Science.gov

Sample records for complex spatio-temporal order

  1. SPATIO-TEMPORAL COMPLEXITY OF THE AORTIC SINUS VORTEX.

    PubMed

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-06-01

    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.

  2. 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

  3. Spatio-temporal phenomena in complex systems with time delays

    NASA Astrophysics Data System (ADS)

    Yanchuk, Serhiy; Giacomelli, Giovanni

    2017-03-01

    Real-world systems can be strongly influenced by time delays occurring in self-coupling interactions, due to unavoidable finite signal propagation velocities. When the delays become significantly long, complicated high-dimensional phenomena appear and a simple extension of the methods employed in low-dimensional dynamical systems is not feasible. We review the general theory developed in this case, describing the main destabilization mechanisms, the use of visualization tools, and commenting on the most important and effective dynamical indicators as well as their properties in different regimes. We show how a suitable approach, based on a comparison with spatio-temporal systems, represents a powerful instrument for disclosing the very basic mechanism of long-delay systems. Various examples from different models and a series of recent experiments are reported.

  4. 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.

  5. 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

    2015-10-07

    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. 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

  7. 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

  8. 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

  9. 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.

  10. Spatio-temporal modelling of lightning climatologies for complex terrain

    NASA Astrophysics Data System (ADS)

    Simon, Thorsten; Umlauf, Nikolaus; Zeileis, Achim; Mayr, Georg J.; Schulz, Wolfgang; Diendorfer, Gerhard

    2017-03-01

    This study develops methods for estimating lightning climatologies on the day-1 km-2 scale for regions with complex terrain and applies them to summertime observations (2010-2015) of the lightning location system ALDIS in the Austrian state of Carinthia in the Eastern Alps. Generalized additive models (GAMs) are used to model both the probability of occurrence and the intensity of lightning. Additive effects are set up for altitude, day of the year (season) and geographical location (longitude/latitude). The performance of the models is verified by 6-fold cross-validation. The altitude effect of the occurrence model suggests higher probabilities of lightning for locations on higher elevations. The seasonal effect peaks in mid-July. The spatial effect models several local features, but there is a pronounced minimum in the north-west and a clear maximum in the eastern part of Carinthia. The estimated effects of the intensity model reveal similar features, though they are not equal. The main difference is that the spatial effect varies more strongly than the analogous effect of the occurrence model. A major asset of the introduced method is that the resulting climatological information varies smoothly over space, time and altitude. Thus, the climatology is capable of serving as a useful tool in quantitative applications, i.e. risk assessment and weather prediction.

  11. Complex network based techniques to identify extreme events and (sudden) transitions in spatio-temporal systems.

    PubMed

    Marwan, Norbert; Kurths, Jürgen

    2015-09-01

    We present here two promising techniques for the application of the complex network approach to continuous spatio-temporal systems that have been developed in the last decade and show large potential for future application and development of complex systems analysis. First, we discuss the transforming of a time series from such systems to a complex network. The natural approach is to calculate the recurrence matrix and interpret such as the adjacency matrix of an associated complex network, called recurrence network. Using complex network measures, such as transitivity coefficient, we demonstrate that this approach is very efficient for identifying qualitative transitions in observational data, e.g., when analyzing paleoclimate regime transitions. Second, we demonstrate the use of directed spatial networks constructed from spatio-temporal measurements of such systems that can be derived from the synchronized-in-time occurrence of extreme events in different spatial regions. Although there are many possibilities to investigate such spatial networks, we present here the new measure of network divergence and how it can be used to develop a prediction scheme of extreme rainfall events.

  12. Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

    PubMed Central

    Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jürgen; Schoeman, David S.

    2011-01-01

    Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy

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

    PubMed

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

    2012-03-01

    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.

  14. 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

  15. Probing Spatio-Temporal Correlation in Complex Aqueous Systems through 2D-IR Spectroscopy

    NASA Astrophysics Data System (ADS)

    Bagchi, Biman; Biswas, Rajib; Samanta, Tuhin; Ghosh, Rikhia; Roy, Susmita

    2015-03-01

    Heterogeneity is ubiquitous in aqueous solutions, e.g., in protein and DNA solutions, micelles and reverse micelles, density fluctuations during phase transitions (e,g., water to ice). Origin of heterogeneity can be diverse, sometimes stimulated by external biomolecular subsystems (proteins, DNA, lipids), nanoscopic materials etc, but may also be intrinsic to the thermodynamic nature of the aqueous solution itself. The altered dynamics of water in presence of such diverse surfaces have attracted considerable attention in recent years. However, efficiently capturing the length and timescale of heterogeneous dynamics of water is indeed a challenging task. Recent development of two dimensional infra-red (2D-IR) allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuation and calculate. The respective studies reveal a number of interesting facts. Spatio-temporal correlation of water dynamics with varying size of reverse micelles is well captured through the spectral diffusion of corresponding 2D-IR spectra. In case of supercritical water also, we observe strong signature of dynamic heterogeneity from the elongated nature of the spectra.

  16. Spatio-temporal clustering

    NASA Astrophysics Data System (ADS)

    Kisilevich, Slava; Mansmann, Florian; Nanni, Mirco; Rinzivillo, Salvatore

    Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new subfield of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness of all kinds of location-based or environmental devices that record position, time or/and environmental properties of an object or set of objects in real-time. As a consequence, different types and large amounts of spatio-temporal data became available that introduce new challenges to data analysis and require novel approaches to knowledge discovery. In this chapter we concentrate on the spatio-temporal clustering in geographic space. First, we provide a classification of different types of spatio-temporal data. Then, we focus on one type of spatio-temporal clustering - trajectory clustering, provide an overview of the state-of-the-art approaches and methods of spatio-temporal clustering and finally present several scenarios in different application domains such as movement, cellular networks and environmental studies.

  17. High-order Spatio-temporal Schemes for Coupled, Multi-physics Reactor Simulations

    SciTech Connect

    Mr. Vijay S. Mahadevan; Dr. Jean C. Ragusa

    2008-09-01

    This report summarizes the work done in the summer of 08 by the Ph.D. student Vijay Mahadevan. The main focus of the work was to coupled 3-D neutron difusion to 3-D heat conduction in parallel with accuracy greater than or equal to 2nd order in space and time. Results show that the goal was attained.

  18. Spatio-temporal complexity of chimpanzee food: How cognitive adaptations can counteract the ephemeral nature of ripe fruit.

    PubMed

    Janmaat, Karline R L; Boesch, Christophe; Byrne, Richard; Chapman, Colin A; Goné Bi, Zoro B; Head, Josephine S; Robbins, Martha M; Wrangham, Richard W; Polansky, Leo

    2016-06-01

    Ecological complexity has been proposed to play a crucial role in primate brain-size evolution. However, detailed quantification of ecological complexity is still limited. Here we assess the spatio-temporal distribution of tropical fruits and young leaves, two primary chimpanzee (Pan troglodytes) foods, focusing on the predictability of their availability in individual trees. Using up to 20 years of information on monthly availability of young leaf, unripe and ripe fruit in plant species consumed by chimpanzees from tropical forests in East, Central, and West Africa, we estimated: (1) the forest-wide frequency of occurrence of each food type and (2) the predictability of finding ripe fruit-bearing trees, focusing on the timing, frequency, and amount of ripe fruit present. In all three forests, at least half of all encountered trees belonged to species that chimpanzees were known to feed on. However, the proportion of these trees bearing young leaves and fruit fluctuated widely between months. Ripe fruit was the most ephemeral food source, and trees that had more than half of their crown filled were at least nine times scarcer than other trees. In old growth forests only one large ripe fruit crop was on average encountered per 10 km. High levels of inter-individual variation in the number of months that fruit was present existed, and in some extreme cases individuals bore ripe fruit more than seven times as often as conspecifics. Some species showed substantially less variation in such ripe fruit production frequencies and fruit quantity than others. We hypothesize that chimpanzees employ a suite of cognitive mechanisms, including abilities to: (1) generalize or classify food trees; (2) remember the relative metrics of quantity and frequency of fruit production across years; and (3) flexibly plan return times to feeding trees to optimize high-energy food consumption in individual trees, and efficient travel between them. Am. J. Primatol. 78:626-645, 2016. © 2016

  19. Spatio-Temporal Complexity and Large-Scale Structures in Problems of Continuum Mechanic

    DTIC Science & Technology

    1993-07-15

    TEMPORAL COMPLEXITY & LARGE SCALE STRUCTURES IN PROBLEMS OF CONTINUUM MECHANICS" (U) 61103D 3484/D7 (URI) 6. AUTHOR(S) Drs. Basil Nicolaenko, Dieter...orbits on-the attractor. We have applied our method to two experimental data sets from Taylor-Couette flows . 14. SUBJECT TERMS -WS.-UMBER OF PAGES’ 14 S...8217 .. . .,16. PRICE CODE 17. SECURITY CLASSIFICATION 1. SECURITY CLASSIFICATION 19., SECURITY CLASSIFICATION 20. LIMITATION OFA. OF REPORT OF THIS

  20. Dynamic Topology and Spatio-Temporal Complexity of Stick-Slip Events in Natural Faulted Westerly Granite

    NASA Astrophysics Data System (ADS)

    Ghaffari, H.; Thompson, B. D.; Young, R.

    2011-12-01

    The patterns of acoustic events prior to and after a stick-slip event are transformed to complex networks and the characteristics of the networks are measured. The patterns are the result of acoustic emission monitoring through loading a cylindrical sample of Westerly granite containing a natural fault [1].Two approaches are implemented in construction of the networks. In the first approach the network is constructed based on nearest neighbour events while the interactions of the main fault with the second and third faults are inspected through analyzing the spatial communities of the networks. The second approach uses a network method on phase space of time series (i.e., constructing a smooth manifold) obtained from the waveforms of over occurrence rank of events [2]. With the later implementation, we characterize the source mechanism of events while we compare the characteristics of the obtained networks (i.e., motif distribution and eigenvector of Laplacian) with the inferred source mechanism from the inverse moment tensor approach. Our results show the correlation of motifs rank evolution with source mechanism. Furthermore, with respect to the shape of triangles (as well as stretching and folding) over spatial complex networks and based on the first approach, the 3 point nodes motif distributions are extended to consider possible statistical geometry of events. Thus, the spatio-temporal complexity and possible coupling of events in time and space in terms of network parameters is inferred. We compare our results with the recent analysis of networks motifs from pure shear rupture associated with sudden variation of contact strings [3]. Keyword:, Stick-sllip; Westerly granite, Acoustic Emission Patterns; Complex Networks, and Motifs Ref. [1] Thompson, B.D., D.A. Lockner and R.P. Young, Premonitory acoustic emissions and stick slip in natural and smooth faulted Westerly granite,J. Geophysical Research, Vol 114, B02205, doi: 10.1029/2008jb005753, 2009. [2] J. F

  1. RSTFC: A Novel Algorithm for Spatio-Temporal Filtering and Classification of Single-Trial EEG.

    PubMed

    Qi, Feifei; Li, Yuanqing; Wu, Wei

    2015-12-01

    Learning optimal spatio-temporal filters is a key to feature extraction for single-trial electroencephalogram (EEG) classification. The challenges are controlling the complexity of the learning algorithm so as to alleviate the curse of dimensionality and attaining computational efficiency to facilitate online applications, e.g., brain-computer interfaces (BCIs). To tackle these barriers, this paper presents a novel algorithm, termed regularized spatio-temporal filtering and classification (RSTFC), for single-trial EEG classification. RSTFC consists of two modules. In the feature extraction module, an l2 -regularized algorithm is developed for supervised spatio-temporal filtering of the EEG signals. Unlike the existing supervised spatio-temporal filter optimization algorithms, the developed algorithm can simultaneously optimize spatial and high-order temporal filters in an eigenvalue decomposition framework and thus be implemented highly efficiently. In the classification module, a convex optimization algorithm for sparse Fisher linear discriminant analysis is proposed for simultaneous feature selection and classification of the typically high-dimensional spatio-temporally filtered signals. The effectiveness of RSTFC is demonstrated by comparing it with several state-of-the-arts methods on three brain-computer interface (BCI) competition data sets collected from 17 subjects. Results indicate that RSTFC yields significantly higher classification accuracies than the competing methods. This paper also discusses the advantage of optimizing channel-specific temporal filters over optimizing a temporal filter common to all channels.

  2. Controlling spatio-temporal chaos in the scenario of the one-dimensional complex Ginzburg-Landau equation.

    PubMed

    Boccaletti, S; Bragard, J

    2006-09-15

    We discuss some issues related with the process of controlling space-time chaotic states in the one-dimensional complex Ginzburg-Landau equation. We address the problem of gathering control over turbulent regimes with the use of only a limited number of controllers, each one of them implementing, in parallel, a local control technique for restoring an unstable plane-wave solution. We show that the system extension does not influence the density of controllers needed in order to achieve control.

  3. Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

    NASA Astrophysics Data System (ADS)

    Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

    2001-12-01

    This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

  4. Spatio-temporal variation in the strength and mode of selection acting on major histocompatibility complex diversity in water vole (Arvicola terrestris) metapopulations.

    PubMed

    Oliver, Matthew K; Lambin, Xavier; Cornulier, Thomas; Piertney, Stuart B

    2009-01-01

    Patterns of spatio-temporal genetic variation at a class II major histocompatibility complex (MHC) locus and multiple microsatellite loci were analysed within and between three water vole metapopulations in Scotland, UK. Comparisons of MHC and microsatellite spatial genetic differentiation, based on standardised tests between two demographically asynchronous zones within a metapopulation, suggested that spatial MHC variation was affected by balancing selection, directional selection and random genetic drift, but that the relative effects of these microevolutionary forces vary temporally. At the metapopulation level, between-year differentiation for MHC loci was significantly correlated with that of microsatellites, signifying that neutral factors such as migration and drift were primarily responsible for overall temporal genetic change at the metapopulation scale. Between metapopulations, patterns of genetic differentiation implied that, at large spatial scales, MHC variation was primarily affected by directional selection and drift. Levels of MHC heterozygosity in excess of Hardy-Weinberg expectations were consistent with overdominant balancing selection operating on MHC variation within metapopulations. However, this effect was not constant among all samples, indicating temporal variation in the strength of selection relative to other factors. The results highlight the benefit of contrasting variation at MHC with neutral markers to separate the effects of stochastic and deterministic microevolutionary forces, and add to a growing body of evidence showing that the mode and relative strength of selection acting on MHC diversity varies both spatially and temporally.

  5. The electric organ discharge of pulse gymnotiforms: the transformation of a simple impulse into a complex spatio-temporal electromotor pattern

    PubMed

    Caputi

    1999-05-01

    An understanding of how the nervous system processes an impulse-like input to yield a stereotyped, species-specific electromotor output is relevant for electric fish physiology, but also for understanding the general mechanisms of coordination of effector patterns. In pulse gymnotids, the electromotor system is repetitively activated by impulse-like signals generated by a pacemaker nucleus in the medulla. This nucleus activates a set of relay cells whose axons descend along the spinal cord and project to electromotor neurones which, in turn, project to electrocytes. Relay neurones, electromotor neurones and electrocytes may be considered as layers of a network arranged with a lattice hierarchy. This network is able to coordinate a spatio-temporal pattern of postsynaptic and action currents generated by the electrocyte membranes. Electrocytes may be innervated at their rostral face, at their caudal face or at both faces, depending on the site of the organ and the species. Thus, the species-specific electric organ discharge patterns depend on the electric organ innervation pattern and on the coordinated activation of the electrocyte faces. The activity of equally oriented faces is synchronised by a synergistic combination of delay lines. The activation of oppositely oriented faces is coordinated in a precise sequence resulting from the orderly recruitment of subsets of electromotor neurones according to the 'size principle' and to their position along the spinal cord. The body of the animal filters the electric organ output electrically, and the whole fish is transformed into a distributed electric source.

  6. Detecting hidden spatial and spatio-temporal structures in glasses and complex physical systems by multiresolution network clustering.

    PubMed

    Ronhovde, P; Chakrabarty, S; Hu, D; Sahu, M; Sahu, K K; Kelton, K F; Mauro, N A; Nussinov, Z

    2011-09-01

    We elaborate on a general method that we recently introduced for characterizing the "natural" structures in complex physical systems via multi-scale network analysis. The method is based on "community detection" wherein interacting particles are partitioned into an "ideal gas" of optimally decoupled groups of particles. Specifically, we construct a set of network representations ("replicas") of the physical system based on interatomic potentials and apply a multiscale clustering ("multiresolution community detection") analysis using information-based correlations among the replicas. Replicas may i) be different representations of an identical static system, ii) embody dynamics by considering replicas to be time separated snapshots of the system (with a tunable time separation), or iii) encode general correlations when different replicas correspond to different representations of the entire history of the system as it evolves in space-time. Inputs for our method are the inter-particle potentials or experimentally measured two (or higher order) particle correlations. We apply our method to computer simulations of a binary Kob-Andersen Lennard-Jones system in a mixture ratio of A(80)B(20) , a ternary model system with components "A", "B", and "C" in ratios of A(88)B(7)C(5) (as in Al(88)Y(7)Fe(5) , and to atomic coordinates in a Zr(80)Pt(20) system as gleaned by reverse Monte Carlo analysis of experimentally determined structure factors. We identify the dominant structures (disjoint or overlapping) and general length scales by analyzing extrema of the information theory measures. We speculate on possible links between i) physical transitions or crossovers and ii) changes in structures found by this method as well as phase transitions associated with the computational complexity of the community detection problem. We also briefly consider continuum approaches and discuss rigidity and the shear penetration depth in amorphous systems; this latter length scale increases as

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

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  8. 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

  9. Spatio-temporal topological relationships between land parcels in cadastral database

    NASA Astrophysics Data System (ADS)

    Song, W.; Zhang, F.

    2014-04-01

    There are complex spatio-temporal relationships among cadastral entities. Cadastral spatio-temporal data model should not only describe the data structure of cadastral objects, but also express cadastral spatio-temporal relationships between cadastral objects. In the past, many experts and scholars have proposed a variety of cadastral spatio-temporal data models, but few of them concentrated on the representation of spatiotemporal relationships and few of them make systematic studies on spatiotemporal relationships between cadastral objects. The studies on spatio-temporal topological relationships are not abundant. In the paper, we initially review current approaches to the studies of spatio-temporal topological relationships, and argue that spatio-temporal topological relation is the combination of temporal topology on the time dimension and spatial topology on the spatial dimension. Subsequently, we discuss and develop an integrated representation of spatio-temporal topological relationships within a 3-dimensional temporal space. In the end, based on the semantics of spatiotemporal changes between land parcels, we conclude the possible spatio-temporal topological relations between land parcels, which provide the theoretical basis for creating, updating and maintaining of land parcels in the cadastral database.

  10. A top-down hierarchical spatio-temporal process description method and its data organization

    NASA Astrophysics Data System (ADS)

    Xie, Jiong; Xue, Cunjin

    2009-10-01

    Modeling and representing spatio-temporal process is the key foundation for analyzing geographic phenomenon and acquiring spatio-temporal high-level knowledge. Spatio-temporal representation methods with bottom-up approach based on object modeling view lack of explicit definition of geographic phenomenon and finer-grained representation of spatio-temporal causal relationships. Based on significant advances in data modeling of spatio-temporal object and event, aimed to represent discrete regional dynamic phenomenon composed with group of spatio-temporal objects, a regional spatio-temporal process description method using Top-Down Hierarchical approach (STP-TDH) is proposed and a data organization structure based on relational database is designed and implemented which builds up the data structure foundation for carrying out advanced data utilization and decision-making. The land use application case indicated that process modeling with top-down approach was proved to be good with the spatio-temporal cognition characteristic of our human, and its hierarchical representation framework can depict dynamic evolution characteristic of regional phenomenon with finer-grained level and can reduce complexity of process description.

  11. 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.

  12. Network Analysis Using Spatio-Temporal Patterns

    NASA Astrophysics Data System (ADS)

    Miranda, Gisele H. B.; Machicao, Jeaneth; Bruno, Odemir M.

    2016-08-01

    Different network models have been proposed along the last years inspired by real-world topologies. The characterization of these models implies the understanding of the underlying network phenomena, which accounts structural and dynamic properties. Several mathematical tools can be employed to characterize such properties as Cellular Automata (CA), which can be defined as dynamical systems of discrete nature composed by spatially distributed units governed by deterministic rules. In this paper, we proposed a method based on the modeling of one specific CA over distinct network topologies in order to perform the classification of the network model. The proposed methodology consists in the modeling of a binary totalistic CA over a network. The transition function that governs each CA cell is based on the density of living neighbors. Secondly, the distribution of the Shannon entropy is obtained from the evolved spatio-temporal pattern of the referred CA and used as a network descriptor. The experiments were performed using a dataset composed of four different types of networks: random, small-world, scale-free and geographical. We also used cross-validation for training purposes. We evaluated the accuracy of classification as a function of the initial number of living neighbors, and, also, as a function of a threshold parameter related to the density of living neighbors. The results show high accuracy values in distinguishing among the network models which demonstrates the feasibility of the proposed method.

  13. What Is Spatio-Temporal Data Warehousing?

    NASA Astrophysics Data System (ADS)

    Vaisman, Alejandro; Zimányi, Esteban

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

  14. 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.

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

    PubMed

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

    2014-12-01

    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.

  16. 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.

  17. Measuring ultracomplex supercontinuum pulses and spatio-temporal distortions

    NASA Astrophysics Data System (ADS)

    Gu, Xun

    This thesis contains two components of research: studies of supercontinuum pulses generated in the novel microstructure fiber, and research on spatio-temporal coupling in ultrafast laser beams. One of the most exciting developments in optics in recent years has been the invention of the microstructure optical fiber. By controlling the structural parameters of these novel fibers in design and manufacturing, their dispersion profile can be freely tailored, opening up a huge application base. One particularly interesting effect in the microstructure fiber is the generation of ultrabroadband supercontinuum with only nJ-level Ti:sapphire oscillator pulse pump. This supercontinuum is arguably the most complicated ultrafast pulse ever generated, with its huge time-bandwidth product (>1000 from a 16-cm-long fiber). Although many applications have been demonstrated or envisioned with this continuum, its generation is a very complicated process that is poorly understood, and the characteristics of the continuum pulses are not clearly known. In this work, we make a full-intensity-and-phase measurement of the continuum pulses using cross-correlation frequency-resolved optical gating (XFROG). The results reveal surprising unstable fine spectral structure in the continuum pulses, which is confirmed by single-shot measurements. Our study on the coherence of the continuum, on the other hand, shows that the spectral phase of the supercontinuum is fairly stable. Numerical simulations are carried out whose results are in good agreement with experiments. The second component of this thesis is the study of spatio-temporal coupling in ultrafast beams. We propose two definitions of spatial chirp, point out their respective physical meanings, and derive their relationship. On the common perception of the equivalence between pulse-front tilt and angular dispersion, we show that the equivalence only holds for plane waves. We establish a generalized theory of ultrafast laser beams with first-order

  18. 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

  19. 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.

  20. Spatio-Temporal Updating in the Left Posterior Parietal Cortex

    PubMed Central

    Wada, Makoto; Takano, Kouji; Ikegami, Shiro; Ora, Hiroki; Spence, Charles; Kansaku, Kenji

    2012-01-01

    Adopting an unusual posture can sometimes give rise to paradoxical experiences. For example, the subjective ordering of successive unseen tactile stimuli delivered to the two arms can be affected when people cross them. A growing body of evidence now highlights the role played by the parietal cortex in spatio-temporal information processing when sensory stimuli are delivered to the body or when actions are executed; however, little is known about the neural basis of such paradoxical feelings resulting from such unusual limb positions. Here, we demonstrate increased fMRI activation in the left posterior parietal cortex when human participants adopted a crossed hands posture with their eyes closed. Furthermore, by assessing tactile temporal order judgments (TOJs) in the same individuals, we observed a positive association between activity in this area and the degree of reversal in TOJs resulting from crossing arms. The strongest positive association was observed in the left intraparietal sulcus. This result implies that the left posterior parietal cortex may be critically involved in monitoring limb position and in spatio-temporal binding when serial events are delivered to the limbs. PMID:22768126

  1. 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

  2. Onset of spatio temporal disorder described by directed percolation

    NASA Astrophysics Data System (ADS)

    Wester, Tom; Traphan, Dominik; Gülker, Gerd; Peinke, Joachim; AG TWiSt Team

    2016-11-01

    The energy transport and mixing behavior of a fluid strongly depends on the state of the flow. These properties change drastically if the flow changes from laminar to turbulent state. This transition is a very complex and highly unsteady phenomenon, which is not fully understood up to now. The biggest problem is the characterization of the onset of spatio temporal disorder. This means that turbulent spots in the flow field irregularly spread or decay on their way downstream. In this presentation we will show that this critical behavior of turbulent spreading in the flow can be described by the directed percolation model. This approach was already used for a transitive channel flow, pipe flows or different couette flows. The charm of this model is the complete characterization of the whole transition with only a few unique exponents. In contrast to the majority of previous studies, the underlying data base of this study is acquired experimentally by high-speed Particle Image Velocimetry. Thus the evolving flow can be captured in a highly resolved spatio-temporal manner. In this way it is easily possible to determine the critical exponents which describe the transient area between laminar and turbulent flow. The results will be presented and compared to theoretical expectations. DAAD, DFG.

  3. Spatio-temporal distribution of global solar radiation for Mexico using GOES data

    NASA Astrophysics Data System (ADS)

    Bonifaz, R.; Cuahutle, M.; Valdes, M.; Riveros, D.

    2013-05-01

    Increased need of sustainable and renewable energies around the world requires studies about the amount and distribution of such types of energies. Global solar radiation distribution in space and time is a key component on order to know the availability of the energy for different applications. Using GOES hourly data, the heliosat model was implemented for Mexico. Details about the model and its components are discussed step by stem an once obtained the global solar radiation images, different time datasets (hourly, daily, monthly and seasonal) were built in order to know the spatio-temporal behavior of this type of energy. Preliminary maps of the available solar global radiation energy for Mexico are presented, the amount and variation of the solar radiation by regions are analyzed and discussed. Future work includes a better parametrization of the model using calibrated ground stations data and more use of more complex models for better results.

  4. Deciphering the spatio-temporal regulation of entry and progression through mitosis.

    PubMed

    Gheghiani, Lilia; Gavet, Olivier

    2014-02-01

    Mitosis has been studied since the early 1880s as a key event of the cell division cycle where remarkable changes in cellular architecture take place and ultimately lead to an equal segregation of duplicated chromosomes into two daughter cells. A detailed description of the complex and highly ordered cellular events taking place is now available. Many regulators involved in key steps including entry into mitosis, nuclear envelope breakdown, microtubule (MT) spindle formation, and chromosome attachment, as well as mitotic exit and cytokinesis, have also been identified. However, understanding the precise spatio-temporal contribution of each regulator in the cell reorganization process has been technically challenging. This review will focus on a number of recent advances in our understanding of the spatial distribution of protein activities and the temporal regulation of their activation and inactivation during entry and progression through mitosis by the use of intramolecular Förster resonance energy transfer (FRET)-based biosensors.

  5. Excitability of the Motor Cortex Ipsilateral to the Moving Body Side Depends on Spatio-Temporal Task Complexity and Hemispheric Specialization

    PubMed Central

    van den Berg, Femke E.; Swinnen, Stephan P.; Wenderoth, Nicole

    2011-01-01

    Unilateral movements are mainly controlled by the contralateral hemisphere, even though the primary motor cortex ipsilateral (M1ipsi) to the moving body side can undergo task-related changes of activity as well. Here we used transcranial magnetic stimulation (TMS) to investigate whether representations of the wrist flexor (FCR) and extensor (ECR) in M1ipsi would be modulated when unilateral rhythmical wrist movements were executed in isolation or in the context of a simple or difficult hand-foot coordination pattern, and whether this modulation would differ for the left versus right hemisphere. We found that M1ipsi facilitation of the resting ECR and FCR mirrored the activation of the moving wrist such that facilitation was higher when the homologous muscle was activated during the cyclical movement. We showed that this ipsilateral facilitation increased significantly when the wrist movements were performed in the context of demanding hand-foot coordination tasks whereas foot movements alone influenced the hand representation of M1ipsi only slightly. Our data revealed a clear hemispheric asymmetry such that MEP responses were significantly larger when elicited in the left M1ipsi than in the right. In experiment 2, we tested whether the modulations of M1ipsi facilitation, caused by performing different coordination tasks with the left versus right body sides, could be explained by changes in short intracortical inhibition (SICI). We found that SICI was increasingly reduced for a complex coordination pattern as compared to rest, but only in the right M1ipsi. We argue that our results might reflect the stronger involvement of the left versus right hemisphere in performing demanding motor tasks. PMID:21408031

  6. 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

  7. Spatio-temporal properties of letter crowding.

    PubMed

    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.

  8. 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

  9. 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

  10. Spatio-Temporal Interpolation Is Accomplished by Binocular Form and Motion Mechanisms

    PubMed Central

    Kandil, Farid I.; Lappe, Markus

    2007-01-01

    Spatio-temporal interpolation describes the ability of the visual system to perceive shapes as whole figures (Gestalts), even if they are moving behind narrow apertures, so that only thin slices of them meet the eye at any given point in time. The interpolation process requires registration of the form slices, as well as perception of the shape's global motion, in order to reassemble the slices in the correct order. The commonly proposed mechanism is a spatio-temporal motion detector with a receptive field, for which spatial distance and temporal delays are interchangeable, and which has generally been regarded as monocular. Here we investigate separately the nature of the motion and the form detection involved in spatio-temporal interpolation, using dichoptic masking and interocular presentation tasks. The results clearly demonstrate that the associated mechanisms for both motion and form are binocular rather than monocular. Hence, we question the traditional view according to which spatio-temporal interpolation is achieved by monocular first-order motion-energy detectors in favour of models featuring binocular motion and form detection. PMID:17327923

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

    PubMed

    Blangiardo, Marta; Cameletti, Michela; Baio, Gianluca; Rue, Håvard

    2013-12-01

    During the last three decades, Bayesian methods have developed greatly in the field of epidemiology. Their main challenge focusses around computation, but the advent of Markov Chain Monte Carlo methods (MCMC) and in particular of the WinBUGS software has opened the doors of Bayesian modelling to the wide research community. However model complexity and database dimension still remain a constraint. Recently the use of Gaussian random fields has become increasingly popular in epidemiology as very often epidemiological data are characterised by a spatial and/or temporal structure which needs to be taken into account in the inferential process. The Integrated Nested Laplace Approximation (INLA) approach has been developed as a computationally efficient alternative to MCMC and the availability of an R package (R-INLA) allows researchers to easily apply this method. In this paper we review the INLA approach and present some applications on spatial and spatio-temporal data.

  12. Spatial and spatio-temporal models with R-INLA.

    PubMed

    Blangiardo, Marta; Cameletti, Michela; Baio, Gianluca; Rue, Håvard

    2013-03-01

    During the last three decades, Bayesian methods have developed greatly in the field of epidemiology. Their main challenge focusses around computation, but the advent of Markov Chain Monte Carlo methods (MCMC) and in particular of the WinBUGS software has opened the doors of Bayesian modelling to the wide research community. However model complexity and database dimension still remain a constraint. Recently the use of Gaussian random fields has become increasingly popular in epidemiology as very often epidemiological data are characterised by a spatial and/or temporal structure which needs to be taken into account in the inferential process. The Integrated Nested Laplace Approximation (INLA) approach has been developed as a computationally efficient alternative to MCMC and the availability of an R package (R-INLA) allows researchers to easily apply this method. In this paper we review the INLA approach and present some applications on spatial and spatio-temporal data.

  13. 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.

  14. Spatio-temporal structure of hooded gull flocks.

    PubMed

    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.

  15. Spatio-temporal patterns of Campylobacter colonization in Danish broilers.

    PubMed

    Chowdhury, S; Themudo, G E; Sandberg, M; Ersbøll, A K

    2013-05-01

    Despite a number of risk-factor studies in different countries, the epidemiology of Campylobacter colonization in broilers, particularly spatial dependencies, is still not well understood. A series of analyses (visualization and exploratory) were therefore conducted in order to obtain a better understanding of the spatial and temporal distribution of Campylobacter in the Danish broiler population. In this study, we observed a non-random temporal occurrence of Campylobacter, with high prevalence during summer and low during winter. Significant spatio-temporal clusters were identified in the same areas in the summer months from 2007 to 2009. Range of influence between broiler farms were estimated at distances of 9.6 km and 13.5 km in different years. Identification of areas and time with greater risk indicates variable presence of risk factors with space and time. Implementation of safety measures on farms within high-risk clusters during summer could have an impact in reducing prevalence.

  16. 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.

  17. Spatio-Temporal Analysis of Forest Fire Risk and Danger Using LANDSAT Imagery

    PubMed Central

    Sağlam, Bülent; Bilgili, Ertuğrul; Durmaz, Bahar Dinç; Kadıoğulları, Ali İhsan; Küçük, Ömer

    2008-01-01

    Computing fire danger and fire risk on a spatio-temporal scale is of crucial importance in fire management planning, and in the simulation of fire growth and development across a landscape. However, due to the complex nature of forests, fire risk and danger potential maps are considered one of the most difficult thematic layers to build up. Remote sensing and digital terrain data have been introduced for efficient discrete classification of fire risk and fire danger potential. In this study, two time-series data of Landsat imagery were used for determining spatio-temporal change of fire risk and danger potential in Korudag forest planning unit in northwestern Turkey. The method comprised the following two steps: (1) creation of indices of the factors influencing fire risk and danger; (2) evaluation of spatio-temporal changes in fire risk and danger of given areas using remote sensing as a quick and inexpensive means and determining the pace of forest cover change. Fire risk and danger potential indices were based on species composition, stand crown closure, stand development stage, insolation, slope and, proximity of agricultural lands to forest and distance from settlement areas. Using the indices generated, fire risk and danger maps were produced for the years 1987 and 2000. Spatio-temporal analyses were then realized based on the maps produced. Results obtained from the study showed that the use of Landsat imagery provided a valuable characterization and mapping of vegetation structure and type with overall classification accuracy higher than 83%. PMID:27879918

  18. 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.

  19. 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.

  20. 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.

  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 variability in ventricular fibrillation

    NASA Astrophysics Data System (ADS)

    Hastings, Harold M.; Evans, Steven J.; Fenton, Flavio H.; Garfinkel, Alan

    2001-03-01

    It is widely believed that reentrant ventricular tachycardia arises when a spiral wave of activation takes over and drives the ventricle at a rate significantly faster than sinus rhythm, and that ventricular fibrillation (VF), a spatio-temporally disorganized form of cardiac activity leading to sudden cardiac death, arises when this spiral breaks down into multiple offspring. Many authors have found that VF displays significant spatial and temporal organization. The purpose of this research is to quantify time scales and temporal and spatial variability in VF. Surface electrograms were obtained from a stable canine model of VF (cf. Nwasokwa and Bodenheimer, Am. J. Physiol. 253, H643 (1987)). These electrograms were analyzed to identify activation times to an accuracy of 1 ms (cf. Garfinkel et al., J. Clin. Invest. 99, 305 (1997)), yielded eighteen usable series, each containing over 1024 intervactivation intervals, two or three from widely spaced sites per episode of VF, 7 total episodes in 4 animals. Spatial and long-term (60 - 120 sec) temporal variability were analyzed and compared by ANOVA techniques (Evans et al., Proc. Royal Soc. B265, 2167 (1998)). In 6 of 7 episodes, spatial variability among sites was statistically more significant than variability between the first and second halves of each series. More recently, Fourier analysis of these series found three distinct scaling regions, with power law dynamics in each and break points of ca. 1 sec and 4 sec. Finally, there was significant variability in the fraction of "short" interactivation intervals (lasting < 60 of 125 ms) among sites. Together these results suggest variability in physiological properties among sites and consequent variability in spiral wave dynamics among sites.

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

    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.

  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. 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.

  7. Spatio-temporal modeling of Active Layer Thickness

    NASA Astrophysics Data System (ADS)

    Touyz, J.; Apanasovich, T. V.; Streletskiy, D. A.; Shiklomanov, N. I.

    2015-12-01

    Arctic Regions are 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 climate and environmental changes and plays an important role in the functioning of Arctic ecosystems, planning, and economic activities. Knowledge about spatio-temporal variability of ALT is crucial for environmental and engineering applications. The objective of this study is to provide the methodology to model and estimate spatio-temporal variation in the active layer thickness (ALT) at several sites located in the Circumpolar region spanning the Alaska North Slope, and to demonstrate its use in spatio-temporal interpolation as well as time-forward prediction. In our data analysis we estimate a parametric trend and examine residuals for the presence of spatial and temporal dependence. We propose models that provide a description of residual space-time variability in ALT. Formulations that take into account interaction among spatial and temporal components are also developed. Moreover, we compare our models to naive models in which residual spatio-temporal and temporal correlations are not considered. The predicted root mean squared and absolute errors are significantly reduced when our approach is employed. While the methodology is developed in the context of ALT, it can also be applied to model and predict other environmental variables which use similar spatio-temporal sampling designs.

  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. 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.

  10. Computational EEG modelling of decision making under ambiguity reveals spatio-temporal dynamics of outcome evaluation.

    PubMed

    Jollans, Lee; Whelan, Robert; Venables, Louise; Turnbull, Oliver H; Cella, Matteo; Dymond, Simon

    2017-03-15

    Complex human cognition, such as decision-making under ambiguity, is reflected in dynamic spatio-temporal activity in the brain. Here, we combined event-related potentials with computational modelling of the time course of decision-making and outcome evaluation during the Iowa Gambling Task. Measures of choice probability generated using the Prospect Valence Learning Delta (PVL-Delta) model, in addition to objective trial outcomes (outcome magnitude and valence), were applied as regressors in a general linear model of the EEG signal. The resulting three-dimensional spatio-temporal characterization of task-related neural dynamics demonstrated that outcome valence, outcome magnitude, and PVL-Delta choice probability were expressed in distinctly separate event related potentials. Our findings showed that the P3 component was associated with an experience-based measure of outcome expectancy.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Spatio-temporal statistical models for river monitoring networks.

    PubMed

    Clement, L; Thas, O; Vanrolleghem, P A; Ottoy, J P

    2006-01-01

    When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.

  17. Spatio-temporal effects of low impact development practices

    NASA Astrophysics Data System (ADS)

    Gilroy, Kristin L.; McCuen, Richard H.

    2009-04-01

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

  18. 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.

  19. 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

  20. 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

    " adaptation) or over a 30-year period centred around the date considered ("prospective" adaptation). These adaptation scenarios are translated into local-scale transient drought thresholds, as opposed to a non-adaptation scenario where the drought threshold remains constant. The perceived spatio-temporal characteristics derived from the theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of local-scale adaptation and global-scale mitigation. This study thus proposes a proof of concept for using standardized drought indices for (1) assessing projections of spatio-temporal drought characteristics and (2) building theoretical adaptation scenarios and associated perceived changes in hydrological impact studies (Vidal et al., submitted). Vidal J.-P., Martin E., Franchistéguy L., Habets F., Soubeyroux J.-M., Blanchard M. & Baillon M. (2010) Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite. Hydrology and Earth System Sciences, 14, 459-478.doi: 10.5194/hess-14-459-2010 Vidal J.-P., Martin E., Kitova N., Najac J. & Soubeyroux, J. M. (submitted) Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios. Submitted to Hydrology and earth System Sciences

  1. The changing spatio-temporal dynamics of thaw lake development, Seward Peninsula, Alaska.

    NASA Astrophysics Data System (ADS)

    Cooper, Michael; Rees, Gareth; Bartsch, Annett

    2014-05-01

    study region; however, the core of this research relied upon the analysis of the changing lake morphology using visible and near-infrared spectra from MODIS and Landsat products. This research explored: (1) intra-annual variability of freeze-thaw cycles and resultant effects on thaw lake development; and (2) the spatio-temporal trends and changing dynamism of thaw lake activity. Research presented here within suggests that although climatic trends do indeed influence widespread changes within thaw lake characteristics, site-specific phenomena of sediment type and ice-content and fluvial activity also play integral roles. Understanding and observing changing spatio-temporal dynamics, particularly on an intra-annual basis, has helped to gather more information concerning complex lake processes, and increase the understanding of permafrost decay and thaw lake development.

  2. Spatio-temporal patterns of forest fires: a comprehensive application of the K-function

    NASA Astrophysics Data System (ADS)

    Tonini, Marj; Vega Orozco, Carmen; Kanevski, Mikhaïl; Conedera, Marco

    2013-04-01

    temporal cluster behaviour at the corresponding temporal scale t. For the analysis of the space-time clustering, we applied the spatio-temporal (bivariate) K-function K(r,t), which evaluates if events are closer in both space and time. Intuitively, if there is no space-time interaction K(r,t) = K(r) * K(t). Accordingly, if K(r,t) minus K(r) * K(t) is positive, this indicates an interaction between space and time in producing clusters, which arise from a well detectable spatial and temporal scales. This study allowed detecting: 1) the purely spatial and the purely temporal scales at which the registered forest fires events are clustered, given by the results of the K(r) and the K(t) computations; and 2) the time period where spatial clusters take place at a given distance scale, exhibited by the results of the K(r,t) computation. Key words: spatio-temporal sequences, cluster, Ripley's K-function, forest fires. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Bivand R., Rowlingson B., and Diggle P. (2012) - splancs package in R project - Diggle P., Chetwynd A., Haggkvist R. and Morris S. (1995) Second-order analysis of space-time clustering. Statistical Methods in Medical Research, vol. 4(2): 124-136. - R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/. - Vega Orozco C., Tonini M., Conedera M., Kanveski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, GeoInformatica, vol. 16(4): 653-673.

  3. 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.

  4. Spatio-temporal saliency perception via hypercomplex frequency spectral contrast.

    PubMed

    Li, Ce; Xue, Jianru; Zheng, Nanning; Lan, Xuguang; Tian, Zhiqiang

    2013-03-12

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

  5. 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…

  6. 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.

  7. 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.

  8. Spatio-temporal Laplacian pyramid coding for action recognition.

    PubMed

    Shao, Ling; Zhen, Xiantong; Tao, Dacheng; Li, Xuelong

    2014-06-01

    We present a novel descriptor, called spatio-temporal Laplacian pyramid coding (STLPC), for holistic representation of human actions. In contrast to sparse representations based on detected local interest points, STLPC regards a video sequence as a whole with spatio-temporal features directly extracted from it, which prevents the loss of information in sparse representations. Through decomposing each sequence into a set of band-pass-filtered components, the proposed pyramid model localizes features residing at different scales, and therefore is able to effectively encode the motion information of actions. To make features further invariant and resistant to distortions as well as noise, a bank of 3-D Gabor filters is applied to each level of the Laplacian pyramid, followed by max pooling within filter bands and over spatio-temporal neighborhoods. Since the convolving and pooling are performed spatio-temporally, the coding model can capture structural and motion information simultaneously and provide an informative representation of actions. The proposed method achieves superb recognition rates on the KTH, the multiview IXMAS, the challenging UCF Sports, and the newly released HMDB51 datasets. It outperforms state of the art methods showing its great potential on action recognition.

  9. 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.

  10. Video object tracking in the compressed domain using spatio-temporal Markov random fields.

    PubMed

    Khatoonabadi, Sayed Hossein; Bajić, Ivan V

    2013-01-01

    Despite the recent progress in both pixel-domain and compressed-domain video object tracking, the need for a tracking framework with both reasonable accuracy and reasonable complexity still exists. This paper presents a method for tracking moving objects in H.264/AVC-compressed video sequences using a spatio-temporal Markov random field (ST-MRF) model. An ST-MRF model naturally integrates the spatial and temporal aspects of the object's motion. Built upon such a model, the proposed method works in the compressed domain and uses only the motion vectors (MVs) and block coding modes from the compressed bitstream to perform tracking. First, the MVs are preprocessed through intracoded block motion approximation and global motion compensation. At each frame, the decision of whether a particular block belongs to the object being tracked is made with the help of the ST-MRF model, which is updated from frame to frame in order to follow the changes in the object's motion. The proposed method is tested on a number of standard sequences, and the results demonstrate its advantages over some of the recent state-of-the-art methods.

  11. 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.

  12. Health impact assessment of industrial development projects: a spatio-temporal visualization.

    PubMed

    Winkler, Mirko S; Krieger, Gary R; Divall, Mark J; Singer, Burton H; Utzinger, Jürg

    2012-05-01

    Development and implementation of large-scale industrial projects in complex eco-epidemiological settings typically require combined environmental, social and health impact assessments. We present a generic, spatio-temporal health impact assessment (HIA) visualization, which can be readily adapted to specific projects and key stakeholders, including poorly literate communities that might be affected by consequences of a project. We illustrate how the occurrence of a variety of complex events can be utilized for stakeholder communication, awareness creation, interactive learning as well as formulating HIA research and implementation questions. Methodological features are highlighted in the context of an iron ore development in a rural part of Africa.

  13. Effective and efficient analysis of spatio-temporal data

    NASA Astrophysics Data System (ADS)

    Zhang, Zhongnan

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

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

    SciTech Connect

    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 at 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.

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

    DOE PAGES

    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

  16. Spatio-Temporal Process Variability in Watershed Scale Wetland Restoration Planning

    NASA Astrophysics Data System (ADS)

    Evenson, G. R.

    2012-12-01

    Watershed scale restoration decision making processes are increasingly informed by quantitative methodologies providing site-specific restoration recommendations - sometimes referred to as "systematic planning." The more advanced of these methodologies are characterized by a coupling of search algorithms and ecological models to discover restoration plans that optimize environmental outcomes. Yet while these methods have exhibited clear utility as decision support toolsets, they may be critiqued for flawed evaluations of spatio-temporally variable processes fundamental to watershed scale restoration. Hydrologic and non-hydrologic mediated process connectivity along with post-restoration habitat dynamics, for example, are commonly ignored yet known to appreciably affect restoration outcomes. This talk will present a methodology to evaluate such spatio-temporally complex processes in the production of watershed scale wetland restoration plans. Using the Tuscarawas Watershed in Eastern Ohio as a case study, a genetic algorithm will be coupled with the Soil and Water Assessment Tool (SWAT) to reveal optimal wetland restoration plans as measured by their capacity to maximize nutrient reductions. Then, a so-called "graphical" representation of the optimization problem will be implemented in-parallel to promote hydrologic and non-hydrologic mediated connectivity amongst existing wetlands and sites selected for restoration. Further, various search algorithm mechanisms will be discussed as a means of accounting for temporal complexities such as post-restoration habitat dynamics. Finally, generalized patterns of restoration plan optimality will be discussed as an alternative and possibly superior decision support toolset given the complexity and stochastic nature of spatio-temporal process variability.

  17. Local Spatio-Temporal Analysis in Vision Systems

    DTIC Science & Technology

    1994-07-31

    evaluation, purchase and installation of a MasPar parallel computer. 14. SUBJECT TERMS 15. NUMBER OF PAGES 30 •ic QuaLlY INSPECTED 3 16. PRICE CODE 17...called "energy" models of spatio-temporal v!ion), and also in engineering analysis of digitized images (viz: the Fast Fourier Transform , which decomposes...nonstationary image data, and (when coupled with multiband/ wavelet decompositions) for the computation of symbolic descriptions of space-varying

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  19. 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.

  20. Spatio-temporal optimization of a laser produced Al-plasma: Generation of highly ionized species

    NASA Astrophysics Data System (ADS)

    Smijesh, N.; H. Rao, Kavya; Klemke, N.; Philip, R.; Litvinyuk, I. V.; Sang, R. T.

    2016-11-01

    Laser produced plasmas are transient in nature, and their properties, which depend on the laser parameters as well as the material properties and the irradiation conditions, can be tailored for different applications. Highly ionized Al plasmas generated using 7 ns and negatively chirped 60 ps pulses are optimized for the purpose of generating Al IV and Al III, respectively. The plasma is optimized spatio-temporally for Al IV or Al III with irradiation energy as the control parameter using time-resolved optical emission spectroscopy. Plasmas attuned for higher charged states could be utilized as a good alternative source for the generation of high order harmonics.

  1. 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

  2. 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

  3. Spatio-temporal Dependency of Extremes: Some Results and a Study on Indian Summer Precipitation Data

    NASA Astrophysics Data System (ADS)

    Chatterjee, S.

    2015-12-01

    Observations over spatial, temporal and spatiotemporal grids are expected to have statistical dependencies, and modeling to account for such dependencies adds complexity, but not necessarily value, in many cases of climate and other data analyses. Sometimes however, there may not be any additional dependency beyond what can be accounted for using covariates and fixed and random effects. Additionally, dependency patterns may not besimilar for different quantities of interest, for example, the dependency properties while modeling for a mean may not be the same as those obtained while modeling an extreme quantile. Thus, there is a need to quantify the degree of dependency, and test for different hypotheses including that of a lack of dependency, or structured patterns of dependency. We study a classical Space-Time Index measure suggested for testing spatio-temporal associations and show that it has low power in hypothesis tests and is generally unreliable. Newer, computation-driven statistical and machine learning methods for quantifying and testing dependency patterns are presented, and some of their statistical properties are studied in detail. We conduct a study of spatio-temporal dependency in Indiansummer precipitation data, and particularly the properties of extreme precipitation during Indian monsoons. As expected, we find that the nature of extreme precipitations depend on some global and some local climate features. However, the spatio-temporal relationship between extreme precipitation events depends additionally on the threshold used to define an extreme event. This may be leveraged for a more precise modeling of extreme events, and for reducing uncertainty in predicting such events.

  4. Spatio-temporal Modeling of Mosquito Distribution

    NASA Astrophysics Data System (ADS)

    Dumont, Y.; Dufourd, C.

    2011-11-01

    We consider a quasilinear parabolic system to model mosquito displacement. In order to use efficiently vector control tools, like insecticides, and mechanical control, it is necessary to provide density estimates of mosquito populations, taking into account the environment and entomological knowledges. After a brief introduction to mosquito dispersal modeling, we present some theoretical results. Then, considering a compartmental approach, we get a quasilinear system of PDEs. Using the time splitting approach and appropriate numerical methods for each operator, we construct a reliable numerical scheme. Considering vector control scenarii, we show that the environment can have a strong influence on mosquito distribution and in the efficiency of vector control tools.

  5. Spatio-Temporal Variation in Landscape Composition May Speed Resistance Evolution of Pests to Bt Crops.

    PubMed

    Ives, Anthony R; Paull, Cate; Hulthen, Andrew; Downes, Sharon; Andow, David A; Haygood, Ralph; Zalucki, Myron P; Schellhorn, Nancy A

    2017-01-01

    Transgenic crops that express insecticide genes from Bacillus thuringiensis (Bt) are used worldwide against moth and beetle pests. Because these engineered plants can kill over 95% of susceptible larvae, they can rapidly select for resistance. Here, we use a model for a pyramid two-toxin Bt crop to explore the consequences of spatio-temporal variation in the area of Bt crop and non-Bt refuge habitat. We show that variability over time in the proportion of suitable non-Bt breeding habitat, Q, or in the total area of Bt and suitable non-Bt habitat, K, can increase the overall rate of resistance evolution by causing short-term surges of intense selection. These surges can be exacerbated when temporal variation in Q and/or K cause high larval densities in refuges that increase density-dependent mortality; this will give resistant larvae in Bt fields a relative advantage over susceptible larvae that largely depend on refuges. We address the effects of spatio-temporal variation in a management setting for two bollworm pests of cotton, Helicoverpa armigera and H. punctigera, and field data on landscape crop distributions from Australia. Even a small proportion of Bt fields available to egg-laying females when refuges are sparse may result in high exposure to Bt for just a single generation per year and cause a surge in selection. Therefore, rapid resistance evolution can occur when Bt crops are rare rather than common in the landscape. These results highlight the need to understand spatio-temporal fluctuations in the landscape composition of Bt crops and non-Bt habitats in order to design effective resistance management strategies.

  6. 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.

  7. Spatio-Temporal Variation in Landscape Composition May Speed Resistance Evolution of Pests to Bt Crops

    PubMed Central

    Ives, Anthony R.; Paull, Cate; Hulthen, Andrew; Downes, Sharon; Andow, David A.; Haygood, Ralph; Zalucki, Myron P.; Schellhorn, Nancy A.

    2017-01-01

    Transgenic crops that express insecticide genes from Bacillus thuringiensis (Bt) are used worldwide against moth and beetle pests. Because these engineered plants can kill over 95% of susceptible larvae, they can rapidly select for resistance. Here, we use a model for a pyramid two-toxin Bt crop to explore the consequences of spatio-temporal variation in the area of Bt crop and non-Bt refuge habitat. We show that variability over time in the proportion of suitable non-Bt breeding habitat, Q, or in the total area of Bt and suitable non-Bt habitat, K, can increase the overall rate of resistance evolution by causing short-term surges of intense selection. These surges can be exacerbated when temporal variation in Q and/or K cause high larval densities in refuges that increase density-dependent mortality; this will give resistant larvae in Bt fields a relative advantage over susceptible larvae that largely depend on refuges. We address the effects of spatio-temporal variation in a management setting for two bollworm pests of cotton, Helicoverpa armigera and H. punctigera, and field data on landscape crop distributions from Australia. Even a small proportion of Bt fields available to egg-laying females when refuges are sparse may result in high exposure to Bt for just a single generation per year and cause a surge in selection. Therefore, rapid resistance evolution can occur when Bt crops are rare rather than common in the landscape. These results highlight the need to understand spatio-temporal fluctuations in the landscape composition of Bt crops and non-Bt habitats in order to design effective resistance management strategies. PMID:28046073

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

    DOE PAGES

    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

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2013-04-01

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

  11. 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

  12. 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.

  13. Spatio-Temporal Waveform Design for Multiuser Massive MIMO Downlink With 1-bit Receivers

    NASA Astrophysics Data System (ADS)

    Gokceoglu, Ahmet; Bjornson, Emil; Larsson, Erik G.; Valkama, Mikko

    2017-03-01

    Internet-of-Things (IoT) refers to a high-density network of low-cost low-bitrate terminals and sensors where also low energy consumption is one central feature. As the power-budget of classical receiver chains is dominated by the high-resolution analog-to-digital converters (ADCs), there is a growing interest towards deploying receiver architectures with reduced-bit or even 1-bit ADCs. In this paper, we study waveform design, optimization and detection aspects of multi-user massive MIMO downlink where user terminals adopt very simple 1-bit ADCs with oversampling. In order to achieve spectral efficiency higher than 1 bit/s/Hz per real-dimension, we propose a two-stage precoding, namely a novel quantization precoder followed by maximum-ratio transmission (MRT) or zero-forcing (ZF) type spatial channel precoder which jointly form the multi-user-multiantenna transmit waveform. The quantization precoder outputs are optimized, under appropriate transmitter and receiver filter bandwidth constraints, to provide controlled inter-symbol-interference (ISI) enabling the input symbols to be uniquely detected from 1-bit quantized observations with a low-complexity symbol detector in the absence of noise. An additional optimization constraint is also imposed in the quantization precoder design to increase the robustness against noise and residual inter-user-interference (IUI). The purpose of the spatial channel precoder, in turn, is to suppress the IUI and provide high beamforming gains such that good symbol-error rates (SERs) can be achieved in the presence of noise and interference. Extensive numerical evaluations illustrate that the proposed spatio-temporal precoder based multiantenna waveform design can facilitate good multi-user link performance, despite the extremely simple 1-bit ADCs in the receivers, hence being one possible enabling technology for the future low-complexity IoT networks.

  14. Sparse Representation with Spatio-Temporal Online Dictionary Learning for Efficient Video Coding.

    PubMed

    Dai, Wenrui; Shen, Yangmei; Tang, Xin; Zou, Junni; Xiong, Hongkai; Chen, Chang Wen

    2016-07-27

    Classical dictionary learning methods for video coding suer from high computational complexity and interfered coding eciency by disregarding its underlying distribution. This paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to speed up the convergence rate of dictionary learning with a guarantee of approximation error. The proposed algorithm incorporates stochastic gradient descents to form a dictionary of pairs of 3-D low-frequency and highfrequency spatio-temporal volumes. In each iteration of the learning process, it randomly selects one sample volume and updates the atoms of dictionary by minimizing the expected cost, rather than optimizes empirical cost over the complete training data like batch learning methods, e.g. K-SVD. Since the selected volumes are supposed to be i.i.d. samples from the underlying distribution, decomposition coecients attained from the trained dictionary are desirable for sparse representation. Theoretically, it is proved that the proposed STOL could achieve better approximation for sparse representation than K-SVD and maintain both structured sparsity and hierarchical sparsity. It is shown to outperform batch gradient descent methods (K-SVD) in the sense of convergence speed and computational complexity, and its upper bound for prediction error is asymptotically equal to the training error. With lower computational complexity, extensive experiments validate that the STOL based coding scheme achieves performance improvements than H.264/AVC or HEVC as well as existing super-resolution based methods in ratedistortion performance and visual quality.

  15. Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

    NASA Astrophysics Data System (ADS)

    Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

    2016-06-01

    For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    The intracellular release of calcium from the endoplasmic reticulum is controlled by ion channels. The resulting calcium signals exhibit a rich spatio-temporal signature, which originates at least partly from microscopic fluctuations. While stochasticity in the gating transition of ion channels has been incorporated into many models, the distribution of calcium is usually described by deterministic reaction-diffusion equations. Here we test the validity of the latter modeling approach by using two different models to calculate the frequency of localized calcium signals (calcium puffs) from clustered IP3 receptor channels. The complexity of the full calcium system is here limited to the basic opening mechanism of the ion channels and, in the mathematical reduction simplifies to the calculation of a first passage time. Two models are then studied: (i) a hybrid model, where channel gating is treated stochastically, while calcium concentration is deterministic and (ii) a fully stochastic model with noisy channel gating and Brownian calcium ion motion. The second model utilises the recently developed two-regime method [M. B. Flegg, S. J. Chapman, and R. Erban, "The two-regime method for optimizing stochastic reaction-diffusion simulations," J. R. Soc., Interface 9, 859-868 (2012)], 10.1098/rsif.2011.0574 in order to simulate a large domain with precision required only near the Ca2+ absorbing channels. The expected time for a first channel opening that results in a calcium puff event is calculated. It is found that for a large diffusion constant, predictions of the interpuff time are significantly overestimated using the model (i) with a deterministic non-spatial calcium variable. It is thus demonstrated that the presence of diffusive noise in local concentrations of intracellular Ca2+ ions can substantially influence the occurrence of calcium signals. The presented approach and results may also be relevant for other cell-physiological first-passage time problems with

  18. A Spatio-Temporal Atlas of the Human Fetal Brain with Application to Tissue Segmentation

    PubMed Central

    Habas, Piotr A.; Kim, Kio; Rousseau, Francois; Glenn, Orit A.; Barkovich, A. James; Studholme, Colin

    2012-01-01

    Modeling and analysis of MR images of the early developing human brain is a challenge because of the transient nature of different tissue classes during brain growth. To address this issue, a statistical model that can capture the spatial variation of structures over time is needed. Here, we present an approach to building a spatio-temporal model of tissue distribution in the developing brain which can incorporate both developed tissues as well as transient tissue classes such as the germinal matrix by using constrained higher order polynomial models. This spatio-temporal model is created from a set of manual segmentations through groupwise registration and voxelwise non-linear modeling of tissue class membership, that allows us to represent the appearance as well as disappearance of the transient brain structures over time. Applying this model to atlas-based segmentation, we generate age-specific tissue probability maps and use them to initialize an EM segmentation of the fetal brain tissues. The approach is evaluated using clinical MR images of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. Results indicate improvement in performance of atlas-based EM segmentation provided by higher order temporal models that capture the variation of tissue occurrence over time. PMID:20425999

  19. 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

  20. Large scale stochastic spatio-temporal modelling with PCRaster

    NASA Astrophysics Data System (ADS)

    Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.

    2013-04-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model builders as Python functions. The software comes with Python framework classes providing control flow for spatio-temporal modelling, Monte Carlo simulation, and data assimilation (Ensemble Kalman Filter and Particle Filter). Models are built by combining the spatial operations in these framework classes. This approach enables modellers without specialist programming experience to construct large, rather complicated models, as many technical details of modelling (e.g., data storage, solving spatial operations, data assimilation algorithms) are taken care of by the PCRaster toolbox. Exploratory modelling is supported by routines for prompt, interactive visualisation of stochastic spatio-temporal data generated by the models. The high computational requirements for stochastic spatio-temporal modelling, and an increasing demand to run models over large areas at high resolution, e.g. in global hydrological modelling, require an optimal use of available, heterogeneous computing resources by the modelling framework. Current work in the context of the eWaterCycle project is on a parallel implementation of the modelling engine, capable of running on a high-performance computing infrastructure such as clusters and supercomputers. Model runs will be distributed over multiple compute nodes and multiple processors (GPUs and CPUs). Parallelization will be done by parallel execution of Monte Carlo realizations and sub regions of the modelling domain. In our approach we use multiple levels of parallelism, improving scalability considerably. On the node level we will use OpenCL, the industry standard for low-level high performance computing kernels. To combine multiple nodes we will use

  1. 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.

  2. Tracking pedestrians using local spatio-temporal motion patterns in extremely crowded scenes.

    PubMed

    Kratz, Louis; Nishino, Ko

    2012-05-01

    Tracking pedestrians is a vital component of many computer vision applications, including surveillance, scene understanding, and behavior analysis. Videos of crowded scenes present significant challenges to tracking due to the large number of pedestrians and the frequent partial occlusions that they produce. The movement of each pedestrian, however, contributes to the overall crowd motion (i.e., the collective motions of the scene's constituents over the entire video) that exhibits an underlying spatially and temporally varying structured pattern. In this paper, we present a novel Bayesian framework for tracking pedestrians in videos of crowded scenes using a space-time model of the crowd motion. We represent the crowd motion with a collection of hidden Markov models trained on local spatio-temporal motion patterns, i.e., the motion patterns exhibited by pedestrians as they move through local space-time regions of the video. Using this unique representation, we predict the next local spatio-temporal motion pattern a tracked pedestrian will exhibit based on the observed frames of the video. We then use this prediction as a prior for tracking the movement of an individual in videos of extremely crowded scenes. We show that our approach of leveraging the crowd motion enables tracking in videos of complex scenes that present unique difficulty to other approaches.

  3. 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

  4. Measuring spatio-temporal parameters of uphill ski-mountaineering with ski-fixed inertial sensors.

    PubMed

    Fasel, Benedikt; Praz, Caroline; Kayser, Bengt; Aminian, Kamiar

    2016-09-06

    In this study an algorithm designed for the diagonal stride in classical cross-country skiing was adapted to compute spatio-temporal parameters for uphill ski mountaineering using a ski fixed inertial sensor. Cycle duration, thrust duration, cycle speed, cycle distance, elevation gain, and slope angle were computed and validated against a marker-based motion capture system during indoor treadmill skiing. Skiing movement of 12 experienced, recreational level athletes was measured for nine different speed and slope angle combinations. The accuracy (i.e. mean error) and precision (i.e. standard deviation of the error) were below 3ms and 13ms for the cycle duration and thrust duration, respectively. Accuracy (precision) for cycle speed, cycle distance and elevation gain were -0.013m/s (0.032m/s), -0.027m (0.018m), and 0.006m (0.011m), respectively. Slope angle accuracy and precision were 0.40° and 0.32°, respectively. If the cross-country skiing algorithm would be used without adaptations, errors would be up to one order of magnitude larger. The adapted algorithm proved valid for measuring spatio-temporal parameters for ski-mountaineering on treadmill. It is expected that the algorithm shows similar performance on snow.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

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

    PubMed Central

    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. PMID:24463569

  7. Emergence of oscillations and spatio-temporal coherence states in a continuum-model of excitatory and inhibitory neurons.

    PubMed

    Sabatini, Silvio P; Solari, Fabio; Secchi, Luca

    2005-01-01

    A neural field model of the reaction-diffusion type for the emergence of oscillatory phenomena in visual cortices is proposed. To investigate the joint spatio-temporal oscillatory dynamics in a continuous distribution of excitatory and inhibitory neurons, the coupling among oscillators is modelled as a diffusion process, combined with non-linear point interactions. The model exhibits cooperative activation properties in both time and space, by reacting to volleys of activations at multiple cortical sites with ordered spatio-temporal oscillatory states, similar to those found in the physiological experiments on slow-wave field potentials. The possible use of the resulting spatial distributions of coherent states, as a flexible medium to establish feature association, is discussed.

  8. Batch processing of overlapping molecular spectra as a tool for spatio-temporal diagnostics of power modulated microwave plasma jet

    NASA Astrophysics Data System (ADS)

    Voráč, Jan; Synek, Petr; Potočňáková, Lucia; Hnilica, Jaroslav; Kudrle, Vít

    2017-02-01

    Power modulated microwave plasma jet operating in argon at atmospheric pressure was studied by spatio-temporally resolved optical emission spectroscopy (OES) in order to clarify the influence of modulation on plasma parameters. OES was carried out in OH, NH, N2 and {{{N}}}2+ spectral regions using a spectrometer with intensified CCD detector synchronised with 101–103 Hz sine modulating signal. A special software, able to fit even the overlapping spectra, was developed to batch process the massive datasets produced by this spatio-temporal study. Results show that studied species with the exception of {{{N}}}2+ have balanced rotational and vibrational temperatures across the modulation frequencies. Significant influence of modulation can be clearly observed on temperature spatial gradients. Whereas for low modulation frequencies where the temperatures reach sharp maxima upon discharge tip, the high frequency modulation produces thermally homogeneous plasma.

  9. Spatio-temporal Linear Stability Analysis of Multiple Reacting Wakes

    NASA Astrophysics Data System (ADS)

    Kunnumpuram Sebastian, Jacob; Emerson, Benjamin; Lieuwen, Tim

    2016-11-01

    Hydrodynamic stability of reacting shear flows plays a key role in controlling a variety of combustor behaviors, such as combustion instability, mixing and entrainment, and blowoff. A significant literature exists on the hydrodynamics of single bluff body flows, but not the multi-bluff body flows that are found in applications. The objective of this work was to compare the spatio-temporal stability of multiple reacting wakes and single reacting wakes, within the framework of linear stability theory. Spatio-temporal stability analyses are conducted on model velocity and density profiles, with key parameters being the density ratio across the flame, bluff body spacing, dimensionless shear, and asymmetry parameters (if the two wakes are dissimilar). The introduction of the additional bluff body can exert both a stabilizing and destabilizing effect on the combined two-wake system, depending on the spatial separation between the bluff bodies. Furthermore, while the most rapidly amplified mode of the single wake mode is the sinuous (asymmetric) one, in the two wake system, the most rapidly amplified mode can be either sinuous or varicose (symmetric), also depending on spatial separation.

  10. Perception of oppositely moving verniers and spatio-temporal interpolation.

    PubMed

    Fahle, M

    1995-04-01

    Even at moderate speeds, moving objects stimulate many retinal photoreceptors within the integration time of the receptors, yet usually no motion blur is experienced. An elegant model for the elimination of motion blur was proposed by Anderson and van Essen [(1987) Proceedings of the National Academy of Science U.S.A., 84, 6297-6301]. These authors suggested that so-called shifter circuits shift the neuronal representation of retinal images on their way to the cortex. The retinal image of an object moving in the outer world is thus shifted in the opposite direction to the object motion, and the cortical representation of objects would be stable at least during short periods of time. To test the hypothesis of "shifter circuits", I measured thresholds for two vernier stimuli, moving simultaneously into opposite directions over identical parts of the retina. Motion blur for these stimuli was not stronger than with a single moving stimulus, and thresholds for the detection of vernier offsets could be below a photoreceptor diameter. This finding poses serious problems for the hypothesis of shifter circuits, since shifter circuits would be able to stabilize only one of the stimuli. In additional experiments, stimuli moved discontinuously, requiring spatio-temporal interpolation for the perception of smooth motion. The results are consistent with those obtained with continuous motion. Precision of spatio-temporal interpolation is in the hyperacuity range even for stimuli moving in opposite directions over the same small part of the visual field.

  11. Regularized feature reconstruction for spatio-temporal saliency detection.

    PubMed

    Ren, Zhixiang; Gao, Shenghua; Chia, Liang-Tien; Rajan, Deepu

    2013-08-01

    Multimedia applications such as image or video retrieval, copy detection, and so forth can benefit from saliency detection, which is essentially a method to identify areas in images and videos that capture the attention of the human visual system. In this paper, we propose a new spatio-temporal saliency detection framework on the basis of regularized feature reconstruction. Specifically, for video saliency detection, both the temporal and spatial saliency detection are considered. For temporal saliency, we model the movement of the target patch as a reconstruction process using the patches in neighboring frames. A Laplacian smoothing term is introduced to model the coherent motion trajectories. With psychological findings that abrupt stimulus could cause a rapid and involuntary deployment of attention, our temporal model combines the reconstruction error, regularizer, and local trajectory contrast to measure the temporal saliency. For spatial saliency, a similar sparse reconstruction process is adopted to capture the regions with high center-surround contrast. Finally, the temporal saliency and spatial saliency are combined together to favor salient regions with high confidence for video saliency detection. We also apply the spatial saliency part of the spatio-temporal model to image saliency detection. Experimental results on a human fixation video dataset and an image saliency detection dataset show that our method achieves the best performance over several state-of-the-art approaches.

  12. 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.

  13. 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

  14. Analysing Spatio-Temporal Clustering of Meningococcal Meningitis Outbreaks in Niger Reveals Opportunities for Improved Disease Control

    PubMed Central

    Paireau, Juliette; Girond, Florian; Collard, Jean-Marc; Maïnassara, Halima B.; Jusot, Jean-François

    2012-01-01

    Background Meningococcal meningitis is a major health problem in the “African Meningitis Belt” where recurrent epidemics occur during the hot, dry season. In Niger, a central country belonging to the Meningitis Belt, reported meningitis cases varied between 1,000 and 13,000 from 2003 to 2009, with a case-fatality rate of 5–15%. Methodology/Principal Findings In order to gain insight in the epidemiology of meningococcal meningitis in Niger and to improve control strategies, the emergence of the epidemics and their diffusion patterns at a fine spatial scale have been investigated. A statistical analysis of the spatio-temporal distribution of confirmed meningococcal meningitis cases was performed between 2002 and 2009, based on health centre catchment areas (HCCAs) as spatial units. Anselin's local Moran's I test for spatial autocorrelation and Kulldorff's spatial scan statistic were used to identify spatial and spatio-temporal clusters of cases. Spatial clusters were detected every year and most frequently occurred within nine southern districts. Clusters most often encompassed few HCCAs within a district, without expanding to the entire district. Besides, strong intra-district heterogeneity and inter-annual variability in the spatio-temporal epidemic patterns were observed. To further investigate the benefit of using a finer spatial scale for surveillance and disease control, we compared timeliness of epidemic detection at the HCCA level versus district level and showed that a decision based on threshold estimated at the HCCA level may lead to earlier detection of outbreaks. Conclusions/Significance Our findings provide an evidence-based approach to improve control of meningitis in sub-Saharan Africa. First, they can assist public health authorities in Niger to better adjust allocation of resources (antibiotics, rapid diagnostic tests and medical staff). Then, this spatio-temporal analysis showed that surveillance at a finer spatial scale (HCCA) would be more

  15. Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

  16. 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.

  17. Discussion on spatio-temporal data model of mining-land use change

    NASA Astrophysics Data System (ADS)

    Liu, Chang-Hua; Zhang, Hou-Tian; Wang, Shi-Dong

    2009-12-01

    To build and apply Temporal Geographic Information System (TGIS), to manage mining land spatio-temporal data is a key research aspect for present production administration and ecological environment protection. Spatio-temporal database, whose foundation is spatio-temporal data model, is the core of TGIS. Considering the feature of land use to change, this paper builds up a model of mining land spatio-temporal data based on ground-state amended model with some improvements. This data model stores space information and time information of mining land in spatial database. From judging the spatio-temporal information in historical and current database, the land use situation at different historical period can be recurred very conveniently. At the same time, the mutual transforming situation among lands at different periods can be educed from overlaying the lands by use of the related analyzed function of GIS. Accordingly, that will give an important reference to open out the rule of mining land evolution.

  18. Spatio-temporal population estimates for risk management

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Accurate estimation of population at risk from hazards and effective emergency management of events require not just appropriate spatio-temporal modelling of hazards but also of population. While much recent effort has been focused on improving the modelling and predictions of hazards (both natural and anthropogenic), there has been little parallel advance in the measurement or modelling of population statistics. Different hazard types occur over diverse temporal cycles, are of varying duration and differ significantly in their spatial extent. Even events of the same hazard type, such as flood events, vary markedly in their spatial and temporal characteristics. Conceptually and pragmatically then, population estimates should also be available for similarly varying spatio-temporal scales. Routine population statistics derived from traditional censuses or surveys are usually static representations in both space and time, recording people at their place of usual residence on census/survey night and presenting data for administratively defined areas. Such representations effectively fix the scale of population estimates in both space and time, which is unhelpful for meaningful risk management. Over recent years, the Pop24/7 programme of research, based at the University of Southampton (UK), has developed a framework for spatio-temporal modelling of population, based on gridded population surfaces. Based on a data model which is fully flexible in terms of space and time, the framework allows population estimates to be produced for any time slice relevant to the data contained in the model. It is based around a set of origin and destination centroids, which have capacities, spatial extents and catchment areas, all of which can vary temporally, such as by time of day, day of week, season. A background layer, containing information on features such as transport networks and landuse, provides information on the likelihood of people being in certain places at specific times

  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. Entropy quantification of human brain spatio-temporal dynamics

    NASA Astrophysics Data System (ADS)

    Pezard, Laurent; Martinerie, Jacques; Müller-Gerking, Johannes; Varela, Francisco J.; Renault, Bernard

    We present a procedure to quantify spatio-temporal dynamics applied here to brain surface recordings during three distinct cognitive tasks. The method uses 19 sites of EEG recording as spatial embedding for the reconstruction of trajectories, global and local linear indices, and non-linear forecasting methods to quantify the global and local information loss of the dynamics (K-entropy). We show that K-entropy can differentiate between raw and multivariate phase random surrogate data in a significant percentage of EEG segments, and that relevant non-linear indices are best studied in time segments not longer than 4s. We also find a certain complementarity between local non-linear and linear indices for the discrimination between the three cognitive tasks. Moreover, localized projections onto electrode site of K-entropy provide a new kind of brain mapping with functional significance.

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

    PubMed

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

    2015-01-01

    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.

  2. 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

  3. 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.

  4. 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

  5. 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

  6. Taxis of Artificial Swimmers in a Spatio-Temporally Modulated Activation Medium

    NASA Astrophysics Data System (ADS)

    Geiseler, Alexander; Hänggi, Peter; Marchesoni, Fabio

    2017-03-01

    Contrary to microbial taxis, where a tactic response to external stimuli is controlled by complex chemical pathways acting like sensor-actuator loops, taxis of artificial microswimmers is a purely stochastic effect associated with a non-uniform activation of the particles' self-propulsion. We study the tactic response of such swimmers in a spatio-temporally modulated activating medium by means of both numerical and analytical techniques. In the opposite limits of very fast and very slow rotational particle dynamics, we obtain analytic approximations that closely reproduce the numerical description. A swimmer drifts on average either parallel or anti-parallel to the propagation direction of the activating pulses, depending on their speed and width. The drift in line with the pulses is solely determined by the finite persistence length of the active Brownian motion performed by the swimmer, whereas the drift in the opposite direction results from the combination of ballistic and diffusive properties of the swimmer's dynamics.

  7. 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.

  8. 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

  9. 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.

  10. Spatio-temporal variability of faunal and floral assemblages in Mediterranean temporary wetlands.

    PubMed

    Rouissi, Maya; Boix, Dani; Muller, Serge D; Gascón, Stéphanie; Ruhí, Albert; Sala, Jordi; Bouattour, Ali; Ben Haj Jilani, Imtinen; Ghrabi-Gammar, Zeineb; Ben Saad-Limam, Samia; Daoud-Bouattour, Amina

    2014-12-01

    Six temporary wetlands in the region of Sejenane (Mogods, NW Tunisia) were studied in order to characterize the aquatic flora and fauna and to quantify their spatio-temporal variability. Samplings of aquatic fauna, phytosociological relevés, and measurements of the physicochemical parameters of water were taken during four different field visits carried out during the four seasons of the year (November 2009-July 2010). Despite the strong anthropic pressures on them, these temporary wetlands are home to rich and diversified biodiversity, including rare and endangered species. Spatial and temporal variations affect fauna and flora differently, as temporal variability influences the fauna rather more than the plants, which are relatively more dependent on spatial factors. These results demonstrate the interest of small water bodies for maintaining biodiversity at the regional level, and thus underscore the conservation issues of Mediterranean temporary wetlands that are declining on an ongoing basis currently.

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  12. A spatio-temporal mining approach towards summarizing and analyzing protein folding trajectories.

    PubMed

    Yang, Hui; Parthasarathy, Srinivasan; Ucar, Duygu

    2007-04-04

    Understanding the protein folding mechanism remains a grand challenge in structural biology. In the past several years, computational theories in molecular dynamics have been employed to shed light on the folding process. Coupled with high computing power and large scale storage, researchers now can computationally simulate the protein folding process in atomistic details at femtosecond temporal resolution. Such simulation often produces a large number of folding trajectories, each consisting of a series of 3D conformations of the protein under study. As a result, effectively managing and analyzing such trajectories is becoming increasingly important. In this article, we present a spatio-temporal mining approach to analyze protein folding trajectories. It exploits the simplicity of contact maps, while also integrating 3D structural information in the analysis. It characterizes the dynamic folding process by first identifying spatio-temporal association patterns in contact maps, then studying how such patterns evolve along a folding trajectory. We demonstrate that such patterns can be leveraged to summarize folding trajectories, and to facilitate the detection and ordering of important folding events along a folding path. We also show that such patterns can be used to identify a consensus partial folding pathway across multiple folding trajectories. Furthermore, we argue that such patterns can capture both local and global structural topology in a 3D protein conformation, thereby facilitating effective structural comparison amongst conformations. We apply this approach to analyze the folding trajectories of two small synthetic proteins-BBA5 and GSGS (or Beta3S). We show that this approach is promising towards addressing the above issues, namely, folding trajectory summarization, folding events detection and ordering, and consensus partial folding pathway identification across trajectories.

  13. Quantifying Uncertainty in Spatio-temporal Forest Composition Changes Inferred from Fossil Pollen Records

    NASA Astrophysics Data System (ADS)

    Dawson, A.; Paciorek, C. J.; McLachlan, J. S.; Goring, S. J.; Williams, J. W.; Jackson, S. T.

    2014-12-01

    Understanding past compositional changes in vegetation provides insight about ecosystem dynamics in response to changing environments. Past vegetation reconstructions rely predominantly on fossil pollen data from sedimentary lake cores, which acts as a proxy record for the surrounding vegetation. Stratigraphic changes in these pollen records allow us to infer changes in composition and species distributions. Pollen records collected from a network of sites allow us to make inference about the spatio-temporal changes in vegetation over thousands of years. However, the complexity of the relationship between pollen deposits and surrounding vegetation, as well as the spatially sparse set of fossil pollen sites are important sources of uncertainty. In addition, uncertainty arises from the carbon dating and age-depth modelling processes. To reconstruct vegetation composition including uncertainty for the Upper Midwestern USA, we build a Bayesian hierarchical model that links vegetation composition to fossil pollen data via a dispersal model. In the calibration phase, we estimate the relationship between vegetation and pollen for the settlement era using Public Land Survey data and a network of pollen records. In the prediction phase, parameter estimates obtained during the calibration phase are used to estimate latent species distributions and relative abundances over the last 2500 years. We account for additional uncertainty in the pollen records by: allowing expert palynologists to identify pre-settlement pollen samples to be included in our calibration data, and through the incorporation of age uncertainty obtained from the Bayesian age-depth model BACON in our prediction data. Resulting spatio-temporal composition and abundance estimates will be used to improve forecasting capabilities of ecosystem models.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. Localized Spatio-Temporal Constraints for Accelerated CMR Perfusion

    PubMed Central

    Akçakaya, Mehmet; Basha, Tamer A.; Pflugi, Silvio; Foppa, Murilo; Kissinger, Kraig V.; Hauser, Thomas H.; Nezafat, Reza

    2013-01-01

    Purpose To develop and evaluate an image reconstruction technique for cardiac MRI (CMR)perfusion that utilizes localized spatio-temporal constraints. Methods CMR perfusion plays an important role in detecting myocardial ischemia in patients with coronary artery disease. Breath-hold k-t based image acceleration techniques are typically used in CMR perfusion for superior spatial/temporal resolution, and improved coverage. In this study, we propose a novel compressed sensing based image reconstruction technique for CMR perfusion, with applicability to free-breathing examinations. This technique uses local spatio-temporal constraints by regularizing image patches across a small number of dynamics. The technique is compared to conventional dynamic-by-dynamic reconstruction, and sparsity regularization using a temporal principal-component (pc) basis, as well as zerofilled data in multi-slice 2D and 3D CMR perfusion. Qualitative image scores are used (1=poor, 4=excellent) to evaluate the technique in 3D perfusion in 10 patients and 5 healthy subjects. On 4 healthy subjects, the proposed technique was also compared to a breath-hold multi-slice 2D acquisition with parallel imaging in terms of signal intensity curves. Results The proposed technique results in images that are superior in terms of spatial and temporal blurring compared to the other techniques, even in free-breathing datasets. The image scores indicate a significant improvement compared to other techniques in 3D perfusion (2.8±0.5 vs. 2.3±0.5 for x-pc regularization, 1.7±0.5 for dynamic-by-dynamic, 1.1±0.2 for zerofilled). Signal intensity curves indicate similar dynamics of uptake between the proposed method with a 3D acquisition and the breath-hold multi-slice 2D acquisition with parallel imaging. Conclusion The proposed reconstruction utilizes sparsity regularization based on localized information in both spatial and temporal domains for highly-accelerated CMR perfusion with potential utility in free

  20. Spatio-temporal patterns of proportions of influenza B cases

    PubMed Central

    He, Daihai; Chiu, Alice P. Y.; Lin, Qianying; Yu, Duo

    2017-01-01

    We studied the spatio-temporal patterns of the proportions of influenza B cases out of all typed cases, with data from 139 countries and regions downloaded from the FluNet compiled by the World Health Organization, from January 2006 to October 2015. We restricted our analysis to 34 countries that reported more than 2,000 confirmations for each of types A and B over the study period. Globally, we found that Pearson’s correlation is greater than 0.6 between effective distance from Mexico and the proportions of influenza B cases among the countries during the post-pandemic era (i.e. Week 1, 2010 to Week 40, 2015). Locally, in the United States, the proportions of influenza B cases in the pre-pandemic period (2003–2008) negatively correlated with that in the post-pandemic era (2010–2015) at the regional level. Our study limitations are the country-level variations in both surveillance methods and testing policies. The proportions of influenza B cases displayed wide variations over the study period. Our findings suggest that the 2009 influenza pandemic has an evident impact on the relative burden of the two influenza types. Future studies should examine whether there are other additional factors. This study has potential implications in prioritizing public health control measures. PMID:28067277

  1. Contour Tracking with a Spatio-Temporal Intensity Moment.

    PubMed

    Demi, Marcello

    2016-06-01

    Standard edge detection operators such as the Laplacian of Gaussian and the gradient of Gaussian can be used to track contours in image sequences. When using edge operators, a contour, which is determined on a frame of the sequence, is simply used as a starting contour to locate the nearest contour on the subsequent frame. However, the strategy used to look for the nearest edge points may not work when tracking contours of non isolated gray level discontinuities. In these cases, strategies derived from the optical flow equation, which look for similar gray level distributions, appear to be more appropriate since these can work with a lower frame rate than that needed for strategies based on pure edge detection operators. However, an optical flow strategy tends to propagate the localization errors through the sequence and an additional edge detection procedure is essential to compensate for such a drawback. In this paper a spatio-temporal intensity moment is proposed which integrates the two basic functions of edge detection and tracking.

  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. Spatio-temporal distribution of human lifespan in China

    NASA Astrophysics Data System (ADS)

    Wang, Shaobin; Luo, Kunli; Liu, Yonglin

    2015-09-01

    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.

  4. Robust Kronecker Product PCA for Spatio-Temporal Covariance Estimation

    NASA Astrophysics Data System (ADS)

    Greenewald, Kristjan; Hero, Alfred O.

    2015-12-01

    Kronecker PCA involves the use of a space vs. time Kronecker product decomposition to estimate spatio-temporal covariances. In this work the addition of a sparse correction factor is considered, which corresponds to a model of the covariance as a sum of Kronecker products of low (separation) rank and a sparse matrix. This sparse correction extends the diagonally corrected Kronecker PCA of [Greenewald et al 2013, 2014] to allow for sparse unstructured "outliers" anywhere in the covariance matrix, e.g. arising from variables or correlations that do not fit the Kronecker model well, or from sources such as sensor noise or sensor failure. We introduce a robust PCA-based algorithm to estimate the covariance under this model, extending the rearranged nuclear norm penalized LS Kronecker PCA approaches of [Greenewald et al 2014, Tsiligkaridis et al 2013]. An extension to Toeplitz temporal factors is also provided, producing a parameter reduction for temporally stationary measurement modeling. High dimensional MSE performance bounds are given for these extensions. Finally, the proposed extension of KronPCA is evaluated on both simulated and real data coming from yeast cell cycle experiments. This establishes the practical utility of robust Kronecker PCA in biological and other applications.

  5. Spatio-temporal credit assignment in neuronal population learning.

    PubMed

    Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

    2011-06-01

    In learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain.

  6. Nonlinear spatio-temporal interactions and neural connections in human vision using transient and M-sequence stimuli

    SciTech Connect

    Chen, H.W.; Aine, C.J.; Flynn, E.R.; Wood, C.C.

    1996-02-01

    Reciprocal connections, in essence, are the dynamic wiring (connections) of the neural network circuitry. Given the high complexity of the neural circuitry in the human brain, it is quite a challenge to study the dynamic wiring of highly parallel and widely distributed neural networks. The measurements of stimulus evoked coherent oscillations provide indirect evidence of dynamic wiring. In this study, in addition to the coherent oscillation measurements, two more techniques are discussed for testing possible dynamic wiring: measurements of spatio-temporal interactions beyond the classical receptive fields, and neural structural testing using nonlinear systems analysis.

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

    NASA Astrophysics Data System (ADS)

    Bertazzon, Stefania

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

  8. Research on testing field flaws of image intensifier based on spatio-temporal SNR

    NASA Astrophysics Data System (ADS)

    Zhou, Bin; Liu, Bingqi; Wu, Dongsheng

    2010-10-01

    Image intensifier is the kernel of low-light-level device. The field flaw is one of the important index parameters of the image intensifier. Traditionally the statistic number of the image intensifier's field flaws is calculated through the people's eyes by the aid of an optical microscope, which main limitation is subjective and inefficient. With the broad application of the high-powered CCD and digital imaging processing method in testing performance of image intensifier, the method of appraising SNR based on spatio-temporal noise theory can accurately reflect the spatio-temporal heterogeneous of fluorescence's output image and fulfill the requirements of digital and automatic test. The limitation of the flaws' shape and position can be disregard and the accurate flaws' inspection can be realized rapidly by this method. In this paper, the main factors of forming the field flaws are analyzed and the mathematic model of spatio-temporal SNR is deduced. The hardware devices of the test system for image intensifier's spatio-temporal SNR are discussed. The spatio-temporal SNR of Gen image intensifier is tested by this test system and the test software based on Visual C++ and Matlab. The digital and automatic test of a factitious field flaw is realized by the theory of spatio-temporal SNR. The test precision can achieve pixel level. The experimental results show that this new method is rational, reliable and visualized.

  9. Network-oriented massive spatio-temporal data model and its applications

    NASA Astrophysics Data System (ADS)

    Liu, Renyi; Liu, Nan; Bao, Weizheng; Zhu, Yan

    2006-10-01

    It is foundation and key of developing GIS platforms of new generation to study the network-oriented massive spatial and spatio-temporal data model. But the research has met many difficulties. The paper combines two models of massive spatial data and spatio-temporal data seemed to be independent to study together in theory and technique. On the base of analyzing the limitations of present geographical spatial data model and spatio-temporal data model, a new model with characteristics of new generation's GIS platform, that is, Feature-Oriented Massive Spatio-temporal Object Tree (FOMSOT) with four-tier architectures is presented. The FOMSOT breaks down the constraint of map layer. It can deal with the massive spatio-temporal data better. The dynamic multi-base state with amendment (DMSA), fast index of base state with amendment in section, storage factors of variable granularity (SFVG) are used in FOMSOT which can manage the massive spatio-temporal data in high efficiency. A prototype "LyranMap" of new generation's GIS platform with the theory and technical method of FOMSOT has been realized, and it has been used in some application systems, for example, the land planning system "LandPlanner", land investigation system "LandExplorer" and land cadastral system "LandReGIS". These verify the correctness and effectiveness of the FOMSOT.

  10. 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.

  11. 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.

  12. 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

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

    USGS Publications Warehouse

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

    2016-01-01

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

  14. Dynamical Cell Assembly Hypothesis - Theoretical Possibility of Spatio-temporal Coding in the Cortex.

    PubMed

    Tsukada, Minoru; Ichinose, Natsuhiro; Aihara, Kazuyuki; Ito, Hiroyuki; Fujii, Hiroshi

    1996-11-01

    This paper is an attempt to understand how knowledge and events are represented and processed in the brain. An important point is the question of what carries information in the brain - the mean firing rate or the timing of spikes? The idea we want to pursue is that, contrary to the traditional view, the brain might use higher order statistics, which means in essence that timing of spikes plays a critical role in encoding, representing, and processing knowledge and events in the brain.A recently revealed salient nature of cortical pyramidal cells, i.e., the high variability of inter-spike intervals suggests that a cortical neuron may function effectively as a coincidence detector. At the same time, non-classical experimental phenomena of task-related, short time-scaled dynamical modulations of temporal correlations between neurons suggest a non-classical view on the dynamics working in the brain. In response to contexts or external events, a group of neurons, a dynamical cell assembly, spontaneously organizes, linked temporarily by coincident timing of incident spikes, showing correlated firing with each other. This is an emergent property of neuronal populations in the cortex.We make a theoretical exploration on issues as (1) the description of such emergent dynamics of dynamical cell assemblies based on the working hypothesis that a cortica neuron functions effectively as a coincidence detector, and (2) the principle of spatio-temporal coding based on the hypothetical emergent dynamics. Note that the conventional rate coding hypothesis does not give satisfactory answers to fundamental questions on the representation and processing of knowledge or events in the brain, e.g., the questions of cross-modular integration of information or the binding problem, and representation of hierarchical knowledge etc.The first goal is to give a non-encyclopedic review on (1) the temporal structure of spike sequences, focusing on the question of the basic code in the brain; (2

  15. Spatio-temporal Trends in Hydrology at the Turkey Lakes Watershed: Insights from 35 Years of Monitoring

    NASA Astrophysics Data System (ADS)

    Webster, K. L.; Beall, F.; Semkin, R.

    2014-12-01

    The Turkey Lake Watershed (TLW) is located on the Precambrian Shield in central Ontario, Canada and has been the site of multi-discipline ecosystem research since 1979. The 10.5 km2 watershed is within the Great Lakes - St. Lawrence forest region with an uneven-aged tolerant hardwood forest having 90% of the basal area as mature to over-mature sugar maple. Podzolic soils and small forested wetlands have developed in the complex topography of the watershed where variable glacial till deposits occur over predominantly metamorphic silicate bedrock. Within the watershed, 13 first-order catchments that vary in size and topography have been monitored to elucidate spatio-temporal processes controlling run-off patterns. Over the 35 year period mean annual air temperatures at the TLW have increased at a rate of 0.75 oC per decade, with large inter-annual climate variability due to the influence of regional climate oscillations. As a result of warmer climate there has been a decline in annual export of water, as well as, changes in the seasonal distribution of runoff, Snowmelt has been occurring earlier and the number of zero-flow days are increasing. Declines in runoff were greater for catchments with steep slopes and less for those with shallow slopes and wetland areas. The large year to year variability in weather conditions made detecting the impacts on runoff from different harvesting treatments in 1997 difficult. These changes and fluctuations in water yields induced by fluctuating and changing climate have been shown to have had large consequences on element (carbon, nitrogen and sulphur) cycling within and export from catchments.

  16. 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

  17. Visibility conditions and diel period affect small-scale spatio-temporal behaviour of pike Esox lucius in the absence of prey and conspecifics.

    PubMed

    Nilsson, P A; Baktoft, H; Boel, M; Meier, K; Jacobsen, L; Rokkjaer, E M; Clausen, T; Skov, C

    2012-05-01

    Pike Esox lucius in the absence of prey and conspecifics were shown to have the highest habitat-change activity during dusk and to decrease preference for complex habitats in turbid water. As the behaviours indicate routine responses in the absence of behavioural interactions, E. lucius spatio-temporal distributions should be directly affected and thereby more easily assessed and avoided by prey, with potential consequences for encounter rates.

  18. Polynomial chaos representation of spatio-temporal random fields from experimental measurements

    SciTech Connect

    Das, Sonjoy Ghanem, Roger Finette, Steven

    2009-12-10

    Two numerical techniques are proposed to construct a polynomial chaos (PC) representation of an arbitrary second-order random vector. In the first approach, a PC representation is constructed by matching a target joint probability density function (pdf) based on sequential conditioning (a sequence of conditional probability relations) in conjunction with the Rosenblatt transformation. In the second approach, the PC representation is obtained by having recourse to the Rosenblatt transformation and simultaneously matching a set of target marginal pdfs and target Spearman's rank correlation coefficient (SRCC) matrix. Both techniques are applied to model an experimental spatio-temporal data set, exhibiting strong non-stationary and non-Gaussian features. The data consists of a set of oceanographic temperature records obtained from a shallow-water acoustics transmission experiment. The measurement data, observed over a finite denumerable subset of the indexing set of the random process, is treated as a collection of observed samples of a second-order random vector that can be treated as a finite-dimensional approximation of the original random field. A set of properly ordered conditional pdfs, that uniquely characterizes the target joint pdf, in the first approach and a set of target marginal pdfs and a target SRCC matrix, in the second approach, are estimated from available experimental data. Digital realizations sampled from the constructed PC representations based on both schemes capture the observed statistical characteristics of the experimental data with sufficient accuracy. The relative advantages and disadvantages of the two proposed techniques are also highlighted.

  19. 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.

  20. Disentangling Multidimensional Spatio-Temporal Data into Their Common and Aberrant Responses

    PubMed Central

    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

  1. Spatio-Temporal Brain Mapping of Motion-Onset VEPs Combined with fMRI and Retinotopic Maps

    PubMed Central

    Pitzalis, Sabrina; Strappini, Francesca; De Gasperis, Marco; Bultrini, Alessandro; Di Russo, Francesco

    2012-01-01

    Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR). PMID:22558222

  2. In situ spatio-temporal changes in pollution-induced community tolerance to zinc in autotrophic and heterotrophic biofilm communities.

    PubMed

    Tlili, Ahmed; Corcoll, Natalia; Bonet, Berta; Morin, Soizic; Montuelle, Bernard; Bérard, Annette; Guasch, Helena

    2011-11-01

    Pollution-induced community tolerance (PICT) uses increased tolerance in populations at contaminated sites as an indicator of contaminant effects. However, given the broad structural and functional complexity that characterizes biological communities, the acquisition of PICT could vary with (i) target community, (ii) intensity of toxicant exposure, (iii) the species succession stage, and (iv) the physicochemical characteristics of the studied site. To assess the spatio-temporal changes of zinc-induced tolerance in fluvial biofilm communities, we conducted an in situ study in Osor River (North-East Catalonia, Spain), which has zinc contamination. Biofilms were developed for 5 weeks in a non-metal-polluted site, and were then transferred to different sites in Osor River with different levels of zinc contamination. The spatio-temporal changes of biofilm PICT to zinc was determined using photosynthetic activity bioassays and respiration-induced aerobic bioassays at T(0), and at 1, 3 and 5 weeks of exposure. We also performed physicochemical characterization of the sites, taxonomic analysis of diatoms, bacterial and fungal diversity and profiled pigments of phototrophic communities. We used multivariate ordination to analyze results. In addition to natural species succession, the intensity of metal pollution exerted structural pressure by selecting the most metal-tolerant species, but differently depending on the type of biofilm. Zn-tolerance values indicated that exposure to high levels of zinc had effects that were similar to a longer exposure to lower levels of zinc.

  3. 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

  4. 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.

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

    PubMed Central

    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

  6. Factors Related to Rape Reporting Behavior in Brazil: Examining the Role of Spatio-Temporal Factors.

    PubMed

    Melo, Silas Nogueira de; Beauregard, Eric; Andresen, Martin A

    2016-07-10

    The reporting of rape to police is an important component of this crime to have the criminal justice system involved and, potentially, punish offenders. However, for a number of reasons (fear of retribution, self-blame, etc.), most rapes are not reported to police. Most often, the research investigating this phenomenon considers incident and victim factors with little attention to the spatio-temporal factors of the rape. In this study, we consider incident, victim, and spatio-temporal factors relating to rape reporting in Campinas, Brazil. Our primary research question is whether or not the spatio-temporal factors play a significant role in the reporting of rape, over and above incident and victim factors. The subjects under study are women who were admitted to the Women's Integrated Healthcare Center at the State University of Campinas, Brazil, and surveyed by a psychologist or a social worker. Rape reporting to police was measured using a dichotomous variable. Logistic regression was used to predict the probability of rape reporting based on incident, victim, and spatio-temporal factors. Although we find that incident and victim factors matter for rape reporting, spatio-temporal factors (rape/home location and whether the rape was in a private or public place) play an important role in rape reporting, similar to the literature that considers these factors. This result has significant implications for sexual violence education. Only when we know why women decide not to report a rape may we begin to work on strategies to overcome these hurdles.

  7. 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.

  8. Effects of a structured midsole on spatio-temporal variables and running economy in overground running.

    PubMed

    Wunsch, Tobias; Kröll, Josef; Stöggl, Thomas; Schwameder, Hermann

    2017-04-01

    Research to enhance running performance has led to the design of a leaf spring-structured midsole shoe (LEAF). In treadmill running, it has been shown that LEAF led to an increased running economy and increased stride length (SL) through a horizontal foot shift during stance compared to a standard foam shoe (FOAM). The purpose of this study was to analyse whether (a) these findings can also be observed in overground running and (b) relations exist between spatio-temporal variables and running economy. Ten male long-distance heel-strike runners ran at their individual 2 mmol/l blood lactate speed with LEAF and FOAM in randomized order. Kinematic data were recorded with an inertial measurement unit synchronized with 2D video. Oxygen consumption was measured using an automated metabolic gas analysis system. Blood lactate was collected after each run. The strike pattern was unaffected by LEAF. SL was increased by 0.9 ± 1.1 cm (95% CI 0.2 to 1.5; p = .040; dz = 0.76), stride rate (SR) was reduced by -0.4 ± 0.3 strides/min (95% CI -0.6 to -0.1; p = .029; dz = 0.82) and oxygen consumption tended to be reduced by 1% (-0.4 ± 0.6 ml/min/kg; 95% CI -0.8 to 0.0; p = .082; dz = 0.62) when running with LEAF compared to FOAM. Changes in oxygen consumption in LEAF were correlated with SL (r = 0.71; p = .022) and SR (r = -0.68; p = .031). It can be concluded that LEAF has the potential to cause small changes in spatio-temporal variables during running. Runners increasing SL and decreasing SR in response to LEAF can achieve small improvements in running economy, which is beneficial in terms of performance.

  9. Retrieval of Spatio-temporal Distributions of Particle Parameters from Multiwavelength Lidar Measurements Using the Linear Estimation Technique and Comparison with AERONET

    NASA Technical Reports Server (NTRS)

    Veselovskii, I.; Whiteman, D. N.; Korenskiy, M.; Kolgotin, A.; Dubovik, O.; Perez-Ramirez, D.; Suvorina, A.

    2013-01-01

    The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3 Beta + 1 alpha lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement.

  10. The Homeobox Genes of Caenorhabditis elegans and Insights into Their Spatio-Temporal Expression Dynamics during Embryogenesis

    PubMed Central

    Abou-Zied, Akram M.; Lüppert, Martin; Dethlefsen, Johan; Mukherjee, Krishanu; Tong, Yong Guang; Tang, Lois; Gangishetti, Umesh; Baillie, David L.; Bürglin, Thomas R.

    2015-01-01

    Homeobox genes play crucial roles for the development of multicellular eukaryotes. We have generated a revised list of all homeobox genes for Caenorhabditis elegans and provide a nomenclature for the previously unnamed ones. We show that, out of 103 homeobox genes, 70 are co-orthologous to human homeobox genes. 14 are highly divergent, lacking an obvious ortholog even in other Caenorhabditis species. One of these homeobox genes encodes 12 homeodomains, while three other highly divergent homeobox genes encode a novel type of double homeodomain, termed HOCHOB. To understand how transcription factors regulate cell fate during development, precise spatio-temporal expression data need to be obtained. Using a new imaging framework that we developed, Endrov, we have generated spatio-temporal expression profiles during embryogenesis of over 60 homeobox genes, as well as a number of other developmental control genes using GFP reporters. We used dynamic feedback during recording to automatically adjust the camera exposure time in order to increase the dynamic range beyond the limitations of the camera. We have applied the new framework to examine homeobox gene expression patterns and provide an analysis of these patterns. The methods we developed to analyze and quantify expression data are not only suitable for C. elegans, but can be applied to other model systems or even to tissue culture systems. PMID:26024448

  11. Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes.

    PubMed

    Tasdemir, Kasim; Kurugollu, Fatih; Sezer, Sakir

    2016-05-11

    A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

  12. NeuCube: a spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data.

    PubMed

    Kasabov, Nikola K

    2014-04-01

    The brain functions as a spatio-temporal information processing machine. Spatio- and spectro-temporal brain data (STBD) are the most commonly collected data for measuring brain response to external stimuli. An enormous amount of such data has been already collected, including brain structural and functional data under different conditions, molecular and genetic data, in an attempt to make a progress in medicine, health, cognitive science, engineering, education, neuro-economics, Brain-Computer Interfaces (BCI), and games. Yet, there is no unifying computational framework to deal with all these types of data in order to better understand this data and the processes that generated it. Standard machine learning techniques only partially succeeded and they were not designed in the first instance to deal with such complex data. Therefore, there is a need for a new paradigm to deal with STBD. This paper reviews some methods of spiking neural networks (SNN) and argues that SNN are suitable for the creation of a unifying computational framework for learning and understanding of various STBD, such as EEG, fMRI, genetic, DTI, MEG, and NIRS, in their integration and interaction. One of the reasons is that SNN use the same computational principle that generates STBD, namely spiking information processing. This paper introduces a new SNN architecture, called NeuCube, for the creation of concrete models to map, learn and understand STBD. A NeuCube model is based on a 3D evolving SNN that is an approximate map of structural and functional areas of interest of the brain related to the modeling STBD. Gene information is included optionally in the form of gene regulatory networks (GRN) if this is relevant to the problem and the data. A NeuCube model learns from STBD and creates connections between clusters of neurons that manifest chains (trajectories) of neuronal activity. Once learning is applied, a NeuCube model can reproduce these trajectories, even if only part of the input

  13. Source characterization and spatio-temporal evolution of the metal pollution in the sediments of the Basque estuaries (Bay of Biscay).

    PubMed

    Legorburu, Irati; Rodríguez, José Germán; Borja, Angel; Menchaca, Iratxe; Solaun, Oihana; Valencia, Victoriano; Galparsoro, Ibon; Larreta, Joana

    2013-01-15

    According to Water Framework Directive requirements, Member States must identify and analyze effects derived from human pressures in aquatic systems. As different kind of pressures can impact water bodies at different scales, analyses of spatio-temporal evolution of water bodies becomes essential in order to understand ecosystem responses. In this investigation, an analysis of spatio-temporal evolution of sedimentary metal pollution (Cd, Cr, Cu, Hg, Ni, Pb, Zn) in 12 Basque estuaries (Bay of Biscay) is presented. Data collected in extensive sampling surveys is the basis for the GIS-based statistical approach used. The implementation of pollution abatement measures is reflected in a long-term decontamination process, mostly evident in estuaries with highest historical sediment pollution levels. Spatial evolution is determined by either naturally occurring or human driven processes. Such spatial processes are more obviously being reflected in estuaries with lower historical sediment pollution levels.

  14. Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

    PubMed Central

    Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

    2016-01-01

    Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

  15. Spatio-temporal evolution of uranium emission in laser-produced plasmas

    NASA Astrophysics Data System (ADS)

    Harilal, S. S.; Diwakar, P. K.; LaHaye, N. L.; Phillips, M. C.

    2015-09-01

    Laser-induced plasma spectroscopy provides much impetus as a nuclear forensics tool because of its capability of standoff detection and real-time analysis. However, special nuclear materials like U, Pu, etc. provide very crowded spectra and, when combined with shifts and broadening of spectral lines caused by ambient atmospheric operation, generate a complex plasma spectroscopy system. We explored the spatio-temporal evolution of excited U species in a laser ablation plume under various ambient pressure conditions. Plasmas were generated using 1064 nm, 6 ns pulses from a Nd:YAG laser on a U containing glass matrix target. The role of air ambient pressure on U line intensities, signal-to-background ratios, and linewidths were investigated. Spatially and temporally resolved optical time-of-flight emission spectroscopy of excited uranium atoms were used for studying the expansion hydrodynamics and the persistence of U species in the plume. Our results showed that U emission linewidths increased with pressure due to increased Stark broadening; however, the broadening was less than that for Ca. A comparison with U emission features in the presence of an inert gas showed the persistence of U species in plasmas in ambient air is significantly reduced; this could be due to oxide and other reactive species formation.

  16. Electrical brain imaging reveals spatio-temporal dynamics of timbre perception in humans.

    PubMed

    Meyer, Martin; Baumann, Simon; Jancke, Lutz

    2006-10-01

    Timbre is a major attribute of sound perception and a key feature for the identification of sound quality. Here, we present event-related brain potentials (ERPs) obtained from sixteen healthy individuals while they discriminated complex instrumental tones (piano, trumpet, and violin) or simple sine wave tones that lack the principal features of timbre. Data analysis yielded enhanced N1 and P2 responses to instrumental tones relative to sine wave tones. Furthermore, we applied an electrical brain imaging approach using low-resolution electromagnetic tomography (LORETA) to estimate the neural sources of N1/P2 responses. Separate significance tests of instrumental vs. sine wave tones for N1 and P2 revealed distinct regions as principally governing timbre perception. In an initial stage (N1), timbre perception recruits left and right (peri-)auditory fields with an activity maximum over the right posterior Sylvian fissure (SF) and the posterior cingulate (PCC) territory. In the subsequent stage (P2), we uncovered enhanced activity in the vicinity of the entire cingulate gyrus. The involvement of extra-auditory areas in timbre perception may imply the presence of a highly associative processing level which might be generally related to musical sensations and integrates widespread medial areas of the human cortex. In summary, our results demonstrate spatio-temporally distinct stages in timbre perception which not only involve bilateral parts of the peri-auditory cortex but also medially situated regions of the human brain associated with emotional and auditory imagery functions.

  17. Systems Reliability Approach To Spatio-Temporal Probability Of Microbial Water Contamination

    NASA Astrophysics Data System (ADS)

    Myers, J. R.; Yeghiazarian, L.

    2015-12-01

    Sustainable management of water resources is unattainable without addressing microbial contamination of surface waters. Fecal microorganisms are the leading cause of surface water impairment, presenting a problem of national importance. In the US, approximately 93,000 river and stream miles contain elevated levels of fecal bacteria. Because microbial fate and transport are driven by inherently random environmental processes taking place in complex, multi-component environmental systems, a systems-based stochastic approach is needed to better understand patterns of microbial contamination. We have applied systems reliability theory to compute the spatio-temporal distribution of probability of water contamination in dendritic flow networks. This approach allows to measure probabilistically the impact of watershed components and microbial sources on overall water quality, and to determine watershed characteristics and external environmental parameters to which microbial water quality is most sensitive. This, in turn, helps (1) identify the "hot spots" exerting the highest impact, and (2) quantify of sustainability metrics such as reliability, vulnerability and resilience - all of which will, in turn, guide prioritization of management measures under various conditions.

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  19. Taming of Modulation Instability by Spatio-Temporal Modulation of the Potential

    PubMed Central

    Kumar, S.; Herrero, R.; Botey, M.; Staliunas, K.

    2015-01-01

    Spontaneous pattern formation in a variety of spatially extended nonlinear systems always occurs through a modulation instability, sometimes called Turing instability: the homogeneous state of the system becomes unstable with respect to growing modulation modes. Therefore, the manipulation of the modulation instability is of primary importance in controlling and manipulating the character of spatial patterns initiated by that instability. We show that a spatio-temporal periodic modulation of the potential of spatially extended systems results in a modification of its pattern forming instability. Depending on the modulation character the instability can be partially suppressed, can change its spectrum (for instance the long wave instability can transform into short wave instability), can split into two, or can be completely eliminated. The latter result is of special practical interest, as it can be used to stabilize the intrinsically unstable system. The result bears general character, as it is shown here on a universal model of the Complex Ginzburg-Landau equation in one and two spatial dimensions (and time). The physical mechanism of the instability suppression can be applied to a variety of intrinsically unstable dissipative systems, like self-focusing lasers, reaction-diffusion systems, as well as in unstable conservative systems, like attractive Bose Einstein condensates. PMID:26286250

  20. Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity.

    PubMed

    Jeni, László A; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F; Kanade, Takeo

    2014-01-01

    In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods.

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

    PubMed

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

    2016-11-22

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

  2. Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity

    PubMed Central

    Jeni, László A.; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F.; Kanade, Takeo

    2016-01-01

    In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods1. PMID:27830214

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

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

    PubMed Central

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

    2016-01-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

  6. Active processing of spatio-temporal input patterns in silicon dendrites.

    PubMed

    Wang, Yingxue; Liu, Shih-Chii

    2013-06-01

    Capturing the functionality of active dendritic processing into abstract mathematical models will help us to understand the role of complex biophysical neurons in neuronal computation and to build future useful neuromorphic analog Very Large Scale Integrated (aVLSI) neuronal devices. Previous work based on an aVLSI multi-compartmental neuron model demonstrates that the compartmental response in the presence of either of two widely studied classes of active mechanisms, is a nonlinear sigmoidal function of the degree of either input temporal synchrony OR input clustering level. Using the same silicon model, this work expounds the interaction between both active mechanisms in a compartment receiving input patterns of varying temporal AND spatial clustering structure and demonstrates that this compartmental response can be captured by a combined sigmoid and radial-basis function over both input dimensions. This paper further shows that the response to input spatio-temporal patterns in a one-dimensional multi-compartmental dendrite, can be described by a radial-basis like function of the degree of temporal synchrony between the inter-compartmental inputs.

  7. Quantitative live-cell imaging reveals spatio-temporal dynamics and cytoplasmic assembly of the 26S proteasome.

    PubMed

    Pack, Chan-Gi; Yukii, Haruka; Toh-e, Akio; Kudo, Tai; Tsuchiya, Hikaru; Kaiho, Ai; Sakata, Eri; Murata, Shigeo; Yokosawa, Hideyoshi; Sako, Yasushi; Baumeister, Wolfgang; Tanaka, Keiji; Saeki, Yasushi

    2014-03-06

    The 26S proteasome is a 2.5-MDa multisubunit protease complex that degrades polyubiquitylated proteins. Although its functions and structure have been extensively characterized, little is known about its dynamics in living cells. Here, we investigate the absolute concentration, spatio-temporal dynamics and complex formation of the proteasome in living cells using fluorescence correlation spectroscopy. We find that the 26S proteasome complex is highly mobile, and that almost all proteasome subunits throughout the cell are stably incorporated into 26S proteasomes. The interaction between 19S and 20S particles is stable even in an importin-α mutant, suggesting that the 26S proteasome is assembled in the cytoplasm. Furthermore, a genetically stabilized 26S proteasome mutant is able to enter the nucleus. These results suggest that the 26S proteasome completes its assembly process in the cytoplasm and translocates into the nucleus through the nuclear pore complex as a holoenzyme.

  8. Spatio-temporal current density reconstruction (stCDR) from EEG/MEG-data.

    PubMed

    Darvas, F; Schmitt, U; Louis, A K; Fuchs, M; Knoll, G; Buchner, H

    2001-01-01

    Among the different approaches to the bioelectromagnetic inverse problem, the current-density reconstruction methods (CDR) provide the most general solutions. Since the inverse problem does not have a unique solution, model assumptions have to be taken into account. Multi-channel measurements contain not only spatial, but also temporal information about the sources, so a naturally extension to existing methods leads to spatio-temporal model constraints. Spatio-temporal CDR's (stCDR) have been tested in simplified volume conductor models, assuming different spatial model constraints and a smooth temporal activation model. Comparison to existing spatial model constraints showed a significant improvement of spatial and temporal resolution of the reconstructed sources for the spatio-temporal models especial in noisy data.

  9. 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.

  10. Applying spatio-temporal models to assess variations across health care areas and regions: Lessons from the decentralized Spanish National Health System

    PubMed Central

    Librero, Julián; Martínez-Lizaga, Natalia; Peiró, Salvador; Bernal-Delgado, Enrique

    2017-01-01

    Objective To illustrate the ability of hierarchical Bayesian spatio-temporal models in capturing different geo-temporal structures in order to explain hospital risk variations using three different conditions: Percutaneous Coronary Intervention (PCI), Colectomy in Colorectal Cancer (CCC) and Chronic Obstructive Pulmonary Disease (COPD). Research design This is an observational population-based spatio-temporal study, from 2002 to 2013, with a two-level geographical structure, Autonomous Communities (AC) and Health Care Areas (HA). Setting The Spanish National Health System, a quasi-federal structure with 17 regional governments (AC) with full responsibility in planning and financing, and 203 HA providing hospital and primary care to a defined population. Methods A poisson-log normal mixed model in the Bayesian framework was fitted using the INLA efficient estimation procedure. Measures The spatio-temporal hospitalization relative risks, the evolution of their variation, and the relative contribution (fraction of variation) of each of the model components (AC, HA, year and interaction AC-year). Results Following PCI-CCC-CODP order, the three conditions show differences in the initial hospitalization rates (from 4 to 21 per 10,000 person-years) and in their trends (upward, inverted V shape, downward). Most of the risk variation is captured by phenomena occurring at the HA level (fraction variance: 51.6, 54.7 and 56.9%). At AC level, the risk of PCI hospitalization follow a heterogeneous ascending dynamic (interaction AC-year: 17.7%), whereas in COPD the AC role is more homogenous and important (37%). Conclusions In a system where the decisions loci are differentiated, the spatio-temporal modeling allows to assess the dynamic relative role of different levels of decision and their influence on health outcomes. PMID:28166233

  11. Neural processes in symmetry perception: a parallel spatio-temporal model.

    PubMed

    Zhu, Tao

    2014-04-01

    Symmetry is usually computationally expensive to detect reliably, while it is relatively easy to perceive. In spite of many attempts to understand the neurofunctional properties of symmetry processing, no symmetry-specific activation was found in earlier cortical areas. Psychophysical evidence relating to the processing mechanisms suggests that the basic processes of symmetry perception would not perform a serial, point-by-point comparison of structural features but rather operate in parallel. Here, modeling of neural processes in psychophysical detection of bilateral texture symmetry is considered. A simple fine-grained algorithm that is capable of performing symmetry estimation without explicit comparison of remote elements is introduced. A computational model of symmetry perception is then described to characterize the underlying mechanisms as one-dimensional spatio-temporal neural processes, each of which is mediated by intracellular horizontal connections in primary visual cortex and adopts the proposed algorithm for the neural computation. Simulated experiments have been performed to show the efficiency and the dynamics of the model. Model and human performances are comparable for symmetry perception of intensity images. Interestingly, the responses of V1 neurons to propagation activities reflecting higher-order perceptual computations have been reported in neurophysiologic experiments.

  12. Large-Scale Spatio-Temporal Patterns of Mediterranean Cephalopod Diversity

    PubMed Central

    Keller, Stefanie; Bartolino, Valerio; Hidalgo, Manuel; Bitetto, Isabella; Casciaro, Loredana; Cuccu, Danila; Esteban, Antonio; Garcia, Cristina; Garofalo, Germana; Josephides, Marios; Jadaud, Angelique; Lefkaditou, Evgenia; Maiorano, Porzia; Manfredi, Chiara; Marceta, Bojan; Massutí, Enric; Micallef, Reno; Peristeraki, Panagiota; Relini, Giulio; Sartor, Paolo; Spedicato, Maria Teresa; Tserpes, George; Quetglas, Antoni

    2016-01-01

    Species diversity is widely recognized as an important trait of ecosystems’ functioning and resilience. Understanding the causes of diversity patterns and their interaction with the environmental conditions is essential in order to effectively assess and preserve existing diversity. While diversity patterns of most recurrent groups such as fish are commonly studied, other important taxa such as cephalopods have received less attention. In this work we present spatio-temporal trends of cephalopod diversity across the entire Mediterranean Sea during the last 19 years, analysing data from the annual bottom trawl survey MEDITS conducted by 5 different Mediterranean countries using standardized gears and sampling protocols. The influence of local and regional environmental variability in different Mediterranean regions is analysed applying generalized additive models, using species richness and the Shannon Wiener index as diversity descriptors. While the western basin showed a high diversity, our analyses do not support a steady eastward decrease of diversity as proposed in some previous studies. Instead, high Shannon diversity was also found in the Adriatic and Aegean Seas, and high species richness in the eastern Ionian Sea. Overall diversity did not show any consistent trend over the last two decades. Except in the Adriatic Sea, diversity showed a hump-shaped trend with depth in all regions, being highest between 200–400 m depth. Our results indicate that high Chlorophyll a concentrations and warmer temperatures seem to enhance species diversity, and the influence of these parameters is stronger for richness than for Shannon diversity. PMID:26760965

  13. Robust spatio-temporal registration of 4D cardiac ultrasound sequences

    NASA Astrophysics Data System (ADS)

    Bersvendsen, Jørn; Toews, Matthew; Danudibroto, Adriyana; Wells, William M.; Urheim, Stig; Estépar, Raúl San José; Samset, Eigil

    2016-04-01

    Registration of multiple 3D ultrasound sectors in order to provide an extended field of view is important for the appreciation of larger anatomical structures at high spatial and temporal resolution. In this paper, we present a method for fully automatic spatio-temporal registration between two partially overlapping 3D ultrasound sequences. The temporal alignment is solved by aligning the normalized cross correlation-over-time curves of the sequences. For the spatial alignment, corresponding 3D Scale Invariant Feature Transform (SIFT) features are extracted from all frames of both sequences independently of the temporal alignment. A rigid transform is then calculated by least squares minimization in combination with random sample consensus. The method is applied to 16 echocardiographic sequences of the left and right ventricles and evaluated against manually annotated temporal events and spatial anatomical landmarks. The mean distances between manually identified landmarks in the left and right ventricles after automatic registration were (mean+/-SD) 4.3+/-1.2 mm compared to a reference error of 2.8 +/- 0.6 mm with manual registration. For the temporal alignment, the absolute errors in valvular event times were 14.4 +/- 11.6 ms for Aortic Valve (AV) opening, 18.6 +/- 16.0 ms for AV closing, and 34.6 +/- 26.4 ms for mitral valve opening, compared to a mean inter-frame time of 29 ms.

  14. Spatio-Temporal Variability of Saturated Crevasses Along the Margins of Jakobshavn ISBRÆ

    NASA Astrophysics Data System (ADS)

    Ring, A.; Lampkin, D. J.

    2014-12-01

    Jakobshavn Isbræ is the fastest marine-terminating outlet glacier on the Greenland Ice Sheet and has experienced speed up, thinning and increased mass discharge primarily due to ocean-ice interactions at the terminus, over the last two decades. Approximately 60% of the total driving stress within the main ice stream is compensated by resistance due to lateral shear. We have observed the presence of water-filled crevasses, which fill in local depressions and drain seasonally, resulting in meltwater filtration directly into the shear margins. Injection of meltwater into the shear margins can result in shear weakening with implications for observed changes within the ice stream, in addition to, potentially enhancing mass flux into the main trough. Shear weakening, due to infiltrated meltwater, can increase sliding due to basal lubrication or reduce ice stiffness due to cryo-hydrologic warming. In this study, LandSat-7 ETM+ and LandSat-8 OLI images at 15m spatial resolutions are used to characterize the spatio-temporal variability of saturated crevasses during the ablation seasons from 2000 through 2013. Changes in the delineated area of water-filled crevasses are compared to variability in ice surface velocity fields during the analysis period as a first-order assessment on the potential impact these features may have on marginal ice dynamics.

  15. Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA

    PubMed Central

    Guardiola, Magdalena; Wangensteen, Owen S.; Taberlet, Pierre; Coissac, Eric; Uriz, María Jesús

    2016-01-01

    We assessed spatio-temporal patterns of diversity in deep-sea sediment communities using metabarcoding. We chose a recently developed eukaryotic marker based on the v7 region of the 18S rRNA gene. Our study was performed in a submarine canyon and its adjacent slope in the Northwestern Mediterranean Sea, sampled along a depth gradient at two different seasons. We found a total of 5,569 molecular operational taxonomic units (MOTUs), dominated by Metazoa, Alveolata and Rhizaria. Among metazoans, Nematoda, Arthropoda and Annelida were the most diverse. We found a marked heterogeneity at all scales, with important differences between layers of sediment and significant changes in community composition with zone (canyon vs slope), depth, and season. We compared the information obtained from metabarcoding DNA and RNA and found more total MOTUs and more MOTUs per sample with DNA (ca. 20% and 40% increase, respectively). Both datasets showed overall similar spatial trends, but most groups had higher MOTU richness with the DNA template, while others, such as nematodes, were more diverse in the RNA dataset. We provide metabarcoding protocols and guidelines for biomonitoring of these key communities in order to generate information applicable to management efforts. PMID:28028473

  16. Robust Spatio-Temporal Registration of 4D Cardiac Ultrasound Sequences

    PubMed Central

    Bersvendsen, Jørn; Toews, Matthew; Danudibroto, Adriyana; Wells, William M.; Urheim, Stig; Estépar, Raúl San José; Samset, Eigil

    2016-01-01

    Registration of multiple 3D ultrasound sectors in order to provide an extended field of view is important for the appreciation of larger anatomical structures at high spatial and temporal resolution. In this paper, we present a method for fully automatic spatio-temporal registration between two partially overlapping 3D ultrasound sequences. The temporal alignment is solved by aligning the normalized cross correlation-over-time curves of the sequences. For the spatial alignment, corresponding 3D Scale Invariant Feature Transform (SIFT) features are extracted from all frames of both sequences independently of the temporal alignment. A rigid transform is then calculated by least squares minimization in combination with random sample consensus. The method is applied to 16 echocardiographic sequences of the left and right ventricles and evaluated against manually annotated temporal events and spatial anatomical landmarks. The mean distances between manually identified landmarks in the left and right ventricles after automatic registration were (mean ± SD) 4.3 ± 1.2 mm compared to a reference error of 2.8 ± 0.6 mm with manual registration. For the temporal alignment, the absolute errors in valvular event times were 14.4 ± 11.6 ms for Aortic Valve (AV) opening, 18.6 ± 16.0 ms for AV closing, and 34.6 ± 26.4 ms for mitral valve opening, compared to a mean inter-frame time of 29 ms. PMID:27516706

  17. Spatio-temporal coherence mapping of few-cycle vortex pulses

    PubMed Central

    Grunwald, R.; Elsaesser, T.; Bock, M.

    2014-01-01

    Light carrying an orbital angular momentum (OAM) displays an optical phase front rotating in space and time and a vanishing intensity, a so-called vortex, in the center. Beyond continuous-wave vortex beams, optical pulses with a finite OAM are important for many areas of science and technology, ranging from the selective manipulation and excitation of matter to telecommunications. Generation of vortex pulses with a duration of few optical cycles requires new methods for characterising their coherence properties in space and time. Here we report a novel approach for flexibly shaping and characterising few-cycle vortex pulses of tunable topological charge with two sequentially arranged spatial light modulators. The reconfigurable optical arrangement combines interferometry, wavefront sensing, time-of-flight and nonlinear correlation techniques in a very compact setup, providing complete spatio-temporal coherence maps at minimum pulse distortions. Sub-7 fs pulses carrying different optical angular momenta are generated in single and multichannel geometries and characterised in comparison to zero-order Laguerre-Gaussian beams. To the best of our knowledge, this represents the shortest pulse durations reported for direct vortex shaping and detection with spatial light modulators. This access to space-time coupling effects with sub-femtosecond time resolution opens new prospects for tailored twisted light transients of extremely short duration. PMID:25413789

  18. Cortical spatio-temporal dynamics underlying phonological target detection in humans.

    PubMed

    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

    2011-06-01

    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 recordings during this task revealed a highly ordered temporal progression of high gamma (HG, 70-200 Hz) activity across the lateral hemisphere in less than 1 sec. The sequence demonstrated concurrent regional sensory processing of speech syllables in the posterior superior temporal gyrus (STG) and speech motor cortex, and then transitioned to sequential task-dependent processing from prefrontal cortex (PFC), to the final motor response in the hand sensorimotor cortex. STG activation was modestly enhanced for target over nontarget sounds, supporting a selective gain mechanism in early sensory processing, whereas PFC was entirely selective to targets, supporting its role in guiding response behavior. These results reveal that target detection is not a single cognitive event, but rather a process of progressive target selectivity that involves large-scale rapid parallel and serial processing in sensory, cognitive, and motor structures to support goal-directed human behavior.

  19. 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.

  20. Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA.

    PubMed

    Guardiola, Magdalena; Wangensteen, Owen S; Taberlet, Pierre; Coissac, Eric; Uriz, María Jesús; Turon, Xavier

    2016-01-01

    We assessed spatio-temporal patterns of diversity in deep-sea sediment communities using metabarcoding. We chose a recently developed eukaryotic marker based on the v7 region of the 18S rRNA gene. Our study was performed in a submarine canyon and its adjacent slope in the Northwestern Mediterranean Sea, sampled along a depth gradient at two different seasons. We found a total of 5,569 molecular operational taxonomic units (MOTUs), dominated by Metazoa, Alveolata and Rhizaria. Among metazoans, Nematoda, Arthropoda and Annelida were the most diverse. We found a marked heterogeneity at all scales, with important differences between layers of sediment and significant changes in community composition with zone (canyon vs slope), depth, and season. We compared the information obtained from metabarcoding DNA and RNA and found more total MOTUs and more MOTUs per sample with DNA (ca. 20% and 40% increase, respectively). Both datasets showed overall similar spatial trends, but most groups had higher MOTU richness with the DNA template, while others, such as nematodes, were more diverse in the RNA dataset. We provide metabarcoding protocols and guidelines for biomonitoring of these key communities in order to generate information applicable to management efforts.

  1. A registration strategy for long spatio-temporal aerial remote sensing image sequence

    NASA Astrophysics Data System (ADS)

    Cao, Yutian; Yan, Dongmei; Li, Jianming; Wang, Gang

    2015-12-01

    A novel registration strategy for aerial image sequence is put forward to adapt to the long spatio-temporal span of the aerial remote sensing imaging. By setting keyframe, this strategy aligns all images in sequence to a unified datum with high registration sustainability and precision. The contrast experiment on different registration strategies is carried out based on SIFT feature matching of mid-infrared aerial sequences. The experiment results show that the proposed strategy performs well on long spatio-temporal sequences with different imaging resolutions and scenes.

  2. Application of 3D Spatio-Temporal Data Modeling, Management, and Analysis in DB4GEO

    NASA Astrophysics Data System (ADS)

    Kuper, P. V.; Breunig, M.; Al-Doori, M.; Thomsen, A.

    2016-10-01

    Many of todaýs world wide challenges such as climate change, water supply and transport systems in cities or movements of crowds need spatio-temporal data to be examined in detail. Thus the number of examinations in 3D space dealing with geospatial objects moving in space and time or even changing their shapes in time will rapidly increase in the future. Prominent spatio-temporal applications are subsurface reservoir modeling, water supply after seawater desalination and the development of transport systems in mega cities. All of these applications generate large spatio-temporal data sets. However, the modeling, management and analysis of 3D geo-objects with changing shape and attributes in time still is a challenge for geospatial database architectures. In this article we describe the application of concepts for the modeling, management and analysis of 2.5D and 3D spatial plus 1D temporal objects implemented in DB4GeO, our service-oriented geospatial database architecture. An example application with spatio-temporal data of a landfill, near the city of Osnabrück in Germany demonstrates the usage of the concepts. Finally, an outlook on our future research focusing on new applications with big data analysis in three spatial plus one temporal dimension in the United Arab Emirates, especially the Dubai area, is given.

  3. Construction of An Unbiased Spatio-Temporal Atlas of the Tongue During Speech.

    PubMed

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

    2015-01-01

    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.

  4. 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.

  5. 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...

  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. Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient.

    PubMed

    Karanth, K Ullas; Srivathsa, Arjun; Vasudev, Divya; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N Samba

    2017-02-08

    Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole (Cuon alpinus), leopard (Panthera pardus) and tiger (Panthera tigris) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds.

  8. 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…

  9. Flexible Representation of Spatio-Temporal Random Fields in the Model Web

    NASA Astrophysics Data System (ADS)

    Gräler, B.; Stasch, C.

    2012-04-01

    The Model Web envisions an infrastructure for coupling environmental models in the Web. In environmental sciences, the phenomena of interest are usually not well-bounded objects, but rather continuous phenomena in space and time. These phenomena are commonly referred to as spatial or spatio-temporal fields and are often modelled as random variables. Currently, spatio-temporal fields are usually represented and exchanged as raster data. Besides the communication overhead this imposes, exchanging rasters has also other drawbacks. For example, the interpolation method used to calculate the raster values as well as the original observations the raster originates from are usually not part of the resulting data. Furthermore, the interpolated values are commonly single moment estimates of the random variables such as their expectation values. Thus, the natural randomness in the interpolated variables and interpolation uncertainties are also not available any more after interpolation. We propose a new model for exchanging spatio-temporal random fields as the original sample data plus information about the model of spatial or spatio-temporal variance describing the random field. This allows to communicate the complete random variables and their associated uncertainties opposed to single estimates. In addition, this approach suggests a particular interpolation method to calculate rasters from the field. The desired raster resolution and projection can then be chosen by the user of the field data. This is advantageous to the classical approach, as transformations between coordinate reference systems typically distort the given raster and changing the raster's resolution usually imposes a second model assumption on the interpolated field data. Using a standardized language to describe spatio-temporal random fields allows for a fully machine readable approach. Depending on the target application, one can thus easily obtain one to several simulations of the field reflecting its

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

    DOE PAGES

    Chang, Young Hwan; Korkola, James; Amin, Dhara N.; ...

    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

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

    PubMed

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

    2015-08-01

    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.

  12. Predicting saltwater intrusion into aquifers in vicinity of deserts using spatio-temporal kriging.

    PubMed

    Bahrami Jovein, E; Hosseini, S M

    2017-02-01

    The primary objective of this study was to provide a detailed framework to use the spatio-temporal kriging to model the spatio-temporal variations of salinity data and predict saltwater intrusion into freshwater aquifers in the vicinity of deserts. EC data, measured in extraction wells in the Mahvelat plain located in the Northeastern part of Iran, available from 2007 to 2013, were used to demonstrate the developed framework. The source of data was not a well-designed measurement network. Therefore, to homogenize the data, spatial analysis was used to find EC distribution in the area in each year of study. To conduct the spatial analysis, a guideline and a systematic process were developed to select an appropriate kriging method and optimize its parameters. This process can be applied to different variables. After spatial analysis of EC data for all the years of the analysis period using empirical Bayesian kriging (EBK) method with manually optimized parameters, spatio-temporal and corresponding variogram analysis was conducted using R software. This process was based on a separable product-sum model applied to the data from 2007 to 2012. The data of 2013 and the data available for the years 1999 and 2006 were used for evaluating the performance of the spatio-temporal model. The EC distribution maps, developed for different years until 2021, show a high level of EC in the north, south, and west of the study area and growing saltwater intrusion into the central freshwater aquifer. This result can be attributed to the over-exploitation of the aquifer and hydraulic head and gradient distribution in the area. The framework provided in this study for spatio-temporal analysis of unstructured EC data is useful for groundwater managers in making proper decisions.

  13. 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

  14. Spatio-temporal sequence of cross-regulatory events in root meristem growth

    PubMed Central

    Scacchi, Emanuele; Salinas, Paula; Gujas, Bojan; Santuari, Luca; Krogan, Naden; Ragni, Laura; Berleth, Thomas; Hardtke, Christian S.

    2010-01-01

    A central question in developmental biology is how multicellular organisms coordinate cell division and differentiation to determine organ size. In Arabidopsis roots, this balance is controlled by cytokinin-induced expression of SHORT HYPOCOTYL 2 (SHY2) in the so-called transition zone of the meristem, where SHY2 negatively regulates auxin response factors (ARFs) by protein–protein interaction. The resulting down-regulation of PIN-FORMED (PIN) auxin efflux carriers is considered the key event in promoting differentiation of meristematic cells. Here we show that this regulation involves additional, intermediary factors and is spatio-temporally constrained. We found that the described cytokinin–auxin crosstalk antagonizes BREVIS RADIX (BRX) activity in the developing protophloem. BRX is an auxin-responsive target of the prototypical ARF MONOPTEROS (MP), a key promoter of vascular development, and transiently enhances PIN3 expression to promote meristem growth in young roots. At later stages, cytokinin induction of SHY2 in the vascular transition zone restricts BRX expression to down-regulate PIN3 and thus limit meristem growth. Interestingly, proper SHY2 expression requires BRX, which could reflect feedback on the auxin responsiveness of SHY2 because BRX protein can directly interact with MP, likely acting as a cofactor. Thus, cross-regulatory antagonism between BRX and SHY2 could determine ARF activity in the protophloem. Our data suggest a model in which the regulatory interactions favor BRX expression in the early proximal meristem and SHY2 prevails because of supplementary cytokinin induction in the later distal meristem. The complex equilibrium of this regulatory module might represent a universal switch in the transition toward differentiation in various developmental contexts. PMID:21149702

  15. 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

  16. Effects of neural refractoriness on spatio-temporal variability in spike initiations with Electrical stimulation.

    PubMed

    Mino, Hiroyuki; Rubinstein, Jay T

    2006-09-01

    In this paper, the effects of neural refractoriness on action potential (spike) initiations with electrical stimulation are investigated using computer modeling and simulation techniques. The computational model was composed of a myelinated nerve fiber with 50 nodes of Ranvier, each consisting of stochastic sodium and potassium channels, making it possible to represent the fluctuations of spike initiation. A series of two-pulse stimuli was presented by a stimulating electrode above the central (26th) node of Ranvier. The amplitude of the first (masker) pulse stimulus was set such that the masker pulse stimulus evoked spikes on each trial, while that of the second (probe) pulse stimulus was set such that the probe pulse stimulus evoked spikes on a half of trials, threshold values. Then the transmembrane potentials in response to the probe pulse stimulus were recorded at each node (i.e., 1-50 nodes) in order to determine the spike initiation node and time. From the observation of the spike initiation node and time, a spatio-temporal histogram as well as a spatial variability and a temporal variability of spike initiations was generated which allowed us to interpret fluctuations in spike initiation node and time. It was shown that the distribution of spike initiations tended to become greater spatially and longer temporally as the masker-probe intervals (MPIs) of the two-pulse stimuli shortened. It was also shown that the number of activated sodium channels as functions of space and time tended to become smaller due to inactivation of sodium channels and varied spatially and temporally as MPIs shortened. These findings may imply that the stochastic sodium channels during a relative refractory period may contribute to enhancing the fluctuations in spike initiations, and give us an insight into encoding information with electric stimuli to improve the performance of the prosthetic devices, especially cochlear implants.

  17. PROPAGATION OF SEISMIC WAVES THROUGH A SPATIO-TEMPORALLY FLUCTUATING MEDIUM: HOMOGENIZATION

    SciTech Connect

    Hanasoge, Shravan M.; Gizon, Laurent; Bal, Guillaume

    2013-08-20

    Measurements of seismic wave travel times at the photosphere of the Sun have enabled inferences of its interior structure and dynamics. In interpreting these measurements, the simplifying assumption that waves propagate through a temporally stationary medium is almost universally invoked. However, the Sun is in a constant state of evolution, on a broad range of spatio-temporal scales. At the zero-wavelength limit, i.e., when the wavelength is much shorter than the scale over which the medium varies, the WKBJ (ray) approximation may be applied. Here, we address the other asymptotic end of the spectrum, the infinite-wavelength limit, using the technique of homogenization. We apply homogenization to scenarios where waves are propagating through rapidly varying media (spatially and temporally), and derive effective models for the media. One consequence is that a scalar sound speed becomes a tensorial wave speed in the effective model and anisotropies can be induced depending on the nature of the perturbation. The second term in this asymptotic two-scale expansion, the so-called corrector, contains contributions due to higher-order scattering, leading to the decoherence of the wave field. This decoherence may be causally linked to the observed wave attenuation in the Sun. Although the examples we consider here consist of periodic arrays of perturbations to the background, homogenization may be extended to ergodic and stationary random media. This method may have broad implications for the manner in which we interpret seismic measurements in the Sun and for modeling the effects of granulation on the scattering of waves and distortion of normal-mode eigenfunctions.

  18. Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression

    NASA Astrophysics Data System (ADS)

    Tipton, John; Hooten, Mevin; Goring, Simon

    2017-01-01

    Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal

  19. Assessing parasite community structure in cockles Cerastoderma edule at various spatio-temporal scales

    NASA Astrophysics Data System (ADS)

    de Montaudouin, Xavier; Binias, Cindy; Lassalle, Géraldine

    2012-09-01

    Cockles (Cerastoderma edule) are among the most exploited bivalves in Europe. They live in lagoons and estuaries where they undergo many stressors including parasites. Trematodes are the most prevalent macroparasites of cockles and can exert a significant impact on their host populations depending on parasite species and infection intensity. Monitoring these parasite-host systems in order to predict potential host mortalities require a correct knowledge of the spatio-temporal variation of infection. A yearly monitoring of cockles from six stations around Ile aux Oiseaux, Arcachon Bay (France) was conducted between 1998 and 2005. Distance between two stations was ca. 1 km. Nine trematode species were identified. Despite a relative homogeneity of the parasite community structure in cockles, between three and six clusters were identified by Hierarchical Ascendant Classification showing that among-sites heterogeneity of trematode communities in cockles was higher than within-site heterogeneity. At the scale of 8 years, and for 2-year old cockles, these patterns remained stable in four out of six stations. Spatial aggregation disappeared with cockle age, since parasite communities in 3-year cockles did not reflect any particular station(s): with age, cockles eventually accumulated most trematode species and lost the site signature. On the other hand, we demonstrated that the commonly accepted theory stating that older/larger cockles accumulate more trematode larvae was not verified and that there could exist a vulnerable age/size that doesn't correspond to largest values. This study provided a new insight in the parasite community heterogeneity in their host, and in the significance of samples in relation with space and time.

  20. Spatio-temporal filtering for determination of common mode error in regional GNSS networks

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually estimated with the regional spatial filtering, such as the "stacking". In this paper, we show the stacking approach for the set of ASG-EUPOS permanent stations, assuming that spatial distribution of the CME is uniform over the whole region of Poland (more than 600 km extent). The ASG-EUPOS is a multifunctional precise positioning system based on the reference network designed for Poland. We used a 5- year span time series (2008-2012) of daily solutions in the ITRF2008 from Bernese 5.0 processed by the Military University of Technology EPN Local Analysis Centre (MUT LAC). At the beginning of our analyses concerning spatial dependencies, the correlation coefficients between each pair of the stations in the GNSS network were calculated. This analysis shows that spatio-temporal behaviour of the GPS-derived time series is not purely random, but there is the evident uniform spatial response. In order to quantify the influence of filtering using CME, the norms L1 and L2 were determined. The values of these norms were calculated for the North, East and Up components twice: before performing the filtration and after stacking. The observed reduction of the L1 and L2 norms was up to 30% depending on the dimension of the network. However, the question how to define an optimal size of CME-analysed subnetwork remains unanswered in this research, due to the fact that our network is not extended enough.

  1. 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

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

    PubMed

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Zuluaga-Arias, Manuel D.

    2011-12-01

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

  4. 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.

  5. 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.

  6. Estimating the spatio-temporal distribution of surface water availability across India

    NASA Astrophysics Data System (ADS)

    Singh, R.; Kumar, R.

    2015-12-01

    Quantifying the spatio-temporal variation of future surface water availability across India is critical for water resources planning and management in the water stressed region. However, this remains a challenge as long-term streamflow data is scarce and there is significant uncertainty regarding unmonitored withdrawals. We present a framework to estimate long-term (surface) water availability and its vulnerability to climate change across India using hydro-climatic variables based on long-term precipitation, potential and actual evapotranspiration. We derive estimates of actual evapotranspiration through a probabilistic Budyko framework which further allows us to obtain uncertainty bounds on surface water availability. We define vulnerability as a relative change in long-term surface water availability for a unit change in long-term precipitation. Based on this, we present vulnerability maps for India which shows the spatio-temporal variation of vulnerability of surface water resources to climate change across India.

  7. Identification of the neighborhood and CA rules from spatio-temporal CA patterns.

    PubMed

    Billings, S A; Yang, Yingxu

    2003-01-01

    Extracting the rules from spatio-temporal patterns generated by the evolution of cellular automata (CA) usually produces a CA rule table without providing a clear understanding of the structure of the neighborhood or the CA rule. In this paper, a new identification method based on using a modified orthogonal least squares or CA-OLS algorithm to detect the neighborhood structure and the underlying polynomial form of the CA rules is proposed. The Quine-McCluskey method is then applied to extract minimum Boolean expressions from the polynomials. Spatio-temporal patterns produced by the evolution of 1D, 2D, and higher dimensional binary CAs are used to illustrate the new algorithm, and simulation results show that the CA-OLS algorithm can quickly select both the correct neighborhood structure and the corresponding rule.

  8. Automatic Cystocele Severity Grading in Ultrasound by Spatio-Temporal Regression

    PubMed Central

    Ji, Xing; Gao, Yaozong; Cheng, Jie-Zhi; Wang, Huifang; Qin, Jing; Lei, Baiying; Wang, Tianfu; Wu, Guorong; Shen, Dinggang

    2017-01-01

    Cystocele is a common disease in woman. Accurate assessment of cystocele severity is very important for treatment options. The transperineal ultrasound (US) has recently emerged as an alternative tool for cystocele grading. The cystocele severity is usually evaluated with the manual measurement of the maximal descent of the bladder (MDB) relative to the symphysis pubis (SP) during Valsalva maneuver. However, this process is time-consuming and operator-dependent. In this study, we propose an automatic scheme for csystocele grading from transperineal US video. A two-layer spatio-temporal regression model is proposed to identify the middle axis and lower tip of the SP, and segment the bladder, which are essential tasks for the measurement of the MDB. Both appearance and context features are extracted in the spatio-temporal domain to help the anatomy detection. Experimental results on 85 transperineal US videos show that our method significantly outperforms the state-of-the-art regression method.

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

    PubMed

    Arab, Ali

    2015-08-28

    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.

  10. Management of spatio-temporal data for dynamic segmentation in transportation application

    NASA Astrophysics Data System (ADS)

    Gui, Lan; Gong, Jianya

    2005-10-01

    There have been many research studies focusing on linear data modeling for transportation application. However, research on spatio-temporal modeling is still in its infancy, which limits transportation agencies to implement improved solutions. Transportation applications offer challenges to GIS technology. Not only are the attributes of transportation features dynamic, but also many features are dynamic. The authors firstly review the definition and characteristics of dynamic segmentation, an important technology in transportation application. The paper then presents a data model for dynamic segmentation with timing dimension and its implementation. This paper shows the design of spatio-temporal data structure. Both linear elements and events are tagged with start and end temporal expressions, thus it makes temporal querying easier. Segment geocoding, segment overlay and data maintenance is discussed in detailed.

  11. 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

  12. Activity Changes Induced by Spatio-Temporally Correlated Stimuli in Cultured Cortical Networks

    NASA Astrophysics Data System (ADS)

    Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko

    Activity-dependent plasticity probably plays a key role in learning and memory in biological information processing systems. Though long-term potentiation and depression have been extensively studied in the filed of neuroscience, little is known on the mechanisms for integrating these modifications on network-wide activity changes. In this report, we studied effects of spatio-temporally correlated stimuli on the neuronal network activity. Rat cortical neurons were cultured on substrates with 64 embedded micro-electrodes and the evoked responses were extracellularly recorded and analyzed. We compared spatio-temporal patterns of the responses between before and after repetitive application of correlated stimuli. After the correlated stimuli, the networks showed significantly different responses from those in the initial states. The modified activity reflected structures of the repeatedly applied correlated stimuli. The results suggested that spatiotemporally correlated inputs systematically induced modification of synaptic strengths in neuronal networks, which could serve as an underlying mechanism of associative memory.

  13. 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.

  14. A Bayesian latent model with spatio-temporally varying coefficients in low birth weight incidence data

    PubMed Central

    Choi, Jungsoon; Lawson, Andrew B; Cai, Bo; Hossain, Md Monir; Kirby, Russell S; Liu, Jihong

    2017-01-01

    In spatial epidemiology studies, the effects of covariates on adverse health outcomes could vary over space and time so examining the spatio-temporally varying effects is useful. In particular, the association between covariates and health outcomes could have locally different temporal patterns. In this article, we develop a Bayesian spatio-temporal latent model to identify spatial clusters in each of which covariate effects have homogeneous temporal patterns as well as estimate heterogeneous temporal effects of covariates depending on spatial groups. We compare the proposed model to several alternative models to assess the performance of the proposed model in terms of a range of model assessment measures. Low birth weight incidence data in Georgia for the years 1997–2006 are used. PMID:22534428

  15. 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.

  16. 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.

  17. Simultaneous spatio-temporal matching pursuit decomposition of evoked brain responses in MEG.

    PubMed

    Kordowski, Paweł; Matysiak, Artur; König, Reinhard; Sielużycki, Cezary

    2017-02-01

    We present a novel approach to the spatio-temporal decomposition of evoked brain responses in magnetoencephalography (MEG) aiming at a sparse representation of the underlying brain activity in terms of spatio-temporal atoms. Our approach is characterized by three attributes which constitute significant improvements with respect to existing approaches: (1) the spatial and temporal decomposition is addressed simultaneously rather than sequentially, with the benefit that source loci and corresponding waveforms can be unequivocally allocated to each other, and, hence, allow a plausible physiological interpretation of the parametrized data; (2) it is free from severe a priori assumptions about the solution space; (3) it comprises an optimization technique for the use of very large spatial and temporal subdirectories to greatly reduce the otherwise enormous computational cost by making use of the Cauchy-Schwarz inequality. We demonstrate the efficiency of the approach with simulations and real MEG data obtained from a subject exposed to a simple auditory stimulus.

  18. Meteor tracking via local pattern clustering in spatio-temporal domain

    NASA Astrophysics Data System (ADS)

    Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

    2016-09-01

    Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

  19. At what spatio-temporal scales can inertial waves be found in rotating turbulence?

    NASA Astrophysics Data System (ADS)

    Cortet, Pierre-Philippe; Campagne, Antoine; Gallet, Basile; Moisy, Frédéric

    2014-11-01

    We present a spatio-temporal analysis of a statistically stationary rotating turbulence experiments aiming to extract a statistical signature of inertial waves and to determine at what scales and frequencies these waves can be detected. This analysis is performed from two-point correlations of temporal Fourier transform of the velocity fields time series obtained from stereoscopic PIV measurements in the rotating frame. From this data, it is possible to quantify the degree of anisotropy of turbulence due to global rotation both as a function of angular frequency ω and spatial scale normal to the rotation axis r⊥. This frequency and scale dependent anisotropy is found compatible with the dispersion relation of inertial waves, provided that a weak non-linearity condition is satisfied in terms of a properly defined Rossby number dependant on the spatio-temporal scale (ω,r⊥).

  20. 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.

  1. Enhanced spatio-temporal clustering in the detection of neonatal seizures using context-based rules.

    PubMed

    Mitra, Joyeeta; Glover, John R; Frost, James D; Ktonas, Periklis A; Hrachovy, Richard A; Mizrahi, Eli M

    2004-01-01

    This work describes the clustering stage of a three-stage automated neonatal seizure detection system. This stage clusters spatio-temporally the short candidate seizure segments detected in prior stages, and then applies a variety of context-based rules to eliminate false detections and determine the final detected seizures. The work discusses important considerations in the implementation of rules and presents preliminary results.

  2. Lack of influence of muscular performance parameters on spatio-temporal adaptations with increased running velocity.

    PubMed

    Roche-Seruendo, Luis E; García-Pinillos, Felipe; Haicaguerre, Joana; Bataller-Cervero, Ana V; Soto-Hermoso, Víctor M; Latorre-Román, Pedro Á

    2017-02-08

    This study aimed to analyse the influence of muscular performance parameters on spatio-temporal gait characteristics during running when gradually increasing speed. 51 recreationally trained male endurance runners (age: 28 ± 8 years) voluntarily participated in this study. Subjects performed a battery of jumping tests (squat jump, countermovement jump, and 20 cm drop jump), and after that, the subjects performed an incremental running test (10 to 20 km/h) on a motorized treadmill. Spatio-temporal parameters were measured using the OptoGait system. Cluster k-means analysis grouped subjects according to the jumping test performance, by obtaining a group of good jumpers (GJ, n = 19) and a group of bad jumpers (BJ, n = 32). With increased running velocity, contact time was shorter, flight time and step length longer, whereas cadence and stride angle were greater (p < 0.001). No significant differences between groups (p ≥ 0.05) were found at any running speed. The results obtained indicate that increased running velocity produced no differences in spatio-temporal adaptations between those runners with good jumping ability and those with poor jumping ability. Based on that, it seems that muscular performance parameters do not play a key role in spatio-temporal adaptations experienced by recreational endurance runners with increased velocity. However, taken into consideration the well-known relationship between running performance and neuromuscular performance, the authors suggest that muscular performance parameters would be much more determinant in the presence of fatigue (exhausted condition), or in the case of considering other variables such as running economy or kinetic.

  3. Spacecraft relative guidance via spatio-temporal resolution in atmospheric density forecasting

    NASA Astrophysics Data System (ADS)

    Guglielmo, David; Pérez, David; Bevilacqua, Riccardo; Mazal, Leonel

    2016-12-01

    Spacecraft equipped with the capability to vary their ballistic coefficient can use differential drag as the control force to perform propellant-less relative maneuvers. Because atmospheric drag is proportional to atmospheric density, uncertainty in atmospheric density makes the generation and tracking of drag-based guidances difficult. Spatio-temporal resolution, or the mapping of density information to altitude and time, is shown in this work to improve atmospheric density estimation from forecasted density for spacecraft in LEO. This is achieved by propagating simulated orbits for two spacecraft using forecasted density. Additionally, a receding-horizon control algorithm is introduced, with the goal of improving the tracking of guidances. Using a simulated perfect forecast of the atmospheric density for propagation of the orbits, relative guidance trajectories are generated and tracked, establishing the benefit of adding spatio-temporal resolution. Next, imperfect density forecasting is added, indicating that the benefit of spatio-temporal resolution is retained in the presence of imperfect forecasting. Finally, a receding-horizon control algorithm is used with imperfect forecasting, demonstrating that receding-horizon control improves the tracking of guidances compared to single-horizon control.

  4. 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.

  5. 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.

  6. Spatio-temporal Dynamics of Sources of Hard X-Ray Pulsations in Solar Flares

    NASA Astrophysics Data System (ADS)

    Kuznetsov, S. A.; Zimovets, I. V.; Morgachev, A. S.; Struminsky, A. B.

    2016-11-01

    We present a systematic analysis of the spatio-temporal evolution of sources of hard X-ray (HXR) pulsations in solar flares. We concentrate on disk flares whose impulsive phases are accompanied by a series of more than three successive peaks (pulsations) of HXR emission detected in the RHESSI 50 - 100 keV energy channel with a four-second time cadence. Twenty-nine such flares observed from February 2002 to June 2015 with characteristic time differences between successive peaks P ≈8 - 270 s are studied. The main observational result of the analysis is that sources of HXR pulsations in all flares are not stationary, they demonstrate apparent movements or displacements in the parent active regions from pulsation to pulsation. The flares can be subdivided into two main groups depending on the character of the dynamics of the HXR sources. Group 1 consists of 16 flares (55 %) that show systematic dynamics of the HXR sources from pulsation to pulsation with respect to a magnetic polarity inversion line (MPIL), which has a simple extended trace on the photosphere. Group 2 consists of 13 flares (45 %) that show more chaotic displacements of the HXR sources with respect to an MPIL with a more complex structure, and sometimes several MPILs are present in the parent active regions of such flares. Based on the observations, we conclude that the mechanism of the flare HXR pulsations (at least with time differences of the considered range) is related to successive triggering of the flare energy release process in different magnetic loops (or bundles of loops) of the parent active regions. Group 1 flare regions consist of loops stacked into magnetic arcades that are extended along MPILs. Group 2 flare regions have more complex magnetic structures, and the loops are arranged more chaotically and randomly there. We also found that at least 14 (88 %) group 1 flares and 11 (85 %) group 2 flares are accompanied by coronal mass ejections (CMEs), i.e. the absolute majority of the

  7. Local spatio-temporal analysis in vision systems

    NASA Astrophysics Data System (ADS)

    Geisler, Wilson S.; Bovik, Alan; Cormack, Lawrence; Ghosh, Joydeep; Gildeen, David

    1994-07-01

    The aims of this project are the following: (1) develop a physiologically and psychophysically based model of low-level human visual processing (a key component of which are local frequency coding mechanisms); (2) develop image models and image-processing methods based upon local frequency coding; (3) develop algorithms for performing certain complex visual tasks based upon local frequency representations, (4) develop models of human performance in certain complex tasks based upon our understanding of low-level processing; and (5) develop a computational testbed for implementing, evaluating and visualizing the proposed models and algorithms, using a massively parallel computer. Progress has been substantial on all aims. The highlights include the following: (1) completion of a number of psychophysical and physiological experiments revealing new, systematic and exciting properties of the primate (human and monkey) visual system; (2) further development of image models that can accurately represent the local frequency structure in complex images; (3) near completion in the construction of the Texas Active Vision Testbed; (4) development and testing of several new computer vision algorithms dealing with shape-from-texture, shape-from-stereo, and depth-from-focus; (5) implementation and evaluation of several new models of human visual performance; and (6) evaluation, purchase and installation of a MasPar parallel computer.

  8. Harmonics rejection in pixelated interferograms using spatio-temporal demodulation.

    PubMed

    Padilla, J M; Servin, M; Estrada, J C

    2011-09-26

    Pixelated phase-mask interferograms have become an industry standard in spatial phase-shifting interferometry. These pixelated interferograms allow full wavefront encoding using a single interferogram. This allows the study of fast dynamic events in hostile mechanical environments. Recently an error-free demodulation method for ideal pixelated interferograms was proposed. However, non-ideal conditions in interferometry may arise due to non-linear response of the CCD camera, multiple light paths in the interferometer, etc. These conditions generate non-sinusoidal fringes containing harmonics which degrade the phase estimation. Here we show that two-dimensional Fourier demodulation of pixelated interferograms rejects most harmonics except the complex ones at {-3(rd), +5(th), -7(th), +9(th), -11(th),…}. We propose temporal phase-shifting to remove these remaining harmonics. In particular, a 2-step phase-shifting algorithm is used to eliminate the -3(rd) and +5(th) complex harmonics, while a 3-step one is used to remove the -3(rd), +5<(th), -7(th) and +9(th) complex harmonics.

  9. 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

    2015-10-15

    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.

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

    PubMed

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

    2008-06-06

    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

  11. 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

  12. Spatio-temporal correlation of vegetation and temperature patterns

    NASA Astrophysics Data System (ADS)

    Coppola, R.; D'Emilio, M.; Imbrenda, V.; Lanfredi, M.; Macchiato, M.; Simoniello, T.

    2010-05-01

    Temperature is one of the variables largely influencing vegetation species distributions (biogeographical regions) and plant development (phenological cycle). Anomalies in temperature regional patterns and in microclimate conditions induce modifications in vegetation cover phenology; in particular in European regions, the responsiveness of vegetation to temperature increase is greater in warmer Mediterranean countries. In order to assess the spatial arrangement and the temporal variability of vegetation and temperature patterns in a typical Mediterranean environment, we investigated monthly NDVI-AVHRR and temperature time series over Southern Italy, core of Mediterranean Basin. Temperature data, obtained from 35 meteoclimatic stations, were rasterized by adopting a combined deterministic-stochastic procedure we suitably implemented for the investigated region in order to obtain spatial data comparable with NDVI maps. For the period 1996-1998, monthly MVC data were clusterized on annual basis by means of a classification procedure to aggregate areas with similar phenological cycles. The same procedure was adopted to jointly evaluate temperature and vegetation profiles and identify areas having similar phenological and temperature patterns. The comparison of the identified clusters showed that the classification obtained with and without temperature profiles are very similar enhancing the strong role of this variable in vegetation development. Some exceptions in the cluster arrangement are due to local anomalies in vegetation distribution, such as forest fires. In order to spatially analyze such a dependence, we also elaborated a time correlation map for each year and we found that the correlation patterns are persistent on the year basis and generally follow the land cover distributions. The correlation values are very high and positive for the forested mountainous areas (R>0.8), whereas they are negative for plan coastal areas (R<-0.8). Low correlation values (R

  13. Multi-scale spatio-temporal analysis of human mobility.

    PubMed

    Alessandretti, Laura; Sapiezynski, Piotr; Lehmann, Sune; Baronchelli, Andrea

    2017-01-01

    The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spatial and temporal scales. Here, we characterise mobility behaviour across several orders of magnitude by analysing ∼850 individuals' digital traces sampled every ∼16 seconds for 25 months with ∼10 meters spatial resolution. We show that the distributions of distances and waiting times between consecutive locations are best described by log-normal and gamma distributions, respectively, and that natural time-scales emerge from the regularity of human mobility. We point out that log-normal distributions also characterise the patterns of discovery of new places, implying that they are not a simple consequence of the routine of modern life.

  14. Multi-scale spatio-temporal analysis of human mobility

    PubMed Central

    Alessandretti, Laura; Sapiezynski, Piotr; Lehmann, Sune; Baronchelli, Andrea

    2017-01-01

    The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spatial and temporal scales. Here, we characterise mobility behaviour across several orders of magnitude by analysing ∼850 individuals’ digital traces sampled every ∼16 seconds for 25 months with ∼10 meters spatial resolution. We show that the distributions of distances and waiting times between consecutive locations are best described by log-normal and gamma distributions, respectively, and that natural time-scales emerge from the regularity of human mobility. We point out that log-normal distributions also characterise the patterns of discovery of new places, implying that they are not a simple consequence of the routine of modern life. PMID:28199347

  15. Spatio-temporal modeling of signaling protein recruitment to EGFR

    PubMed Central

    2010-01-01

    Background A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors. Results The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCγ1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering. Conclusions Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process. PMID:20459599

  16. Improved searching for spatial features in spatio-temporal data

    SciTech Connect

    Stockinger, Kurt; Wu, Kesheng

    2004-09-27

    Scientific data analysis often requires mining large databases or data warehouses to find features in space. One important task is to find regions of interest such as stellar objects in astrophysics or flame fronts in combustion studies. Typically, this task is performed in two steps. The first step (searching) identifies records satisfying certain conditions specified by the user and outputs a set of cells. The second step (region-growing) groups these cells into connected regions. Most common approaches essentially perform a brute-force scan for these arching step. A number of indexing schemes have been proposed to speed up the searching step. Because they usually also slow down the region-growing step, these schemes have not reduced the overall time. In this article, we propose an approach based on compressed bitmap indices. Our approach speeds up not only the searching step, but also the region-growing step. In the literature, the time complexity of the region-growing step is demonstrated to be linear in the number of records in the dataset. In our tests, we show that the response time of our region-growing algorithm is linear in the number of records close to the surface of the regions of interest which is a small subset of all cells.

  17. 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

  18. Spatio-temporal variability of periphytic protozoa related to environment in the Niyang River, Tibet, China

    NASA Astrophysics Data System (ADS)

    Liu, Haiping; Ye, Shaowen; Yang, Xuefeng; Guo, Chuanbo; Zhang, Huijuan; Fan, Liqing; Zhang, Liangsong; Sovan, Lek; Li, Zhongjie

    2016-06-01

    The Niyang River, a main tributary of the Yarlung Zangbo River, is an important and typical plateau river ecosystem in Tibet, China. At present, few studies have focused on its aquatic living resources and river ecology. In this study, the composition, abundance, and diversity of periphytic protozoa were investigated across four seasons from 2008 to 2009 to better understand their spatio-temporal patterns and relationship to the environment. Our investigation shows that periphytic protozoa in the Niyang River contained 15 genera, belonged to Tubulinea, Alveolata, Discosea and Rhizaria, Alveolata possessed most genera, up to nine, with highest share in abundance, exceeding 50%, Difflugia and Glaucoma were dominant genera. Moreover, four diversity indices of periphytic protozoa, including species richness, total abundance, Shannon-Wiener diversity index and Pielou's evenness index, displayed a significant descending trend as the seasons continued, in the order of winter, spring, summer and autumn; with a significant difference existing between winter and summer (or autumn) for Shannon-Wiener diversity index and species richness (P<0.05). Four of these diversity indices also presented a V-shaped pattern between the upper middle course of the Niyang River and the confluence of the Niyang River and Yarlung Zangbo River, with the lowest value occurred in the middle course of the Niyang River. However, no significant variation was found through the Niyang River (P>0.05). In addition, canonical correlation analysis (CCA) shows that the densities of Difflugia, Glaucomais, Enchelydium, Cyphoderia, and Enchelys correlate with water temperature, alkalinity, hardness, pH, and dissolved oxygen, respectively. Lastly, the relationship between periphytic protozoa diversity and the environmental factors of the Niyang River can be predicted using classification and regression trees (CART) annalysis, which suggests that the total abundance and Shannon-Wiener diversity index would be

  19. 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

  20. 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.

  1. Spatio-temporal alignment of pedobarographic image sequences.

    PubMed

    Oliveira, Francisco P M; Sousa, Andreia; Santos, Rubim; Tavares, João Manuel R S

    2011-07-01

    This article presents a methodology to align plantar pressure image sequences simultaneously in time and space. The spatial position and orientation of a foot in a sequence are changed to match the foot represented in a second sequence. Simultaneously with the spatial alignment, the temporal scale of the first sequence is transformed with the aim of synchronizing the two input footsteps. Consequently, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is automatically attained, making the study easier and more straightforward. In terms of spatial alignment, the methodology can use one of four possible geometric transformation models: rigid, similarity, affine, or projective. In the temporal alignment, a polynomial transformation up to the 4th degree can be adopted in order to model linear and curved time behaviors. Suitable geometric and temporal transformations are found by minimizing the mean squared error (MSE) between the input sequences. The methodology was tested on a set of real image sequences acquired from a common pedobarographic device. When used in experimental cases generated by applying geometric and temporal control transformations, the methodology revealed high accuracy. In addition, the intra-subject alignment tests from real plantar pressure image sequences showed that the curved temporal models produced better MSE results (P < 0.001) than the linear temporal model. This article represents an important step forward in the alignment of pedobarographic image data, since previous methods can only be applied on static images.

  2. Imposing spatio-temporal support in magnetic resonance angiographic imaging

    NASA Astrophysics Data System (ADS)

    Bones, Philip J.; Vafadar, Bahareh; Watts, Richard; Wu, Bing

    2010-08-01

    A method to improve time resolution in 3D contrast-enhanced magnetic resonance angiography (CE-MRA) is proposed. A temporal basis based on prior knowledge of the contrast flow dynamics is applied to a sequence of image reconstructions. In CE-MRA a contrast agent (gadolinium) is injected into a peripheral vein and MR data is acquired as the agent arrives in the arteries and then the veins of the region of clinical interest. The acquisition extends over several minutes. Information is effectively measured in 3D k-space (spatial frequency space) one line at-atime. That line may be along a Cartesian grid line in k-space, a radial line or a spiral trajectory. A complete acquisition comprises many such lines but in order to improve temporal resolution, reconstructions are made from only partial sets of k-space data. By imposing a basis for the temporal changes, based on prior expectation of the smoothness of the changes in contrast concentration with time, it is demonstrated that a significant reduction in artifacts caused by the under-sampling of k-space can be achieved. The basis is formed from a set of gamma variate functions. Results are presented for a simulated set of 2D spiral-sampled CE-MRA data.

  3. Spatio-temporal colour correction of strongly degraded movies

    NASA Astrophysics Data System (ADS)

    Islam, A. B. M. Tariqul; Farup, Ivar

    2011-01-01

    The archives of motion pictures represent an important part of precious cultural heritage. Unfortunately, these cinematography collections are vulnerable to different distortions such as colour fading which is beyond the capability of photochemical restoration process. Spatial colour algorithms-Retinex and ACE provide helpful tool in restoring strongly degraded colour films but, there are some challenges associated with these algorithms. We present an automatic colour correction technique for digital colour restoration of strongly degraded movie material. The method is based upon the existing STRESS algorithm. In order to cope with the problem of highly correlated colour channels, we implemented a preprocessing step in which saturation enhancement is performed in a PCA space. Spatial colour algorithms tend to emphasize all details in the images, including dust and scratches. Surprisingly, we found that the presence of these defects does not affect the behaviour of the colour correction algorithm. Although the STRESS algorithm is already in itself more efficient than traditional spatial colour algorithms, it is still computationally expensive. To speed it up further, we went beyond the spatial domain of the frames and extended the algorithm to the temporal domain. This way, we were able to achieve an 80 percent reduction of the computational time compared to processing every single frame individually. We performed two user experiments and found that the visual quality of the resulting frames was significantly better than with existing methods. Thus, our method outperforms the existing ones in terms of both visual quality and computational efficiency.

  4. 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

  5. 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.

  6. Environmental and socio-economic change in Thailand: quantifying spatio-temporal risk factors of dengue to inform decision making

    NASA Astrophysics Data System (ADS)

    Rodo, X.; Lowe, R.; Karczewska-Gibert, A.; Cazelles, B.

    2013-12-01

    Dengue is a peri-urban mosquito-transmitted disease, ubiquitous in the tropics and the subtropics. The geographic distribution of dengue and its more severe form, dengue haemorrhagic fever (DHF), have expanded dramatically in the last decades and dengue is now considered to be the world's most important arboviral disease. Recent demographic changes have greatly contributed to the acceleration and spread of the disease along with uncontrolled urbanization, population growth and increased air travel, which acts as a mechanism for transporting and exchanging dengue viruses between endemic and epidemic populations. The dengue vector and virus are extremely sensitive to environmental conditions such as temperature, humidity and precipitation that influence mosquito biology, abundance and habitat and the virus replication speed. In order to control the spread of dengue and impede epidemics, decision support systems are required that take into account the multi-faceted array of factors that contribute to increased dengue risk. Due to availability of seasonal climate forecasts, that predict the average climate conditions for forthcoming months/seasons in both time and space, there is an opportunity to incorporate precursory climate information in a dengue decision support system to aid epidemic planning months in advance. Furthermore, oceanic indicators from teleconnected areas in the Pacific and Indian Ocean, that can provide some indication of the likely prevailing climate conditions in certain regions, could potentially extend predictive lead time in a dengue early warning system. In this paper we adopt a spatio-temporal Bayesian modelling framework for dengue in Thailand to support public health decision making. Monthly cases of dengue in the 76 provinces of Thailand for the period 1982-2012 are modelled using a multi-layered approach. Explanatory variables at various spatial and temporal resolutions are incorporated into a hierarchical model in order to make spatio-temporal

  7. The spatio-temporal relationship between alcohol outlets and violence before and after privatization: A natural experiment, Seattle, Wa 2010-2013.

    PubMed

    Tabb, Loni Philip; Ballester, Lance; Grubesic, Tony H

    2016-11-01

    Alcohol-related violence is a well-documented public health concern, where various individual and community-level factors contribute to this relationship. The purpose of this study is to examine the impact of a significant policy change at the local level, which privatized liquor sales and distribution. Specifically, we explored the relationship between alcohol and violence in Seattle, WA, 2010-2013, via hierarchical spatio-temporal disease mapping models. To measure and map this complex spatio-temporal relationship at the census block group level (n=567), we examined a variety of models using integrated nested Laplace approximations and used the deviance information criterion to gauge model complexity and fit. For each additional off-premises and on-premises alcohol outlet in a given census block group, we found a significant increase of 8% and 5% for aggravated assaults and 6% and 5% for non-aggravated assaults, respectively. Lastly, our maps showed variation in the estimated relative risks across the city of Seattle.

  8. Gait characteristics and spatio-temporal variables of climbing in bonobos (Pan paniscus).

    PubMed

    Schoonaert, Kirsten; D'Août, Kristiaan; Samuel, Diana; Talloen, Willem; Nauwelaerts, Sandra; Kivell, Tracy L; Aerts, Peter

    2016-11-01

    Although much is known about the terrestrial locomotion of great apes, their arboreal locomotion has been studied less extensively. This study investigates arboreal locomotion in bonobos (Pan paniscus), focusing on the gait characteristics and spatio-temporal variables associated with locomotion on a pole. These features are compared across different substrate inclinations (0°, 30°, 45°, 60°, and 90°), and horizontal quadrupedal walking is compared between an arboreal and a terrestrial substrate. Our results show greater variation in footfall patterns with increasing incline, resulting in more lateral gait sequences. During climbing on arboreal inclines, smaller steps and strides but higher stride frequencies and duty factors are found compared to horizontal arboreal walking. This may facilitate better balance control and dynamic stability on the arboreal substrate. We found no gradual change in spatio-temporal variables with increasing incline; instead, the results for all inclines were clustered together. Bonobos take larger strides at lower stride frequencies and lower duty factors on a horizontal arboreal substrate than on a flat terrestrial substrate. We suggest that these changes are the result of the better grip of the grasping feet on an arboreal substrate. Speed modulation of the spatio-temporal variables is similar across substrate inclinations and between substrate types, suggesting a comparable underlying motor control. Finally, we contrast these variables of arboreal inclined climbing with those of terrestrial bipedal locomotion, and briefly discuss the results with respect to the origin of habitual bipedalism. Am. J. Primatol. 78:1165-1177, 2016. © 2016 Wiley Periodicals, Inc.

  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. 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.

  11. Sensitivity of cochlear nucleus neurons to spatio-temporal changes in auditory nerve activity

    PubMed Central

    Wang, Grace I.

    2012-01-01

    The spatio-temporal pattern of auditory nerve (AN) activity, representing the relative timing of spikes across the tonotopic axis, contains cues to perceptual features of sounds such as pitch, loudness, timbre, and spatial location. These spatio-temporal cues may be extracted by neurons in the cochlear nucleus (CN) that are sensitive to relative timing of inputs from AN fibers innervating different cochlear regions. One possible mechanism for this extraction is “cross-frequency” coincidence detection (CD), in which a central neuron converts the degree of coincidence across the tonotopic axis into a rate code by preferentially firing when its AN inputs discharge in synchrony. We used Huffman stimuli (Carney LH. J Neurophysiol 64: 437–456, 1990), which have a flat power spectrum but differ in their phase spectra, to systematically manipulate relative timing of spikes across tonotopically neighboring AN fibers without changing overall firing rates. We compared responses of CN units to Huffman stimuli with responses of model CD cells operating on spatio-temporal patterns of AN activity derived from measured responses of AN fibers with the principle of cochlear scaling invariance. We used the maximum likelihood method to determine the CD model cell parameters most likely to produce the measured CN unit responses, and thereby could distinguish units behaving like cross-frequency CD cells from those consistent with same-frequency CD (in which all inputs would originate from the same tonotopic location). We find that certain CN unit types, especially those associated with globular bushy cells, have responses consistent with cross-frequency CD cells. A possible functional role of a cross-frequency CD mechanism in these CN units is to increase the dynamic range of binaural neurons that process cues for sound localization. PMID:22972956

  12. Spatio-temporal availability of soft mast in clearcuts in the Southern Appalachians

    USGS Publications Warehouse

    Reynolds-Hogland, M. J.; Mitchell, M.S.; Powell, R.A.

    2006-01-01

    Soft mast is an important resource for many wild populations in the Southern Appalachians, yet the way clear-cutting affects availability of soft mast though time is not fully understood. We tested a theoretical model of temporal availability of soft mast in clearcuts using empirical data on percent cover and berry production of Gaylussacia, Vaccinium, and Rubus spp. plants in 100 stands that were clearcut (0-122 years old) in the Southern Appalachian Mountains. We modeled the relationship between soft mast availability and stand age, evaluated the effects of topography and forest type on soft mast, developed statistical models for predicting the spatio-temporal distribution of soft mast, and tested the hypothesis that percent cover of berry plants and berry production provided similar information about soft mast availability. We found temporal dynamics explained berry production better than it predicted percent plant cover, whereas topographic variables influenced percent plant cover more than they influenced berry production. Berry production and percent plant cover were highest in ???2-9-year-old stands. Percent plant cover was lowest in 10-69-year-old stands and intermediate in 70+-year-old stands. Three of our spatio-temporal models performed well during model testing and they were not biased by the training data, indicating the inferences about spatio-temporal availability of soft mast extended beyond our sample data. The methods we used to estimate the distribution of soft mast may be useful for modeling distributions of other resources. ?? 2006 Elsevier B.V. All rights reserved.

  13. 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

  14. Bayesian spatio-temporal modelling of tobacco-related cancer mortality in Switzerland.

    PubMed

    Jürgens, Verena; Ess, Silvia; Phuleria, Harish C; Früh, Martin; Schwenkglenks, Matthias; Frick, Harald; Cerny, Thomas; Vounatsou, Penelope

    2013-05-01

    Tobacco smoking is a main cause of disease in Switzerland; lung cancer being the most common cancer mortality in men and the second most common in women. Although disease-specific mortality is decreasing in men, it is steadily increasing in women. The four language regions in this country might play a role in this context as they are influenced in different ways by the cultural and social behaviour of neighbouring countries. Bayesian hierarchical spatio-temporal, negative binomial models were fitted on subgroup-specific death rates indirectly standardized by national references to explore age- and gender-specific spatio-temporal patterns of mortality due to lung cancer and other tobacco-related cancers in Switzerland for the time period 1969-2002. Differences influenced by linguistic region and life in rural or urban areas were also accounted for. Male lung cancer mortality was found to be rather homogeneous in space, whereas women were confirmed to be more affected in urban regions. Compared to the German-speaking part, female mortality was higher in the French-speaking part of the country, a result contradicting other reports of similar comparisons between France and Germany. The spatio-temporal patterns of mortality were similar for lung cancer and other tobacco-related cancers. The estimated mortality maps can support the planning in health care services and evaluation of a national tobacco control programme. Better understanding of spatial and temporal variation of cancer of the lung and other tobacco-related cancers may help in allocating resources for more effective screening, diagnosis and therapy. The methodology can be applied to similar studies in other settings.

  15. 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

  16. 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.

  17. Spatio-temporal changes in agrochemical inputs and the risk assessment before and after the Grain-For-Green Policy in China.

    PubMed

    Wang, Xiuhong

    2013-02-01

    China's Grain-For-Green Policy (GFGP) of returning marginal cropland to forest or grassland is one of the most important large-scale initiatives to combat land degradation in its ecologically vulnerable regions. In order to maintain and increase crop production from decreasing areas of cropland, substantial spatio-temporal changes in agrochemical inputs have occurred, which have strongly influenced the ecological and environmental status of land in China. Based on the agrochemical inputs (chemical fertilizer, pesticide, plastic sheeting, and agricultural diesel oil) at the provincial level between 1993 and 2009, cluster analysis and gravity center modeling were used to trace these spatio-temporal changes. A regional comparative study was also undertaken to investigate the changes in the relative size of agrochemical inputs in the eastern, central, and western regions of China. It was found that the agrochemical inputs increased considerably at the nation level after the GFGP, which in order of increasing rate were: plastic sheeting > agricultural diesel oil > pesticide > chemical fertilizer. The gravity centers of agrochemical inputs moved substantially towards the northwest or west during the latter period of GFGP and regional comparative analysis showed that the agrochemical inputs increased substantially in the western region between 2004 and 2009. The ecological degradation caused by the expansion of the area devoted to crop production in the western region and the potential risk of agricultural non-point pollution caused by the increasing agrochemical inputs are the main factors restricting this area's sustainable development.

  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 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.

  20. Population dynamics of wetland fishes: Spatio-temporal patterns synchronized by hydrological disturbance?

    USGS Publications Warehouse

    Ruetz, C. R.; Trexler, J.C.; Jordan, F.; Loftus, W.F.; Perry, S.A.

    2005-01-01

    1. Drought is a natural disturbance that can cause widespread mortality of aquatic organisms in wetlands. We hypothesized that seasonal drying of marsh surfaces (i.e. hydrological disturbance) shapes spatio-temporal patterns of fish populations. 2. We tested whether population dynamics of fishes were synchronized by hydrological disturbance (Moran effect) or distance separating study sites (dispersal). Spatio-temporal patterns were examined in local populations of five abundant species at 17 sites (sampled five times per year from 1996 to 2001) in a large oligotrophic wetland. 3. Fish densities differed significantly across spatio-temporal scales for all species. For all species except eastern mosquitofish (Gambusia holbrooki), a significant portion of spatio-temporal variation in density was attributed to drying events (used as a covariate). 4. We observed three patterns of response to hydrological disturbance. Densities of bluefin killifish (Lucania goodei), least killifish (Heterandria formosa), and golden top-minnow (Fundulus chrysotus) were usually lowest after a dry down and recovered slowly. Eastern mosquitofish showed no distinct response to marsh drying (i.e. they recovered quickly). Flagfish (Jordanella floridae) density was often highest after a dry down and then declined. Population growth after a dry down was often asymptotic for bluefin killifish and golden topminnow, with greatest asymptotic density and longest time to recovery at sites that dried infrequently. 5. Fish population dynamics were synchronized by hydrological disturbance (independent of distance) and distance separating study sites (independent of hydrological disturbance). Our ability to separate the relative importance of the Moran effect from dispersal was strengthened by a weak association between hydrological synchrony and distance among study sites. Dispersal was the primary mechanism for synchronous population dynamics of flagfish, whereas hydrological disturbance was the primary

  1. 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

    2014-05-06

    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

  2. Synchronization and information transmission in spatio-temporal networks of deformable units

    NASA Astrophysics Data System (ADS)

    Moukam Kakmeni, F. M.; Baptista, M. S.

    2008-06-01

    We study the relationship between synchronization and the rate with which information is exchanged between nodes in a spatio-temporal network that describes the dynamics of classical particles under a substrate Remoissenet-Peyrard potential. We also show how phase and complete synchronization can be detected in this network. The difficulty in detecting phase synchronization in such a network appears due to the highly non-coherent character of the particle dynamics which unables a proper definition of the phase dynamics. The difficulty in detecting complete synchronization appears due to the spatio character of the potential which results in an asymptotic state highly dependent on the initial state.

  3. Spatio-temporal modelling for assessing air pollution in Santiago de Chile

    NASA Astrophysics Data System (ADS)

    Nicolis, Orietta; Camaño, Christian; Mařın, Julio C.; Sahu, Sujit K.

    2017-01-01

    In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)

  4. 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.

  5. Distributed Configuration of Sensor Network for Fault Detection in Spatio-Temporal Systems

    NASA Astrophysics Data System (ADS)

    Patan, Maciej; Kowalów, Damian

    2017-01-01

    The problem of fault detection in spatio-temporal systems is formulated as that of maximizing the power of a parametric hypothesis test verifying the nominal state of the process under consideration. Then, adopting a pairwise communication schemes, a computational procedure is developed for the spatial configuration of the observation locations for sensor network which monitor changes in the underlying parameters of a distributed parameter system. As a result, the problem of planning the percentage of experimental effort spent at given sensor locations can be solved in a fully decentralized fashion. The approach is verified on a numerical example involving sensor selection for a convective diffusion process.

  6. 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.

  7. Spatio-temporal organization of replication in bacteria and eukaryotes (nucleoids and nuclei).

    PubMed

    Jackson, Dean; Wang, Xindan; Rudner, David Z

    2012-08-01

    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.

  8. Detailed analysis of the spatio-temporal evolution of tremor, foreshock, and aftershock activities near the September 5, 2012 Nicoya Peninsula earthquake

    NASA Astrophysics Data System (ADS)

    Walter, J. I.; Peng, Z.; Schwartz, S. Y.; Meng, X.; Newman, A. V.; Protti, M.

    2013-05-01

    The subduction megathrust interface, at the Nicoya Peninsula, exhibits a wide range of complex fault behavior, from recently discovered slow slip and tremor, numerous microearthquakes, to infrequent megathrust (> Mw 7) earthquakes. In contrast to other subduction zones, the Nicoya tremor originates up-dip, down-dip, and within the seismogenic zone. The September 5, 2012 earthquake makes the Nicoya Peninsula uniquely poised to investigate the wide range of fault behavior and spatio-temporal evolution of seismic activity around the mainshock, as the seismogenic zone lies directly below the Peninsula. Preliminary matched-filter analysis using a template earthquake that precedes the mainshock by ~120 s indicates similar events occurring 20-40 min prior to the mainshock, as well as, immediately following the mainshock. We are expanding this analysis with a broader catalogue of template events and utilizing matched-filter codes optimized for graphics processing units (GPUs). While detailed analysis of the foreshock/aftershock sequence is ongoing, the early aftershocks cluster in a distinct region that is immediately adjacent to regions that have undergone slow slip in past events. We hope to gain better insight into the spatio-temporal transitions from stable sliding to stick-slip motion, and underlying physics of earthquake nucleation and interaction.

  9. Spatio-temporal rectification of tower-based eddy-covariance flux measurements for consistently informing process-based models

    NASA Astrophysics Data System (ADS)

    Metzger, S.; Xu, K.; Desai, A. R.; Taylor, J. R.; Kljun, N.; Schneider, D.; Kampe, T. U.; Fox, A. M.

    2013-12-01

    Process-based models, such as land surface models (LSMs), allow insight in the spatio-temporal distribution of stocks and the exchange of nutrients, trace gases etc. among environmental compartments. More recently, LSMs also become capable of assimilating time-series of in-situ reference observations. This enables calibrating the underlying functional relationships to site-specific characteristics, or to constrain the model results after each time-step in an attempt to minimize drift. The spatial resolution of LSMs is typically on the order of 10^2-10^4 km2, which is suitable for linking regional to continental scales and beyond. However, continuous in-situ observations of relevant stock and exchange variables, such as tower-based eddy-covariance (EC) fluxes, represent orders of magnitude smaller spatial scales (10^-6-10^1 km2). During data assimilation, this significant gap in spatial representativeness is typically either neglected, or side-stepped using simple tiling approaches. Moreover, at ';coarse' resolutions, a single LSM evaluation per time-step implies linearity among the underlying functional relationships as well as among the sub-grid land cover fractions. This, however, is not warranted for land-atmosphere exchange processes over more complex terrain. Hence, it is desirable to explicitly consider spatial variability at LSM sub-grid scales. Here we present a procedure that determines from a single EC tower the spatially integrated probability density function (PDF) of the surface-atmosphere exchange for individual land covers. These PDFs allow quantifying the expected value, as well as spatial variability over a target domain, can be assimilated in tiling-capable LSMs, and mitigate linearity assumptions at ';coarse' resolutions. The procedure is based on the extraction and extrapolation of environmental response functions (ERFs), for which a technical-oriented companion poster is submitted. In short, the subsequent steps are: (i) Time

  10. Spatio-temporal variability of droughts and terrestrial water storage over Lake Chad Basin using independent component analysis

    NASA Astrophysics Data System (ADS)

    Ndehedehe, Christopher E.; Agutu, Nathan O.; Okwuashi, Onuwa; Ferreira, Vagner G.

    2016-09-01

    Lake Chad has recently been perceived to be completely desiccated and almost extinct due to insufficient published ground observations. Given the high spatial variability of rainfall in the region, and the fact that extreme climatic conditions (for example, droughts) could be intensifying in the Lake Chad basin (LCB) due to human activities, a spatio-temporal approach to drought analysis becomes essential. This study employed independent component analysis (ICA), a fourth-order cumulant statistics, to decompose standardised precipitation index (SPI), standardised soil moisture index (SSI), and terrestrial water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) into spatial and temporal patterns over the LCB. In addition, this study uses satellite altimetry data to estimate variations in the Lake Chad water levels, and further employs relevant climate teleconnection indices (El-Niño Southern Oscillation-ENSO, Atlantic Multi-decadal Oscillation-AMO, and Atlantic Meridional Mode-AMM) to examine their links to the observed drought temporal patterns over the basin. From the spatio-temporal drought analysis, temporal evolutions of SPI at 12 month aggregation show relatively wet conditions in the last two decades (although with marked alterations) with the 2012-2014 period being the wettest. In addition to the improved rainfall conditions during this period, there was a statistically significant increase of 0.04 m/yr in altimetry water levels observed over Lake Chad between 2008 and 2014, which confirms a shift in the hydrological conditions of the basin. Observed trend in TWS changes during the 2002-2014 period shows a statistically insignificant increase of 3.0 mm/yr at the centre of the basin, coinciding with soil moisture deficit indicated by the temporal evolutions of SSI at all monthly accumulations during the 2002-2003 and 2009-2012 periods. Further, SPI at 3 and 6 month scales indicated fluctuating drought conditions at the extreme south

  11. 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.

  12. 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.

  13. Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

    PubMed Central

    Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

    2017-01-01

    Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns. PMID:28383525

  14. Spatio-temporal modelling of individual exposure to air pollution and its uncertainty

    NASA Astrophysics Data System (ADS)

    Gerharz, Lydia E.; Klemm, Otto; Broich, Anna V.; Pebesma, Edzer

    2013-01-01

    We developed a generic spatio-temporal model to quantify individual exposure to air pollution, using personal activity profiles derived from GPS and diaries, ambient air quality, and an indoor model. To enhance accessibility and reusability, the model approach is deployed as a web service. The model is applied to estimate personal exposure towards PM10 and PM2.5 for ten individuals in Münster, Germany. Modelled daily averages range for PM10 between 17 and 126 and between 6 and 84 μg m-3 for PM2.5. Comparison with personal monitoring data shows good agreement at temporal resolutions from 5 min to one day. Uncertainties in the model results are considerable and increase with higher exposure levels. Large deviations between modelled and measured exposure can often be explained by missing data on indoor emissions or insufficiently detailed activity diaries. The developed model allows the assessment of individual exposure with uncertainties on a high spatio-temporal resolution. By providing the methodology through a web service interface and using generic indoor parameter distributions, the model can be easily transferred to new application areas or could be provided for public use to identify hazardous exposure events.

  15. 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.

  16. Automatic identification of seismic swarms and other spatio-temporal clustering from catalogs

    NASA Astrophysics Data System (ADS)

    Nava, F. Alejandro; Glowacka, Ewa

    1994-06-01

    Statistical analysis of seismic catalogs usually requires identification of swarms and foreshocks-main event-aftershocks sequences-a tedious and time-consuming chore. SWaRMSHoW, a simple but versatile QBASIC program for PC, graphically displays on screen catalog epicentral activity, with optional temporal distribution scaling; identifies spatio-temporal hypocentral clusters (SwrSeq) which may be swarms or foreshocks-main event-aftershocks sequences and discriminates between these; and displays SwrSeq locations and limits, and assigns them equivalent magnitudes corresponding to those of single events having seismic energy equal to that of the whole SwrSeq. SWaRMSHoW features optional detailed disk output of swarms and clusters, including origin time, location, constituent events, equivalent magnitudes, and current parameters, that allows easy application of results. Graphic screen display includes optional maps and drawings. Operation can be completely automatic or interactive. Working parameters can be reset at any time during operation. Besides swarm and sequence identification, this program's modeling of the seismicity, scaled in both space and time, is useful for studying many aspects of spatio-temporal seismicity, such as fault activation, migration of activity, quiescence, etc.

  17. Spatio-temporal variability in sea surface temperatures for the Yellow Sea based on MODIS dataset

    NASA Astrophysics Data System (ADS)

    Liu, Chunli; Sun, Qiwei; Xing, Qianguo; Liang, Zhenlin; Deng, Yue; Zhu, Lixin

    2017-02-01

    The spatio-temporal variabilities in sea surface temperature (SST) were analyzed using a time series of MODIS datasets for four separate regions in the Yellow Sea (YS) that were located along a north-south axis. The space variant temporal anomaly was further decomposed using an empirical orthogonal function (EOF) for estimating spatially distributed SST. The monthly SSTs showed similar temporal patterns in each region, which ranged from 2.4°C to 28.4°C in the study years 2011 to 2013, with seasonal cycles being stronger at the higher latitudes and weaker at the lower latitudes. Spatially, although there were no significant differences among the four regions (p < 0.05) in any year, the geographical distribution of SST was characterized by an obvious gradient whereby SST decreased along the north-south axis. The monthly thermal difference among regions was largest in winter since the SST in the southeast was mainly affected by the Yellow Sea Warm Currents. The EOF1 mode accounted for 56% of the total spatial variance and exhibited a warming signal during the study period. The EOF2 mode accounted for 8% of the total variance and indicated the warm current features in the YS. The EOF3 mode accounted for 6% of the total variance and indicated the topographical features. The methodology used in this study demonstrated the spatio-temporal variabilities in the YS.

  18. 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.

  19. Lattice dynamical wavelet neural networks implemented using particle swarm optimization for spatio-temporal system identification.

    PubMed

    Wei, Hua-Liang; Billings, Stephen A; Zhao, Yifan; Guo, Lingzhong

    2009-01-01

    In this brief, by combining an efficient wavelet representation with a coupled map lattice model, a new family of adaptive wavelet neural networks, called lattice dynamical wavelet neural networks (LDWNNs), is introduced for spatio-temporal system identification. A new orthogonal projection pursuit (OPP) method, coupled with a particle swarm optimization (PSO) algorithm, is proposed for augmenting the proposed network. A novel two-stage hybrid training scheme is developed for constructing a parsimonious network model. In the first stage, by applying the OPP algorithm, significant wavelet neurons are adaptively and successively recruited into the network, where adjustable parameters of the associated wavelet neurons are optimized using a particle swarm optimizer. The resultant network model, obtained in the first stage, however, may be redundant. In the second stage, an orthogonal least squares algorithm is then applied to refine and improve the initially trained network by removing redundant wavelet neurons from the network. An example for a real spatio-temporal system identification problem is presented to demonstrate the performance of the proposed new modeling framework.

  20. An adaptive wavelet neural network for spatio-temporal system identification.

    PubMed

    Wei, H L; Billings, S A; Zhao, Y F; Guo, L Z

    2010-12-01

    Starting from the basic concept of coupled map lattices, a new family of adaptive wavelet neural networks (AWNN) is introduced for spatio-temporal system identification, by combining an efficient wavelet representation with a coupled map lattice model. A new orthogonal projection pursuit (OPP) method, coupled with a particle swarm optimization (PSO) algorithm, is proposed for augmenting the proposed network. A novel two-stage hybrid training scheme is developed for constructing a parsimonious network model. In the first stage, by applying the orthogonal projection pursuit algorithm, significant wavelet neurons are adaptively and successively recruited into the network, where adjustable parameters of the associated wavelet neurons are optimized using a particle swarm optimizer. The resultant network model, obtained in the first stage, may however be redundant. In the second stage, an orthogonal least squares algorithm is then applied to refine and improve the initially trained network by removing redundant wavelet neurons from the network. The proposed two-stage hybrid training procedure can generally produce a parsimonious network model, where a ranked list of wavelet neurons, according to the capability of each neuron to represent the total variance in the system output signal is produced. Two spatio-temporal system identification examples are presented to demonstrate the performance of the proposed new modelling framework.

  1. Mining and analysing spatio-temporal patterns of gene expression in an integrative database framework.

    PubMed

    Belmamoune, M; Potikanond, D; Verbeek, F J

    2010-03-25

    Mining patterns of gene expression provides a crucial approach in discovering knowledge such as finding genetic networks that underpin the embryonic development. Analysis of mining results and evaluation of their relevance in the domain remains a major concern. In this paper we describe our explorative studies in support of solutions to facilitate the analysis and interpretation of mining results. In our particular case we describe a solution that is found in the extension of the Gene Expression Management System (GEMS), i.e. an integrative framework for spatio-temporal organization of gene expression patterns of zebrafish to a framework supporting data mining, data analysis and patterns interpretation As a proof of principle, the GEMS has been equipped with data mining functionality suitable for spatio-temporal tracking, thereby generating added value to the submission of data for data mining and analysis. The analysis of the genetic networks is based on the availability of domain ontologies which dynamically provides meaning to the discovered patterns of gene expression data. Combination of data mining with the already presently available capabilities of GEMS will significantly augment current data processing and functional analysis strategies.

  2. Spatio-temporal pattern of EEG in young brain respiration-training children.

    PubMed

    Kim, H R; Kim, S Y; Kim, D J; Kim, Y Y; Park, S K; Chae, J H; Kim, K S; Lee, K H; Lee, S H

    2001-01-01

    We have evaluated the effect of 'Brain Respiration' training on brain activity using Karhunen-Loeve (KL) decomposition as a method for spatio-temporal analysis of the electroencephalogram (EEG). BR training is a form of breath-work to optimize the function of the brain by concentrating Qi energy in the brain. Recently, BR-training has been reported to improve emotional maturity (i.e., EQ), short-term memory and intuition (Yoo et al., 1998). EEG data were taken during BR-training from 12 young BR-trainees (average age: 9.4 years) who had trained for 4 to 14 months, and during relaxation from age matched non-trained children. Spatio-temporal analysis showed a significant difference of EEG dynamics in right prefrontal, right inferior frontal, posterior temporal, parietal and occipital areas between BR-trainees and the control group. Amplitude of eigenvector components of BR-trainees in the areas of frontal, temporal and occipital cortex was larger than that of non-trained children (values were smaller in parietal cortex), with remarkably high amplitude alpha coherence all over the scalp. These results suggest that BR-training possibly activates brain function through changes in the activity of the frontal association area where higher mental integration and creative activities are mediated.

  3. 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.

  4. Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

    PubMed

    Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

    2013-09-01

    Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. .

  5. Spatio-temporal variations of precipitation considering the orographic effects on Jeju Island

    NASA Astrophysics Data System (ADS)

    Um, Myoung-Jin; Heo, Jun-Haeng; Kim, Nam-Won

    2016-11-01

    In this study, we use factor analysis and spatial analysis to study the spatio-temporal distribution of daily precipitation on Jeju Island, which includes marine and mountainous areas. The precipitation time series from 82 weather stations were used to fill in missing and ungauged data for some periods at 38 stations, and then the daily spatial distribution was analyzed from 1992 to 2013. Factor analysis and multiple regression showed that the statistical characteristics of the extended data fit well to those of the observed time series. The point precipitation characteristics, such as the mean and standard deviation, show small differences between observed and extended data, and the relationships to elevation also have similar behavior for seasonal and annual precipitation. However, the spatial precipitation characteristics for observed and extended data show significant differences with respect to elevation because the data for high-elevation areas are mainly interpolated for the period 1992 to 2013. For annual and five-year moving-average spatial precipitation, the amount of precipitation shows seasonal and spatial variability. Annual spatial precipitation in high-elevation areas usually shows high variation over time. These results suggest the need to consider completing missing and ungauged data series for assessment the spatio-temporal variation of precipitation.

  6. Small-Scale Spatio-Temporal Distribution of Bactrocera minax (Enderlein) (Diptera: Tephritidae) Using Probability Kriging.

    PubMed

    Wang, S Q; Zhang, H Y; Li, Z L

    2016-10-01

    Understanding spatio-temporal distribution of pest in orchards can provide important information that could be used to design monitoring schemes and establish better means for pest control. In this study, the spatial and temporal distribution of Bactrocera minax (Enderlein) (Diptera: Tephritidae) was assessed, and activity trends were evaluated by using probability kriging. Adults of B. minax were captured in two successive occurrences in a small-scale citrus orchard by using food bait traps, which were placed both inside and outside the orchard. The weekly spatial distribution of B. minax within the orchard and adjacent woods was examined using semivariogram parameters. The edge concentration was discovered during the most weeks in adult occurrence, and the population of the adults aggregated with high probability within a less-than-100-m-wide band on both of the sides of the orchard and the woods. The sequential probability kriged maps showed that the adults were estimated in the marginal zone with higher probability, especially in the early and peak stages. The feeding, ovipositing, and mating behaviors of B. minax are possible explanations for these spatio-temporal patterns. Therefore, spatial arrangement and distance to the forest edge of traps or spraying spot should be considered to enhance pest control on B. minax in small-scale orchards.

  7. Spatio-temporal approach to moving window block kriging of satellite data v1.0

    NASA Astrophysics Data System (ADS)

    Tadić, Jovan M.; Qiu, Xuemei; Miller, Scot; Michalak, Anna M.

    2017-02-01

    Numerous existing satellites observe physical or environmental properties of the Earth system. Many of these satellites provide global-scale observations, but these observations are often sparse and noisy. By contrast, contiguous, global maps are often most useful to the scientific community (i.e., Level 3 products). We develop a spatio-temporal moving window block kriging method to create contiguous maps from sparse and/or noisy satellite observations. This approach exhibits several advantages over existing methods: (1) it allows for flexibility in setting the spatial resolution of the Level 3 map, (2) it is applicable to observations with variable density, (3) it produces a rigorous uncertainty estimate, (4) it exploits both spatial and temporal correlations in the data, and (5) it facilitates estimation in real time. Moreover, this approach only requires the assumption that the observable quantity exhibits spatial and temporal correlations that are inferable from the data. We test this method by creating Level 3 products from satellite observations of CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT), CH4 (XCH4) from the Infrared Atmospheric Sounding Interferometer (IASI) and solar-induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). We evaluate and analyze the difference in performance of spatio-temporal vs. recently developed spatial kriging methods.

  8. Detecting spatio-temporal modes in multivariate data by entropy field decomposition

    NASA Astrophysics Data System (ADS)

    Frank, Lawrence R.; Galinsky, Vitaly L.

    2016-09-01

    A new data analysis method that addresses a general problem of detecting spatio-temporal variations in multivariate data is presented. The method utilizes two recent and complimentary general approaches to data analysis, information field theory (IFT) and entropy spectrum pathways (ESPs). Both methods reformulate and incorporate Bayesian theory, thus use prior information to uncover underlying structure of the unknown signal. Unification of ESP and IFT creates an approach that is non-Gaussian and nonlinear by construction and is found to produce unique spatio-temporal modes of signal behavior that can be ranked according to their significance, from which space-time trajectories of parameter variations can be constructed and quantified. Two brief examples of real world applications of the theory to the analysis of data bearing completely different, unrelated nature, lacking any underlying similarity, are also presented. The first example provides an analysis of resting state functional magnetic resonance imaging data that allowed us to create an efficient and accurate computational method for assessing and categorizing brain activity. The second example demonstrates the potential of the method in the application to the analysis of a strong atmospheric storm circulation system during the complicated stage of tornado development and formation using data recorded by a mobile Doppler radar. Reference implementation of the method will be made available as a part of the QUEST toolkit that is currently under development at the Center for Scientific Computation in Imaging.

  9. 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

  10. Spatio-temporal variability in sea surface temperatures for the Yellow Sea based on MODIS dataset

    NASA Astrophysics Data System (ADS)

    Liu, Chunli; Sun, Qiwei; Xing, Qianguo; Liang, Zhenlin; Deng, Yue; Zhu, Lixin

    2017-03-01

    The spatio-temporal variabilities in sea surface temperature (SST) were analyzed using a time series of MODIS datasets for four separate regions in the Yellow Sea (YS) that were located along a north-south axis. The space variant temporal anomaly was further decomposed using an empirical orthogonal function (EOF) for estimating spatially distributed SST. The monthly SSTs showed similar temporal patterns in each region, which ranged from 2.4°C to 28.4°C in the study years 2011 to 2013, with seasonal cycles being stronger at the higher latitudes and weaker at the lower latitudes. Spatially, although there were no significant differences among the four regions ( p < 0.05) in any year, the geographical distribution of SST was characterized by an obvious gradient whereby SST decreased along the north-south axis. The monthly thermal difference among regions was largest in winter since the SST in the southeast was mainly affected by the Yellow Sea Warm Currents. The EOF1 mode accounted for 56% of the total spatial variance and exhibited a warming signal during the study period. The EOF2 mode accounted for 8% of the total variance and indicated the warm current features in the YS. The EOF3 mode accounted for 6% of the total variance and indicated the topographical features. The methodology used in this study demonstrated the spatio-temporal variabilities in the YS.

  11. 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.

  12. 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.

  13. A dense array stimulator to generate arbitrary spatio-temporal tactile stimuli

    PubMed Central

    Killebrew, Justin H.; Bensmaïa, Sliman J.; Dammann, John F.; Denchev, Peter; Hsiao, Steven S.; Craig, James C.

    2007-01-01

    The generation and presentation of tactile stimuli presents a unique challenge. Unlike vision and audition, in which standard equipment such as monitors and audio systems can be used for most experiments, tactile stimuli and/or stimulators often have to be tailor-made for a given study. Here, we present a novel tactile stimulator designed to present arbitrary spatio-temporal stimuli to the skin. The stimulator consists of 400 pins, arrayed over a 1 cm2 area, each under independent computer control. The dense array allows for an unprecedented number of stimuli to be presented within an experimental session (e.g., up to 1200 stimuli per minute) and for stimuli to be generated adaptively. The stimulator can be used in a variety of modes and can deliver indented and scanned patterns as well as stimuli defined by mathematical spatio-temporal functions (e.g., drifting sinusoids). We describe the hardware and software of the system, and discuss previous and prospective applications. PMID:17134760

  14. 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.

  15. 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.

  16. 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.

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

    PubMed

    Bartolino, Valerio; Tian, Huidong; Bergström, Ulf; Jounela, Pekka; Aro, Eero; Dieterich, Christian; Meier, H E Markus; Cardinale, Massimiliano; Bland, Barbara; Casini, Michele

    2017-01-01

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

  18. 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

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

    PubMed Central

    Bartolino, Valerio; Tian, Huidong; Bergström, Ulf; Jounela, Pekka; Aro, Eero; Dieterich, Christian; Meier, H. E. Markus; Cardinale, Massimiliano; Bland, Barbara

    2017-01-01

    Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes. PMID:28207804

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

    PubMed

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

    2015-12-14

    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.

  1. 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

  2. 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.

  3. 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

  4. A Groud and Aerial BattleField Spatio-Temporal Data Unified OrganizeModel and Aplication

    NASA Astrophysics Data System (ADS)

    Feng, LI; Qin, Li; Gang, WAN; Xuefeng, CAO

    2016-11-01

    Aiming at the requirement of battlefield environment data model in joint operations, this paper proposed a groud and aerial battlefield spatio-temporal data unified organize model based on grid division. The thought of shere grid division is adopt to divide the space, and extend to the time dimension. Also, the spatio-temporal grid coding is designed. The field and object are combined to build the BSTD organization model, where the panet layer unit and panet volume unit are considered as the reference space separately to quantitatively describe the field, and the spatio-temporal grid coding is adopt to describe the space and time attributes of the objects. The relevant experiment is designed in paratroop tactics wargame simulation, and the results verify the feasibility of the model.

  5. 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

  6. Spatio-temporal flow analysis in bileaflet heart valve hinge regions: potential analysis for blood element damage.

    PubMed

    Simon, Hélène A; Dasi, Lakshmi P; Leo, Hwa-Liang; Yoganathan, Ajit P

    2007-08-01

    Point-wise velocity measurements have been traditionally acquired to estimate blood damage potential induced by prosthetic heart valves with emphasis on peak values of velocity magnitude and Reynolds stresses. However, the inherently Lagrangian nature of platelet activation and hemolysis makes such measurements of limited predictive value. This study provides a refined fluid mechanical analysis, including blood element paths and stress exposure times, of the hinge flows of a CarboMedics bileaflet mechanical heart valve placed under both mitral and aortic conditions and a St Jude Medical bileaflet valve placed under aortic conditions. The hinge area was partitioned into characteristic regions based on dominant flow structures and spatio-temporal averaging was performed on the measured velocities and Reynolds shear stresses to estimate the average bulk stresses acting on blood elements transiting through the hinge. A first-order estimate of viscous stress levels and exposure times were computed. Both forward and leakage flow phases were characterized in each partition by dynamic flows dependent on subtle leaflet movements and transvalvular pressure fluctuations. Blood elements trapped in recirculation regions may experience exposure times as long as the entire forward flow phase duration. Most calculated stresses were below the accepted blood damage threshold. Estimates of the stress levels indicate that the flow conditions within the boundary layers near the hinge and leaflet walls may be more detrimental to blood cells than bulk flow conditions, while recirculation regions may promote thrombus buildup.

  7. Spatio-temporal changes of photosynthesis in carnivorous plants in response to prey capture, retention and digestion.

    PubMed

    Pavlovič, Andrej

    2010-11-01

    Carnivorous plants have evolved modified leaves into the traps which assist in nutrient uptake from captured prey. It is known that the traps of carnivorous plants have usually 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 (Ф PSII) in response to ant-derived formic acid during its capture and digestion.

  8. 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.

  9. Spatio-temporal coherence of free-electron laser radiation in the extreme ultraviolet determined by a Michelson interferometer

    NASA Astrophysics Data System (ADS)

    Hilbert, V.; Rödel, C.; Brenner, G.; Döppner, T.; Düsterer, S.; Dziarzhytski, S.; Fletcher, L.; Förster, E.; Glenzer, S. H.; Harmand, M.; Hartley, N. J.; Kazak, L.; Komar, D.; Laarmann, T.; Lee, H. J.; Ma, T.; Nakatsutsumi, M.; Przystawik, A.; Redlin, H.; Skruszewicz, S.; Sperling, P.; Tiggesbäumker, J.; Toleikis, S.; Zastrau, U.

    2014-09-01

    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.

  10. Spatio-temporal clustering of cholera: the impact of flood control in Matlab, Bangladesh, 1983-2003.

    PubMed

    Carrel, Margaret; Emch, Michael; Streatfield, Peter K; Yunus, Mohammad

    2009-09-01

    Introducing flood control to an area of endemic waterborne diseases could have significant impacts on spatio-temporal occurrence of cholera. Using 21-year data from Bangladesh, we conducted cluster analysis to explore changes in spatial and temporal distribution of cholera incidence since the construction of flood control structures. Striking changes in temporal cluster patterns emerged, including a shift from dry-season to rainy-season clusters following flood protection and delayed clustering inside the protected areas. Spatial differences in pre-flood protection and post-protection cholera clusters are weaker. Changes in spatio-temporal cholera clustering, associated with implementation of flood protection strategies, could affect local cholera prevention efforts.

  11. 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.

  12. 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

  13. A realistic framework for investigating decision-making in the brain with high spatio-temporal resolution using simultaneous EEG/fMRI and joint ICA.

    PubMed

    Kyathanahally, Sreenath; Franco-Watkins, Ana; Zhang, Xiaoxia; Calhoun, Vince; Deshpande, Gopikrishna

    2016-07-12

    Human decision-making is a multidimensional construct, driven by a complex interplay between external factors, internal biases and computational capacity constraints. Here we propose a layered approach to experimental design in which multiple tasks - from simple to complex - with additional layers of complexity introduced at each stage, are incorporated for investigating decision-making. This is demonstrated using tasks involving intertemporal choice between immediate and future prospects. Previous functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) studies have separately investigated the spatial and temporal neural substrates, respectively, of specific factors underlying decision making. In contrast, we performed simultaneous acquisition of EEG/fMRI data and fusion of both modalities using joint independent component analysis (jICA) such that: (i) the native temporal/spatial resolutions of either modality is not compromised and (ii) fast temporal dynamics of decision-making as well as involved deeper striatal structures can be characterized. We show that spatio-temporal neural substrates underlying our proposed complex intertemporal task simultaneously incorporating rewards, costs and uncertainty of future outcomes can be predicted (using a linear model) from neural substrates of each of these factors, which were separately obtained by simpler tasks. This was not the case for spatial and temporal features obtained separately from fMRI and EEG respectively. However, certain prefrontal activations in the complex task could not be predicted from activations in simpler tasks, indicating that the assumption of pure insertion has limited validity. Overall, our approach provides a realistic and novel framework for investigating the neural substrates of decision making with high spatio-temporal resolution.

  14. 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

  15. Incorporating social contact data in spatio-temporal models for infectious disease spread

    PubMed Central

    Held, Leonhard

    2017-01-01

    Summary Routine public health surveillance of notifiable infectious diseases gives rise to weekly counts of reported cases—possibly stratified by region and/or age group. We investigate how an age-structured social contact matrix can be incorporated into a spatio-temporal endemic–epidemic model for infectious disease counts. To illustrate the approach, we analyze the spread of norovirus gastroenteritis over six age groups within the 12 districts of Berlin, 2011–2015, using contact data from the POLYMOD study. The proposed age-structured model outperforms alternative scenarios with homogeneous or no mixing between age groups. An extended contact model suggests a power transformation of the survey-based contact matrix toward more within-group transmission. PMID:28025182

  16. 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}.

  17. 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.

  18. 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.

  19. Self-guiding of laser pulses and spatio-temporal optical vortices in plasma

    NASA Astrophysics Data System (ADS)

    Hine, George; Jhajj, Nihal; Milchberg, Howard

    2016-10-01

    Relativistic self-focusing and self-guiding are processes fundamental to laser-plasma particle acceleration. Recent work in optical filamentation has discovered the existence of spatio-temporal optical vortices (STOVs) and has shown their integral connection to all self-focusing collapse and self-guiding scenarios. Here we show that STOVs are an essential feature of LWFA through their generation by relativistic self-focusing. Three dimensional particle-in-cell (PIC) simulations show the formation of STOVs in the pulse, corresponding to vortical flow of the Poynting vector, which then influences subsequent pulse propagation such as the self-healing of the relativistic self-guiding process. This work is supported by the Department of Energy, the National Science Foundation, and the Air Force Office of Scientific Research.

  20. A collaborative large spatio-temporal data visual analytics architecture for emergence response

    NASA Astrophysics Data System (ADS)

    Guo, D.; Li, J.; Cao, H.; Zhou, Y.

    2014-02-01

    The unconventional emergency, usually outbreaks more suddenly, and is diffused more quickly, but causes more secondary damage and derives more disaster than what it is usually expected. The data volume and urgency of emergency exceeds the capacity of current emergency management systems. In this paper, we propose a three-tier collaborative spatio-temporal visual analysis architecture to support emergency management. The prototype system, based on cloud computation environment, supports aggregation of massive unstructured and semi-structured data, integration of various computing model sand algorithms; collaborative visualization and visual analytics among users with a diversity of backgrounds. The distributed data in 100TB scale is integrated in a unified platform and shared with thousands of experts and government agencies by nearly 100 models. The users explore, visualize and analyse the big data and make a collaborative countermeasures to emergencies.

  1. 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

  2. Spatio-Temporally Restricted Expression of Cell Adhesion Molecules during Chicken Embryonic Development

    PubMed Central

    Roy, Priti; Bandyopadhyay, Amitabha

    2014-01-01

    Differential cell adhesive properties are known to regulate important developmental events like cell sorting and cell migration. Cadherins and protocadherins are known to mediate these cellular properties. Though a large number of such molecules have been predicted, their characterization in terms of interactive properties and cellular roles is far from being comprehensive. To narrow down the tissue context and collect correlative evidence for tissue specific roles of these molecules, we have carried out whole-mount in situ hybridization based RNA expression study for seven cadherins and four protocadherins. In developing chicken embryos (HH stages 18, 22, 26 and 28) cadherins and protocadherins are expressed in tissue restricted manner. This expression study elucidates precise expression domains of cell adhesion molecules in the context of developing embryos. These expression domains provide spatio-temporal context in which the function of these genes can be further explored. PMID:24806091

  3. 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.

  4. Spatio-temporal evolution of two-plasmon decay in homogeneous plasma

    NASA Astrophysics Data System (ADS)

    Dimitrijević, D. R.; Maluckov, A. A.

    2010-10-01

    A hydrodynamic model of two-plasmon decay in a homogeneous plasma slab near the quarter-critical density is utilized to study 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, assuming that the secondary coupling of two daughter electron plasma waves with an ion-acoustic wave is the principal mechanism of saturation of the instability. The impact of inherently non-resonant nature of this secondary coupling on the development of TPD is investigated for the first time and it is shown to significantly influence the electron plasma wave dynamics. Its inclusion leads to non-uniformity 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.

  5. 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.

  6. Two-Dimensional Spatio-Temporal Signal Processing for Dispersion Compensation in Time-Stretched ADC

    NASA Astrophysics Data System (ADS)

    Tarighat, Alireza; Gupta, Shalabh; Sayed, Ali H.; Jalali, Bahram

    2007-06-01

    Time-stretched analog-to-digital converters (ADCs) have offered revolutionary enhancements in the performance of electronic converters by reducing the signal bandwidth prior to digitization. An inherent limitation of the time-stretched ADC is the frequency-selective response of the optical system that reduces the effective number of bits for ultrawideband signals. This paper proposes a solution based on spatio-temporal digital processing. The digital algorithm exploits the optical phase diversity to create a flat RF frequency response, even when the system's transfer function included deep nulls within the signal spectrum. For a 10× time-stretch factor with a 10-GHz input signal, simulations show that the proposed solution increases the overall achievable signal-to-noise-and-distortion ratio to 52 dB in the presence of linear distortions. The proposed filter can be used to mitigate the dispersion penalty in other fiber optic applications as well.

  7. 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.

  8. REVIEWS OF TOPICAL PROBLEMS: Spatio-temporal problems of locomotion control

    NASA Astrophysics Data System (ADS)

    Smolyaninov, Vladimir V.

    2000-10-01

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

  9. Spatio-temporal Features of Neurogenesis in the Retina of Medaka, Oryzias latipes

    PubMed Central

    Kitambi, Satish S.; Malicki, Jarema J.

    2010-01-01

    The vertebrate retina is very well conserved in evolution. Its structure and functional features are very similar in phyla as different as primates and teleost fish. Here we describe the spatio-temporal characteristics of neurogenesis in the retina of a teleost, medaka, and compare them to other species, primarily the zebrafish. Several intriguing differences are observed between medaka and zebrafish. For example, photoreceptor differentiation in the medaka retina starts independently in two different areas, and at more advanced stages of differentiation, medaka and zebrafish retinae display obviously different patterns of the photoreceptor cell mosaic. Medaka and zebrafish evolutionary lineages are thought to have separated from each other 110 million years ago, and so the differences between these species are not unexpected, and may be exploited to gain insight into the architecture of developmental pathways. Importantly, this work highlights the benefits of using multiple teleost models in parallel to understand a developmental process. PMID:19035349

  10. Geographic boundary analysis in spatial and spatio-temporal epidemiology: Perspective and prospects

    PubMed Central

    Jacquez, Geoffrey M.

    2010-01-01

    Geographic boundary analysis is a relatively new approach that is just beginning to be applied in spatial and spatio-temporal epidemiology to quantify spatial variation in health outcomes, predictors and correlates; generate and test epidemiologic hypotheses; to evaluate health-environment relationships; and to guide sampling design. Geographic boundaries are zones of rapid change in the value of a spatially distributed variable, and mathematically may be defined as those locations with a large second derivative of the spatial response surface. Here we introduce a pattern analysis framework based on Value, Change and Association questions, and boundary analysis is shown to fit logically into Change and Association paradigms. This article addresses fundamental questions regarding what boundary analysis can tell us in public health and epidemiology. It explains why boundaries are of interest, illustrates analysis approaches and limitations, and concludes with prospects and future research directions. PMID:21218153

  11. 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

  12. Spatio-temporal propagation of cascading overload failures in spatially embedded networks.

    PubMed

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-12

    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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Mechanisms for spatio-temporal pattern formation in highway traffic models.

    PubMed

    Wilson, R Eddie

    2008-06-13

    A key qualitative requirement for highway traffic models is the ability to replicate a type of traffic jam popularly referred to as a phantom jam, shock wave or stop-and-go wave. Despite over 50 years of modelling, the precise mechanisms for the generation and propagation of stop-and-go waves and the associated spatio-temporal patterns are in dispute. However, the increasing availability of empirical datasets, such as those collected from motorway incident detection and automatic signalling system (MIDAS) inductance loops in the UK or the next-generation simulation trajectory data (NGSIM) project in the USA, means that we can expect to resolve these questions definitively in the next few years. This paper will survey the essence of the competing explanations of highway traffic pattern formation and introduce and analyse a new mechanism, based on dynamical systems theory and bistability, which can help resolve the conflict.

  18. Fst-Filter: A flexible spatio-temporal filter for biomedical multichannel data denoising.

    PubMed

    Nuanprasert, Somchai; Adachi, Yoshiaki; Suzuki, Takashi

    2015-08-01

    In this paper, we present the noise reduction method for a multichannel measurement system where the true underlying signal is spatially low-rank and contaminated by spatially correlated noise. Our proposed formulation applies generalized singular value decomposition (GSVD) with signal recovery approach to extend the conventional subspace-based methods for performing the spatio-temporal filtering. Without necessarily requiring the noise covariance data in advance, the implemented optimization scheme allows users to choose the denoising function, F(·) flexibly satisfying for different temporal noise characteristics from a variety of existing efficient temporal filters. An effectiveness of proposed method is demonstrated by yielding the better accuracy for the brain source estimation on simulated magnetoencephalography (MEG) experiments than some traditional methods, e.g., principal component analysis (PCA), robust principal component analysis (RPCA) and multivariate wavelet denoising (MWD).

  19. RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint.

    PubMed

    Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun

    2016-11-03

    The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods.

  20. RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint

    PubMed Central

    Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun

    2016-01-01

    The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods. PMID:27827882

  1. Coexistence through spatio-temporal heterogeneity and species sorting in grassland plant communities.

    PubMed

    Questad, Erin J; Foster, Bryan L

    2008-07-01

    The effect of spatial heterogeneity on species coexistence relies on the degree of niche heterogeneity in the habitat and the ability of species to exploit the available niche opportunities. We studied species coexistence in a perennial grassland, and tested whether small-scale disturbances create environmental heterogeneity that affects coexistence and whether the functional diversity of species in the species pool affects the ability of community composition to reflect heterogeneity through species sorting. We manipulated the spatio-temporal heterogeneity of disturbance and the functional diversity of species added as seed and measured their impact on the spatial turnover of species composition. Disturbance increased environmental heterogeneity and spatial turnover, and the effect of heterogeneity on turnover was greatest in the presence of a functionally diverse species pool, showing the importance of trait variation among species for exploiting environmental heterogeneity, and suggesting that coexistence occurred due to species sorting among heterogeneous niches.

  2. Spatio-temporal Modeling of Lasing Action in Core–Shell Metallic Nanoparticles

    PubMed Central

    2016-01-01

    Nanoscale laser sources based on single metallic nanoparticles (spasers) have attracted significant interest for their fundamental implications and technological potential. Here we theoretically investigate the spatio-temporal dynamics of lasing action in core–shell metallic nanoparticles that include optically pumped four-level gain media. By using detailed semiclassical simulations based on a time-domain generalization of the finite-element method, we study the evolution of the lasing dynamics when going from a spherical case to an elongated nanorod configuration. Our calculations show that there exists an optimal nanoparticle elongation that exhibits significantly improved lasing threshold and slope efficiency over those obtained for its spherical counterpart. These results are accounted for in terms of a coupled-mode theory analysis of the variation with elongation of the light confinement properties of localized surface plasmons. This work could be of importance for further development of nanoscale light sources based on localized surface plasmon resonances. PMID:27785457

  3. 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.

  4. Spatio-temporal study of non-degenerate two-wave mixing in bacteriorhodopsin films.

    PubMed

    Blaya, Salvador; González, Alejandro; Acebal, Pablo; Carretero, Luis

    2016-10-31

    A spatio-temporal analysis of non-degenerate two-wave mixing in a saturable absorber, such as bacteriorhodopsin (bR) film, is performed. To do this, a theoretical model describing the temporal variation of the intensities is developed by taking into account the dielectric constant as a function of bR population. A good agreement between theory and experimental measurements is obtained. Thus, the dependence of the optical gain and the main dielectric constant parameters are studied at different intensities and frequencies. As a result, the best intensity-frequency zones where higher coupling is reached are proposed, and it is also demonstrated that non-uniform patterns, which evolve over time as a function of frequency difference, can be observed.

  5. On the spatio-temporal behavior of magnetohydrodynamic turbulence in a magnetized plasma

    NASA Astrophysics Data System (ADS)

    Lugones, R.; Dmitruk, P.; Mininni, P. D.; Wan, M.; Matthaeus, W. H.

    2016-11-01

    Using direct numerical simulations of three-dimensional magnetohydrodynamic turbulence, the spatio-temporal behavior of magnetic field fluctuations is analyzed. Cases with relatively small, medium, and large values of a mean background magnetic field are considered. The (wavenumber) scale dependent time correlation function is directly computed for different simulations, varying the mean magnetic field value. From this correlation function, the time decorrelation is computed and compared with different theoretical times, namely, the local non-linear time, the random sweeping time, and the Alfvénic time, the latter being a wave effect. It is observed that time decorrelations are dominated by sweeping effects, and only at large values of the mean magnetic field and for wave vectors mainly aligned with this field time decorrelations are controlled by Alfvénic effects.

  6. 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

  7. 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.

  8. Climate change forecasts, long-term spatio-temporal prediction and the resilience of dry ecosystems

    NASA Astrophysics Data System (ADS)

    Shafran-Natan, Rakefet; Svoray, Tal; Avi, Perevolotsky

    2010-05-01

    Primary production is an important indicator to climatic changes in drylands, while reduction in productivity has many consequences on ecosystem functioning. We suggest that the response of dry ecosystems to climate change should lead to a change in spatial patterns of grasses without a substantial change in ecosystem resilience. We used field data and a recently published spatio-temporally explicit model to study factors affecting long-term variation in primary production in two dry ecosystems: semi-arid (SAE) and Mediterranean (DME) dominated by annual vegetation. The model was operated in both patch and landscape scales and was executed along 30 years (1979-2008) at SAE and along 21 years (1986-1990; 1993-2008) at DME. Model predictions were validated against samples that were harvested in each site at the end of the growing season, over 15 seasons (1994-2008) at SAE (0.63

  9. Multiblock copolymers exhibiting spatio-temporal structure with autonomous viscosity oscillation

    NASA Astrophysics Data System (ADS)

    Onoda, Michika; Ueki, Takeshi; Shibayama, Mitsuhiro; Yoshida, Ryo

    2015-10-01

    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.

  10. Spatio-temporal heterogeneity in Arabidopsis thaliana leaves under drought stress.

    PubMed

    Sperdouli, I; Moustakas, M

    2012-01-01

    Using chlorophyll (chl) fluorescence imaging, we studied the effect of mild (MiDS), moderate (MoDS) and severe (SDS) drought stress on photosystem II (PSII) photochemistry of 4-week-old Arabidopsis thaliana. Spatio-temporal heterogeneity in all chl fluorescence parameters was maintained throughout water stress. After exposure to drought stress, maximum quantum yield of PSII photochemistry (F(v)/F(m)) and quantum efficiency of PSII photochemistry (Φ(PSΙΙ)) decreased less in the proximal (base) than in the distal (tip) leaf. The chl fluorescence parameter F(v) /F(m) decreased less after MoDS than MiDS. Under MoDS, the antioxidant mechanism of A. thaliana leaves seemed to be sufficient in scavenging reactive oxygen species, as evident by the decreased lipid peroxidation, the more excitation energy dissipated by non-photochemical quenching (NPQ) and decreased excitation pressure (1-q(p)). Arabidopsis leaves appear to function normally under MoDS, but do not seem to have particular metabolic tolerance mechanisms under MiDS and SDS, as revealed by the level of lipid peroxidation and decreased quantum yield for dissipation after down-regulation in PSII (Φ(NPQ)), indicating that energy dissipation by down-regulation did not function and electron transport (ETR) was depressed. The simultaneous increased quantum yield of non-regulated energy dissipation (Φ(NO)) indicated that both the photochemical energy conversion and protective regulatory mechanism were insufficient. The non-uniform photosynthetic pattern under drought stress may reflect different zones of leaf anatomy and mesophyll development. The data demonstrate that the effect of different degrees of drought stress on A. thaliana leaves show spatio-temporal heterogeneity, implying that common single time point or single point leaf analyses are inadequate.

  11. Impact of spatio-temporal sampling on the evaluation of models with observations

    NASA Astrophysics Data System (ADS)

    Schutgens, Nick; Gryspeerdt, Edward; Weigum, Natalie; Tsyro, Svetlana; Schulz, Michael; Stier, Philip

    2015-04-01

    Global models and observations differ strongly in their spatio-temporal sampling. First, Model results are typical of large gridboxes (100 km), while observations are made over much smaller areas (1 to 10 km). Second, model results are always available in contrast to observations that are intermittent due to sampling strategies, retrieval limitations and instrument failure/maintenance. We investigate the consequences of spatio-temporal sampling for the evaluation of models with observations and find them to be significant (differences up to 100% in monthly or yearly averages due to sampling alone). Using high resolution WRF-Chem and EMEP simulations, we study the impact of evaluating low resolution global models with highly localised observations. Results suggest that significant differences due to the spatial aggregation alone will exist between models and observations, even after averaging data over e.g. a month. When using realistic observational sampling, these differences will be even bigger. Results depend on the concerned observable: a column-integrated property like AOT, easily advected by the flow, will exhibit smaller differences than a surface property like PM2.5, especially if that surface property shows little advection (e.g. number density). We explain these results qualitatively as a consequence of flow structure and aerosol source length-scales. Furthermore, we show that proper temporal collocation of model data with the observations and further spatial aggregation of the observations can reduce (but not entirely remove!) these sampling-induced differences. We point out that even temporal collocation is by no means a standard procedure for researchers and often it is simply assumed that 'over time' issues due to sampling will average out (we show they will not).

  12. Spatio-temporal processing of words and nonwords: hemispheric laterality and acute alcohol intoxication

    PubMed Central

    Marinkovic, Ksenija; Rosen, Burke Q.; Cox, Brendan; Hagler, Donald J.

    2014-01-01

    This study examined neurofunctional correlates of reading by modulating semantic, lexical, and orthographic attributes of letter strings. It compared the spatio-temporal activity patterns elicited by real words (RW), pseudowords, orthographically regular, pronounceable nonwords (PN) that carry no meaning, and orthographically illegal, nonpronounceable nonwords (NN). A double-duty lexical decision paradigm instructed participants to detect RW while ignoring nonwords and to additionally respond to words that refer to animals (AW). Healthy social drinkers (N=22) participated in both alcohol (0.6 g/kg ethanol for men, 0.55 g/kg for women) and placebo conditions in a counterbalanced design. Whole-head MEG signals were analyzed with an anatomically-constrained MEG method. Simultaneously acquired ERPs confirm previous evidence. Spatio-temporal MEG estimates to RW and PN are consistent with the highly replicable left-lateralized ventral visual processing stream. However, the PN elicit weaker activity than other stimuli starting at ~230 ms and extending to the M400 (magnetic equivalent of N400) in the left lateral temporal area, indicating their reduced access to lexicosemantic stores. In contrast, the NN uniquely engage the right hemisphere during the M400. Increased demands on lexicosemantic access imposed by AW result in greater activity in the left temporal cortex starting at ~230 ms and persisting through the M400 and response preparation stages. Alcohol intoxication strongly attenuates early visual responses occipito-temporally overall. Subsequently, alcohol selectively affects the left prefrontal cortex as a function of orthographic and semantic dimensions, suggesting that it modulates the dynamics of the lexicosemantic processing in a top-down manner, by increasing difficulty of semantic retrieval. PMID:24565928

  13. Performance evaluation of spatio-temporal multi-resolution analysis with deinterlacer banks

    NASA Astrophysics Data System (ADS)

    Ishida, Takuma; Muramatsu, Shogo; Kitagawa, Daisuke; Uchita, Jun; Hiki, Minoru; Kikuchi, Hisakazu

    2005-07-01

    In this work, hierarchical motion compensated three-dimensional (3-D) filter banks for spatio-temporal multi-resoution analysis are presented as new tools for scalable video format control. For recent developments in scalable video coding, most of them are based on 3-D wavelet transform with motion compensation. To achieve the function of frame-rate and spatial resolution scalabilities, motion compensated temporal filtering (MCTF) through lifting wavelet transform currently attracts many researchers as an effective temporal decomposition tool. As previous works, we proposed single stage deinterlacer banks as novel 3-D filter banks. Unlike other filter banks, our proposed system is constructed in a way unique to multi-dimensional systems by using invertible deinterlacers, which we have proposed before. The single stage deinterlacer banks decompose a progressive video into two subband sequences of a half frame-rate in the progressive scanning manner. Even though the system handles interlaced videos as intermediate data, introducing a multistage decomposition is simply achieved because the output sequences have also the progressive format as like the input. Our proposed hierarchical deinterlacer banks are accompanied by 2-D discrete wavelet transforms (DWT) as spatial transforms. The multistage technique provides interlaced sequences as well as several reduced-rate progressive sequences while maintaining the reconstruction of the original full-resolution full-rate video sequence. We show that fine granular control of spatio-temporal resolution can be acchieved through the hierarchical process. Some experimental results show novel functions and the significance of the proposed filter banks.

  14. 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.

  15. Spatio-temporal trends of mortality in small areas of Southern Spain

    PubMed Central

    2010-01-01

    Background Most mortality atlases show static maps from count data aggregated over time. This procedure has several methodological problems and serious limitations for decision making in Public Health. The evaluation of health outcomes, including mortality, should be approached from a dynamic time perspective that is specific for each gender and age group. At the moment, researches in Spain do not provide a dynamic image of the population's mortality status from a spatio-temporal point of view. The aim of this paper is to describe the spatial distribution of mortality from all causes in small areas of Andalusia (Southern Spain) and evolution over time from 1981 to 2006. Methods A small-area ecological study was devised using the municipality as the unit for analysis. Two spatio-temporal hierarchical Bayesian models were estimated for each age group and gender. One of these was used to estimate the specific mortality rate, together with its time trends, and the other to estimate the specific rate ratio for each municipality compared with Spain as a whole. Results More than 97% of the municipalities showed a diminishing or flat mortality trend in all gender and age groups. In 2006, over 95% of municipalities showed male and female mortality specific rates similar or significantly lower than Spanish rates for all age groups below 65. Systematically, municipalities in Western Andalusia showed significant male and female mortality excess from 1981 to 2006 only in age groups over 65. Conclusions The study shows a dynamic geographical distribution of mortality, with a different pattern for each year, gender and age group. This information will contribute towards a reflection on the past, present and future of mortality in Andalusia. PMID:20089142

  16. 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.

  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.

  18. Spatio-temporal expression of peroxisome proliferator-activated receptor α during human prenatal development.

    PubMed

    Cizkova, Katerina; Rajdova, Aneta; Ehrmann, Jiri

    2015-04-01

    Peroxisome proliferator-activated receptor α (PPARα) is a ligand-dependent transcription factor which is activated by various endogenous as well as exogenous compounds. It is involved in the regulation of a variety of biological processes, such as nutrient metabolism, energy homoeostasis, immunological response and xenobiotic metabolism. Little is known about its expression during human prenatal development. We examined the spatio-temporal expression pattern of PPARα in human embryonic/foetal intestines, liver and kidney from the 5th to 20th week of prenatal life by indirect two-step immunohistochemistry. PPARα expression can already be detected in the early stages of prenatal development; as early as the 7th week of intrauterine development (IUD) in the intestines, 5th week of IUD in the liver and 6th week of IUD in the kidney. We found age-dependent changes in the PPARα expression pattern in the intestines and kidney. These events occur approximately at the commencement of function of these organs. In the intestines, we detected an obvious change of the PPARα expression pattern along the crypt-villous axis in the 11th week of IUD. In the kidney, the most apparent change was increased expression of PPARα in glomeruli in the 12th week of IUD. Moreover, in the liver, we detected a strong positivity in part of the developing blood elements. Information about the spatio-temporal expression pattern of PPARα could be the first step in evaluating the potential harmful impact of a wide range of environmental or pharmaceutical compounds which serve as PPARα ligands on the developing human organism.

  19. 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.

  20. Elucidating the spatio-temporal dynamics of an emerging wildlife pathogen using approximate Bayesian computation.

    PubMed

    Rey, Olivier; Fourtune, Lisa; Paz-Vinas, Ivan; Loot, Géraldine; Veyssière, Charlotte; Roche, Benjamin; Blanchet, Simon

    2015-11-01

    Emerging pathogens constitute a severe threat for human health and biodiversity. Determining the status (native or non-native) of emerging pathogens, and tracing back their spatio-temporal dynamics, is crucial to understand the eco-evolutionary factors promoting their emergence, to control their spread and mitigate their impacts. However, tracing back the spatio-temporal dynamics of emerging wildlife pathogens is challenging because (i) they are often neglected until they become sufficiently abundant and pose socio-economical concerns and (ii) their geographical range is often little known. Here, we combined classical population genetics tools and approximate Bayesian computation (i.e. ABC) to retrace the dynamics of Tracheliastes polycolpus, a poorly documented pathogenic ectoparasite emerging in Western Europe that threatens several freshwater fish species. Our results strongly suggest that populations of T. polycolpus in France emerged from individuals originating from a unique genetic pool that were most likely introduced in the 1920s in central France. From this initial population, three waves of colonization occurred into peripheral watersheds within the next two decades. We further demonstrated that populations remained at low densities, and hence undetectable, during 10 years before a major demographic expansion occurred, and before its official detection in France. These findings corroborate and expand the few historical records available for this emerging pathogen. More generally, our study demonstrates how ABC can be used to determine the status, reconstruct the colonization history and infer key evolutionary parameters of emerging wildlife pathogens with low data availability, and for which samples from the putative native area are inaccessible.

  1. 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

  2. Spatio-Temporal Modeling of Seismic Provinces of Iran Using DBSCAN Algorithm

    NASA Astrophysics Data System (ADS)

    Kazemi-Beydokhti, Mohammad; Ali Abbaspour, Rahim; Mojarab, Masoud

    2017-03-01

    One of the most important issues in the field of engineering seismology is identification and classification of seismic provinces. Due to the importance of this issue in Iran, various studies have been conducted using different methods such as expert judgment, computational methods, data-driven methods, and smart methods. The purpose of the present research is to develop a spatio-temporal seismic model for Iran using robust and objective clustering tools. In the present study, one of the most powerful clustering methods, DBSCAN, is selected based on its ability to analyze huge amounts of data. The DBSCAN algorithm, which acts based on the density of seismic events, is capable of detecting arbitrarily shaped clusters. The seismic datasets used in this study, which were obtained from the seismic catalog of Iran from 1900 to 2015, have been divided into three window periods including 2- , 5- , and 10-year intervals. Afterward, different seismicity patterns for each period are obtained by applying DBSCAN algorithm. Then, those exhibited high agreements in terms of shapes and locations of clusters with the other models are determined. Ultimately, by considering these models and using expert judgments, a unified spatio-temporal model is presented. The results reveal meaningful information in different parts of Iran especially in Zagros, Alborz, and Azerbaijan zones and are generally in good agreement with previous studies. Moreover, the results emphasize that a seismic model, which is obtained based on considering seismogenic zones in various time periods along with the application of density-based clustering tools, will produce reliable results.

  3. 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

  4. 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…

  5. A Non-Homogeneous, Spatio-Temporal, Wavelet Multiresolution Analysis and Its Application to the Analysis of Motion

    DTIC Science & Technology

    1993-12-01

    36 iv Page 3.3 Discrete Multiresolution Decomposition Algorithm ..... ........... 40 3.4 Spatio-Temporal Filter Bank Representation...List of Figures Figure Page 1. Spatial and temporal frequency sensitivity of motion cells ................... 3 2. STFT and wavelet filter banks ...construction of a wavelet filter bank that provides directional selectivity, 5) combining the coefficients obtained in the decomposition process to

  6. 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.

  7. Domain-specific perceptual causality in children depends on the spatio-temporal configuration, not motion onset.

    PubMed

    Schlottmann, Anne; Cole, Katy; Watts, Rhianna; White, Marina

    2013-01-01

    Humans, even babies, perceive causality when one shape moves briefly and linearly after another. Motion timing is crucial in this and causal impressions disappear with short delays between motions. However, the role of temporal information is more complex: it is both a cue to causality and a factor that constrains processing. It affects ability to distinguish causality from non-causality, and social from mechanical causality. Here we study both issues with 3- to 7-year-olds and adults who saw two computer-animated squares and chose if a picture of mechanical, social or non-causality fit each event best. Prior work fit with the standard view that early in development, the distinction between the social and physical domains depends mainly on whether or not the agents make contact, and that this reflects concern with domain-specific motion onset, in particular, whether the motion is self-initiated or not. The present experiments challenge both parts of this position. In Experiments 1 and 2, we showed that not just spatial, but also animacy and temporal information affect how children distinguish between physical and social causality. In Experiments 3 and 4 we showed that children do not seem to use spatio-temporal information in perceptual causality to make inferences about self- or other-initiated motion onset. Overall, spatial contact may be developmentally primary in domain-specific perceptual causality in that it is processed easily and is dominant over competing cues, but it is not the only cue used early on and it is not used to infer motion onset. Instead, domain-specific causal impressions may be automatic reactions to specific perceptual configurations, with a complex role for temporal information.

  8. Spatio-temporal variations in biomass and mercury concentrations of epiphytic biofilms and their host in a large river wetland (Lake St. Pierre, Qc, Canada).

    PubMed

    Hamelin, Stéphanie; Planas, Dolors; Amyot, Marc

    2015-02-01

    Within wetlands, epiphytes and macrophytes play an important role in storage and transfer of metals, through the food web. However, there is a lack of information about spatial and temporal changes in their metal levels, including those of mercury (Hg), a key priority contaminant of aquatic systems. We assessed total mercury (THg) and methylmercury (MeHg) concentrations of epiphyte/macrophyte complexes in Lake St. Pierre, a large fluvial lake of the St. Lawrence River (Québec, Canada). THg and MeHg concentrations were ten fold higher in epiphytes than in macrophytes. THg concentrations in epiphytes linearly decreased as a function of the autotrophic index, suggesting a role of algae in epiphyte Hg accumulation, and % of MeHg in epiphytes reached values as high as 74%. Spatio-temporal variability in THg and MeHg concentrations in epiphytes and macrophytes were influenced by water temperature, available light, host species, water level, dissolved organic carbon and dissolved oxygen.

  9. Tier-Scalable Reconnaissance Missions for Autonomous Exploration and Spatio-Temporal Monitoring of Climate Change with Particular Application to Glaciers and their Environs

    NASA Astrophysics Data System (ADS)

    Fink, W.; Tarbell, M. A.; Furfaro, R.; Kargel, J. S.

    2010-12-01

    Spatio-temporal monitoring of climate change and its impacts is needed globally and thus requires satellite-based observations and analysis. However, needed ground truth can only be obtained in situ. In situ exploration of extreme and often hazardous environments can pose a significant challenge to human access. We propose the use of a disruptive exploration paradigm that has earlier been introduced with autonomous robotic space exploration, termed Tier-Scalable Reconnaissance (PSS 2005; SCIENCE 2010). Tier-scalable reconnaissance utilizes orbital, aerial, and surface/subsurface robotic platforms working in concert, enabling event-driven and integrated global to regional to local reconnaissance capabilities. We report on the development of a robotic test bed for Tier-scalable Reconnaissance at the University of Arizona and Caltech (SCIENCE 2010) for distributed and science-driven autonomous exploration, mapping, and spatio-temporal monitoring of climate change in hazardous or inaccessible environments. We focus in particular on glaciers and their environs, especially glacier lakes. Such glacier lakes can pose a significant natural hazard to inhabited areas and economies downstream. The test bed currently comprises several robotic surface vehicles: rovers equipped with cameras, and boats equipped with cameras and side-scanning sonar technology for bathymetry and the characterization of subsurface structures in glacier lakes and other water bodies. To achieve a fully operational Tier-scalable Reconnaissance test bed, aerial platforms will be integrated in short order. Automated mapping and spatio-temporal monitoring of glaciers and their environs necessitate increasing degrees of operational autonomy: (1) Automatic mapping of an operational area from different vantages (i.e., airborne, surface, subsurface); (2) automatic sensor deployment and sensor data gathering; (3) automatic feature extraction and region-of-interest/anomaly identification within the mapped

  10. Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid (Spain) through an extensive field campaign

    NASA Astrophysics Data System (ADS)

    Borge, Rafael; Narros, Adolfo; Artíñano, Begoña; Yagüe, Carlos; Gómez-Moreno, Francisco Javier; de la Paz, David; Román-Cascón, Carlos; Díaz, Elías; Maqueda, Gregorio; Sastre, Mariano; Quaassdorff, Christina; Dimitroulopoulou, Chrysanthi; Vardoulakis, Sotiris

    2016-09-01

    Poor urban air quality is one of the main environmental concerns worldwide due to its implications for population exposure and health-related issues. However, the development of effective abatement strategies in cities requires a consistent and holistic assessment of air pollution processes, taking into account all the relevant scales within a city. This contribution presents the methodology and main results of an intensive experimental campaign carried out in a complex pollution hotspot in Madrid (Spain) under the TECNAIRE-CM research project, which aimed at understanding the microscale spatio-temporal variation of ambient concentration levels in areas where high pollution values are recorded. A variety of instruments were deployed during a three-week field campaign to provide detailed information on meteorological and micrometeorological parameters and spatio-temporal variations of the most relevant pollutants (NO2 and PM) along with relevant information needed to simulate pedestrian fluxes. The results show the strong dependence of ambient concentrations on local emissions and meteorology that turns out in strong spatial and temporal variations, with gradients up to 2 μg m-3 m-1 for NO2 and 55 μg m-3 min-1 for PM10. Pedestrian exposure to these pollutants also presents strong variations temporally and spatially but it concentrates on pedestrian crossings and bus stops. The analysis of the results show that the high concentration levels found in urban hotspots depend on extremely complex dynamic processes that cannot be captured by routinely measurements made by air quality monitoring stations used for regulatory compliance assessment. The large influence from local traffic in the concentration fields highlights the need for a detailed description of specific variables that determine emissions and dispersion at microscale level. This also indicates that city-scale interventions may be complemented with local control measures and exposure management, to improve

  11. Complex higher order derivative theories

    SciTech Connect

    Margalli, Carlos A.; Vergara, J. David

    2012-08-24

    In this work is considered a complex scalar field theory with higher order derivative terms and interactions. A procedure is developed to quantize consistently this system avoiding the presence of negative norm states. In order to achieve this goal the original real scalar high order field theory is extended to a complex space attaching a complex total derivative to the theory. Next, by imposing reality conditions the complex theory is mapped to a pair of interacting real scalar field theories without the presence of higher derivative terms.

  12. IDE spatio-temporal impact fluxes and high time-resolution studies of multi-impact events and long-lived debris clouds

    NASA Technical Reports Server (NTRS)

    Mulholland, J. Derral; Singer, S. Fred; Oliver, John P.; Weinberg, Jerry L.; Cooke, William J.; Montague, Nancy L.; Wortman, Jim J.; Kassel, Phillip C.; Kinard, William H.

    1992-01-01

    The purpose of the Interplanetary Dust Experiment (IDE) on the Long Duration Exposure Facility (LDEF) was to sample the cosmic dust environment and to use the spatio-temporal aspect of the experiment to distinguish between the various components of the environment: zodiacal cloud, beta meteoroids, meteor streams, interstellar dust, and orbital debris. It was found that the introduction of precise time and even rudimentary directionality as co-lateral observables in sampling the particulate environment in near-Earth space produces an enormous qualitative improvement in the information content of the impact data. The orbital debris population is extremely clumpy, being dominated by persistent clouds in which the fluxes may rise orders of magnitude above the background. The IDE data suggest a strategy to minimize the damage to sensitive spacecraft components, using the observed characteristics of cloud encounters.

  13. Visual exploration of big spatio-temporal urban data: a study of New York City taxi trips.

    PubMed

    Ferreira, Nivan; Poco, Jorge; Vo, Huy T; Freire, Juliana; Silva, Cláudio T

    2013-12-01

    As increasing volumes of urban data are captured and become available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based decision making and policies. In this paper, we focus on a particularly important urban data set: taxi trips. Taxis are valuable sensors and information associated with taxi trips can provide unprecedented insight into many different aspects of city life, from economic activity and human behavior to mobility patterns. But analyzing these data presents many challenges. The data are complex, containing geographical and temporal components in addition to multiple variables associated with each trip. Consequently, it is hard to specify exploratory queries and to perform comparative analyses (e.g., compare different regions over time). This problem is compounded due to the size of the data-there are on average 500,000 taxi trips each day in NYC. We propose a new model that allows users to visually query taxi trips. Besides standard analytics queries, the model supports origin-destination queries that enable the study of mobility across the city. We show that this model is able to express a wide range of spatio-temporal queries, and it is also flexible in that not only can queries be composed but also different aggregations and visual representations can be applied, allowing users to explore and compare results. We have built a scalable system that implements this model which supports interactive response times; makes use of an adaptive level-of-detail rendering strategy to generate clutter-free visualization for large results; and shows hidden details to the users in a summary through the use of overlay heat maps. We present a series of case studies motivated by traffic engineers and economists that show how our model and system enable domain experts to perform tasks that were previously unattainable for them.

  14. Individual and spatio-temporal variations in the home range behaviour of a long-lived, territorial species.

    PubMed

    Campioni, Letizia; Delgado, María del Mar; Lourenço, Rui; Bastianelli, Giulia; Fernández, Nestor; Penteriani, Vincenzo

    2013-06-01

    Despite the fact that investigations of home range behaviour have exponentially evolved on theoretical, analytical and technological grounds, the factors that shape animal home range behaviour still represent an unsolved question and a challenging field of research. However, home range studies have recently begun to be approached under a new integrated conceptual framework, considering home range behaviour as the result of the simultaneous influences of temporal, spatial and individual-level processes, with potential consequences at the population level. Following an integrated approach, we studied the influence of both external and internal factors on variations in the home range behaviour of 34 radiotagged eagle owl (Bubo bubo) breeders. Home range behaviour was characterised through complementary analysis of space use, movement patterns and rhythms of activity at multiple spatio-temporal scales. The effects of the different phases of the biological cycle became considerably evident at the level of movement patterns, with males travelling longer distances than females during incubation and nestling periods. Both external (i.e. habitat structure and composition) and internal (i.e. sex and health state) factors explained a substantial amount of the variation in home range behaviour. At the broader temporal scale, home range and core area size were negatively correlated with landscape heterogeneity. Males showed (1) smaller home range and core area sizes, (2) more complex home range internal structure and (3) higher rates of movement. The better the physiological condition of the individuals, the simpler the internal home range structure. Finally, inter- and intra-individual effects contributed to shaping space use and movement patterns during the biological cycle. Because of the plurality of behavioural and ecological processes simultaneously involved in home range behaviour, we claim that an integrative approach is required for adequate investigation of its

  15. Lipidomic and spatio-temporal imaging of fat by mass spectrometry in mice duodenum during lipid digestion.

    PubMed

    Seyer, Alexandre; Cantiello, Michela; Bertrand-Michel, Justine; Roques, Véronique; Nauze, Michel; Bézirard, Valérie; Collet, Xavier; Touboul, David; Brunelle, Alain; Coméra, Christine

    2013-01-01

    Intestinal absorption of dietary fat is a complex process mediated by enterocytes leading to lipid assembly and secretion of circulating lipoproteins as chylomicrons, vLDL and intestinal HDL (iHDL). Understanding lipid digestion is of importance knowing the correlation between excessive fat absorption and atherosclerosis. By using time-of-flight secondary ion mass spectrometry (TOF-SIMS), we illustrated a spatio-temporal localization of fat in mice duodenum, at different times of digestion after a lipid gavage, for the first time. Fatty acids progressively increased in enterocytes as well as taurocholic acid, secreted by bile and engaged in the entero-hepatic re-absorption cycle. Cytosolic lipid droplets (CLD) from enterocytes were originally purified separating chylomicron-like, intermediate droplets and smaller HDL-like. A lipidomic quantification revealed their contents in triglycerides, free and esterified cholesterol, phosphatidylcholine, sphingomyelin and ceramides but also in free fatty acids, mono- and di-acylglycerols. An acyl-transferase activity was identified and the enzyme monoacylglycerol acyl transferase 2 (MGAT2) was immunodetected in all CLD. The largest droplets was also shown to contain the microsomal triglyceride transfer protein (MTTP), the acyl-coenzyme A-cholesterol acyltransferases (ACAT) 1 and 2, hormone sensitive lipase (HSL) and adipose triglyceride lipase (ATGL). This highlights the fact that during the digestion of fats, enterocyte CLD contain some enzymes involved in the different stages of the metabolism of diet fatty acids and cholesterol, in anticipation of the crucial work of endoplasmic reticulum in the process. The data further underlines the dual role of chylomicrons and iHDL in fat digestion which should help to efficiently complement lipid-lowering therapy.

  16. Model of spatio-temporal propagation of action potentials in the Schaffer collateral pathway of the CA1 area of the rat hippocampus.

    PubMed

    Bernard, C; Cannon, R C; Ben Ari, Y; Wheal, H V

    1997-01-01

    There is a sharp contrast between the profuse in vivo axonal arborization of CA3 pyramidal cells in the CA1 area and the low probability of finding pairs of connected CA3-CA1 pyramidal cells in vitro. These anatomical differences contribute to a connectivity argument for discrepancies between electrophysiological data recorded in vitro and in vivo. In order to investigate this issue, we have developed a realistic computer model of the Schaffer collateral pathway of the hippocampus and analyzed the spatio-temporal distribution of action potentials along this pathway following three different types of electrical test stimulus. Direct activation of mossy fibers, CA3 pyramidal cells and focal stimulation of CA1 stratum radiatum were investigated. The parameters of the model were selected from available biological data. Spikes in Schaffer collaterals were followed from their onset in the CA3 pyramidal cell initial segment to the last order branches of their axonal tree in two types of configuration: the whole hippocampus and the slice configuration. The anatomical and electropysiological characteristics of the mossy fibre and Schaffer collateral pathways were found to impose strong constraints on the spatio-temporal distribution of action potentials in the CA1 area. Specific projection zones are determined by the spatial localization of the emitting CA3 pyramidal cells. Their position also defines precise time windows during which some CA1 projection zones receive a large number of correlated signals. Moreover, the variability of the delay at the mossy fibre/CA3 pyramidal cell synapse seems to provide the CA1 projection zones with a background level of excitation. Finally, we show how the patterns of activation obtained in the whole hippocampus are different from those obtained in the slice.

  17. Assessing the regional spatio-temporal pattern of water stress: A case study in Zhangye City of China

    NASA Astrophysics Data System (ADS)

    Zhang, Qian; Liu, Bing; Zhang, Weige; Jin, Gui; Li, Zhaohua

    Water scarcity and stress have attracted increasing attention as water has become increasingly regarded as one of the most critical resources in the world's sustainable development. The Water Poverty Index (WPI), an interdisciplinary but straightforward measure that considers water availability from both the bio-geophysical perspective and the socio-economic perspective of people's capacity to access water, has been successfully applied at national, regional, and local levels around the world. However, the general assessment of water stress at a macro level over only a snapshot limits the understanding of the geographic differences in and dynamics of water stress; this will, in turn, mislead decision-makers and may result in improper water strategies being implemented. In addition, to date, the typologies and trajectories of water stress have been underexplored. To fill this knowledge gap, we examine the spatio-temporal patterns, trajectories, and typologies of water stress using an adapted WPI for six counties in Zhangye City, which lies within an arid region of China, in order to provide policy priorities for each county. The results of our assessment indicate that water stress has become more severe over time (2005-2011) in most of the counties in Zhangye City. The results also show a distinct spatial variation in water scarcity and stress. Specifically, the results for Shandan county reflect its progressive policies on water access and management, and this county is regarded as engaging in good water governance. In contrast, Ganzhou district has faced more severe water pressure and is regarded as practicing poor water governance. Typology results show that each county faces its own particular challenges and opportunities in the context of water scarcity and stress. In addition, the trajectory map reveals that none of the counties has shown substantial improvement in both water access and management, a finding that should draw decision-makers' close attention.

  18. Monitoring spatio-temporal aerosol patterns over Pakistan based on MODIS, TOMS and MISR satellite data and a HYSPLIT model

    NASA Astrophysics Data System (ADS)

    Alam, Khan; Qureshi, Salman; Blaschke, Thomas

    2011-09-01

    Three different satellite-borne sensors, namely the Total Ozone Mapping Spectrometer (TOMS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Multi-angle Imaging Spectroradiometer (MISR), were used to investigate the spatial and temporal variations of aerosols over several cities in Pakistan. A Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used for trajectory analysis in order to reconstruct the origins of air masses and understand the spatio-temporal variability of aerosol concentrations. Recent MODIS aerosol data (2002-2008) and earlier TOMS data (1979-2001) revealed increasing concentrations of aerosols over Pakistan and adjacent areas. Validation of MODIS and MISR derived aerosol optical depths (AODs) with Aerosol Robotic Network (AERONET) data for 2007 demonstrated that the MISR data was more accurate when close to the ocean, while the MODIS was more accurate over vegetated areas. The relationship between MODIS and MISR AOD data from 2002 to 2008 was analyzed, revealing a strong correlation between the two datasets. An assessment of seasonal variability in AOD for industrial, urban, semi-urban, rural, and semi-arid areas revealed maximum AOD values during the summer over all the areas investigated. Back trajectory analyses indicated that while winter air masses reaching Pakistan had travelled long distances, summer air masses had travelled only short distances. The higher aerosol concentrations during the summer are interpreted to be a result of the air masses spending more time over land during the summer than they do during the winter. While monsoonal rainfall tends to reduce aerosol concentrations by washing aerosols out of the atmosphere, this effect is mainly restricted to the eastern and south-eastern parts of Pakistan.

  19. Stochastic simulation of the spatio-temporal dynamics of reaction-diffusion systems: the case for the bicoid gradient.

    PubMed

    Lecca, Paola; Ihekwaba, Adaoha E C; Dematté, Lorenzo; Priami, Corrado

    2010-11-23

    Reaction-diffusion systems are mathematical models that describe how the concentrations of substances distributed in space change under the influence of local chemical reactions, and diffusion which causes the substances to spread out in space. The classical representation of a reaction-diffusion system is given by semi-linear parabolic partial differential equations, whose solution predicts how diffusion causes the concentration field to change with time. This change is proportional to the diffusion coefficient. If the solute moves in a homogeneous system in thermal equilibrium, the diffusion coefficients are constants that do not depend on the local concentration of solvent and solute. However, in nonhomogeneous and structured media the assumption of constant intracellular diffusion coefficient is not necessarily valid, and, consequently, the diffusion coefficient is a function of the local concentration of solvent and solutes. In this paper we propose a stochastic model of reaction-diffusion systems, in which the diffusion coefficients are function of the local concentration, viscosity and frictional forces. We then describe the software tool Redi (REaction-DIffusion simulator) which we have developed in order to implement this model into a Gillespie-like stochastic simulation algorithm. Finally, we show the ability of our model implemented in the Redi tool to reproduce the observed gradient of the bicoid protein in the Drosophila Melanogaster embryo. With Redi, we were able to simulate with an accuracy of 1% the experimental spatio-temporal dynamics of the bicoid protein, as recorded in time-lapse experiments obtained by direct measurements of transgenic bicoidenhanced green fluorescent protein.

  20. 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.

  1. Reliable Averages and Risky Extremes - Analysis of spatio-temporal variability in solar irradiance and persistent cloud cover patterns over Switzerland

    NASA Astrophysics Data System (ADS)

    Kahl, Annelen; Nguyen, Viet-Anh; Sarrasin, Karine; Lehning, Michael

    2016-04-01

    from the rest of the country, and leads us to believe that this zone plays a valuable role in compensating temporary deficits in solar production from other regions of the country. This is just one of many example that highlight the complexity of spatio-temporal variability in solar irradiance and its implications for a reliable electricity supply in a future renewable Switzerland.

  2. 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

  3. 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

  4. 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

  5. Anticipating the spatio-temporal response of plant diversity and vegetation structure to climate and land use change in a protected area.

    PubMed

    Boulangeat, Isabelle; Georges, Damien; Dentant, Cédric; Bonet, Richard; Van Es, Jérémie; Abdulhak, Sylvain; Zimmermann, Niklaus E; Thuiller, Wilfried

    2014-12-01

    Vegetation is a key driver of ecosystem functioning (e.g. productivity and stability) and of the maintenance of biodiversity (e.g. creating habitats for other species groups). While vegetation sensitivity to climate change has been widely investgated, its spatio-temporally response to the dual efects of land management and climate change has been ignored at landscape scale. Here we use a dynamic vegetation model called FATE-HD, which describes the dominant vegetation dynamics and associated functional diversity, in order to anticipate vegetation response to climate and land-use changes in both short and long-term perspectives. Using three contrasted management scenarios for the Ecrins National Park (French Alps) developed in collaboration with the park managers, and one regional climate change scenario, we tracked the dynamics of vegetation structure (forest expansion) and functional diversity over 100 years of climate change and a further 400 additional years of stabilization. As expected, we observed a slow upward shift in forest cover distribution, which appears to be severely impacted by pasture management (i.e. maintenance or abandonment). The tme lag before observing changes in vegetation cover was the result of demographic and seed dispersal processes. However, plant diversity response to environmental changes was rapid. Afer land abandonment, local diversity increased and spatial turnover was reduced, whereas local diversity decreased following land use intensification. Interestingly, in the long term, as both climate and management scenarios interacted, the regional diversity declined. Our innovative spatio-temporally explicit framework demonstrates that the vegetation may have contrasting responses to changes in the short and the long term. Moreover, climate and land-abandonment interact extensively leading to a decrease in both regional diversity and turnover in the long term. Based on our simulations we therefore suggest a continuing moderate intensity

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

    PubMed Central

    Kidé, Saïkou Oumar; Manté, Claude; Dubroca, Laurent; Demarcq, Hervé; Mérigot, Bastien

    2015-01-01

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

  7. Spatio-temporal evolution of female lung cancer mortality in a region of Spain, is it worth taking migration into account?

    PubMed Central

    Zurriaga, Oscar; Vanaclocha, Hermelinda; Martinez-Beneito, Miguel A; Botella-Rocamora, Paloma

    2008-01-01

    Background The Comunitat Valenciana (CV) is a tourist region on the Mediterranean coast of Spain with a high rate of retirement migration. Lung cancer in women is the cancer mortality cause that has increased most in the CV during the period 1991 to 2000. Moreover, the geographical distribution of risk from this cause in the CV has been previously described and a non-homogenous pattern was determined. The present paper studies the spatio-temporal distribution of lung cancer mortality for women in the CV during the period 1987–2004, in order to gain some insight into the factors, such as migration, that have had an influence on these changes. Methods A novel methodology, consisting of a Bayesian hierarchical model, is used in this paper. Such a model allows the handling of data with a very high disaggregation, while at the same time taking advantage of its spatial and temporal structure. Results The spatio-temporal pattern which was found points to geographical differences in the time trends of risk. In fact, the southern coastal side of the CV has had a higher increase in risk, coinciding with the settlement of a large foreign community in that area, mainly comprised of elderly people from the European Union. Conclusion Migration has frequently been ignored as a risk factor in the description of the geographical risk of lung cancer and it is suggested that this factor should be considered, especially in tourist regions. The temporal component in disease mapping provides a more accurate depiction of risk factors acting on the population. PMID:18234124

  8. Anticipating the spatio-temporal response of plant diversity and vegetation structure to climate and land use change in a protected area

    PubMed Central

    Boulangeat, Isabelle; Georges, Damien; Dentant, Cédric; Bonet, Richard; Van Es, Jérémie; Abdulhak, Sylvain; Zimmermann, Niklaus E.; Thuiller, Wilfried

    2014-01-01

    Vegetation is a key driver of ecosystem functioning (e.g. productivity and stability) and of the maintenance of biodiversity (e.g. creating habitats for other species groups). While vegetation sensitivity to climate change has been widely investgated, its spatio-temporally response to the dual efects of land management and climate change has been ignored at landscape scale. Here we use a dynamic vegetation model called FATE-HD, which describes the dominant vegetation dynamics and associated functional diversity, in order to anticipate vegetation response to climate and land-use changes in both short and long-term perspectives. Using three contrasted management scenarios for the Ecrins National Park (French Alps) developed in collaboration with the park managers, and one regional climate change scenario, we tracked the dynamics of vegetation structure (forest expansion) and functional diversity over 100 years of climate change and a further 400 additional years of stabilization. As expected, we observed a slow upward shift in forest cover distribution, which appears to be severely impacted by pasture management (i.e. maintenance or abandonment). The tme lag before observing changes in vegetation cover was the result of demographic and seed dispersal processes. However, plant diversity response to environmental changes was rapid. Afer land abandonment, local diversity increased and spatial turnover was reduced, whereas local diversity decreased following land use intensification. Interestingly, in the long term, as both climate and management scenarios interacted, the regional diversity declined. Our innovative spatio-temporally explicit framework demonstrates that the vegetation may have contrasting responses to changes in the short and the long term. Moreover, climate and land-abandonment interact extensively leading to a decrease in both regional diversity and turnover in the long term. Based on our simulations we therefore suggest a continuing moderate intensity

  9. Detection of Spatio-temporal variations of rainfall and temperature extremes over India

    NASA Astrophysics Data System (ADS)

    Hari, V.; Karmakar, S.; Ghosh, S.

    2012-12-01

    Hydrologic disturbances are commonly associated with the phenomenal occurrence of extreme events. The human kind has always been facing problem with hydrologic extremes in terms of deaths and economic loss. Hence, a complete analysis of observed extreme events will have a substantial role in planning, designing and management of the water resource systems. In India, the occurrence of extreme events, such as heavy rainfall, which is directly associated with the flash flood have been observed. For example; in 2005, Mumbai city of India suffered a huge economic damage, due to the record rainfall of 94 cm in a day. In the same year, two other major cities Chennai and Bangalore had also experienced the flash floods due to the heavy rainfall. Hence, occurrence of these recent events instigates researchers to investigate long term variation and trend of extreme rainfall over India. Very few previous studies have been conducted in India either considering a particular region or by considering a single extreme rainfall variable (either frequency or intensity of rainfall). In the present study, rainfall variables such as intensity, duration, frequency and volume are considered to investigate spatio-temporal variations for the entire India. The peak over threshold method with 95 percentile is considered to delineate the extreme variables from the observed rainfall data available (at 1×1 deg) for a period of 1901-2004. The temporal variability is determined by implementing a moving window of 30 years. As well as, the correlation analysis is conducted with the implementation of non-parametric coefficients. The spatio-temporal variability of 50 year return level (RL) for the rainfall intensity is determined considering Generalized Pareto and non-parametric kernel distributions as best fit. To identify the significant changes in the derived RL from first to last time window, a bootstrap-based approach proposed by Kharin and Zwiers (2005, Jl. of Climate, 18, 1156-1173) is

  10. 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

  11. Benefiting from a migratory prey: spatio-temporal patterns in allochthonous subsidization of an Arctic predator.

    PubMed

    Giroux, Marie-Andrée; Berteaux, Dominique; Lecomte, Nicolas; Gauthier, Gilles; Szor, Guillaume; Bêty, Joël

    2012-05-01

    1. Flows of nutrients and energy across ecosystem boundaries have the potential to subsidize consumer populations and modify the dynamics of food webs, but how spatio-temporal variations in autochthonous and allochthonous resources affect consumers' subsidization remains largely unexplored. 2. We studied spatio-temporal patterns in the allochthonous subsidization of a predator living in a relatively simple ecosystem. We worked on Bylot Island (Nunavut, Canada), where arctic foxes (Vulpes lagopus L.) feed preferentially on lemmings (Lemmus trimucronatus and Dicrostonyx groenlandicus Traill), and alternatively on colonial greater snow geese (Anser caerulescens atlanticus L.). Geese migrate annually from their wintering grounds (where they feed on farmlands and marshes) to the Canadian Arctic, thus generating a strong flow of nutrients and energy across ecosystem boundaries. 3. We examined the influence of spatial variations in availability of geese on the diet of fox cubs (2003-2005) and on fox reproductive output (1996-2005) during different phases of the lemming cycle. 4. Using stable isotope analysis and a simple statistical routine developed to analyse the outputs of a multisource mixing model (SIAR), we showed that the contribution of geese to the diet of arctic fox cubs decreased with distance from the goose colony. 5. The probability that a den was used for reproduction by foxes decreased with distance from the subsidized goose colony and increased with lemming abundance. When lemmings were highly abundant, the effect of distance from the colony disappeared. The goose colony thus generated a spatial patterning of reproduction probability of foxes, while the lemming cycle generated a strong temporal variation of reproduction probability of foxes. 6. This study shows how the input of energy owing to the large-scale migration of prey affects the functional and reproductive responses of an opportunistic consumer, and how this input is spatially and

  12. The Spatio-temporal Statistical Structure and Ergodic Behaviour of Scalar Turbulence Within a Rod Canopy

    NASA Astrophysics Data System (ADS)

    Ghannam, Khaled; Poggi, Davide; Porporato, Amilcare; Katul, Gabriel G.

    2015-12-01

    Connections between the spatial and temporal statistics of turbulent flow, and their possible convergence to ensemble statistics as assumed by the ergodic hypothesis, are explored for passive scalars within a rod canopy. While complete ergodicity is not expected to apply over all the spatial domain within such heterogeneous flows, the fact that canopy turbulence exhibits self-similar characteristics at a given depth within the canopy encourages a discussion on necessary conditions for an `operational' ergodicity framework. Flows between roughness elements such as within canopies exhibit features that distinguish them from their well-studied classical boundary-layer counterparts. These differences are commonly attributed to short-circuiting of the energy cascade and the prevalence of intermittent von Kármán vortex streets in the deeper layers of the canopy. Using laser-induced fluorescence measurements at two different depths within a rod canopy situated in a large flume, the spatio-temporal statistical properties and concomitant necessary conditions for ergodicity of passive scalar turbulence statistics are evaluated. First, the integral time and length scales are analyzed and their corresponding maximum values are used to guide the construction of an ensemble of independent realizations from repeated spatio-temporal concentration measurements. As a statistical analysis for an operational ergodicity check, a Kolmogorov-Smirnov test on the distributions of temporal and spatial concentration series against the ensemble was conducted. The outcome of this test reveals that ergodicity is reasonably valid over the entire domain except close to the rod elements where wake-induced inhomogeneities and damped turbulence prevail. The spatial concentration statistics within a grid-cell (square domain formed by four corner rods) appear to be less ergodic than their temporal counterparts, which is not surprising given the periodicity and persistence of von Kármán vortices in

  13. Spatio-temporal modeling with GIS and remote sensing for schistosomiasis control in Sichuan, China

    NASA Astrophysics Data System (ADS)

    Xu, Bing

    Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a

  14. Classification of motor intent in transradial amputees using sonomyography and spatio-temporal image analysis

    NASA Astrophysics Data System (ADS)

    Hariharan, Harishwaran; Aklaghi, Nima; Baker, Clayton A.; Rangwala, Huzefa; Kosecka, Jana; Sikdar, Siddhartha

    2016-04-01

    In spite of major advances in biomechanical design of upper extremity prosthetics, these devices continue to lack intuitive control. Conventional myoelectric control strategies typically utilize electromyography (EMG) signal amplitude sensed from forearm muscles. EMG has limited specificity in resolving deep muscle activity and poor signal-to-noise ratio. We have been investigating alternative control strategies that rely on real-time ultrasound imaging that can overcome many of the limitations of EMG. In this work, we present an ultrasound image sequence classification method that utilizes spatiotemporal features to describe muscle activity and classify motor intent. Ultrasound images of the forearm muscles were obtained from able-bodied subjects and a trans-radial amputee while they attempted different hand movements. A grid-based approach is used to test the feasibility of using spatio-temporal features by classifying hand motions performed by the subjects. Using the leave-one-out cross validation on image sequences acquired from able-bodied subjects, we observe that the grid-based approach is able to discern four hand motions with 95.31% accuracy. In case of the trans-radial amputee, we are able to discern three hand motions with 80% accuracy. In a second set of experiments, we study classification accuracy by extracting spatio-temporal sub-sequences the depict activity due to the motion of local anatomical interfaces. Short time and space limited cuboidal sequences are initially extracted and assigned an optical flow behavior label, based on a response function. The image space is clustered based on the location of cuboids and features calculated from the cuboids in each cluster. Using sequences of known motions, we extract feature vectors that describe said motion. A K-nearest neighbor classifier is designed for classification experiments. Using the leave-one-out cross validation on image sequences for an amputee subject, we demonstrate that the classifier is

  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. Spatio-temporal autocorrelation of Neogene-Quaternary volcanic and clastic sedimentary rocks in SW Montana and SE Idaho: Relationship to Cenozoic tectonic and thermally induced extensional events

    NASA Astrophysics Data System (ADS)

    Davarpanah, A.; Babaie, H. A.; Dai, D.

    2013-12-01

    standard deviation ellipses (SDEs), that give the trend of the dispersion of the centroids of lavas erupted at different times, and the spatio-temporally ordered overlap of older lavas by younger ones which were progressively erupted to the northeast of the older lavas, indicate the spatio-temporal migration of the centers of eruption along the SRP. Prominent graben basins which formed and filled during and after the BR normal faulting event were identified from those that formed during and after the cross faulting event based on cross cutting relationships and the trend of their long dimension (determined by applying the Dissolve and Minimum Bounding Geometry tools in ArcGIS 10) relative to the linear directional mean (LDM) of the BR and CF sets. The parallelism of the mean trend of the Ts graben fill polygons with the linear directional mean (LDM) of each of the two BR fault trace sets in the eastern SRP indicates that the Neogene deposition of the Ts is post-BR and pre-to syn-cross faulting. Cross-fault-bounded graben valleys filled with Ts roughly sub-parallel the mean trend of the CF sets, indicating that they formed after the BR faulting event.

  17. The Critical Role of Golgi Cells in Regulating Spatio-Temporal Integration and Plasticity at the Cerebellum Input Stage

    PubMed Central

    D'Angelo, Egidio

    2008-01-01

    The discovery of the Golgi cell is bound to the foundation of the Neuron Doctrine. Recently, the excitable mechanisms of this inhibitory interneuron have been investigated with modern experimental and computational techniques raising renewed interest for the implications it might have for cerebellar circuit functions. Golgi cells are pacemakers with preferential response frequency and phase-reset in the theta-frequency band and can therefore impose specific temporal dynamics to granule cell responses. Moreover, through their connectivity, Golgi cells determine the spatio-temporal organization of cerebellar activity. Finally, Golgi cells, by controlling granule cell depolarization and NMDA channel unblock, regulate the induction of long-term synaptic plasticity at the mossy fiber – granule cell synapse. Thus, the Golgi cells can exert an extensive control on spatio-temporal signal organization and information storage in the granular layer playing a critical role for cerebellar computation. PMID:18982105

  18. Spatio-temporal expression of the pathway-specific regulatory gene redD in S. coelicolor.

    PubMed

    Zhou, Li-hua; Li, Yu-qin; Li, Yong-quan; Wu, Dan

    2005-06-01

    Confocal laser scanning microscopy was used to observe the spatio-temporal expression of the pathway-specific gene redD during S. coelicolor cell cultivation. The corresponding mutant S. coelicolor lyqRY1522 carrying redD::eyfp in the chromosome was constructed. The temporal expression results of the fusion protein during submerged cultivation demonstrated that expression of redD began in the transition phase, continuing through the exponential growth phase to the stationary phase, and reached maximum in the stationary phase. On the other hand, redD was expressed only in substrate mycelia during solid-state culture, while aerial mycelia remained essentially non-fluorescent throughout culture. Results demonstrated that the expression pattern of redD coincides with that of the biosynthesis of the antibiotics during culture, revealing a direct correlation between the spatio-temporal distribution of regulatory gene expression and second metabolism.

  19. Spatio-temporal waves and targeted vaccination in recurrent epidemic network models.

    PubMed

    Litvak-Hinenzon, Anna; Stone, Lewi

    2009-09-06

    The success of an infectious disease to invade a population is strongly controlled by the population's specific connectivity structure. Here, a network model is presented as an aid in understanding the role of social behaviour and heterogeneous connectivity in determining the spatio-temporal patterns of disease dynamics. We explore the controversial origins of long-term recurrent oscillations believed to be characteristic of diseases that have a period of temporary immunity after infection. In particular, we focus on sexually transmitted diseases such as syphilis, where this controversy is currently under review. Although temporary immunity plays a key role, it is found that, in realistic small-world networks, the social and sexual behaviour of individuals also has a great influence in generating long-term cycles. The model generates circular waves of infection with unusual spatial dynamics that depend on focal areas that act as pacemakers in the population. Eradication of the disease can be efficiently achieved by eliminating the pacemakers with a targeted vaccination scheme. A simple difference equation model is derived, which captures the infection dynamics of the network model and gives insights into their origins and their eradication through vaccination. Illustrative videos may be found in the electronic supplementary material.

  20. Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015

    PubMed Central

    Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A.

    2017-01-01

    Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009–2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted. PMID:28319125

  1. Spatio-temporal patterns of leptospirosis in Thailand: is flooding a risk factor?

    PubMed

    Suwanpakdee, S; Kaewkungwal, J; White, L J; Asensio, N; Ratanakorn, P; Singhasivanon, P; Day, N P J; Pan-Ngum, W

    2015-07-01

    We studied the temporal and spatial patterns of leptospirosis, its association with flooding and animal census data in Thailand. Flood data from 2010 to 2012 were extracted from spatial information taken from satellite images. The incidence rate ratio (IRR) was used to determine the relationship between spatio-temporal flooding patterns and the number of human leptospirosis cases. In addition, the area of flood coverage, duration of waterlogging, time lags between flood events, and a number of potential animal reservoirs were considered in a sub-analysis. There was no significant temporal trend of leptospirosis over the study period. Statistical analysis showed an inconsistent relationship between IRR and flooding across years and regions. Spatially, leptospirosis occurred repeatedly and predominantly in northeastern Thailand. Our findings suggest that flooding is less influential in leptospirosis transmission than previously assumed. High incidence of the disease in the northeastern region is explained by the fact that agriculture and animal farming are important economic activities in this area. The periodic rise and fall of reported leptospirosis cases over time might be explained by seasonal exposure from rice farming activities performed during the rainy season when flood events often occur. We conclude that leptospirosis remains an occupational disease in Thailand.

  2. Spatio-temporal control of femtosecond laser filamentation and white-light generation

    NASA Astrophysics Data System (ADS)

    Kaya, N.; Kaya, G.; Strohaber, J.; Kolomenskii, A.; Schuessler, H.

    2017-02-01

    Several possibilities are investigated to control spatio-temporal characteristics of the femtosecond filamentation process and the resulting white-light generation. We controlled the development of self-focusing, and resulting locations of filaments producing white-light in water by changing the transverse spatial phase of an initial Gaussian beam with a computer generated holographic technique and a spatial light modulator. We studied intense femtosecond filamentation and propagation of femtosecond pulses with different transverse modes in water. The filament propagation length was found to increase with Bessel-Gaussian modes of the beams, when more lateral lobes were used, under the conditions of the same peak intensity, pulse duration, and size of the central peak of the incident beam. We also investigated variations of white-light generation when the delay between the two pulses was varied. With a decrease of the relative delay, an enhancement of white-light output was observed, which at near-zero delays was reverted to a suppression of white-light generation.

  3. [Spatio-temporal dynamics of ecosystem service value in Wuhan Urban Agglomeration].

    PubMed

    Zeng, Jie; Li, Jiang-Feng; Yao, Xiao-Wei

    2014-03-01

    Based on the land use vector data of Wuhan Urban Agglomeration in the years 1990, 2000 and 2009, this paper used Costanza' s evaluation formula to estimate the ecosystem service value (ESV) of the study area according to "equivalent value per unit area of ecosystem services in China" and analyze its spatio-temporal characteristics. Then the correlation analysis was applied to explore the association between the ESV evolution and the land use changes. The results showed that due to the substantial growth of water area, the ESV of Wuhan Urban Agglomeration increased by 9.5% during the study period, which showed an overall rising trend. The ESV of water regulation and waste treatment increased obviously. Furthermore, the ESV changes showed obvious regional differences, which were most significant in Xiantao, Xinzhou and Yunmeng. The ESV was higher in the southeast and lower in the northwest. Over time, a Wuhan-centered "low-high-low" hierarchically distributed structure of ESV was formed in the eastern, western and northern parts. The ecologic dominance of the northern mountainous and hilly region was gradually abated, while a structural expansion with a high-ESV cluster had taken place in the southern part of the region in 2009. During the research period, the temporal change of ESV in Wuhan Urban Agglomeration was positively correlated with the area changes of forestland, water, grassland and cultivated land. However, the spatially balanced distribution of ESV was negatively correlated with the dispersion degrees of the cultivated land and unused land.

  4. Differential spatio-temporal expression of carotenoid cleavage dioxygenases regulates apocarotenoid fluxes during AM symbiosis.

    PubMed

    López-Ráez, Juan A; Fernández, Iván; García, Juan M; Berrio, Estefanía; Bonfante, Paola; Walter, Michael H; Pozo, María J

    2015-01-01

    Apocarotenoids are a class of compounds that play important roles in nature. In recent years, a prominent role for these compounds in arbuscular mycorrhizal (AM) symbiosis has been shown. They are derived from carotenoids by the action of the carotenoid cleavage dioxygenase (CCD) enzyme family. In the present study, using tomato as a model, the spatio-temporal expression pattern of the CCD genes during AM symbiosis establishment and functioning was investigated. In addition, the levels of the apocarotenoids strigolactones (SLs), C13 α-ionol and C14 mycorradicin (C13/C14) derivatives were analyzed. The results suggest an increase in SLs promoted by the presence of the AM fungus at the early stages of the interaction, which correlated with an induction of the SL biosynthesis gene SlCCD7. At later stages, induction of SlCCD7 and SlCCD1 expression in arbusculated cells promoted the production of C13/C14 apocarotenoid derivatives. We show here that the biosynthesis of apocarotenoids during AM symbiosis is finely regulated throughout the entire process at the gene expression level, and that CCD7 constitutes a key player in this regulation. Once the symbiosis is established, apocarotenoid flux would be turned towards the production of C13/C14 derivatives, thus reducing SL biosynthesis and maintaining a functional symbiosis.

  5. Spatio-temporal clustering and density estimation of lightning data for the tracking of convective events

    NASA Astrophysics Data System (ADS)

    Strauss, Cesar; Rosa, Marcelo Barbio; Stephany, Stephan

    2013-12-01

    Convective cells are cloud formations whose growth, maturation and dissipation are of great interest among meteorologists since they are associated with severe storms with large precipitation structures. Some works suggest a strong correlation between lightning occurrence and convective cells. The current work proposes a new approach to analyze the correlation between precipitation and lightning, and to identify electrically active cells. Such cells may be employed for tracking convective events in the absence of weather radar coverage. This approach employs a new spatio-temporal clustering technique based on a temporal sliding-window and a standard kernel density estimation to process lightning data. Clustering allows the identification of the cells from lightning data and density estimation bounds the contours of the cells. The proposed approach was evaluated for two convective events in Southeast Brazil. Image segmentation of radar data was performed to identify convective precipitation structures using the Steiner criteria. These structures were then compared and correlated to the electrically active cells in particular instants of time for both events. It was observed that most precipitation structures have associated cells, by comparing the ground tracks of their centroids. In addition, for one particular cell of each event, its temporal evolution was compared to that of the associated precipitation structure. Results show that the proposed approach may improve the use of lightning data for tracking convective events in countries that lack weather radar coverage.

  6. Spatio-temporal distribution of dengue fever under scenarios of climate change in the southern Taiwan

    NASA Astrophysics Data System (ADS)

    Lee, Chieh-Han; Yu, Hwa-Lung

    2014-05-01

    Dengue fever has been recognized as the most important widespread vector-borne infectious disease in recent decades. Over 40% of the world's population is risk from dengue and about 50-100 million people are infected world wide annually. Previous studies have found that dengue fever is highly correlated with climate covariates. Thus, the potential effects of global climate change on dengue fever are crucial to epidemic concern, in particular, the transmission of the disease. This present study investigated the nonlinearity of time-delayed impact of climate on spatio-temporal variations of dengue fever in the southern Taiwan during 1998 to 2011. A distributed lag nonlinear model (DLNM) is used to assess the nonlinear lagged effects of meteorology. The statistically significant meteorological factors are considered, including weekly minimum temperature and maximum 24-hour rainfall. The relative risk and the distribution of dengue fever then predict under various climate change scenarios. The result shows that the relative risk is similar for different scenarios. In addition, the impact of rainfall on the incidence risk is higher than temperature. Moreover, the incidence risk is associated to spatially population distribution. The results can be served as practical reference for environmental regulators for the epidemic prevention under climate change scenarios.

  7. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon

    PubMed Central

    Putman, Nathan F.; Jenkins, Erica S.; Michielsens, Catherine G. J.; Noakes, David L. G.

    2014-01-01

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

  8. Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX

    NASA Astrophysics Data System (ADS)

    da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho

    2016-10-01

    Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.

  9. Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.

    PubMed

    Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A

    2017-01-01

    Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.

  10. Spatio-Temporal Dynamics of Impulse Responses to Figure Motion in Optic Flow Neurons

    PubMed Central

    Lee, Yu-Jen; Jönsson, H. Olof; Nordström, Karin

    2015-01-01

    White noise techniques have been used widely to investigate sensory systems in both vertebrates and invertebrates. White noise stimuli are powerful in their ability to rapidly generate data that help the experimenter decipher the spatio-temporal dynamics of neural and behavioral responses. One type of white noise stimuli, maximal length shift register sequences (m-sequences), have recently become particularly popular for extracting response kernels in insect motion vision. We here use such m-sequences to extract the impulse responses to figure motion in hoverfly lobula plate tangential cells (LPTCs). Figure motion is behaviorally important and many visually guided animals orient towards salient features in the surround. We show that LPTCs respond robustly to figure motion in the receptive field. The impulse response is scaled down in amplitude when the figure size is reduced, but its time course remains unaltered. However, a low contrast stimulus generates a slower response with a significantly longer time-to-peak and half-width. Impulse responses in females have a slower time-to-peak than males, but are otherwise similar. Finally we show that the shapes of the impulse response to a figure and a widefield stimulus are very similar, suggesting that the figure response could be coded by the same input as the widefield response. PMID:25955416

  11. [Spatio-temporal variation of subtidal meiofauna in a sandy beach from Northeastern Venezuela].

    PubMed

    Arana, Ildefonso Liñero; Ojeda, Sol; Amaro, María Elena

    2013-03-01

    Meiofauna organisms that play an important role in the trophic ecology of soft bottom benthos, have short life cycles and they respond quickly to disturbance and pollution. The present study shows the spatio-temporal variation ofsubtidal meiofauna (metazoans passing a 500im sieve but retained on meshes of 40-63micro m) in four shallow subtidal stations. Samples were taken in the sandy beach of San Luis, in the Northeastern coast of Venezuela, from October 2005 until September 2006. For this, three replicate sediment core samples (4.91cm2), were collected monthly to a depth of 10cm into the sediment, and preserved in 6% formalin stained with rose Bengal. Specimens of 14 meiofaunal groups (Foraminifera excluded) were collected, being the nematodes, ostracods and harpacticoid copepods the most abundant. Monthly density was comprised between 64 and 503ind./10cm2, and mean density of stations between 173 and 449ind./10cm2. There is a trend of low densities from October to February (end of the rainy season until the middle of the dry season). The San Luis beach control of the meiofaunal community is shared by climatic conditions and by the biology of the species found. The meiofauna mean density in San Luis beach (263ind./10cm2) was low when compared to other studies in tropical areas.

  12. Pesticide occurrence and spatio-temporal variability in urban run-off across Australia.

    PubMed

    Rippy, Megan A; Deletic, Ana; Black, Jeff; Aryal, Rupak; Lampard, Jane-Louise; Tang, Janet Yat-Man; McCarthy, David; Kolotelo, Peter; Sidhu, Jatinder; Gernjak, Wolfgang

    2017-05-15

    Stormwater is a major driving factor of aquatic ecosystem degradation as well as one of the largest untapped urban freshwater resources. We present results from a long-term, multi-catchment study of urban stormwater pesticides across Australia that addresses this dichotomous identity (threat and resource), as well as dominant spatial and temporal patterns in stormwater pesticide composition. Of the 27 pesticides monitored, only 19 were detected in Australian stormwater, five of which (diuron, MCPA, 2,4-D, simazine, and triclopyr) were found in >50% of samples. Overall, stormwater pesticide concentrations were lower than reported in other countries (including the United States, Canada and Europe), and exceedances of public health and aquatic ecosystem standards were rare (<10% of samples). Spatio-temporal patterns were investigated with principal component analysis. Although stormwater pesticide composition was relatively stable across seasons and years, it varied significantly by catchment. Common pesticide associations appear to reflect 1) user application of common registered formulations containing characteristic suites of active ingredients, and 2) pesticide fate properties (e.g., environmental mobility and persistence). Importantly, catchment-specific occurrence patterns provide opportunities for focusing treatment approaches or stormwater harvesting strategies.

  13. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

    PubMed

    Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

    2014-10-06

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species.

  14. An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data

    PubMed Central

    Ping, Bo; Su, Fenzhen; Meng, Yunshan

    2016-01-01

    In this study, an improved Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm for determination of missing values in a spatio-temporal dataset is presented. Compared with the ordinary DINEOF algorithm, the iterative reconstruction procedure until convergence based on every fixed EOF to determine the optimal EOF mode is not necessary and the convergence criterion is only reached once in the improved DINEOF algorithm. Moreover, in the ordinary DINEOF algorithm, after optimal EOF mode determination, the initial matrix with missing data will be iteratively reconstructed based on the optimal EOF mode until the reconstruction is convergent. However, the optimal EOF mode may be not the best EOF for some reconstructed matrices generated in the intermediate steps. Hence, instead of using asingle EOF to fill in the missing data, in the improved algorithm, the optimal EOFs for reconstruction are variable (because the optimal EOFs are variable, the improved algorithm is called VE-DINEOF algorithm in this study). To validate the accuracy of the VE-DINEOF algorithm, a sea surface temperature (SST) data set is reconstructed by using the DINEOF, I-DINEOF (proposed in 2015) and VE-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF and I-DINEOF algorithms, the VE-DINEOF algorithm can significantly enhance the accuracy of reconstruction and shorten the computational time. PMID:27195692

  15. Spatio-temporal activity in real time (STAR): Optimization of regional fMRI feedback

    PubMed Central

    Magland, Jeremy F.; Tjoa, Christopher W.; Childress, Anna Rose

    2011-01-01

    The use of real-time feedback has expanded fMRI from a brain probe to include potential brain interventions with significant therapeutic promise. However, whereas time-averaged blood oxygenation level-dependent (BOLD) signal measurement is usually sufficient for probing a brain state, the real-time (frame-to-frame) BOLD signal is noisy, compromising feedback accuracy. We have developed a new real-time processing technique (STAR) that combines noise-reduction properties of multi-voxel (e.g., whole-brain) techniques with the regional specificity critical for therapeutics. Nineteen subjects were given real-time feedback in a cognitive control task (imagining repetitive motor activity vs. spatial navigation), and were all able to control a visual feedback cursor based on whole-brain neural activity. The STAR technique was evaluated, retrospectively, for five a priori regions of interest in these data, and was shown to provide significantly better (frame-by-frame) classification accuracy than a regional BOLD technique. In addition to regional feedback signals, the output of the STAR technique includes spatio-temporal activity maps (movies) providing insight into brain dynamics. The STAR approach offers an appealing optimization for real-time fMRI applications requiring an anatomically-localized feedback signal. PMID:21232612

  16. Spatio-temporal feature-extraction techniques for isolated gesture recognition in Arabic sign language.

    PubMed

    Shanableh, Tamer; Assaleh, Khaled; Al-Rousan, M

    2007-06-01

    This paper presents various spatio-temporal feature-extraction techniques with applications to online and offline recognitions of isolated Arabic Sign Language gestures. The temporal features of a video-based gesture are extracted through forward, backward, and bidirectional predictions. The prediction errors are thresholded and accumulated into one image that represents the motion of the sequence. The motion representation is then followed by spatial-domain feature extractions. As such, the temporal dependencies are eliminated and the whole video sequence is represented by a few coefficients. The linear separability of the extracted features is assessed, and its suitability for both parametric and nonparametric classification techniques is elaborated upon. The proposed feature-extraction scheme was complemented by simple classification techniques, namely, K nearest neighbor (KNN) and Bayesian, i.e., likelihood ratio, classifiers. Experimental results showed classification performance ranging from 97% to 100% recognition rates. To validate our proposed technique, we have conducted a series of experiments using the classical way of classifying data with temporal dependencies, namely, hidden Markov models (HMMs). Experimental results revealed that the proposed feature-extraction scheme combined with simple KNN or Bayesian classification yields comparable results to the classical HMM-based scheme. Moreover, since the proposed scheme compresses the motion information of an image sequence into a single image, it allows for using simple classification techniques where the temporal dimension is eliminated. This is actually advantageous for both computational and storage requirements of the classifier.

  17. Spatio-temporal patterns in pollination of deceptive Aristolochia rotunda L. (Aristolochiaceae).

    PubMed

    Oelschlägel, B; von Tschirnhaus, M; Nuss, M; Nikolić, T; Wanke, S; Dötterl, S; Neinhuis, C

    2016-11-01

    Pollination success of highly specialised flowers is susceptible to fluctuations of the pollinator fauna. Mediterranean Aristolochia rotunda has deceptive trap flowers exhibiting a highly specialised pollination system. The sole pollinators are kleptoparasitic flies in search of food. This study investigates these pollinators on a spatio-temporal scale and the impact of weather conditions on their availability. Two potential strategies of the plants to cope with pollinator limitation, i.e. autonomous selfing and an increased floral life span, were tested. A total of 6156 flowers were investigated for entrapped pollinators in 10 Croatian populations. Availability of the main pollinator was correlated to meteorological data. Artificial pollination experiments were conducted and the floral life span was recorded in two populations according to pollinator availability. Trachysiphonella ruficeps (Chloropidae) was identified as dominant pollinator, along with less abundant species of Chloropidae, Ceratopogonidae and Milichiidae. Pollinator compositions varied among populations. Weather conditions 15-30 days before pollination had a significant effect on availability of the main pollinator. Flowers were not autonomously selfing, and the floral life span exhibited considerable plasticity depending on pollinator availability. A. rotunda flowers rely on insect pollen vectors. Plants are specialised on a guild of kleptoparasitic flies, rather than on a single species. Pollinator variability may result in differing selection pressures among populations. The availability/abundance of pollinators depends on weather conditions during their larval development. Flowers show a prolonged trapping flower stage that likely increases outcrossing success during periods of pollinator limitation.

  18. Spatio-temporal patterns of redox potential diffusive boundarys around Potamogeton crispus leaves and stems

    NASA Astrophysics Data System (ADS)

    Dong, B.

    2016-08-01

    To understand functions of a diffusive boundary layer around submerged macrophytes, the redox potential (ORP) around the leaves and stems of Potamogeton crispus were measured using a microsensor. Periphyton attached on macrophytes was analysed with the standard method. Results showed that significant spatio-temporal variations of ORP existed around leaves of P. crispus. In a vertical direction (within 2 mm), ORP significantly decreased with reducing distance from the leaf /stem surfaces and reached a minimum (428.51 mv) at the leaf /stem surface. The ORP microprofile was steepest around the mature leaf at the middle shoot and that of the senescent leaves at the basal shoot was relatively flat. At the temporal scale, the ORP microprofile was steepest at the stable growing stage, and those of the seedling stage and declining stage were relatively flat. Periphyton attached on P. crispus became dense gradually upon macrophyte entering growth stages. The results indicated that characteristics of ORP microprofiles were mainly affected by macrophytic physiological characteristics and periphyton synergistically.

  19. Spatio-Temporal Analysis of Cell-Cell Signaling in a Living Cell Microarray

    NASA Astrophysics Data System (ADS)

    Mirsaidov, Utkur; Timp, Winston; Timp, Kaethe; Matsudaira, Paul; Timp, Greg

    2007-03-01

    Cell-cell signaling plays a central role in biology, enabling individual cells to coordinate their activities. For example, bacteria show evidence of intercellular signaling through quorum sensing, a regulatory mechanism that launches a coordinated response, depending on the population density. To explore the spatio-temporal development of cell-to-cell signaling, we have created regular, heterotypic microarrays of living cells in hydrogel using time-multiplexed optical traps for submicron positional control of the cell orientation and location without loss of viability. We studied the Lux system for quorum sensing; splitting it into sender and receiver plasmids, which were subsequently introduced into E. Coli. Induced by IPTG, the sender cells express a fluorescent reporter (mRFP1) and the LuxI enzyme that catalyzes the synthesis of a molecular signal AHL that diffuses through the cell membrane and the extra-cellular scaffold. The receiver cells collect the AHL signal that binds to the LuxR regulator and reports it through GFP production. We have measured the time-delay between the onset of mRFP1 and GFP dependence on intercellular spacing in the array.

  20. Spatio-temporal expression patterns of anterior Hox genes during Nile tilapia (Oreochromis niloticus) embryonic development.

    PubMed

    Lyon, R Stewart; Davis, Adam; Scemama, Jean-Luc

    2013-01-01

    Hox genes encode transcription factors that function to pattern regional tissue identities along the anterior-posterior axis during animal embryonic development. Divergent nested Hox gene expression patterns within the posterior pharyngeal arches may play an important role in patterning morphological variation in the pharyngeal jaw apparatus (PJA) between evolutionarily divergent teleost fishes. Recent gene expression studies have shown the expression patterns from all Hox paralog group (PG) 2-6 genes in the posterior pharyngeal arches (PAs) for the Japanese medaka (Oryzias latipes) and from most genes of these PGs for the Nile tilapia (Oreochromis niloticus). While several orthologous Hox genes exhibit divergent spatial and temporal expression patterns between these two teleost species in the posterior PAs, several tilapia Hox gene expression patterns from PG3-6 must be documented for a full comparative study. Here we present the spatio-temporal expression patterns of hoxb3b, c3a, b4a, a5a, b5a, b5b, b6a and b6b in the neural tube and posterior PAs of the Nile tilapia. We show that several of these tilapia Hox genes exhibit divergent expression patterns in the posterior PAs from their medaka orthologs. We also compare these gene expression patterns to orthologs in other gnathostome vertebrates, including the dogfish shark.

  1. Spatio-temporal dynamics of genetic diversity in Sorghum bicolor in Niger.

    PubMed

    Deu, Monique; Sagnard, F; Chantereau, J; Calatayud, C; Vigouroux, Y; Pham, J L; Mariac, C; Kapran, I; Mamadou, A; Gérard, B; Ndjeunga, J; Bezançon, G

    2010-05-01

    The dynamics of crop genetic diversity need to be assessed to draw up monitoring and conservation priorities. However, few surveys have been conducted in centres of diversity. Sub-Saharan Africa is the centre of origin of sorghum. Most Sahel countries have been faced with major human, environmental and social changes in recent decades, which are suspected to cause genetic erosion. Sorghum is the second staple cereal in Niger, a centre of diversity for this crop. Niger was submitted to recurrent drought period and to major social changes during these last decades. We report here on a spatio-temporal analysis of sorghum genetic diversity, conducted in 71 villages covering the rainfall gradient and range of agro-ecological conditions in Niger's agricultural areas. We used 28 microsatellite markers and applied spatial and genetic clustering methods to investigate change in genetic diversity over a 26-year period (1976-2003). Global genetic differentiation between the two collections was very low (F (st) = 0.0025). Most of the spatial clusters presented no major differentiation, as measured by F (st), and showed stability or an increase in allelic richness, except for two of them located in eastern Niger. The genetic clusters identified by Bayesian analysis did not show a major change between the two collections in the distribution of accessions between them or in their spatial location. These results suggest that farmers' management has globally preserved sorghum genetic diversity in Niger.

  2. 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

  3. Improving exposure assessment in environmental epidemiology: Application of spatio-temporal visualization tools

    NASA Astrophysics Data System (ADS)

    Meliker, Jaymie R.; Slotnick, Melissa J.; Avruskin, Gillian A.; Kaufmann, Andrew; Jacquez, Geoffrey M.; Nriagu, Jerome O.

    2005-05-01

    A thorough assessment of human exposure to environmental agents should incorporate mobility patterns and temporal changes in human behaviors and concentrations of contaminants; yet the temporal dimension is often under-emphasized in exposure assessment endeavors, due in part to insufficient tools for visualizing and examining temporal datasets. Spatio-temporal visualization tools are valuable for integrating a temporal component, thus allowing for examination of continuous exposure histories in environmental epidemiologic investigations. An application of these tools to a bladder cancer case-control study in Michigan illustrates continuous exposure life-lines and maps that display smooth, continuous changes over time. Preliminary results suggest increased risk of bladder cancer from combined exposure to arsenic in drinking water (>25 μg/day) and heavy smoking (>30 cigarettes/day) in the 1970s and 1980s, and a possible cancer cluster around automotive, paint, and organic chemical industries in the early 1970s. These tools have broad application for examining spatially- and temporally-specific relationships between exposures to environmental risk factors and disease.

  4. A Four Dimensional Spatio-Temporal Analysis of an Agricultural Dataset

    PubMed Central

    Donald, Margaret R.; Mengersen, Kerrie L.; Young, Rick R.

    2015-01-01

    While a variety of statistical models now exist for the spatio-temporal analysis of two-dimensional (surface) data collected over time, there are few published examples of analogous models for the spatial analysis of data taken over four dimensions: latitude, longitude, height or depth, and time. When taking account of the autocorrelation of data within and between dimensions, the notion of closeness often differs for each of the dimensions. Here, we consider a number of approaches to the analysis of such a dataset, which arises from an agricultural experiment exploring the impact of different cropping systems on soil moisture. The proposed models vary in their representation of the spatial correlation in the data, the assumed temporal pattern and choice of conditional autoregressive (CAR) and other priors. In terms of the substantive question, we find that response cropping is generally more effective than long fallow cropping in reducing soil moisture at the depths considered (100 cm to 220 cm). Thus, if we wish to reduce the possibility of deep drainage and increased groundwater salinity, the recommended cropping system is response cropping. PMID:26513746

  5. 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.

  6. Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

    NASA Astrophysics Data System (ADS)

    Naish, S.; Tong, S.

    2014-11-01

    Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

  7. 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.