surface of several strongly scattering samples (ZnO, TiO2, Teflon tape) is performed. A statistical analysis of this Green's matrix allows to investigate locally the spatio-temporal evolution of the diffusive halo within the scattering sample. An image of diffusion tensor is then obtained. It allows to map quantitatively the local concentration of scatterers and their anisotropy within the scattering medium. The next step of this work is to test this approach on biological tissues and illustrate how it can provide an elegant and powerful alternative to diffuse optical imaging techniques.

  14. Spatio-temporal modelling of foot-and-mouth disease outbreaks.

    PubMed

    Malesios, C; Demiris, N; Kostoulas, P; Dadousis, K; Koutroumanidis, T; Abas, Z

    2016-09-01

    We present and analyse data collected during a severe epidemic of foot-and-mouth disease (FMD) that occurred between July and September 2000 in a region of northeastern Greece with strategic importance since it represents the southeastern border of Europe and Asia. We implement generic Bayesian methodology, which offers flexibility in the ability to fit several realistically complex models that simultaneously capture the presence of 'excess' zeros, the spatio-temporal dependence of the cases, assesses the impact of environmental noise and controls for multicollinearity issues. Our findings suggest that the epidemic was mostly driven by the size and the animal type of each farm as well as the distance between farms while environmental and other endemic factors were not important during this outbreak. Analyses of this kind may prove useful to informing decisions related to optimal control measures for potential future FMD outbreaks as well as other acute epidemics such as FMD. PMID:27150839

  15. Satellite Remote Sensing For Spatio-Temporal Changes Analysis Of Urban Surface Biogeophysical Parameters

    NASA Astrophysics Data System (ADS)

    Zoran, Maria

    2010-01-01

    Based on satellite imagery data, this research developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying spatio-temporal changes between 1989-2008 in Bucharest metropolitan area, Romania, and for examining the environmental impact of such changes on urban biogeophysical parameters. The changes over the years of surface biophysical parameters are examined in association with landcover/landuse changes to illustrate how these parameters respond to rapid urban expansion in Bucharest and surrounding region. For detailed landuse classifications in a digital form these properties were analyzed in a statistical way .This study attempts to provide environmental awareness to urban planners in future urban development. The land cover information, properly classified, can provide a spatially and temporally explicit view of societal and environmental attributes and can be an important complement to in-situ measurements. Also, this information provides a perspective for understanding factors potentially mediating the interactions between urbanisation and variations of environmental quality.

  16. Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

    PubMed

    Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

    2016-05-15

    To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. PMID:26775938

  17. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

    NASA Technical Reports Server (NTRS)

    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.

  18. Multiblock copolymers exhibiting spatio-temporal structure with autonomous viscosity oscillation

    PubMed Central

    Onoda, Michika; Ueki, Takeshi; Shibayama, Mitsuhiro; Yoshida, Ryo

    2015-01-01

    Here we report an ABA triblock copolymer that can express microscopic autonomous formation and break-up of aggregates under constant condition to generate macroscopic viscoelastic self-oscillation of the solution. The ABA triblock copolymer is designed to have hydrophilic B segment and self-oscillating A segment at the both sides by RAFT copolymerization. In the A segment, a metal catalyst of chemical oscillatory reaction, i.e., the Belousov-Zhabotinsky (BZ) reaction, is introduced as a chemomechanical transducer to change the aggregation state of the polymer depending on the redox states. Time-resolved DLS measurements of the ABA triblock copolymer confirm the presence of a transitional network structure of micelle aggregations in the reduced state and a unimer structure in the oxidized state. This autonomous oscillation of a well-designed triblock copolymer enables dynamic biomimetic softmaterials with spatio-temporal structure. PMID:26511660

  19. Emergence of spatio-temporal dynamics from exact coherent solutions in pipe flow

    NASA Astrophysics Data System (ADS)

    Ritter, Paul; Mellibovsky, Fernando; Avila, Marc

    2016-08-01

    Turbulent-laminar patterns are ubiquitous near transition in wall-bounded shear flows. Despite recent progress in describing their dynamics in analogy to non-equilibrium phase transitions, there is no theory explaining their emergence. Dynamical-system approaches suggest that invariant solutions to the Navier–Stokes equations, such as traveling waves and relative periodic orbits in pipe flow, act as building blocks of the disordered dynamics. While recent studies have shown how transient chaos arises from such solutions, the ensuing dynamics lacks the strong fluctuations in size, shape and speed of the turbulent spots observed in experiments. We here show that chaotic spots with distinct dynamical and kinematic properties merge in phase space and give rise to the enhanced spatio-temporal patterns observed in pipe flow. This paves the way for a dynamical-system foundation to the phenomenology of turbulent-laminar patterns in wall-bounded extended shear flows.

  20. Neural field simulator: two-dimensional spatio-temporal dynamics involving finite transmission speed

    PubMed Central

    Nichols, Eric J.; Hutt, Axel

    2015-01-01

    Neural Field models (NFM) play an important role in the understanding of neural population dynamics on a mesoscopic spatial and temporal scale. Their numerical simulation is an essential element in the analysis of their spatio-temporal dynamics. The simulation tool described in this work considers scalar spatially homogeneous neural fields taking into account a finite axonal transmission speed and synaptic temporal derivatives of first and second order. A text-based interface offers complete control of field parameters and several approaches are used to accelerate simulations. A graphical output utilizes video hardware acceleration to display running output with reduced computational hindrance compared to simulators that are exclusively software-based. Diverse applications of the tool demonstrate breather oscillations, static and dynamic Turing patterns and activity spreading with finite propagation speed. The simulator is open source to allow tailoring of code and this is presented with an extension use case. PMID:26539105

  1. Assessing the spatio-temporal variations of the completeness magnitude for seismic events in Venezuela

    NASA Astrophysics Data System (ADS)

    Vasquez, R.; Bravo, L.

    2013-05-01

    We investigate the spatio temporal variation of the completeness magnitude Mc, for a set of 18774 well localized earthquakes registered by the Venezuelan Seismological Network over the period 2000-2010. In the entire seismicity region we defined two-dimensional grids of different sizes in order to map the Mc: 11 km, 22 km, 55 km and 111 km. We calculated the completeness magnitude using the Maximum Curvature method (MAXC) for every particular cell taking at least 15 earthquakes to perform computations. The results show an overall variation from 2.0 to 3.6. We found different thresholds and ranges of Mc depending on the dimension of the seismicity zone: western region from 2.2 to 2.8, north central from 2.0 to 3.2 and eastern region from 2.2 to 3.2. We also include remarks in border seismicity, close to Colombia and Trinidad, where the largest Mc values are estimated.

  2. Spatio-temporal propagation of cascading overload failures in spatially embedded networks

    NASA Astrophysics Data System (ADS)

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

  3. A flood risk curve development for inundation disaster considering spatio-temporal rainfall distribution

    NASA Astrophysics Data System (ADS)

    Tanaka, T.; Tachikawa, Y.; Yorozu, K.

    2015-06-01

    To manage flood disaster with an exceeding designed level, flood risk control based on appropriate risk assessment is essential. To make an integrated economic risk assessment by flood disaster, a flood risk curve, which is a relation between flood inundation damage and its exceedance probability, plays an important role. This research purposes a method to develop a flood risk curve by utilizing a probability distribution function of annual maximum rainfall through rainfall-runoff and inundation simulations so that risk assessment can consider climate and socio-economic changes. Among a variety of uncertainties, the method proposed in this study considered spatio-temporal rainfall distributions that have high uncertainty for damage estimation. The method was applied to the Yura-gawa river basin (1882 km2) in Japan; and the annual economic benefit of an existing dam in the basin was successfully quantified by comparing flood risk curves with/without the dam.

  4. Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders

    PubMed Central

    Wang, Xin; Pinto-Duarte, António; Margarita Behrens, M.; Zhou, Xianjin; Sejnowski, Terrence J.

    2015-01-01

    Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies. PMID:26459883

  5. Spatio-temporal propagation of cascading overload failures in spatially embedded networks

    PubMed Central

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  6. Spatio-temporal dynamcis of a cell signal cascade with negative feedback

    NASA Astrophysics Data System (ADS)

    Maya Bernal, Jose Luis; Ramirez-Santiago, Guillermo

    2014-03-01

    We studied the spatio-temporal dynamics of a system of reactio-diffusion equations that models a cell signal transduction pathway with six cycles and negative feedback. The basic cycle consists of the phosphorylation-dephosphorylation of two antagonic proteins. We found two regimes of saturation of the enzimatic reaction in the kinetic parameters space and determined the conditions for the signal propagation in the steady state. The trajectories for which transduction occurs are defined in terms of the ratio of the enzimatic activities. We found that in spite of the negative feedback the cell signal cascade behaves as an amplifier and produces phosphoprotein concentration gradients within the cell. This model behaves also as a noise filter and as a switch. Supported by DGAPA-UNAM Contract IN118410-3.

  7. Automatic right ventricle (RV) segmentation by propagating a basal spatio-temporal characterization

    NASA Astrophysics Data System (ADS)

    Atehortúa, Angélica; Zuluaga, María. A.; Martínez, Fabio; Romero, Eduardo

    2015-12-01

    An accurate right ventricular (RV) function quantification is important to support the evaluation, diagnosis and prognosis of several cardiac pathologies and to complement the left ventricular function assessment. However, expert RV delineation is a time consuming task with high inter-and-intra observer variability. In this paper we present an automatic segmentation method of the RV in MR-cardiac sequences. Unlike atlas or multi-atlas methods, this approach estimates the RV using exclusively information from the sequence itself. For so doing, a spatio-temporal analysis segments the heart at the basal slice, segmentation that is then propagated to the apex by using a non-rigid-registration strategy. The proposed approach achieves an average Dice Score of 0:79 evaluated with a set of 48 patients.

  8. MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering.

    PubMed

    von Landesberger, Tatiana; Brodkorb, Felix; Roskosch, Philipp; Andrienko, Natalia; Andrienko, Gennady; Kerren, Andreas

    2016-01-01

    Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods. PMID:26529684

  9. Assessment of soil organic carbon distribution in Europe scale by spatio-temporal data and geostatistics

    NASA Astrophysics Data System (ADS)

    Aksoy, Ece; Panagos, Panos; Montanarella, Luca

    2013-04-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted using combination of LUCAS soil samples with local soil data and ten spatio-temporal predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, average temperature and precipitation) with Regression-Kriging method in Europe scale. Significant correlation between the covariates and the organic carbon dependent variable was found.

  10. Facilitating Integrated Spatio-Temporal Visualization and Analysis of Heterogeneous Archaeological and Palaeoenvironmental Research Data

    NASA Astrophysics Data System (ADS)

    Willmes, C.; Brocks, S.; Hoffmeister, D.; Hütt, C.; Kürner, D.; Volland, K.; Bareth, G.

    2012-07-01

    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.

  11. Spatio-temporal memories for machine learning: a long-term memory organization.

    PubMed

    Starzyk, Janusz A; He, Haibo

    2009-05-01

    Design of artificial neural structures capable of reliable and flexible long-term spatio-temporal memory is of paramount importance in machine intelligence. To this end, we propose a novel, biologically inspired, long-term memory (LTM) architecture. We intend to use it as a building block of a neuron-level architecture that is able to mimic natural intelligence through learning, anticipation, and goal-driven behavior. A mutual input enhancement and blocking structure is proposed, and its operation is discussed in detail. The paper focuses on a hierarchical memory organization, storage, recognition, and recall mechanisms. Simulation results of the proposed memory show its effectiveness, adaptability, and robustness. Accuracy of the proposed method is compared to other methods including Levenshtein distance method and a Markov chain. PMID:19336289

  12. Predicted spatio-temporal dynamics of radiocesium deposited onto forests following the Fukushima nuclear accident

    PubMed Central

    Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji

    2013-01-01

    The majority of the area contaminated by the Fukushima Dai-ichi nuclear power plant accident is covered by forest. To facilitate effective countermeasure strategies to mitigate forest contamination, we simulated the spatio-temporal dynamics of radiocesium deposited into Japanese forest ecosystems in 2011 using a model that was developed after the Chernobyl accident in 1986. The simulation revealed that the radiocesium inventories in tree and soil surface organic layer components drop rapidly during the first two years after the fallout. Over a period of one to two years, the radiocesium is predicted to move from the tree and surface organic soil to the mineral soil, which eventually becomes the largest radiocesium reservoir within forest ecosystems. Although the uncertainty of our simulations should be considered, the results provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident. PMID:23995073

  13. Urban green spatio- temporal changes assessment through time-series satellite data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

    2015-10-01

    Understanding spatio-temporal changes of urban environments is essential for regional and local planning and environmental management. With the rapid changes of Bucharest city in Romania during past decades, green spaces have been fragmented and dispersed causing impairment and dysfunction of these urban elements. The main goal of this study is to address these tasks in synergy with in-situ data and new analytical methods. Spatio- temporal monitoring of urban vegetation land cover changes is important for policy decisions, regulatory actions and subsequent land use activities. This study explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Land Surface Temperature (LST) and evapotranspiration (ET) data to provide vegetation change detection information for metropolitan area of Bucharest. Training and validation are based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2002- 2014 was assessed to be of 87%, with a reasonable balance between change commission errors (20.24%), change omission errors (25.65%), and Kappa coefficient of 0.72. Annual change detection rates across the urban/periurban areas over the study period (2002-2014) were estimated at 0.79% per annum in the range of 0.46% (2002) to 0.77% (2014).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system. Extracted green space areas were further analyzed quantitatively in relation with air quality data and extreme climate events. The results have been analyzed in terms of environmental impacts and future climate trends.

  14. Spatio-Temporal Variability of Aquatic Vegetation in Taihu Lake over the Past 30 Years

    PubMed Central

    Zhao, Dehua; Lv, Meiting; Jiang, Hao; Cai, Ying; Xu, Delin; An, Shuqing

    2013-01-01

    It is often difficult to track the spatio-temporal variability of vegetation distribution in lakes because of the technological limitations associated with mapping using traditional field surveys as well as the lack of a unified field survey protocol. Using a series of Landsat remote sensing images (i.e. MSS, TM and ETM+), we mapped the composition and distribution area of emergent, floating-leaf and submerged macrophytes in Taihu Lake, China, at approximate five-year intervals over the past 30 years in order to quantify the spatio-temporal dynamics of the aquatic vegetation. Our results indicated that the total area of aquatic vegetation increased from 187.5 km2 in 1981 to 485.0 km2 in 2005 and then suddenly decreased to 341.3 km2 in 2010. Similarly, submerged vegetation increased from 127.0 km2 in 1981 to 366.5 km2 in 2005, and then decreased to 163.3 km2. Floating-leaf vegetation increased continuously through the study period in both area occupied (12.9 km2 in 1981 to 146.2 km2 in 2010) and percentage of the total vegetation (6.88% in 1981 to 42.8% in 2010). In terms of spatial distribution, the aquatic vegetation in Taihu Lake has spread gradually from the East Bay to the surrounding areas. The proportion of vegetation in the East Bay relative to that in the entire lake has decreased continuously from 62.3% in 1981, to 31.1% in 2005 and then to 21.8% in 2010. Our findings have suggested that drastic changes have taken place over the past 30 years in the spatial pattern of aquatic vegetation as well as both its relative composition and the amount of area it occupies. PMID:23823189

  15. Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity.

    PubMed

    Humble, James; Denham, Susan; Wennekers, Thomas

    2012-01-01

    It has previously been shown that by using spike-timing-dependent plasticity (STDP), neurons can adapt to the beginning of a repeating spatio-temporal firing pattern in their input. In the present work, we demonstrate that this mechanism can be extended to train recognizers for longer spatio-temporal input signals. Using a number of neurons that are mutually connected by plastic synapses and subject to a global winner-takes-all mechanism, chains of neurons can form where each neuron is selective to a different segment of a repeating input pattern, and the neurons are feed-forwardly connected in such a way that both the correct input segment and the firing of the previous neurons are required in order to activate the next neuron in the chain. This is akin to a simple class of finite state automata. We show that nearest-neighbor STDP (where only the pre-synaptic spike most recent to a post-synaptic one is considered) leads to "nearest-neighbor" chains where connections only form between subsequent states in a chain (similar to classic "synfire chains"). In contrast, "all-to-all spike-timing-dependent plasticity" (where all pre- and post-synaptic spike pairs matter) leads to multiple connections that can span several temporal stages in the chain; these connections respect the temporal order of the neurons. It is also demonstrated that previously learnt individual chains can be "stitched together" by repeatedly presenting them in a fixed order. This way longer sequence recognizers can be formed, and potentially also nested structures. Robustness of recognition with respect to speed variations in the input patterns is shown to depend on rise-times of post-synaptic potentials and the membrane noise. It is argued that the memory capacity of the model is high, but could theoretically be increased using sparse codes. PMID:23087641

  16. Spatio-temporal simulation of first pass drug perfusion in the liver.

    PubMed

    Schwen, Lars Ole; Krauss, Markus; Niederalt, Christoph; Gremse, Felix; Kiessling, Fabian; Schenk, Andrea; Preusser, Tobias; Kuepfer, Lars

    2014-03-01

    The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the

  17. Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.

    PubMed

    Nicolas, Delphine; Rochette, Sébastien; Llope, Marcos; Licandro, Priscilla

    2014-01-01

    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. PMID:24551103

  18. Stability of the spatio-temporal distribution and niche overlap in neotropical earthworm assemblages

    NASA Astrophysics Data System (ADS)

    Jiménez, Juan-José; Decaëns, Thibaud; Rossi, Jean-Pierre

    2006-11-01

    The spatial distribution of soil invertebrates is aggregated with high-density patches alternating with low-density zones. A high degree of spatio-temporal organization generally exists with identified patches of specific species assemblages, in which species coexist according to assembly rules related to competitive mechanisms for spatial and trophic resources occur. However, these issues have seldom been addressed. The spatio-temporal structure of a native earthworm community in a natural savanna and a grass-legume pasture in the Colombian "Llanos" was studied during a 2-year-period. A spatially explicit sampling design (regular grid) was used to discern the distribution pattern of species assemblages in both systems. Earthworms were collected from small soil pits at three different sampling dates. Data collected from 1 m 2 soil monoliths were also used in the present study. Data were analyzed with the partial triadic analysis (PTA) and correlograms, while niche overlap was computed with the Pianka index. The PTA and correlogram analysis revealed that earthworm communities displayed a similar stable spatial structure in both systems during the 2-year study period. An alternation of population patches where different species' assemblages dominated was common to all sampling dates. The medium-sized Andiodrilus sp. and Glossodrilus sp. exhibited a clear spatial opposition in natural savanna and the grass-legume pasture for the duration of the study. The Pianka index showed a high degree of niche overlapping in several dimensions (vertical distribution, seasonality of population density) between both species. The inclusion of space-time data analysis tools as the PTA and the use of classical ecological indices (Pianka) in soil ecology studies may improve our knowledge of earthworm assemblages' dynamics.

  19. Spatio-Temporal Canopy Complexity and Leaf Acclimation to Variable Canopy Microhabitats.

    NASA Astrophysics Data System (ADS)

    Fotis, A. T.

    2014-12-01

    The theory that forests become carbon (C) neutral with maturity has recently been challenged. While a growing body of evidence shows that net C accumulation continues in forests that are centuries old, the reasons remain poorly known. Increasing canopy structural complexity, quantified by high variability in leaf distribution, has been proposed as a mechanism for sustained rates of C assimilation in mature forests. The goal of our research was to expand on these findings and explore a new idea of spatio-temporal canopy structural complexity as a mechanism linking canopy structure to function (C assimilation).Our work takes place at the UMBS AmeriFlux core facility (US-UMB) in northern Michigan, USA. Canopy structure was quantified over 6 seasons with portable canopy LiDAR (PCL) and canopy spatial microhabitat variability was studied using hemispherical photographs from different heights within the canopy. We found a more even distribution of irradiance in more structurally complex canopies within a single year, and furthermore, that between-year variability of spatial leaf arrangement decreased with increasing canopy complexity. We suggest that in complex canopies less redistribution of leaf material over time may lead to more similar light microhabitats within and among years. Conversely, in less complex canopies this relationship can lead to a year-to-year time lag in morphological leaf acclimation since the effects of the previous-year's light environment are reflected in the morphological characteristics of current-year leaves.Our study harnesses unique spatio-temporal resolution measurements of canopy structure and microhabitat that can inform better management strategies seeking to maximize forest C uptake. Future research quantifying the relationship between canopy structure and light distribution will improve performance of ecosystem models that currently lack spatially explicit canopy structure information.

  20. Characterization and application of simultaneously spatio-temporally focused ultrafast laser pulses

    NASA Astrophysics Data System (ADS)

    Greco, Michael J.

    Chirped pulse amplication of ultrafast laser pulses has become an essential technology in the elds of micromachining, tissue ablation, and microscopy. With specically tailored pulses of light we have been able to begin investigation into lab-on-a-chip technology, which has the potential of revolutionizing the medical industry. Advances in microscopy have allowed sub diraction limited resolution to become a reality as well as lensless imaging of single molecules. An intimate knowledge of ultrafast optical pulses, the ability to manipulate an optical spectrum and generate an optical pulse of a specic temporal shape, allows us to continue pushing these elds forward as well as open new ones. This thesis investigates the spatio-temporal construction of pulses which are simultaneously spatio-temporally focused (SSTF) and about their current and future applications. By laterally chirping a compressed laser pulse we have conned the peak intensity to a shorter distance along the optical axis than can be achieved by conventional methods. This also brings about interesting changes to the structure of the pulse intensity such as pulse front tilt (PFT), an eect where the pulse energy is delayed across the focal spot at the focal plane by longer durations than the pulse itself. Though these pulses have found utility in microscopy and micromachining, in-situ methods for characterizing them spatially and temporally are not yet wide spread. I present here an in-situ characterization technique for both spatial and temporal diagnosis of SSTF pulses. By performing a knife-edge scan and collecting the light in a spectrometer, the relative spectral position as well as beam size can be deduced. Temporal characterization is done by dispersion scan, where a second harmonic crystal through the beam focus. Combining the unknown phase of the pulse with the known phase (a result of angular dispersion) allows the unknown phase to be extracted from the second harmonic spectra.

  1. Spatio-temporal pollution features in Seoul, Korea using magnetic measurements of roadside dusts

    NASA Astrophysics Data System (ADS)

    Doh, S.; Kim, W.; Lee, J.; Park, Y.

    2006-12-01

    Recently, rapid and non-destructive magnetic measurements have been increasingly used as a proxy method for the assessment of heavy metal pollution in urban areas. The spatio-temporal variations of anthropogenic particulate matter in roadside dust of the Seoul metropolitan area have been investigated using 1,353 dust samples collected monthly from 33 locations during 13 months period (February 2002 through February 2003). The S-ratio values and the acquisition patterns of isothermal remanent magnetization indicate that low- coercivity ferrimagnetic minerals are dominant in these roadside dusts. The similar spatial distributions between the magnetic susceptibility values (magnetic concentration) and the reported heavy metal concentrations indicate that magnetic susceptibility can be a useful proxy indicator for heavy metal pollution. Spatially, samples from industrial areas show relatively higher magnetic concentration than those from heavy traffic areas. Samples from residential and park areas reveal the lowest magnetic concentration in this study. Mapping of magnetic susceptibility shows highly polluted areas to be around southwestern, central and northeastern part of Seoul throughout the year. It is considered that anthropogenic materials from industrial complex may be transported along the southwestern part of the city to northeastward because of dominant westerly wind and topographic highs located in the north-northwestern and southern regions of the city. Temporally, the magnetic concentration in winter is higher than that in summer, indicating the seasonal fluctuation of anthropogenic magnetic material influx. It is interpreted that high magnetic concentration during cold and dry winter season might be caused from increased fossil fuel combustion. This interpretation can be supported by that residential areas also show relatively higher magnetic concentration in winter compared to the other seasons. The present study indicates that pollution in the city of

  2. Spatio-temporal filtering techniques for the detection of disaster-related communication.

    PubMed

    Fitzhugh, Sean M; Ben Gibson, C; Spiro, Emma S; Butts, Carter T

    2016-09-01

    Individuals predominantly exchange information with one another through informal, interpersonal channels. During disasters and other disrupted settings, information spread through informal channels regularly outpaces official information provided by public officials and the press. Social scientists have long examined this kind of informal communication in the rumoring literature, but studying rumoring in disrupted settings has posed numerous methodological challenges. Measuring features of informal communication-timing, content, location-with any degree of precision has historically been extremely challenging in small studies and infeasible at large scales. We address this challenge by using online, informal communication from a popular microblogging website and for which we have precise spatial and temporal metadata. While the online environment provides a new means for observing rumoring, the abundance of data poses challenges for parsing hazard-related rumoring from countless other topics in numerous streams of communication. Rumoring about disaster events is typically temporally and spatially constrained to places where that event is salient. Accordingly, we use spatio and temporal subsampling to increase the resolution of our detection techniques. By filtering out data from known sources of error (per rumor theories), we greatly enhance the signal of disaster-related rumoring activity. We use these spatio-temporal filtering techniques to detect rumoring during a variety of disaster events, from high-casualty events in major population centers to minimally destructive events in remote areas. We consistently find three phases of response: anticipatory excitation where warnings and alerts are issued ahead of an event, primary excitation in and around the impacted area, and secondary excitation which frequently brings a convergence of attention from distant locales onto locations impacted by the event. Our results demonstrate the promise of spatio-temporal

  3. Spatio-Temporal Variability of Aquatic Vegetation in Taihu Lake over the Past 30 Years.

    PubMed

    Zhao, Dehua; Lv, Meiting; Jiang, Hao; Cai, Ying; Xu, Delin; An, Shuqing

    2013-01-01

    It is often difficult to track the spatio-temporal variability of vegetation distribution in lakes because of the technological limitations associated with mapping using traditional field surveys as well as the lack of a unified field survey protocol. Using a series of Landsat remote sensing images (i.e. MSS, TM and ETM+), we mapped the composition and distribution area of emergent, floating-leaf and submerged macrophytes in Taihu Lake, China, at approximate five-year intervals over the past 30 years in order to quantify the spatio-temporal dynamics of the aquatic vegetation. Our results indicated that the total area of aquatic vegetation increased from 187.5 km(2) in 1981 to 485.0 km(2) in 2005 and then suddenly decreased to 341.3 km(2) in 2010. Similarly, submerged vegetation increased from 127.0 km(2) in 1981 to 366.5 km(2) in 2005, and then decreased to 163.3 km(2). Floating-leaf vegetation increased continuously through the study period in both area occupied (12.9 km(2) in 1981 to 146.2 km(2) in 2010) and percentage of the total vegetation (6.88% in 1981 to 42.8% in 2010). In terms of spatial distribution, the aquatic vegetation in Taihu Lake has spread gradually from the East Bay to the surrounding areas. The proportion of vegetation in the East Bay relative to that in the entire lake has decreased continuously from 62.3% in 1981, to 31.1% in 2005 and then to 21.8% in 2010. Our findings have suggested that drastic changes have taken place over the past 30 years in the spatial pattern of aquatic vegetation as well as both its relative composition and the amount of area it occupies. PMID:23823189

  4. Spatio-temporal distribution of floating objects in the German Bight (North Sea)

    NASA Astrophysics Data System (ADS)

    Thiel, Martin; Hinojosa, Iván A.; Joschko, Tanja; Gutow, Lars

    2011-04-01

    Floating objects facilitate the dispersal of marine and terrestrial species but also represent a major environmental hazard in the case of anthropogenic plastic litter. They can be found throughout the world's oceans but information on their abundance and the spatio-temporal dynamics is scarce for many regions of the world. This information, however, is essential to evaluate the ecological role of floating objects. Herein, we report the results from a ship-based visual survey on the abundance and composition of flotsam in the German Bight (North Sea) during the years 2006 to 2008. The aim of this study was to identify potential sources of floating objects and to relate spatio-temporal density variations to environmental conditions. Three major flotsam categories were identified: buoyant seaweed (mainly fucoid brown algae), natural wood and anthropogenic debris. Densities of these floating objects in the German Bight were similar to those reported from other coastal regions of the world. Temporal variations in flotsam densities are probably the result of seasonal growth cycles of seaweeds and fluctuating river runoff (wood). Higher abundances were often found in areas where coastal fronts and eddies develop during calm weather conditions. Accordingly, flotsam densities were often higher in the inner German Bight than in areas farther offshore. Import of floating objects and retention times in the German Bight are influenced by wind force and direction. Our results indicate that a substantial amount of floating objects is of coastal origin or introduced into the German Bight from western source areas such as the British Channel. Rapid transport of floating objects through the German Bight is driven by strong westerly winds and likely facilitates dispersal of associated organisms and gene flow among distant populations.

  5. Spatio-temporal analysis techniques for detailed investigations of space storm dynamics

    NASA Astrophysics Data System (ADS)

    Vassiliadis, D.; Daglis, I. A.; Klimas, A. J.; Clauer, C. R.

    2001-09-01

    We present several spatio-temporal analysis techniques, which integrate mid-latitude ground magnetogram data and are useful in identifying key features in the ring current response. In this way we can quantify a) the intensity and spatial extent of inner magnetosphere convection, b) the intensity of the geomagnetic response to interplanetary pressure pulses, c) the penetration of the substorm current wedge to lower latitudes and d) the effect of particle injections on the ring current. The first technique creates a spatio-temporal storm "portrait" based on the axial component of the ground magnetic field H(UT;LT) [Clauer and McPherron, 1974]. Displaying the field data in UT-LT coordinates allows comparison of the activity in the inner magnetosphere. In addition to visual identification of the above features, we introduce a second technique that uses principal component analysis (PCA) of the storm portrait. PCA peaks correspond, in order of decreasing eigenvalue, to symmetric ring current, asymmetric ring current and substorm current wedge, and injections into the ring current, typically during substorms. Identification of the major PCA peaks with large-scale current systems is confirmed by correlation with and timing relative to geomagnetic indices (Dst, AL, etc). The intensity and direction of ring current injections is estimated by a bandpass filter technique for individual magnetograms. Examples using the storms of June 4, 1991, and September 26, 1998, are given. In these cases the asymmetric ring current can have a geomagnetic effect as strong as the azimuthally symmetric part meaning the majority of plasma sheet particles convecting deep into the inner magnetosphere are quickly (~2-3 hours) lost at the dayside magnetopause. On the other hand, the estimate for particle injections compared to slow convection reaches up to 30% in terms of the average geomagnetic field amplitude. Thus, individual substorms can have a significant influence on the storm-time ring

  6. Spatio-Temporal Simulation of First Pass Drug Perfusion in the Liver

    PubMed Central

    Schwen, Lars Ole; Krauss, Markus; Niederalt, Christoph; Gremse, Felix; Kiessling, Fabian; Schenk, Andrea; Preusser, Tobias; Kuepfer, Lars

    2014-01-01

    The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the

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

    PubMed Central

    Marinkovic, Ksenija; Courtney, Maureen G.; Witzel, Thomas; Dale, Anders M.; Halgren, Eric

    2014-01-01

    Although a crucial role of the fusiform gyrus (FG) 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 FG) peaked at ~160 ms 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 ~240 ms 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 interactive neural circuit. PMID

  8. An Ethnographic Case Study of Spatio-Temporal Practices Circulating On- and Off-Line in a Distance Learning Class

    ERIC Educational Resources Information Center

    Kabat-Ryan, Katalin Judith

    2013-01-01

    This dissertation examines the spatio-temporal practices of a distance learning class in a graduate institution in the Northeast United States. Guided by a multispatial and temporal perspective, the case study builds on Hine's (2003) and Leander and McKim's (2003) connective ethnography of offline and online research sites, and frames the research…

  9. Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

    NASA Astrophysics Data System (ADS)

    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.

  10. Anatomical co-registration using spatio-temporal features of a non-contact near-infrared optical scanner

    NASA Astrophysics Data System (ADS)

    Jung, Young-Jin; Gonzalez, Jean; Rodriguez, Suset; Velez Mejia, Maximiliano; Clark, Gabrielle; Godavarty, Anuradha

    2014-02-01

    Non-contact based near-infrared (NIR) optical imaging devices are developed for non-invasive imaging of deep tissues in various clinical applications. Most of these devices focus on obtaining the spatial information for anatomical co-registration of blood vessels as in sub-surface vein localization applications. In the current study, the anatomical co-registration of blood vessels based on spatio-temporal features was performed using NIR optical imaging without the use of external contrast agents. A 710 nm LED source and a compact CCD camera system were employed during simple cuff (0 to 60 mmHg) experiment in order to acquire the dynamic NIR data from the dorsum of a hand. The spatio-temporal features of dynamic NIR data were extracted from the cuff experimental study to localize vessel according to blood dynamics. The blood vessels shape is currently reconstructed from the dynamic data based on spatio-temporal features. Demonstrating the spatio-temporal feature of blood dynamic imaging using a portable non-contact NIR imaging device without external contrast agents is significant for applications such as peripheral vascular diseases.

  11. [Spatio-temporal pattern of larvae and eggs of gastrointestinal nematodes in cattle pastures in Veracruz, Mexico].

    PubMed

    Flota-Bañuelos, Carolina; Martínez, Imelda; López-Collado, José; Vargas Mendoza, Mónica; González Hernández, Hector; Fajersson, Pernilla

    2013-12-01

    The spatial and temporal distribution of gastrointestinal nematodes of cattle has been little studied in Mexico. Previous studies have described periods of higher larval presence, vertical and horizontal migration in grasslands, and the frequency of adult nematodes; as well as the effect of pasture trichomes on the migration and survival of Haemonchus larvae. The aim of this study was to determine the time-space layout and spread of gastrointestinal nematode larvae on pasture, and to estimate the effect of ivermectin applied to cattle on the time-dependent abundance of their eggs in a ranch in Veracruz. To determine the spatio-temporal arrangement, monthly morning grass samples were obtained from 30 sampling points from July 2008 to June 2009. Third stage larvae (L3) from each point were counted, and aggregation patterns were estimated through variance/mean and negative binomial K indices. Additionally, the number of eggs per gram in cattle feces was determined, from samples with (CI) and without ivermectin (SI), using standard techniques. A total of 20 276 L(3) larvae were recovered in the pasture, of which an 80% corresponded to Haemonchus contortus. The highest nematode density with more than 5 000L(3)/kgDM was detected in October 2008, and the lowest in February and March 2009. The L3 showed an aggregated spatial pattern of varying intensity throughout the year. The number of eggs in the stool was not reduced with the ivermectin application to cattle, which suggested a failure of control. However, the highest parasite loads were observed from July to November 2008. We concluded that the application of ivermectin was not effective to control nematodes eggs, and that L3 populations fluctuated on pasture for ten months, providing an infection source to grazing animals afterwards. PMID:24432531

  12. Novelty and spatio-temporal heterogeneity in the bacterial diversity of hypersaline Lake Tebenquiche (Salar de Atacama).

    PubMed

    Demergasso, Cecilia; Escudero, Lorena; Casamayor, Emilio O; Chong, Guillermo; Balagué, Vanessa; Pedrós-Alió, Carlos

    2008-07-01

    Lake Tebenquiche is one of the largest saline water bodies in the Salar de Atacama at 2,500 m above sea level in northeastern Chile. Bacteria inhabiting there have to deal with extreme changes in salinity, temperature and UV dose (i.e., high environmental dissimilarity in the physical landscape). We analyzed the bacterioplankton structure of this lake by 16S rRNA gene analyses along a spatio-temporal survey. The bacterial assemblage within the lake was quite heterogeneous both in space and time. Salinity changed both in space and time ranging between 1 and 30% (w/v), and total abundances of planktonic prokaryotes in the different sampling points within the lake ranged between two and nine times 10(6) cells mL(-1). Community composition changed accordingly to the particular salinity of each point as depicted by genetic fingerprinting analyses (denaturing gradient gel electrophoresis), showing a high level of variation in species composition from place to place (beta-diversity). Three selected sites were analyzed in more detail by clone libraries. We observed a predominance of Bacteroidetes (about one third of the clones) and Gammaproteobacteria (another third) with respect to all the other bacterial groups. The diversity of Bacteroidetes sequences was large and showed a remarkable degree of novelty. Bacteroidetes formed at least four clusters with no cultured relatives in databases and rather distantly related to any known 16S rRNA sequence. Within this phylum, a rich and diverse presence of Salinibacter relatives was found in the saltiest part of the lake. Lake Tebenquiche included several novel microorganisms of environmental importance and appeared as a large unexplored reservoir of unknown bacteria. PMID:18347752

  13. Spatio-temporal analysis of SAR based time series for slope instability characterization: the Corvara in Badia landslide (Dolomites, Italy)

    NASA Astrophysics Data System (ADS)

    Mulas, M.; Petitta, M.; Brazanti, M.; Benedetti, E.; Corsini, A.; Iasio, C.

    2012-04-01

    presence of trends. Fits with exponential functions of the de-trended and de-seasonalized signal have been performed to identify the presence of dissipating deformations. We observed that the signal of velocity and acceleration is characterized by the coexistence of different factors: first, periodic signals associated to seasonal and gravitational kinematic behavior; second, decay effects due to instability events. Moreover, using different points is possible to observe the signal propagation both in time and space. This analysis allow us to determine the spatio-temporal scale of different forcing events and their effect on the total landslide area. Finally, this study represent a new approach for identify the spatio-temporal nature of different factors in the evolution of the landslide for setting-up a system of conscious prediction of maintenance tasks of the exposed structures. The use of the SAR data demonstrated to be an innovative tool for high temporal resolution surveys with a big amount of points that in comparison with GPS surveys results to be economically convenient in wide AOI.

  14. Spatio-temporal characteristics of livestock and their effects on pollution in China based on geographic information system.

    PubMed

    Liu, Ruimin; Xu, Fei; Liu, Yongyan; Wang, Jiawei; Yu, Wenwen

    2016-07-01

    Livestock pollution, caused by rural household's scatter breeding mainly, is one of the major non-point sources. Different animal manures are abundant with different nutrients. Adopting the policies, management practices, and technologies related to livestock production based on livestock structure analysis can improve the efficiency on preventing pollution. Based on statistical data, the component structure of livestock was analyzed and corresponding effect on pollution was evaluated during the period of 1992-2012 in China. The results showed that the average annual growth rate (AAGR) of total China was 1.58 % during the 20 years. Larger amounts of livestock were concentrated in Southwest China and East China. In the view of component structure, each type of livestock had different distribution characteristics and constant increasing amounts were presented during the 20 years. Cattle took the largest proportion in almost every province, and the number of heads was over 40 % of all the livestock quantity for most provinces. Pollution of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) caused by livestock excretion in East and Southeast China was much more serious than that in other regions. However, the load of COD was far less than that of TN and TP. Cattle accounted most for the livestock pollution, and swine was the second one. The intensity characteristics of TN, TP, and COD were different from that of total pollution loads. The spatio-temporal characteristics of amounts and component structure of livestock were influenced by three kinds of factors (natural, economic, and social), such as climate, topography, modes of production, feed grain sector, related policies, and area of the study regions. Different livestock excrements had different impacts on environment. According to various livestock structures and economy conditions, different disposal methods should be adopted. PMID:27053044

  15. Spatio-Temporal Sensitivity of MODIS Land Surface Temperature Anomalies Indicates High Potential for Large-Scale Land Cover Change Detection in Permafrost Landscapes

    NASA Astrophysics Data System (ADS)

    Muster, S.; Langer, M.; Abnizova, A.; Young, K. L.; Boike, J.

    2014-12-01

    The accelerated warming Arctic climate may alter the surface energy balance locally and regionally of which a changing land surface temperature (LST) is a key indicator. Modelling current and anticipated changes of the surface energy balance requires an understanding of the spatio-temporal interactions between LST and land cover. This paper investigated the accuracy of MODIS LST V5 1 km level 3 product and its spatio-temporal sensitivity to land cover properties in a Canadian High Arctic permafrost landscape. Land cover ranged from fully vegetated moss/segde grass tundra to sparsely vegetated bare soil and barren areas. Daily mean MODIS LST were compared to in-situ radiometer measurements over wet tundra for three summers and two winters in 2008, 2009, and 2010. MODIS LST showed an accuracy of 1.8°C and a RMSE of 3.8°C in the total observation period including both summer and winter. Agreement was lowest during summer 2009 and freeze-back periods which were associated with prevailing overcast conditions. A multi-year anomaly analysis revealed robust spatio-temporal patterns taking into account the found uncertainty and different atmospheric conditions. Summer periods with regional mean LST larger than 5°C showed highest spatial diversity with four distinct anomaly classes. Dry ridge areas heated up most whereas wetland areas and dry barren surfaces with high albedo were coolest. Mean inter-annual differences of LST anomalies for different land cover classes were less than 1°C. However, spatial pattern showed fewer positive anomalies in 2010 suggesting differences in surface moisture due to inter­annual differences in the amount of end-of-winter snow. Presented summer LST anomalies might serve as a baseline against which to evaluate past and future changes in land surface properties with regard to the surface energy balance. Sub-temporal heterogeneity due to snow or ice on/off as well as the effect of subpixel water bodies has to be taken into account. A multi

  16. Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

    PubMed

    Kasabov, Nikola; Scott, Nathan Matthew; Tu, Enmei; Marks, Stefan; Sengupta, Neelava; Capecci, Elisa; Othman, Muhaini; Doborjeh, Maryam Gholami; Murli, Norhanifah; Hartono, Reggio; Espinosa-Ramos, Josafath Israel; Zhou, Lei; Alvi, Fahad Bashir; Wang, Grace; Taylor, Denise; Feigin, Valery; Gulyaev, Sergei; Mahmoud, Mahmoud; Hou, Zeng-Guang; Yang, Jie

    2016-06-01

    The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include 'on the fly' new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it. eSTDM can be used for early event prediction due to the ability of the SNN to spike early, before whole input vectors (they were trained on) are presented. A framework for building eSTDM called NeuCube along with a design methodology for building eSTDM using this is presented. The implementation of this framework in MATLAB, Java, and PyNN (Python) is presented. The latter facilitates the use of neuromorphic hardware platforms to run the eSTDM. Selected examples are given of eSTDM for pattern recognition and early event prediction on EEG data, fMRI data, multisensory seismic data, ecological data, climate data, audio-visual data. Future directions are discussed, including extension of the NeuCube framework for building neurogenetic eSTDM and also new applications of eSTDM. PMID:26576468

  17. Quantifying the spatio-temporal dynamics of woody plant encroachment using an integrative remote sensing, GIS, and spatial modeling approach

    NASA Astrophysics Data System (ADS)

    Buenemann, Michaela