WorldWideScience

Sample records for complex spatio-temporal regulation

  1. Spatio-temporal regulation of Hsp90-ligand complex leads to immune activation.

    Directory of Open Access Journals (Sweden)

    Yasuaki eTamura

    2016-05-01

    Full Text Available Hsp90 is the most abundant cytosolic HSP and is known to act as a molecular chaperone. We found that an Hsp90-cancer antigen peptide complex was efficiently cross-presented by human monocyte-derived dendritic cells and induced peptide-specific cytotoxic T lymphocytes. Furthermore, we observed that the internalized Hsp90-peptide complex was strictly sorted to the Rab5+, EEA1+ static early endosome and the Hsp90-chaperoned peptide was processed and bound to MHC class I molecules through a endosome-recycling pathway. We also found that extracellular Hsp90 complexed with CpG-A or self-DNA stimulates production of a large amount of IFN-α from pDCs via static early endosome targeting. Thus, extracellular Hsp90 can target the antigen or nucleic acid to a static early endosome by spatio-temporal regulation. Moreover, we showed that Hsp90 associates with and delivers TLR7/9 from the ER to early endosomes for ligand recognition. Hsp90 inhibitor, geldanamycin derivative inhibited the Hsp90 association with TLR7/9, resulting in inhibition IFN-α production, leading to improvement of SLE symptoms. Interstingly, we observed that serum Hsp90 is clearly increased in patients with active SLE compared with that in patients with inactive disease. Serum Hsp90 detected in SLE patients binds to self-DNA and/or anti-DNA Ab, thus leading to stimulation of pDCs to produce IFN-α. Thus, Hsp90 plays a crucial role in the pathogenesis of SLE and that an Hsp90 inhibitor will therefore provide a new therapeutic approach to SLE and other nucleic acid-related autoimmune diseases. We will discuss how spatio-temporal regulation of Hsp90-ligand complexes within antigen-presenting cells affects the innate immunity and adaptive immunity.

  2. Spatio-temporal databases complex motion pattern queries

    CERN Document Server

    Vieira, Marcos R

    2013-01-01

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

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

    Science.gov (United States)

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

    2016-04-01

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

  4. Spatio-temporal regulation of circular RNA expression during porcine embryonic brain development

    DEFF Research Database (Denmark)

    Venø, Morten T; Hansen, Thomas B; Venø, Susanne T

    2015-01-01

    BACKGROUND: Recently, thousands of circular RNAs (circRNAs) have been discovered in various tissues and cell types from human, mouse, fruit fly and nematodes. However, expression of circRNAs across mammalian brain development has never been examined. RESULTS: Here we profile the expression of circ......RNA in five brain tissues at up to six time-points during fetal porcine development, constituting the first report of circRNA in the brain development of a large animal. An unbiased analysis reveals a highly complex regulation pattern of thousands of circular RNAs, with a distinct spatio-temporal expression...... are functionally conserved between mouse and human. Furthermore, we observe that "hot-spot" genes produce multiple circRNA isoforms, which are often differentially expressed across porcine brain development. A global comparison of porcine circRNAs reveals that introns flanking circularized exons are longer than...

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

    Science.gov (United States)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

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

  6. Emergence of Complex Spatio-Temporal Behavior in Nonlinear Field Theories

    International Nuclear Information System (INIS)

    Gleiser, Marcelo; Howell, Rafael C.

    2006-01-01

    We investigate the emergence of time-dependent nonperturbative configurations during the evolution of nonlinear scalar field models with symmetric and asymmetric double-well potentials. Complex spatio-temporal behavior emerges as the system seeks to establish equipartition after a fast quench. We show that fast quenches may dramatically modify the decay rate of metastable states in first order phase transitions. We discuss possible applications in condensed matter systems and early universe cosmology

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

    Science.gov (United States)

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

    2017-06-15

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

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

    Science.gov (United States)

    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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. Spatio-temporal regulation of ADAR editing during development in porcine neural tissues

    DEFF Research Database (Denmark)

    Venø, Morten Trillingsgaard; Bramsen, Jesper Bertram; Bendixen, Christian

    2012-01-01

    Editing by ADAR enzymes is essential for mammalian life. Still, knowledge of the spatio-temporal editing patterns in mammals is limited. By use of 454 amplicon sequencing we examined the editing status of 12 regionally extracted mRNAs from porcine developing brain encompassing a total of 64...... putative ADAR editing sites. In total 24 brain tissues, dissected from up to five regions from embryonic gestation day 23, 42, 60, 80, 100 and 115, were examined for editing....

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

    Science.gov (United States)

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

    2012-01-01

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

  11. The critical role of Golgi cells in regulating spatio-temporal integration and plasticity at the cerebellum input stage

    Directory of Open Access Journals (Sweden)

    2008-07-01

    Full Text Available After the discovery at the end of the 19th century (Golgi, 1883, the Golgi cell was precisely described by S.R. y Cajal (see Cajal, 1987, 1995 and functionally identified as an inhibitory interneuron 50 years later by J.C. Eccles and colleagues (Eccles e al., 1967. Then, its role has been casted by Marr (1969 within the Motor Learning Theory as a codon size regulator of granule cell activity. It was immediately clear that Golgi cells had to play a critical role, since they are the main inhibitory interneuron of the granular layer and control activity of as many as 100 millions granule cells. In vitro, Golgi cells show pacemaking, resonance, phase-reset and rebound-excitation in the theta-frequency band. These properties are likely to impact on their activity in vivo, which shows irregular spontaneous beating modulated by sensory inputs and burst responses to punctuate stimulation followed by a silent pause. Moreover, investigations have given insight into Golgi cells connectivity within the cerebellar network and on their impact on the spatio-temporal organization of activity. It turns out that Golgi cells can control both the temporal dynamics and the spatial distribution of information transmitted through the cerebellar network. Moreover, Golgi cells regulate the induction of long-term synaptic plasticity at the mossy fiber - granule cell synapse. Thus, the concept is emerging that Golgi cells are of critical importance for regulating granular layer network activity bearing important consequences for cerebellar computation as a whole.

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

    Science.gov (United States)

    Konapala, Goutam; Mishra, Ashok

    2017-12-01

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

  13. Spatio-Temporal Rule Mining

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2005-01-01

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

  14. Identifying Causal Gateways and Mediators in Complex Spatio-Temporal Systems

    Czech Academy of Sciences Publication Activity Database

    Runge, J.; Petoukhov, V.; Donges, J.F.; Hlinka, Jaroslav; Jajcay, Nikola; Vejmelka, Martin; Hartman, David; Marwan, N.; Paluš, Milan; Kurths, J.

    2015-01-01

    Roč. 6, 7 October (2015), Article 8502 ISSN 2041-1723 R&D Projects: GA ČR(CZ) GA14-02634S; GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Grant - others:GA MŠk(CZ) LL1201; AV ČR + DAAD(CZ-DE) DAAD-15-30 Program:Bilaterální spolupráce Institutional support: RVO:67985807 Keywords : causality * climate * complex systems * dimension reduction * atmospheric dynamics * networks * dynamical systems Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 11.329, year: 2015

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

    Science.gov (United States)

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

    2010-12-01

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

  16. Deciphering the spatio-temporal complexity of climate change of the last deglaciation: a model analysis

    Directory of Open Access Journals (Sweden)

    D. M. Roche

    2011-06-01

    Full Text Available Understanding the sequence of events occuring during the last major glacial to interglacial transition (21 ka BP to 9 ka BP is a challenging task that has the potential to unveil the mechanisms behind large scale climate changes. Though many studies have focused on the understanding of the complex sequence of rapid climatic change that accompanied or interrupted the deglaciation, few have analysed it in a more theoretical framework with simple forcings. In the following, we address when and where the first significant temperature anomalies appeared when using slow varying forcing of the last deglaciation. We used here coupled transient simulations of the last deglaciation, including ocean, atmosphere and vegetation components to analyse the spatial timing of the deglaciation. To keep the analysis in a simple framework, we did not include freshwater forcings that potentially cause rapid climate shifts during that time period. We aimed to disentangle the direct and subsequent response of the climate system to slow forcing and moreover, the location where those changes are more clearly expressed. In a data – modelling comparison perspective, this could help understand the physically plausible phasing between known forcings and recorded climatic changes. Our analysis of climate variability could also help to distinguish deglacial warming signals from internal climate variability. We thus are able to better pinpoint the onset of local deglaciation, as defined by the first significant local warming and further show that there is a large regional variability associated with it, even with the set of slow forcings used here. In our model, the first significant hemispheric warming occurred simultaneously in the North and in the South and is a direct response to the obliquity forcing.

  17. A decade of understanding spatio-temporal regulation of DNA repair by the nuclear architecture.

    Science.gov (United States)

    Saad, Hicham; Cobb, Jennifer A

    2016-10-01

    The nucleus is a hub for gene expression and is a highly organized entity. The nucleoplasm is heterogeneous, owing to the preferential localization of specific metabolic factors, which lead to the definition of nuclear compartments or bodies. The genome is organized into chromosome territories, as well as heterochromatin and euchromatin domains. Recent observations have indicated that nuclear organization is important for maintaining genomic stability. For example, nuclear organization has been implicated in stabilizing damaged DNA, repair-pathway choice, and in preventing chromosomal rearrangements. Over the past decade, several studies have revealed that dynamic changes in the nuclear architecture are important during double-strand break repair. Stemming from work in yeast, relocation of a damaged site prior to repair appears to be at least partially conserved in multicellular eukaryotes. In this review, we will discuss genome and nucleoplasm architecture, particularly the importance of the nuclear periphery in genome stability. We will also discuss how the site of relocation regulates repair-pathway choice.

  18. The Voronoi spatio-temporal data structure

    Science.gov (United States)

    Mioc, Darka

    2002-04-01

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

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

    Directory of Open Access Journals (Sweden)

    LI Yinchao

    2016-07-01

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

  20. Spatio-temporal dependence of the signaling response in immune-receptor trafficking networks regulated by cell density: a theoretical model.

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    Pilar García-Peñarrubia

    Full Text Available Cell signaling processes involve receptor trafficking through highly connected networks of interacting components. The binding of surface receptors to their specific ligands is a key factor for the control and triggering of signaling pathways. In most experimental systems, ligand concentration and cell density vary within a wide range of values. Dependence of the signal response on cell density is related with the extracellular volume available per cell. This dependence has previously been studied using non-spatial models which assume that signaling components are well mixed and uniformly distributed in a single compartment. In this paper, a mathematical model that shows the influence exerted by cell density on the spatio-temporal evolution of ligands, cell surface receptors, and intracellular signaling molecules is developed. To this end, partial differential equations were used to model ligand and receptor trafficking dynamics through the different domains of the whole system. This enabled us to analyze several interesting features involved with these systems, namely: a how the perturbation caused by the signaling response propagates through the system; b receptor internalization dynamics and how cell density affects the robustness of dose-response curves upon variation of the binding affinity; and c that enhanced correlations between ligand input and system response are obtained under conditions that result in larger perturbations of the equilibrium ligand + surface receptor [Please see text] ligand - receptor complex. Finally, the results are compared with those obtained by considering that the above components are well mixed in a single compartment.

  1. Spatio-Temporal Data Construction

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    Hai Ha Le

    2013-08-01

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

  2. Compressing spatio-temporal trajectories

    DEFF Research Database (Denmark)

    Gudmundsson, Joachim; Katajainen, Jyrki; Merrick, Damian

    2009-01-01

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

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

    Science.gov (United States)

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  5. Spatio-temporal diversification of the cell wall matrix materials in the developing stomatal complexes of Zea mays.

    Science.gov (United States)

    Giannoutsou, E; Apostolakos, P; Galatis, B

    2016-11-01

    The matrix cell wall materials, in developing Zea mays stomatal complexes are asymmetrically distributed, a phenomenon appearing related to the local cell wall expansion and deformation, the establishment of cell polarity, and determination of the cell division plane. In cells of developing Zea mays stomatal complexes, definite cell wall regions expand determinately and become locally deformed. This differential cell wall behavior is obvious in the guard cell mother cells (GMCs) and the subsidiary cell mother cells (SMCs) that locally protrude towards the adjacent GMCs. The latter, emitting a morphogenetic stimulus, induce polarization/asymmetrical division in SMCs. Examination of immunolabeled specimens revealed that homogalacturonans (HGAs) with a high degree of de-esterification (2F4- and JIM5-HGA epitopes) and arabinogalactan proteins are selectively distributed in the extending and deformed cell wall regions, while their margins are enriched with rhamnogalacturonans (RGAs) containing highly branched arabinans (LM6-RGA epitope). In SMCs, the local cell wall matrix differentiation constitutes the first structural event, indicating the establishment of cell polarity. Moreover, in the premitotic GMCs and SMCs, non-esterified HGAs (2F4-HGA epitope) are preferentially localized in the cell wall areas outlining the cytoplasm where the preprophase band is formed. In these areas, the forthcoming cell plate fuses with the parent cell walls. These data suggest that the described heterogeneity in matrix cell wall materials is probably involved in: (a) local cell wall expansion and deformation, (b) the transduction of the inductive GMC stimulus, and (c) the determination of the division plane in GMCs and SMCs.

  6. Norepinephrine release from Locus Ceruleus:a central regulator for the CNS spatio-temporal activation pattern?

    Directory of Open Access Journals (Sweden)

    Marco Atzori

    2016-08-01

    Full Text Available Norepinephrine (NE is synthesized in the Locus Coeruleus (LC of the brainstem, from where it is released by axonal varicosities throughout the brain via volume transmission. A wealth of data from clinics and from animal models indicates that this catecholamine coordinates the activity of the central nervous system and of the whole organism by modulating cell function in a vast number of brain areas in a coordinated manner. The ubiquity of NE receptors, the daunting number of cerebral areas regulated by the catecholamine, as well as the variety of cellular effects and of their timescales have contributed so far to defeat the attempts to integrate central adrenergic function into a unitary and coherent framework.Since three main families of NE receptors are represented – in decreasing order of affinity for the catecholamine – by: 2 adrenoceptors (2Rs, high affinity, 1 adrenoceptors (1Rs, intermediate affinity, and  adrenoceptors (Rs, low affinity, on a pharmacological basis, and on the ground of recent studies on cellular and systemic central noradrenergic effects, we propose that an increase in LC tonic activity promotes the emergence of four global states covering the whole spectrum of brain activation: 1 sleep: virtual absence of NE, 2 quiet wake: activation of 2Rs, 3 active wake/physiological stress: activation of 2- and 1Rs, 4 distress: activation of 2-, 1-, and Rs.We postulate that excess intensity and/or duration of states 3 and 4 may lead to maladaptive plasticity, causing – in turn – a variety of neuropsychiatric illnesses including depression, schizophrenic psychoses, anxiety disorders, and attention deficit. The interplay between tonic and phasic LC activity identified in the LC in relationship with behavioral response is of critical importance in defining the short- and long-term biological mechanisms associated with the basic states postulated for the central nervous system. While the model

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

    KAUST Repository

    Zhang, Bohai

    2014-01-01

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  9. Spatio-temporal reasoning and decision support tools

    OpenAIRE

    Renso, Chiara; Wachowicz, Monica

    2014-01-01

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

  10. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    Science.gov (United States)

    Schöll, Eckehard

    2005-08-01

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

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

    OpenAIRE

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

    2012-01-01

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

  12. Spatio-Temporal Data Exchange Standards

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Schmidt, Albrecht

    2003-01-01

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

  13. Reliable Collaborative Filtering on Spatio-Temporal Privacy Data

    Directory of Open Access Journals (Sweden)

    Zhen Liu

    2017-01-01

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

  14. Spatio-temporal modeling for residential burglary

    NARCIS (Netherlands)

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

    2017-01-01

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

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

    OpenAIRE

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

    2013-01-01

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

  16. What Is Spatio-Temporal Data Warehousing?

    Science.gov (United States)

    Vaisman, Alejandro; Zimányi, Esteban

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

  17. Statistical methods for spatio-temporal systems

    CERN Document Server

    Finkenstadt, Barbel

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    C. Wu

    2015-07-01

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

  19. Spatio-temporal intermittency on the sandpile

    International Nuclear Information System (INIS)

    Erzan, A.; Sinha, S.

    1990-08-01

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

  20. N-cadherin in adult rat cardiomyocytes in culture. II. Spatio-temporal appearance of proteins involved in cell-cell contact and communication. Formation of two distinct N-cadherin/catenin complexes.

    Science.gov (United States)

    Hertig, C M; Butz, S; Koch, S; Eppenberger-Eberhardt, M; Kemler, R; Eppenberger, H M

    1996-01-01

    The spatio-temporal appearance and distribution of proteins forming the intercalated disc were investigated in adult rat cardiomyocytes (ARC). The 'redifferentiation model' of ARC involves extensive remodelling of the plasma membrane and of the myofibrillar apparatus. It represents a valuable system to elucidate the formation of cell-cell contact between cardiomyocytes and to assess the mechanisms by which different proteins involved in the cell-cell adhesion process are sorted in a precise manner to the sites of function. Appearance of N-cadherin, the catenins and connexin43 within newly formed adherens and gap junctions was studied. Here first evidence is provided for a formation of two distinct and separable N-cadherin/catenin complexes in cardiomyocytes. Both complexes are composed of N-cadherin and alpha-catenin which bind to either beta-catenin or plakoglobin in a mutually exclusive manner. The two N-cadherin/catenin complexes are assumed to be functionally involved in the formation of cell-cell contacts in ARC; however, the differential appearance and localization of the two types of complexes may also point to a specific role during ARC differentiation. The newly synthesized beta-catenin containing complex is more abundant during the first stages in culture after ARC isolation, while the newly synthesized plakoglobin containing complex progressively accumulates during the morphological changes of ARC. ARC formed a tissue-like pattern in culture whereby the new cell-cell contacts could be dissolved through Ca2+ depletion. Presence of cAMP and replenishment of Ca2+ content in the culture medium not only allowed reformation of cell-cell contacts but also affected the relative protein ratio between the two N-cadherin/catenin complexes, increasing the relative amount of newly synthesized beta-catenin over plakoglobin at a particular stage of ARC differentiation. The clustered N-cadherin/catenin complexes at the plasma membrane appear to be a prerequisite for the

  1. Spatio-temporal variations of carbon dioxide and its gross emission regulated by artificial operation in a typical hydropower reservoir in China.

    Science.gov (United States)

    Li, Zhe; Zhang, Zengyu; Xiao, Yan; Guo, Jinsong; Wu, Shengjun; Liu, Jing

    2014-05-01

    Supersaturation and excess emission of greenhouse gases in freshwater reservoirs have received a great deal of attention in recent years. Although impoundment of reservoirs has been shown to contribute to the net emission of greenhouse gases, reservoir age, geographical distribution, submerged soil type and artificial regulation also have a great impact on their emissions. To examine how large scale reservoir operation impact the water column CO2 and its air-water interface flux, a field study was conducted in 2010 to evaluate potential ecological processes that regulate the partial pressure of CO2 (pCO2) in the water column in the Pengxi River backwater area (PBA), a typical tributary in the Three Gorges Reservoir, China. Measurements of total alkalinity (TA), pH and water temperature were applied to compute the pCO2. And this approach was also validated by calculation of pCO2 from the dissolved inorganic carbon data of samples. Partial least squares (PLS) regression was used to determine how the dynamics of the water pCO2 were related to the available variables. The estimated pCO2 in our sample ranged from 26 to 4,087 μatm in the surface water. During low water operation from July to early September, there was an obvious pCO2 stratification, and pCO2 in the surface was almost unsaturated. This phenomenon was also observed in the spring bloom during discharge period. Conversely, there was no significant pCO2 stratification and the entire water column was supersaturated during high water operation from November to the following February. Significant correlation was observed between the magnitude of pCO2, DO and chlorophyll a, suggesting that phytoplankton dynamics regulate pCO2 in the PBA. The average areal rate of CO2 emissions from the Pengxi River ranged from 18.06 to 48.09 mmol m(-2) day(-1), with an estimated gross CO2 emission from the water surface of 14-37 t day(-1) in this area in 2010. Photosynthesis and respiration rates by phytoplankton might be the

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

    KAUST Repository

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

    2014-01-01

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

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

    KAUST Repository

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

    2015-01-01

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

  4. Excitability of the motor cortex ipsilateral to the moving body side depends on spatio-temporal task complexity and hemispheric specialization.

    Directory of Open Access Journals (Sweden)

    Femke E van den Berg

    Full Text Available Unilateral movements are mainly controlled by the contralateral hemisphere, even though the primary motor cortex ipsilateral (M1(ipsi 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 M1(ipsi 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 M1(ipsi 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 M1(ipsi only slightly. Our data revealed a clear hemispheric asymmetry such that MEP responses were significantly larger when elicited in the left M1(ipsi than in the right. In experiment 2, we tested whether the modulations of M1(ipsi 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 M1(ipsi. We argue that our results might reflect the stronger involvement of the left versus right hemisphere in performing demanding motor tasks.

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

    Science.gov (United States)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    WANG Jiayao

    2017-10-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    KAUST Repository

    Xu, Ganggang

    2015-01-01

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

  9. Sex & vision I: Spatio-temporal resolution

    Directory of Open Access Journals (Sweden)

    Abramov Israel

    2012-09-01

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

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

    Science.gov (United States)

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

    2009-10-01

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

  11. Spatio-temporal problems of locomotion control

    International Nuclear Information System (INIS)

    Smolyaninov, Vladimir V

    2000-01-01

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

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

    Monnai, T.

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

  14. Visualization and assessment of spatio-temporal covariance properties

    KAUST Repository

    Huang, Huang

    2017-11-23

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

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

    Science.gov (United States)

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

    2014-09-10

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

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

    Directory of Open Access Journals (Sweden)

    Gerber Susanne

    2011-04-01

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

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

    Science.gov (United States)

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

    2011-04-28

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

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

    Science.gov (United States)

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

    2015-01-01

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

  19. Spatio-temporal dynamics of the tropical rain forest

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-07-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    2012-01-01

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

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

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

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

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

    Böhringer, Klaus; Hess, Ortwin

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

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

    Science.gov (United States)

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

    2017-12-01

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

  6. State estimation of spatio-temporal phenomena

    Science.gov (United States)

    Yu, Dan

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

  7. Discovery of spatio-temporal patterns from location-based social networks

    Science.gov (United States)

    Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

    2016-03-01

    Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

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

    Science.gov (United States)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

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

  9. The Review of Visual Analysis Methods of Multi-modal Spatio-temporal Big Data

    Directory of Open Access Journals (Sweden)

    ZHU Qing

    2017-10-01

    Full Text Available The visual analysis of spatio-temporal big data is not only the state-of-art research direction of both big data analysis and data visualization, but also the core module of pan-spatial information system. This paper reviews existing visual analysis methods at three levels:descriptive visual analysis, explanatory visual analysis and exploratory visual analysis, focusing on spatio-temporal big data's characteristics of multi-source, multi-granularity, multi-modal and complex association.The technical difficulties and development tendencies of multi-modal feature selection, innovative human-computer interaction analysis and exploratory visual reasoning in the visual analysis of spatio-temporal big data were discussed. Research shows that the study of descriptive visual analysis for data visualizationis is relatively mature.The explanatory visual analysis has become the focus of the big data analysis, which is mainly based on interactive data mining in a visual environment to diagnose implicit reason of problem. And the exploratory visual analysis method needs a major break-through.

  10. Spatio-temporal data analytics for wind energy integration

    CERN Document Server

    Yang, Lei; Zhang, Junshan

    2014-01-01

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

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

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo

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

  12. Spatio-temporal modeling of nonlinear distributed parameter systems

    CERN Document Server

    Li, Han-Xiong

    2011-01-01

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

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

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  14. Large scale stochastic spatio-temporal modelling with PCRaster

    NARCIS (Netherlands)

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

    2013-01-01

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

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

    Czech Academy of Sciences Publication Activity Database

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

    2010-01-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  17. On spatio-temporal Lévy based Cox processes

    DEFF Research Database (Denmark)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhiqiang Tian

    2013-03-01

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

  19. Spatio-temporal joins on symbolic indoor tracking data

    DEFF Research Database (Denmark)

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

    2011-01-01

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

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

    Indian Academy of Sciences (India)

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

  1. Simultaneous spatio-temporal focusing for tissue manipulation

    Directory of Open Access Journals (Sweden)

    Squier J.

    2013-11-01

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

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

    Science.gov (United States)

    Ashdown, George W; Owen, Dylan M

    2018-02-02

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

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

    International Nuclear Information System (INIS)

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

    1996-01-01

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

  4. Spatio-temporal coupling of EEG signals in epilepsy

    Science.gov (United States)

    Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

    2011-05-01

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

  5. Effective and efficient analysis of spatio-temporal data

    Science.gov (United States)

    Zhang, Zhongnan

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

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

    KAUST Repository

    Chen, Lisi; Shang, Shuo

    2018-01-01

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

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

    CERN Document Server

    Blangiardo, Marta

    2015-01-01

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

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

    KAUST Repository

    Chen, Lisi

    2018-04-26

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

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

    Directory of Open Access Journals (Sweden)

    Revesz Peter Z.

    2016-01-01

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

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

    Science.gov (United States)

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

    2009-04-01

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

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

    Science.gov (United States)

    Gens, R.

    2017-12-01

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

  12. Spatio temporal media components for neurofeedback

    DEFF Research Database (Denmark)

    Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

    2013-01-01

    A class of Brain Computer Interfaces (BCI) involves interfaces for neurofeedback training, where a user can learn to self-regulate brain activity based on real-time feedback. These particular interfaces are constructed from audio-visual components and temporal settings, which appear to have...... a strong influence on the ability to control brain activity. Therefore, identifying the different interface components and exploring their individual effects might be key for constructing new interfaces that support more efficient neurofeedback training. We discuss experiments involving two different...

  13. Visual search of cyclic spatio-temporal events

    Science.gov (United States)

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

    2018-05-01

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

  14. Spatio-Temporal Encoding in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik

    2005-01-01

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

  15. Scalable Top-k Spatio-Temporal Term Querying

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  16. Image sequence analysis using spatio-temporal texture

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Science.gov (United States)

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

    2016-04-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  19. Spatio-temporal models of mental processes from fMRI.

    Science.gov (United States)

    Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

    2011-07-15

    Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

  20. A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2017-04-01

    Full Text Available With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout the different phases of risk management reaching from pre-disaster mitigation to the response after an event and the long-term recovery of affected assets. Spatio-temporal changes need to be integrated into a sound conceptual and technological framework able to deal with data coming from different sources, at varying scales, and changing in space and time. Especially managing the information life-cycle, the integration of heterogeneous information and the distributed versioning and release of geospatial information are important topics that need to become essential parts of modern exposure modelling solutions. The main purpose of this study is to provide a conceptual and technological framework to tackle the requirements implied by disaster risk management for describing exposed assets in space and time. An information life-cycle management solution is proposed, based on a relational spatio-temporal database model coupled with Git and GeoGig repositories for distributed versioning. Two application scenarios focusing on the modelling of residential building stocks are presented to show the capabilities of the implemented solution. A prototype database model is shared on GitHub along with the necessary scenario data.

  1. Span: spike pattern association neuron for learning spatio-temporal spike patterns.

    Science.gov (United States)

    Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

    2012-08-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

  2. Multiscale recurrence analysis of spatio-temporal data

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Directory of Open Access Journals (Sweden)

    XUE Cunjin

    2016-02-01

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

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

    International Nuclear Information System (INIS)

    Wikle, C.K.

    1996-01-01

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

  6. Mortality from Suicide in the Municipalities of Mainland Portugal: Spatio-Temporal Evolution between 1980 and 2015

    Directory of Open Access Journals (Sweden)

    Adriana Loureiro

    2018-01-01

    Full Text Available Introduction: Suicide is considered a public health priority. It is a complex phenomenon resulting from the interaction of several factors, which do not depend solely on individual conditions. This study analyzes the spatio-temporal evolution of suicide mortality between 1980 and 2015, identifying areas of high risk, and their variation, in the 278 municipalities of Continental Portugal. Material and Methods: Based on the number of self-inflicted injuries and deaths from suicide and the resident population, the spatio-temporal evolution of the suicide mortality rate was assessed via: i a Poisson joinpoint regression model, and ii spatio-temporal clustering methods. Results: The suicide mortality rate evolution showed statistically significant increases over three periods (1980 - 1984; 1999 - 2002 and 2006 - 2015 and two statistically significant periods of decrease (1984 - 1995 and 1995 - 1999. The spatio-temporal analysis identified five clusters of high suicide risk (relative risk >1 and four clusters of low suicide risk (relative risk < 1. Discussion: The periods when suicide mortality increases seem to overlap with times of economic and financial instability. The geographical pattern of suicide risk has changed: presently, the suicide rates from the municipalities in the Center and North are showing more similarity with those seen in the South, thus increasing the ruralization of the phenomenon of suicide. Conclusion: Between 1980 and 2015 the spacio-temporal pattern of mortality from suicide has been changing and is a phenomenon that is currently experiencing a growing trend (since 2006 and is of higher risk in rural areas.

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

    NARCIS (Netherlands)

    Zijlstra, W; Hof, AL

    2003-01-01

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

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

    Science.gov (United States)

    Carcach, Carlos

    2017-04-20

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

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

    Directory of Open Access Journals (Sweden)

    Carlos Carcach

    2017-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Federico eIseppon

    2015-08-01

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

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

    KAUST Repository

    Krupskii, Pavel

    2017-10-13

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

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

    Science.gov (United States)

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

    2012-09-01

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

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

    Science.gov (United States)

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

    2010-05-01

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

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

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2017-01-01

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

  15. Spatio-temporal observations of the tertiary ozone maximum

    Directory of Open Access Journals (Sweden)

    V. F. Sofieva

    2009-07-01

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

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

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

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

    Directory of Open Access Journals (Sweden)

    Michael Cusimano

    2010-01-01

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

  17. Spatio-temporal clustering of wildfires in Portugal

    Science.gov (United States)

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

    2012-04-01

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

  18. High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2013-05-01

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

  1. Spatio-Temporal Analysis of Human Activities in Indoor Environments through Mobile Sensing

    DEFF Research Database (Denmark)

    Prentow, Thor Siiger

    with the intuition and personal experience of the planners. Lack of real-time information on task execution has made it difficult to adapt to changes in the schedules, such as delays or suddenly occurring urgent tasks. The recent advances in methods and devices for mobile sensing provides opportunities...... methods for spatio-temporal analysis of human activities in indoor environments based on mobile sensing. The methods aim to improve scheduling and facility utilization by providing information on the used route networks, transportation modes, travel times, and the flow of people through buildings....... The methods are based on large-scale real-time indoor positioning through the use of existing WiFi infrastructures, which allows for easy deployment even in very large building complexes. The methods are designed for real-time operation, which enables them to detect and adjust to changes as they occur...

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

    Science.gov (United States)

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

    2014-07-21

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

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

    Directory of Open Access Journals (Sweden)

    Shengnan Ke

    2014-07-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    M. Schulte

    2015-06-01

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

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

    Science.gov (United States)

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

    2016-10-15

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

  7. Spatio-temporal evolution of forest fires in Portugal

    Science.gov (United States)

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

    2017-04-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

  9. Self-organization of spatio-temporal earthquake clusters

    Directory of Open Access Journals (Sweden)

    S. Hainzl

    2000-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  11. Spatio-temporal effects of low impact development practices

    Science.gov (United States)

    Gilroy, Kristin L.; McCuen, Richard H.

    2009-04-01

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

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

    Science.gov (United States)

    Baig, S.; Sarfraz, M. S.

    2018-05-01

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

  13. Vehicle Trajectory Estimation Using Spatio-Temporal MCMC

    Directory of Open Access Journals (Sweden)

    Francois Bardet

    2010-01-01

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

  14. Spatio-temporal diffusion of dynamic PET images

    International Nuclear Information System (INIS)

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

    2011-01-01

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    KAUST Repository

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

    2013-01-01

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

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

    KAUST Repository

    Sun, Ying; Genton, Marc G.

    2011-01-01

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

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

    DEFF Research Database (Denmark)

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

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

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

    Science.gov (United States)

    Bertazzon, Stefania

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

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

    OpenAIRE

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

    2016-01-01

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

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

    OpenAIRE

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

    2018-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Justin M J Travis

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

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

    Science.gov (United States)

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

    2017-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Heung-Il Suk

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

  5. Spatio-temporal manipulation of small GTPase activity at subcellular level and on timescale of seconds in living cells.

    Science.gov (United States)

    DeRose, Robert; Pohlmeyer, Christopher; Umeda, Nobuhiro; Ueno, Tasuku; Nagano, Tetsuo; Kuo, Scot; Inoue, Takanari

    2012-03-09

    Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular functions and events(1, 2). Their spatiotemporally dynamic nature has been revealed by visualization of their activity and localization in real time(3). In order to gain deeper understanding of their roles in diverse cellular functions at the molecular level, the next step should be perturbation of protein activities at a precise subcellular location and timing. To achieve this goal, we have developed a method for light-induced, spatio-temporally controlled activation of small GTPases by combining two techniques: (1) rapamycin-induced FKBP-FRB heterodimerization and (2) a photo-caging method of rapamycin. With the use of rapamycin-mediated FKBP-FRB heterodimerization, we have developed a method for rapidly inducible activation or inactivation of small GTPases including Rac(4), Cdc42(4), RhoA(4) and Ras(5), in which rapamycin induces translocation of FKBP-fused GTPases, or their activators, to the plasma membrane where FRB is anchored. For coupling with this heterodimerization system, we have also developed a photo-caging system of rapamycin analogs. A photo-caged compound is a small molecule whose activity is suppressed with a photocleavable protecting group known as a caging group. To suppress heterodimerization activity completely, we designed a caged rapamycin that is tethered to a macromolecule such that the resulting large complex cannot cross the plasma membrane, leading to virtually no background activity as a chemical dimerizer inside cells(6). Figure 1 illustrates a scheme of our system. With the combination of these two systems, we locally recruited a Rac activator to the plasma membrane on a timescale of seconds and achieved light-induced Rac activation at the subcellular level(6).

  6. Spatio-temporal remodeling of functional membrane microdomains organizes the signaling networks of a bacterium.

    Directory of Open Access Journals (Sweden)

    Johannes Schneider

    2015-04-01

    Full Text Available 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.

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

    Science.gov (United States)

    Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

    2012-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

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

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

    Science.gov (United States)

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

    2012-07-01

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

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

    Directory of Open Access Journals (Sweden)

    C. A. O. Vieira

    2012-07-01

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

  12. Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

    Energy Technology Data Exchange (ETDEWEB)

    Sreepathi, Sarat [ORNL; Kumar, Jitendra [ORNL; Mills, Richard T. [Argonne National Laboratory; Hoffman, Forrest M. [ORNL; Sripathi, Vamsi [Intel Corporation; Hargrove, William Walter [United States Department of Agriculture (USDA), United States Forest Service (USFS)

    2017-09-01

    A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like the Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.

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

    Science.gov (United States)

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

    2007-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Ram K Raghavan

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

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

    Directory of Open Access Journals (Sweden)

    K. Zheng

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

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

    2009-06-22

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

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

    Directory of Open Access Journals (Sweden)

    ZHANG Feng

    2016-02-01

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

  19. Neo-Agro-Colonialism, Control over Life, and Imposed Spatio-Temporalities

    Directory of Open Access Journals (Sweden)

    Matheus Hoffmann Pfrimer

    Full Text Available Abstract The control over what Dillon and Lobo-Guerrero (2008 conceptualise as ‘pluripotent’ life has become an essential factor of capitalist agriculture; this occurs through the regulation of strategic genetic resources. We recognise this course as part of a larger project of neo-agro-colonialism, which takes place by controlling both biotechnology and territories as an expression of a fungible power, turning geopolitics into biopolitics and vice-versa. While assessing the power relations and manipulation of spatio-temporalities in the process of life fabrication, we discuss the mechanisms of control over ‘pluripotent’ life – genetically modified seeds and biopiracy through patentisation of traditional knowledges – which turns life into a commodified good. This is to say that the instrumental use of life fabrication within the rationale of globalised capital (recreates post-colonial temporalities that legitimise (renew(ed colonial ties. We ascertain that it is the manipulation of life’s temporality that allows capital to be (reproduced in the agricultural context of the molecular age.

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

    Science.gov (United States)

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

    2016-07-01

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

  1. Theoretical analysis of the spatio-temporal structure of bone multicellular units

    International Nuclear Information System (INIS)

    Buenzli, P R; Pivonka, P; Gardiner, B S; Smith, D W; Dunstan, C R; Mundy, G R

    2010-01-01

    Bone multicellular units (BMUs) maintain the viability of the skeletal tissue by coordinating locally the sequence of bone resorption and bone formation performed by cells of the osteoclastic and osteoblastic lineage. Understanding the emergence and the net bone balance of such structured microsystems out of the complex network of biochemical interactions between bone cells is fundamental for many bone-related diseases and the evaluation of fracture risk. Based on current experimental knowledge, we propose a spatio-temporal continuum model describing the interactions of osteoblastic and osteoclastic cells. We show that this model admits travelling-wave-like solutions with well-confined cell profiles upon specifying external conditions mimicking the environment encountered in cortical bone remodelling. The shapes of the various cell concentration profiles within this travelling structure are intrinsically linked to the parameters of the model such as differentiation, proliferation, and apoptosis rates of bone cells. The internal structure of BMUs is reproduced, allowing for experimental calibration. The spatial distribution of the key regulatory factors can also be exhibited, which in diseased states could give hints as to the biochemical agent most accountable for the disorder.

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

    Science.gov (United States)

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

    2016-11-01

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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

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

    International Nuclear Information System (INIS)

    Du Lin; Xu Wei; Li Zhanguo; Zhou Bingchang

    2011-01-01

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

  6. Spatio-temporal variations of PM2.5 emission in China from 2005 to 2014.

    Science.gov (United States)

    Jin, Qiang; Fang, Xinyue; Wen, Bo; Shan, Aidang

    2017-09-01

    With the rapid development of economy, air pollution has become increasingly serious nowadays in China, especially for the PM2.5. In this paper, the Spatio-temporal variations of PM2.5 emission over the past decade, from 2005 to 2014, were researched by cartograms. Meanwhile, a complex network technology was adopted to study the spatial auto-correlation of PM2.5 emission. The results showed that every province in China suffered a disparate increment in PM2.5 emission during the past ten years and also indicated that provinces in the same region had a huge influence on each other. There were three sectors including the thermal power, biomass burning and building materials that constituted the major sources of PM2.5 emission and they had different changing trends. There existed a dramatic difference in the east and west of China considering that the amount of PM2.5 was closely related to gross domestic product (GDP) and population. With higher GDP and population, eastern provinces emitted the most amount of PM2.5. Normalization results proposed that most of the provinces were PM2.5 exporting provinces in the southeast of China while most in the northwest were importing provinces. This study can help the policy-makers understand the distribution characteristics of PM2.5 emission and propose the effective strategy to mitigate the pollution of haze. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    KAUST Repository

    Sun, Ying

    2011-10-24

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

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

    Directory of Open Access Journals (Sweden)

    Mohammad Nur Shodiq

    2016-03-01

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

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

    Science.gov (United States)

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

    2012-08-01

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

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

    CERN Document Server

    Billings, Stephen A

    2013-01-01

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

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

    DEFF Research Database (Denmark)

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

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

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

    Science.gov (United States)

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

    2018-04-01

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

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

    African Journals Online (AJOL)

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

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

    NARCIS (Netherlands)

    Burghouts, G.J.; Schutte, K.

    2013-01-01

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

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

    African Journals Online (AJOL)

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

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

    Directory of Open Access Journals (Sweden)

    Daniela Cocchi

    2007-12-01

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Science.gov (United States)

    Zaal, Peter; Sweet, Barbara

    2010-01-01

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

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

    Science.gov (United States)

    Deng, Chen; Li-Yong, Wen

    2017-10-24

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    Czech Academy of Sciences Publication Activity Database

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

    2017-01-01

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

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

    DEFF Research Database (Denmark)

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

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

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

    DEFF Research Database (Denmark)

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

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

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

    CSIR Research Space (South Africa)

    Spocter, M

    2011-04-01

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

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

    Science.gov (United States)

    Khorram, Saeed; Ergil, Mustafa

    2018-03-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

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

    International Nuclear Information System (INIS)

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

    2001-01-01

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

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

    KAUST Repository

    Jun, Mikyoung; Genton, Marc G.

    2012-01-01

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

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

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Nengcheng Chen

    2017-02-01

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

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

    Science.gov (United States)

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

    2002-02-01

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

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

    Directory of Open Access Journals (Sweden)

    B. Mao

    2012-07-01

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

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

    International Nuclear Information System (INIS)

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

    2002-01-01

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

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

    Science.gov (United States)

    Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

    2014-05-01

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

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

    Science.gov (United States)

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

    2017-10-18

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

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

    Science.gov (United States)

    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.

  20. Soil moisture spatio-temporal behavior of Pinus pinaster stands on sandy flatlands of central Spain.

    Energy Technology Data Exchange (ETDEWEB)

    Gomez-Sanz, V.; Garcia-Vinas, J. I.

    2011-07-01

    Pinus pinaster stands in the center of the Iberian Peninsula frequently grow in a unique hydrological system characterized by a variable groundwater table near the soil surface and highly permeable soils (arenosols). Over the last few decades, this superficial aquifer has been overused as a water resource, especially for irrigated crops. Overuse has reached a critical level and has caused various environmental impacts and a water sustainability crisis wherein rainfall variability does not allow for a sufficient level of aquifer recharge by natural means. Within this changing scenario, soil water significantly affects the spatio-temporal ecological response, necessitating more extensive characterization of the complex soil-tree water relationship. The primary goal of the present work was to evaluate the influence of root zone soil moisture on the observed spatial response of Pinus pinaster stands. Volumetric soil moisture content was measured at eleven forest sites, using time-domain reflectometry (TDR), over a two-year observation period. The results demonstrate that the combined effect of groundwater table proximity and dune morphology associated with this area are the main factors driving very different water availability conditions among the monitored hydrological response units, which modulate maritime pine installation and development. Topographically lower areas are more heterogeneous in terms of soil moisture behavior. In these areas, the conifer forests that are connected to the water table may be the most sensitive to land use changes within current environmental change scenarios. Consequently, in these pine ecosystems, the combined influences of geomorphology and water table proximity on variations in root zone soil moisture are essential and must be considered to develop adequate adaptive management models. (Author) 25 refs.

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

    KAUST Repository

    Flegg, Mark B.

    2013-01-01

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

  2. Spatio-Temporal Characteristics in the Clearness Index Derived from Global Solar Radiation Observations in Korea

    Directory of Open Access Journals (Sweden)

    Yeonjin Jung

    2016-04-01

    Full Text Available The spatio-temporal characteristics of the clearness index (KT were investigated using daily global solar irradiance measurements (290–2800 nm for the period of 2000–2014 at 21 sites in Korea, a complex region in East Asia with a distinct monsoon season and heavy aerosol loading year-round. The annual mean KT value for all sites is 0.46, with values of 0.63 and 0.25 for clear and overcast skies, respectively. The seasonal variations in monthly average KT show a minimum of 0.37 in July at all sites except for Jeju, where the value was 0.29 in January. The maximum value (KT = 0.51 is observed in October, followed by a secondary peak (KT = 0.49 during February–April. The lowest KT value (KT = 0.42 was observed at both the Seoul and Jeju sites, and the highest (KT = 0.48 in the southeastern regions. Increases in average KT exceeding 4% per decade were observed in the middle and southeastern regions, with the maximum (+8% per decade at the Daegu site. Decreasing trends (<−4% per decade were observed in the southwestern regions, with the maximum (−7% per decade at the Mokpo site. Cloud amount, relative humidity, and aerosol optical depth together explained 57% of the variance in daily mean KT values. The contributions of these three variables to variations in KT are 42%, 9% and 6%, respectively. Thus, the variations in KT in Korea can be primarily attributed to the presence of clouds and water vapor, with relatively weak aerosol effects.

  3. ANALYSIS OF SPATIO-TEMPORAL TRAFFIC PATTERNS BASED ON PEDESTRIAN TRAJECTORIES

    Directory of Open Access Journals (Sweden)

    S. Busch

    2016-06-01

    Full Text Available 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-03-13

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

  5. Spatio-temporal declines in Philippine fisheries and its implications to coastal municipal fishers’ catch and income

    Directory of Open Access Journals (Sweden)

    Jonathan A Anticamara

    2016-03-01

    Full Text Available The problem of overexploitation in global fisheries is well-recognized. However, published assessment of fisheries spatio-temporal trends at the national scale is lacking for many high biodiversity developing countries, which is problematic since fisheries management is often implemented at the local or national levels. Here, we present the long-term spatio-temporal trends of Philippine fisheries production based on the landed national fish catch data (1980-2012 and fishers’ interviews. We found that the total Philippine fish catch volume (Metric Tons MT of most capture fisheries throughout the country has either stagnated or declined over the last three decades. The decline is even more prominent when evaluating fisheries trends at the provincial level, suggesting spatial serial depletion of the country’s fisheries. In contrast, the total Philippine fish catch value (US Dollars US$ or Philippine Pesos PHP has continued to increase over time, despite the declining fish catch volume. However, local municipal fishers are experiencing both low fish catch and income, contributing to observable poverty in many coastal communities in the Philippines. The various stakeholders of Philippine fisheries need to recognize the depleted state of Philippine fisheries, and learn from various experiences of collapsed and recovered fisheries from around the world, in order to recover the Philippines’ capture fisheries. Lessons from the literature on collapsed fisheries offer the following options for recovery: (1 regulate or reduce fisheries exploitation and other human activities impacting the fisheries to allow fisheries to rebuild or recover, (2 enforce effective networks of marine reserves, (3 engage fishers, consumers, and other stakeholders in fisheries management, (4 improve fisheries science, monitoring, and management capacities, and (5 provide alternative livelihood, skills, and improved education to fishers and their families.

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

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

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

  7. Exploring the spatio-temporal interrelation between groundwater and surface water by using the self-organizing maps

    Science.gov (United States)

    Chen, I.-Ting; Chang, Li-Chiu; Chang, Fi-John

    2018-01-01

    In this study, we propose a soft-computing methodology to visibly explore the spatio-temporal groundwater variations of the Kuoping River basin in southern Taiwan. The self-organizing map (SOM) is implemented to investigate the interactive mechanism between surface water and groundwater over the river basin based on large high-dimensional data sets coupled with their occurrence times. We find that extracting the occurrence time from each 30-day moving average data set in the clustered neurons of the SOM is a crucial step to learn the spatio-temporal interaction between surface water and groundwater. We design 2-D Topological Bubble Map to summarize all the groundwater values of four aquifers in a neuron, which can visibly explore the major features of the groundwater in the vertical direction. The constructed SOM topological maps nicely display that: (1) the groundwater movement, in general, extends from the eastern area to the western, where groundwater in the eastern area can be easily recharged from precipitation in wet seasons and discharged into streams during dry seasons due to the high permeability in this area; (2) the water movements in the four aquifers of the study area are quite different, and the seasonal variations of groundwater in the second and third aquifers are larger than those of the others; and (3) the spatial distribution and seasonal variations of groundwater and surface water are comprehensively linked together over the constructed maps to present groundwater characteristics and the interrelation between groundwater and surface water. The proposed modeling methodology not only can classify the large complex high-dimensional data sets into visible topological maps to effectively facilitate the quantitative status of regional groundwater resources but can also provide useful elaboration for future groundwater management.

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

    Directory of Open Access Journals (Sweden)

    Sebastian Meyer

    2017-05-01

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

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2017-03-01

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

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

    KAUST Repository

    Jun, Mikyoung

    2012-01-01

    A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method can be applied to univariate or to multivariate random fields. Our test is based on the asymptotic normality of certain statistics that are functions of estimators of covariances at certain spatial and temporal lags under weak stationarity. Simulation results for spatial as well as spatio-temporal cases on the two types of spatial domains are reported. We describe the results of testing the stationarity of Pacific wind data, and of testing the axial symmetry of climate model errors for surface temperature using the NOAA GFDL model outputs and the observations from the Climate Research Unit in East Anglia and the Hadley Centre.

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

    Science.gov (United States)

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

    2012-04-01

    Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century under different emissions scenarios? (3) How would perceived drought characteristics evolve under theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Boonthanome, Nouanesengsy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States); Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bauer, Andy [Kitware Inc., Clifton Park, NY (United States); Chaudhary, Aashish [Kitware Inc., Clifton Park, NY (United States); Miller, Ross G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-01-01

    For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.

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

    Science.gov (United States)

    Orosz, Gábor; Ashwin, Peter; Townley, Stuart

    2009-07-01

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

  16. Quantification of annual wildfire risk; A spatio-temporal point process approach.

    Directory of Open Access Journals (Sweden)

    Paula Pereira

    2013-10-01

    Full Text Available Policy responses for local and global firemanagement depend heavily on the proper understanding of the fire extent as well as its spatio-temporal variation across any given study area. Annual fire risk maps are important tools for such policy responses, supporting strategic decisions such as location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence without addressing the loss component. In this paper, we study the spatio-temporal point patterns of wildfires and model them by a log Gaussian Cox processes. Themean of predictive distribution of randomintensity function is used in the narrow sense, as the annual fire risk map for next year.

  17. Spatio-Temporal Image Correlation Spectroscopy Measurements of Flow Demonstrated in Microfluidic Channels

    Science.gov (United States)

    Rossow, Molly; Mantulin, William W.; Gratton, Enrico

    2009-01-01

    Accurate blood flow measurements during surgery can improve the operations chance of success. We developed Near-infrared Spatio-Temporal Image Spectroscopy (NIR-STICS), which has the potential to make blood flow measurements that are difficult to accomplish with existing methods. Specifically, we propose the technique and we show feasibility on phantom measurements. NIR-STICS has the potential of measuring the fluid velocity in small blood vessels (less than 1mm in diameter) and of creating a map of blood flow rates over an area of approximately 1cm2. NIR-STICS employs near-infrared spectroscopy to probe inside blood vessel walls and spatio-temporal image correlation spectroscopy to directly—without the use of a model—extract fluid velocity from the fluctuations within an image. Here we present computer simulations and experiments on a phantom system that demonstrate the effectiveness of NIR-STICS. PMID:19405744

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

    Science.gov (United States)

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

    2017-06-01

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

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

    Science.gov (United States)

    Manga, Edna; Awang, Norhashidah

    2016-06-01

    This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

  20. Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models

    DEFF Research Database (Denmark)

    Yang, Bin; Guo, Chenjuan; Jensen, Christian S.

    2013-01-01

    of such time series offers insight into the underlying system and enables prediction of system behavior. While the techniques presented in the paper apply more generally, we consider the case of transportation systems and aim to predict travel cost from GPS tracking data from probe vehicles. Specifically, each...... road segment has an associated travel-cost time series, which is derived from GPS data. We use spatio-temporal hidden Markov models (STHMM) to model correlations among different traffic time series. We provide algorithms that are able to learn the parameters of an STHMM while contending...... with the sparsity, spatio-temporal correlation, and heterogeneity of the time series. Using the resulting STHMM, near future travel costs in the transportation network, e.g., travel time or greenhouse gas emissions, can be inferred, enabling a variety of routing services, e.g., eco-routing. Empirical studies...

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Derr; Milos Manic

    2008-09-01

    Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculation DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.

  3. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno; Mallick, Bani K.

    2011-01-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  4. Role of Temporal Diversity in Inferring Social Ties Based on Spatio-Temporal Data

    OpenAIRE

    Desai, Deshana; Nisar, Harsh; Bhardawaj, Rishab

    2016-01-01

    The last two decades have seen a tremendous surge in research on social networks and their implications. The studies includes inferring social relationships, which in turn have been used for target advertising, recommendations, search customization etc. However, the offline experiences of human, the conversations with people and face-to-face interactions that govern our lives interactions have received lesser attention. We introduce DAIICT Spatio-Temporal Network (DSSN), a spatiotemporal data...

  5. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno

    2011-03-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  6. Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions - a crime case study

    OpenAIRE

    Adepeju, M.; Rosser, G.; Cheng, T.

    2016-01-01

    Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squ...

  7. [Epidemiologic and spatio-temporal characteristics of hepatitis E in China, 2004-2014].

    Science.gov (United States)

    Liu, Z Q; Zuo, J L; Yan, Q; Fang, Q W; Zhang, T J

    2017-10-10

    Objective: To describe and analyze the epidemiologic and spatio-temporal characteristics of hepatitis E in China from 2004 to 2014. Methods: Data on the incidence of hepatitis E in 31 provinces (municipality and autonomous region) from 2004 to 2014, were collected. Empirical Mode Decomposition (EMD) was applied to decompose the time-series data to accurately describe the trend of hepatitis E incidence. Mathematic model was used to estimate the annual change of incidence in each age group and the whole province. Software ArcGIS 10.1 and SaTScan 9.01 were used to analyze the spatio-temporal clusters. Results: During 2004-2014, a total of 245 414 hepatitis E cases were reported in China. The overall incidence showed a slight increase ( OR =1.05, 95 %CI : 1.03-1.10). Incidence rates on hepatitis E were discovered different across the provinces, with significant increase appearing in the southern, central and northwestern areas. The highest increase was seen in the elderly, especially in the 65-69 and 70-74 year-olds. Results from the Local spatial autocorrelation analysis showed that the "high-high cluster" was moving from the north to the south and the "low-low cluster" disappeared as time went by. Data from Spatio-temporal scanning showed that there were five spatio-temporal clustering areas across the country. Conclusion: The overall incidence of hepatitis E was on the rise from 2004 to 2014, in China, but with differences seen across the areas and age groups.

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

    Directory of Open Access Journals (Sweden)

    M. Alkan

    2016-06-01

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

  9. Global asymptotic behavior in a Lotka–Volterra competition system with spatio-temporal delays

    International Nuclear Information System (INIS)

    Zhang, Jia-Fang; Chen, Heshan

    2014-01-01

    This paper is concerned with a Lotka–Volterra competition system with spatio-temporal delays. By using the linearization method, we show the local asymptotic behavior of the nonnegative steady-state solutions. Especially, the global asymptotic stability of the positive steady-state solution is investigated by the method of upper and lower solutions. The result of global asymptotic stability implies that the system has no nonconstant positive steady-state solution

  10. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    OpenAIRE

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-01-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire dis...

  11. Pattern selection and spatio-temporal transition to chaos in Ginzburg-Landau equation

    Energy Technology Data Exchange (ETDEWEB)

    Nozaki, K; Bekki, N

    1983-07-01

    It is shown that a modulationally unstable pattern is selected and propagates into an initially unstable motionless state in the 1-D generalized Ginzburg-Landau equation. A further spatio-temporal transition occurs with a sharp interface from the selected unstable pattern to a stabilized pattern or a chaotic state. The distinct transition makes a coherent structure to coexist with a chaotic state. 12 refs., 4 figs.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Science.gov (United States)

    Alkan, M.; Polat, Z. A.

    2016-06-01

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

  14. Comparison of feature extraction methods within a spatio-temporal land cover change detection framework

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-07-01

    Full Text Available OF FEATURE EXTRACTION METHODS WITHIN A SPATIO-TEMPORAL LAND COVER CHANGE DETECTION FRAMEWORK ??W. Kleynhans,, ??B.P. Salmon, ?J.C. Olivier, ?K.J. Wessels, ?F. van den Bergh ? Electrical, Electronic and Computer Engi- neering University of Pretoria, South... Bergh, and K. Steenkamp, ?Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data,? IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 381?385, Apr. 2010. ...

  15. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  16. On the expected value and variance for an estimator of the spatio-temporal product density function

    DEFF Research Database (Denmark)

    Rodríguez-Corté, Francisco J.; Ghorbani, Mohammad; Mateu, Jorge

    Second-order characteristics are used to analyse the spatio-temporal structure of the underlying point process, and thus these methods provide a natural starting point for the analysis of spatio-temporal point process data. We restrict our attention to the spatio-temporal product density function......, and develop a non-parametric edge-corrected kernel estimate of the product density under the second-order intensity-reweighted stationary hypothesis. The expectation and variance of the estimator are obtained, and closed form expressions derived under the Poisson case. A detailed simulation study is presented...... to compare our close expression for the variance with estimated ones for Poisson cases. The simulation experiments show that the theoretical form for the variance gives acceptable values, which can be used in practice. Finally, we apply the resulting estimator to data on the spatio-temporal distribution...

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  18. Pattern formations in chaotic spatio-temporal systems

    Indian Academy of Sciences (India)

    5Beijing–Hong Kong–Singapore Joint Center of Nonlinear and Complex Systems, ... For theoretical studies most previous work has focused on pattern .... Lyapunov exponents from arbitrary initial conditions, and the plots look rather.

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

    Science.gov (United States)

    Daya Sagar, B. S.

    2005-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhijie Zhang

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

  1. Optimizing Cruising Routes for Taxi Drivers Using a Spatio-Temporal Trajectory Model

    Directory of Open Access Journals (Sweden)

    Liang Wu

    2017-11-01

    Full Text Available Much of the taxi route-planning literature has focused on driver strategies for finding passengers and determining the hot spot pick-up locations using historical global positioning system (GPS trajectories of taxis based on driver experience, distance from the passenger drop-off location to the next passenger pick-up location and the waiting times at recommended locations for the next passenger. The present work, however, considers the average taxi travel speed mined from historical taxi GPS trajectory data and the allocation of cruising routes to more than one taxi driver in a small-scale region to neighboring pick-up locations. A spatio-temporal trajectory model with load balancing allocations is presented to not only explore pick-up/drop-off information but also provide taxi drivers with cruising routes to the recommended pick-up locations. In simulation experiments, our study shows that taxi drivers using cruising routes recommended by our spatio-temporal trajectory model can significantly reduce the average waiting time and travel less distance to quickly find their next passengers, and the load balancing strategy significantly alleviates road loads. These objective measures can help us better understand spatio-temporal traffic patterns and guide taxi navigation.

  2. Spatio-temporal modeling of 210Pb transportation in lake environments

    International Nuclear Information System (INIS)

    Kuelahci, Fatih; Sen, Zekai

    2009-01-01

    Radioactive particle movement analysis in any environment gives valuable information about the effects of the concerned environment on the particle and the transportation phenomenon. In this study, the spatio-temporal point cumulative semivariogram (STPCSV) approach is proposed for the analysis of the spatio-temporal changes in the radioactive particle movement within a surface water body. This methodology is applied to the 210 Pb radioactive isotope measurements at 44 stations, which are determined beforehand in order to characterize the Keban Dam water environment on the Euphrates River in the southeastern part of Turkey. It considers the contributions coming from all the stations and provides information about the spatio-temporal behavior of 210 Pb in the water environment. After having identified the radii of influences at each station it is possible to draw maps for further interpretations. In order to see holistically the spatial changes of the radioisotope after 1st, 3rd and 5th hours, the radius of influence maps are prepared and interpreted accordingly.

  3. Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

    Science.gov (United States)

    Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

    2010-08-01

    Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

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

    Science.gov (United States)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    B. S. Daya Sagar

    2005-01-01

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

  8. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    OpenAIRE

    N. Mou; N. Mou; J. Li; L. Zhang; W. Liu; Y. Xu

    2017-01-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according t...

  9. Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  10. Spatio-temporal keyword queries in social networks

    DEFF Research Database (Denmark)

    Cozza, V.; Messina, Alessandro; Montesi, D.

    2013-01-01

    Due to the large amount of social network data produced at an ever growing speed and their complex nature, recent works have addressed the problem of efficiently querying such data according to social, temporal or spatial dimensions. In this work we propose a data model that keeps into account al...

  11. Experimental devices for the spatio-temporal characterization of femtosecond high-power laser chains

    International Nuclear Information System (INIS)

    Gallet, Valentin

    2014-01-01

    One of the advantages of high-power femtosecond lasers (TW-PW) is to obtain, at the focus of a focusing optic, very high intensities up to 10 22 W.cm -2 (i.e. an electric field of 2.7 PV.m -1 . Therefore, these lasers chains necessarily deliver beams with large diameter (up to 40 cm) and very short pulses (of the order of tens of femto-seconds). As a consequence, the spatial and temporal properties of the pulse are generally not independent. Such dependence, called spatial-temporal coupling has the effect of increasing the pulse duration and the size of the focal spot, which can lead to a significant reduction of the maximum intensity at the focus. Metrology devices commonly used on these high-power femtosecond lasers allow retrieving the spatial and temporal profiles of the pulse only in an independent manner. The aim of this thesis was to develop techniques for measuring spatio-temporal couplings in order to quantify their effect and correct them in order to obtain the maximum intensity at focus. First of all, we adapted an existing technique of spatio-temporal characterization to the measurement of TW lasers. To avoid the issues induced at the focus, such as those related to jittering, measurements were performed on the collimated beam. By adding a reference source to the original device, we managed to take into account the measurement artifacts due to thermal and mechanical variations affecting the interferometer. With this improvement, it was possible to reconstruct the complete spatio-temporal profile of the beam, particularly its wavefront. However, the limitations imposed by this technique led to the development of a new measurement device. Based on a cross-correlation, this technique consists of making the laser beam to interfere with a part of itself, small enough not to be spatio-temporally distorted. We have also implemented a variant of this device for a single-shot measurement along one transverse dimension of the pulse. Using these techniques, we

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

    Science.gov (United States)

    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

  13. STABILITY AND DYNAMICS OF SPATIO-TEMPORAL STRUCTURES

    Energy Technology Data Exchange (ETDEWEB)

    Hermann Riecke

    2005-10-21

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

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

    Science.gov (United States)

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

    2011-09-26

    Pixelated phase-mask interferograms have become an industry standard in spatial phase-shifting interferometry. These pixelated interferograms allow full wavefront encoding using a single interferogram. This allows the study of fast dynamic events in hostile mechanical environments. Recently an error-free demodulation method for ideal pixelated interferograms was proposed. However, non-ideal conditions in interferometry may arise due to non-linear response of the CCD camera, multiple light paths in the interferometer, etc. These conditions generate non-sinusoidal fringes containing harmonics which degrade the phase estimation. Here we show that two-dimensional Fourier demodulation of pixelated interferograms rejects most harmonics except the complex ones at {-3(rd), +5(th), -7(th), +9(th), -11(th),…}. We propose temporal phase-shifting to remove these remaining harmonics. In particular, a 2-step phase-shifting algorithm is used to eliminate the -3(rd) and +5(th) complex harmonics, while a 3-step one is used to remove the -3(rd), +5harmonics. © 2011 Optical Society of America

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

    Science.gov (United States)

    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

  16. A spatio-temporal index for aerial full waveform laser scanning data

    Science.gov (United States)

    Laefer, Debra F.; Vo, Anh-Vu; Bertolotto, Michela

    2018-04-01

    Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2-3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Daisuke Ohshima

    2015-06-01

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

  19. A spatio-temporal analysis of fires in South Africa

    Directory of Open Access Journals (Sweden)

    Sheldon Strydom

    2016-11-01

    Full Text Available The prevalence and history of fires in Africa has led to the continent being named "the fire continent". Fires are common on the continent and lead to a high number of annual fire disasters which result in many human fatalities and considerable financial loss. Increased population growth and concentrated settlement planning increase the probability of fire disasters and the associated loss of human life and financial loss when disasters occur. In order to better understand the spatial and temporal variations and characteristics of fires in South Africa, an 11-year data set of MODIS-derived Active Fire Hotspots was analysed using an open source geographic information system. The study included the mapping of national fire frequency over the 11-year period. Results indicate that the highest fire frequency occurred in the northeastern regions of South Africa, in particular the mountainous regions of KwaZulu-Natal and Mpumalanga, and in the Western Cape. Increasing trends in provincial fire frequency were observed in eight of the nine provinces of South Africa, with Mpumalanga the only province for which a decrease in annual fire frequency was observed. Temporally, fires were observed in all months for all provinces, although distinct fire seasons were observed and were largely driven by rainfall seasons. The southwestern regions of South Africa (winter-rainfall regions experienced higher fire frequencies during the summer months and the rest of the country (summer-rainfall regions during the winter months. Certain regions those which experienced bimodal rainfall seasons did not display distinct fire seasons because of the complex wet and dry seasons. Investigation into the likely effects of climate change on South African fire frequency revealed that increased air temperatures and events such as La Niña have a marked effect on fire activity.

  20. Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

    Science.gov (United States)

    Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

    2014-08-01

    As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good

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

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

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

  2. Spatial and spatio-temporal analysis of malaria in the state of Acre, western Amazon, Brazil

    Directory of Open Access Journals (Sweden)

    Leonardo Augusto Kohara Melchior

    2016-11-01

    Full Text Available Since 2005, the State of Acre, western Amazon, Brazil, has reported the highest annual parasite incidence (API of malaria among the Brazilian states. This study examines malaria incidence in Acre using spatial and spatio-temporal analysis based on an ecological time series study analyzing malaria cases and deaths for the time period 1992- 2014 and using secondary data. API indexes were calculated by age, sex, parasite species, ratio of Plasmodium vivax to P. falciparum malaria, malaria mortality rate and case fatality rate. SaTScan was used to detect spatial and spatio-temporal clusters of malaria cases and data were represented in the form of choropleth maps. A high-risk cluster of malaria was detected in Vale do Juruá and three low-risk clusters in Vale do Acre for both parasite species. Those younger than 19 years of age and females showed a high incidence of malaria in Vale do Juruá, but working-age males were the most affected in Vale do Acre. The malaria mortality rate showed a decreasing trend across the state, while the case fatality rate increased only in the micro-region of Rio Branco during the study period. We conclude that malaria is a focal disease in Acre showing different spatial and spatio-temporal patterns of cases and deaths that vary by age, sex, and parasite species. Malaria incidence is thought to be influenced by factors related to regional characteristics; therefore, appropriate disease and vector control strategies must be implemented at each locality.

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

    Science.gov (United States)

    Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min

    2016-04-13

    In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. © 2016 The Authors.

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

    Directory of Open Access Journals (Sweden)

    Verena Jürgens

    2013-05-01

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

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  6. Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

    Science.gov (United States)

    Varlamova, Eugenia V.; Solovyev, Vladimir S.

    2017-11-01

    Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    Marine disasters are a more prevalent problem in China than in many other countries. Based on the development of a status quo of China's marine disaster the space-time process model is used. The model uses the ocean's temperature field, salinity field, water density field, surface wind field, wave field and other four-dimensional spatio-temporal quantities. This paper studies that model in detail. This study aims at using the theory to provide support during marine disasters in an effort to prevent or decrease their frequency in the future

  8. An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk

    OpenAIRE

    Rushworth, Alastair; Lee, Duncan; Sarran, Christophe

    2014-01-01

    Statistical models used to estimate the spatio-temporal pattern in disease\\ud risk from areal unit data represent the risk surface for each time period with known\\ud covariates and a set of spatially smooth random effects. The latter act as a proxy\\ud for unmeasured spatial confounding, whose spatial structure is often characterised by\\ud a spatially smooth evolution between some pairs of adjacent areal units while other\\ud pairs exhibit large step changes. This spatial heterogeneity is not c...

  9. Joint level-set and spatio-temporal motion detection for cell segmentation.

    Science.gov (United States)

    Boukari, Fatima; Makrogiannis, Sokratis

    2016-08-10

    Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

  10. Principles for statistical inference on big spatio-temporal data from climate models

    KAUST Repository

    Castruccio, Stefano

    2018-02-24

    The vast increase in size of modern spatio-temporal datasets has prompted statisticians working in environmental applications to develop new and efficient methodologies that are still able to achieve inference for nontrivial models within an affordable time. Climate model outputs push the limits of inference for Gaussian processes, as their size can easily be larger than 10 billion data points. Drawing from our experience in a set of previous work, we provide three principles for the statistical analysis of such large datasets that leverage recent methodological and computational advances. These principles emphasize the need of embedding distributed and parallel computing in the inferential process.

  11. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

    Directory of Open Access Journals (Sweden)

    Yanxia Wang

    2014-05-01

    Full Text Available Ischemic heart disease (IHD is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents and the standardized rate (the observed cases standardized by the expected cases of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015 to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction

  12. Assimilation of spatio-temporal distribution of radionuclides in early phase of radiation accident

    Czech Academy of Sciences Publication Activity Database

    Hofman, Radek; Šmídl, Václav

    2010-01-01

    Roč. 18, 7/8 (2010), s. 226-228 ISSN 1210-7085 R&D Projects: GA MŠk(CZ) 1M0572; GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : decision support * early phase * Gaussian model * radioactive pollution transport Subject RIV: DL - Nuclear Waste, Radioactive Pollution ; Quality http://library.utia.cas.cz/separaty/2010/AS/hofman-assimilation of spatio-temporal distribution of radionuclides in early phase of radiation accident .pdf

  13. Principles for statistical inference on big spatio-temporal data from climate models

    KAUST Repository

    Castruccio, Stefano; Genton, Marc G.

    2018-01-01

    The vast increase in size of modern spatio-temporal datasets has prompted statisticians working in environmental applications to develop new and efficient methodologies that are still able to achieve inference for nontrivial models within an affordable time. Climate model outputs push the limits of inference for Gaussian processes, as their size can easily be larger than 10 billion data points. Drawing from our experience in a set of previous work, we provide three principles for the statistical analysis of such large datasets that leverage recent methodological and computational advances. These principles emphasize the need of embedding distributed and parallel computing in the inferential process.

  14. On the genesis of spatio-temporal self-organized structures in plasma devices

    International Nuclear Information System (INIS)

    Talasman, S.J.; Sanduloviciu, M.

    1995-01-01

    The genesis of luminous sharply defined nearly spherical space charges structures formed in an Argon plasma column was experimental investigated. The results reveal spatio-temporal characteristics proper to systems resulting after a self-organization process. Their phenomenology involves electrical charges separation produced by symmetry breaking and spatial separation of the excitation and ionization cross sections functions in a region where electrons are accelerated and, as a result, the appearance of electrostatic forces that, acting as long range correlations, assures, together with dissipative effects, its stability. (Author) 8 Figs., 31 Refs

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

    Science.gov (United States)

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

    2010-01-01

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

  16. Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

    Science.gov (United States)

    Kitsunezaki, S.

    In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

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

    Science.gov (United States)

    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

  18. Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data.

    Science.gov (United States)

    Ashdown, George; Pandžić, Elvis; Cope, Andrew; Wiseman, Paul; Owen, Dylan

    2015-12-17

    Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell interaction known as the immunological synapse. F-actin is also speculated to play a role in regulating molecular distributions at the membrane of cells including sub-membranous vesicle dynamics and protein clustering. While standard light microscope techniques allow generalized and diffraction-limited observations to be made, many cellular and molecular events including clustering and molecular flow occur in populations at length-scales far below the resolving power of standard light microscopy. By combining total internal reflection fluorescence with the super resolution imaging method structured illumination microscopy, the two-dimensional molecular flow of F-actin at the immune synapse of T cells was recorded. Spatio-temporal image correlation spectroscopy (STICS) was then applied, which generates quantifiable results in the form of velocity histograms and vector maps representing flow directionality and magnitude. This protocol describes the combination of super-resolution imaging and STICS techniques to generate flow vectors at sub-diffraction levels of detail. This technique was used to confirm an actin flow that is symmetrically retrograde and centripetal throughout the periphery of T cells upon synapse formation.

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

    Science.gov (United States)

    Jung, Minju; Hwang, Jungsik; Tani, Jun

    2015-01-01

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

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

    Science.gov (United States)

    Jalan, S.; Sharma, K.

    2014-11-01

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

  1. Spatio-temporal trends and risk factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China.

    Directory of Open Access Journals (Sweden)

    Fenyang Tang

    Full Text Available This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission.County-level incidence rates were obtained for analysis using geographic information system (GIS tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions.The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001. The time series model was established as ARIMA (1, 12, 0, which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64 and not having access to a safe water source (OR = 2.04 as the main causes of Shigella in Jiangsu Province.Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time.

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

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    Elisa Viñuela

    2012-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Shouguo Yang

    2015-12-01

    Full Text Available 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.

  4. Spatio-temporal trends and risk factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China.

    Science.gov (United States)

    Tang, Fenyang; Cheng, Yuejia; Bao, Changjun; Hu, Jianli; Liu, Wendong; Liang, Qi; Wu, Ying; Norris, Jessie; Peng, Zhihang; Yu, Rongbin; Shen, Hongbing; Chen, Feng

    2014-01-01

    This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, PHighways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time.

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

    Directory of Open Access Journals (Sweden)

    Valerio Bartolino

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

  6. Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

    Directory of Open Access Journals (Sweden)

    Pan Chen

    2015-05-01

    Full Text Available Understanding the spatio-temporal variation and the potential source of water pollution could greatly improve our knowledge of human impacts on the environment. In this work, data of 11 water quality indices were collected during 2012–2014 at 10 monitoring sites in the mainstream and major tributaries of the Danjiangkou Reservoir Basin, Central China. The fuzzy comprehensive assessment (FCA, the cluster analysis (CA and the discriminant analysis (DA were used to assess the water pollution status and analyze its spatio-temporal variation. Ten sites were classified by the high pollution (HP region and the low pollution (LP region, while 12 months were divided into the wet season and the dry season. It was found that the HP region was mainly in the small tributaries with small drainage areas and low average annual discharges, and it was also found that most of these rivers went through urban areas with industrial and domestic sewages input into the water body. Principal component analysis/factor analysis (PCA/FA was applied to reveal potential pollution sources, whereas absolute principal component score-multiple linear regression (APCS-MLR was used to identify their contributions to each water quality variable. The study area was found as being generally affected by industrial and domestic sewage. Furthermore, the HP region was polluted by chemical industries, and the LP region was influenced by agricultural and livestock sewage.

  7. Spatio-Temporal Database of Places Located in the Border Area

    Directory of Open Access Journals (Sweden)

    Albina Mościcka

    2018-03-01

    Full Text Available As a result of changes in boundaries, the political affiliation of locations also changes. Data on such locations are now collected in datasets with reference to the present or to the past space. Therefore, they can refer to localities that either no longer exist, have a different name now, or lay outside of the current borders of the country. Moreover, thematic data describing the past are related to events, customs, items that are always “somewhere”. Storytelling about the past is incomplete without knowledge about the places in which the given story has happened. Therefore, the objective of the article is to discuss the concept of spatio-temporal database for border areas as an “engine” for visualization of thematic data in time-oriented geographical space. The paper focuses on studying the place names on the Polish-Ukrainian border, analyzing the changes that have occurred in this area over the past 80 years (where there were three different countries during this period, and defining the changeability rules. As a result of the research, the architecture of spatio-temporal databases is defined, as well as the rules for using them for data geovisualisation in historical context.

  8. Statistical study of spatio-temporal distribution of precursor solar flares associated with major flares

    Science.gov (United States)

    Gyenge, N.; Ballai, I.; Baranyi, T.

    2016-07-01

    The aim of the present investigation is to study the spatio-temporal distribution of precursor flares during the 24 h interval preceding M- and X-class major flares and the evolution of follower flares. Information on associated (precursor and follower) flares is provided by Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). Flare list, while the major flares are observed by the Geostationary Operational Environmental Satellite (GOES) system satellites between 2002 and 2014. There are distinct evolutionary differences between the spatio-temporal distributions of associated flares in about one-day period depending on the type of the main flare. The spatial distribution was characterized by the normalized frequency distribution of the quantity δ (the distance between the major flare and its precursor flare normalized by the sunspot group diameter) in four 6 h time intervals before the major event. The precursors of X-class flares have a double-peaked spatial distribution for more than half a day prior to the major flare, but it changes to a lognormal-like distribution roughly 6 h prior to the event. The precursors of M-class flares show lognormal-like distribution in each 6 h subinterval. The most frequent sites of the precursors in the active region are within a distance of about 0.1 diameter of sunspot group from the site of the major flare in each case. Our investigation shows that the build-up of energy is more effective than the release of energy because of precursors.

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

    International Nuclear Information System (INIS)

    Frank, Lawrence R; Galinsky, Vitaly L

    2016-01-01

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

  10. A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets

    Directory of Open Access Journals (Sweden)

    Min Deng

    2016-02-01

    Full Text Available Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly developed for space-time processes that exhibit stationarity in space and time. It is still challenging to model heterogeneity of space-time data in the interpolation model. To overcome this limitation, in this study, a novel space-time interpolation method considering both spatial and temporal heterogeneity is developed for estimating missing data in space-time datasets. The interpolation operation is first implemented in spatial and temporal dimensions. Heterogeneous covariance functions are constructed to obtain the best linear unbiased estimates in spatial and temporal dimensions. Spatial and temporal correlations are then considered to combine the interpolation results in spatial and temporal dimensions to estimate the missing data. The proposed method is tested on annual average temperature and precipitation data in China (1984–2009. Experimental results show that, for these datasets, the proposed method outperforms three state-of-the-art methods—e.g., spatio-temporal kriging, spatio-temporal inverse distance weighting, and point estimation model of biased hospitals-based area disease estimation methods.

  11. Spatio-Temporal Series Remote Sensing Image Prediction Based on Multi-Dictionary Bayesian Fusion

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-11-01

    Full Text Available Contradictions in spatial resolution and temporal coverage emerge from earth observation remote sensing images due to limitations in technology and cost. Therefore, how to combine remote sensing images with low spatial yet high temporal resolution as well as those with high spatial yet low temporal resolution to construct images with both high spatial resolution and high temporal coverage has become an important problem called spatio-temporal fusion problem in both research and practice. A Multi-Dictionary Bayesian Spatio-Temporal Reflectance Fusion Model (MDBFM has been proposed in this paper. First, multiple dictionaries from regions of different classes are trained. Second, a Bayesian framework is constructed to solve the dictionary selection problem. A pixel-dictionary likehood function and a dictionary-dictionary prior function are constructed under the Bayesian framework. Third, remote sensing images before and after the middle moment are combined to predict images at the middle moment. Diverse shapes and textures information is learned from different landscapes in multi-dictionary learning to help dictionaries capture the distinctions between regions. The Bayesian framework makes full use of the priori information while the input image is classified. The experiments with one simulated dataset and two satellite datasets validate that the MDBFM is highly effective in both subjective and objective evaluation indexes. The results of MDBFM show more precise details and have a higher similarity with real images when dealing with both type changes and phenology changes.

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

    Science.gov (United States)

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

    2007-07-01

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

  13. Spatio-temporal analysis of Modified Omori law in Bayesian framework

    Science.gov (United States)

    Rezanezhad, V.; Narteau, C.; Shebalin, P.; Zoeller, G.; Holschneider, M.

    2017-12-01

    This work presents a study of the spatio temporal evolution of the modified Omori parameters in southern California in then time period of 1981-2016. A nearest-neighbor approach is applied for earthquake clustering. This study targets small mainshocks and corresponding big aftershocks ( 2.5 ≤ mmainshocks ≤ 4.5 and 1.8 ≤ maftershocks ≤ 2.8 ). We invert for the spatio temporal behavior of c and p values (especially c) all over the area using a MCMC based maximum likelihood estimator. As parameterizing families we use Voronoi cells with randomly distributed cell centers. Considering that c value represents a physical character like stress change we expect to see a coherent c value pattern over seismologically coacting areas. This correlation of c valus can actually be seen for the San Andreas, San Jacinto and Elsinore faults. Moreover, the depth dependency of c value is studied which shows a linear behavior of log(c) with respect to aftershock's depth within 5 to 15 km depth.

  14. Spatio-temporal epidemiology of the cholera outbreak in Papua New Guinea, 2009-2011.

    Science.gov (United States)

    Horwood, Paul F; Karl, Stephan; Mueller, Ivo; Jonduo, Marinjho H; Pavlin, Boris I; Dagina, Rosheila; Ropa, Berry; Bieb, Sibauk; Rosewell, Alexander; Umezaki, Masahiro; Siba, Peter M; Greenhill, Andrew R

    2014-08-20

    Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in >15,500 cases and >500 deaths. Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.

  15. Spatio-temporal flow maps for visualizing movement and contact patterns

    Directory of Open Access Journals (Sweden)

    Bing Ni

    2017-03-01

    Full Text Available The advanced telecom technologies and massive volumes of intelligent mobile phone users have yielded a huge amount of real-time data of people’s all-in-one telecommunication records, which we call telco big data. With telco data and the domain knowledge of an urban city, we are now able to analyze the movement and contact patterns of humans in an unprecedented scale. Flow map is widely used to display the movements of humans from one single source to multiple destinations by representing locations as nodes and movements as edges. However, it fails the task of visualizing both movement and contact data. In addition, analysts often need to compare and examine the patterns side by side, and do various quantitative analysis. In this work, we propose a novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact. We also propose integrating the spatiotemporal flow maps into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns. We report a potential application the proposed techniques can be applied to. The results show that our design and techniques properly unveil hidden information, while analysis can be achieved efficiently. Keywords: Spatio-temporal data, Flow map, Urban mobility

  16. BUILDING A BILLION SPATIO-TEMPORAL OBJECT SEARCH AND VISUALIZATION PLATFORM

    Directory of Open Access Journals (Sweden)

    D. Kakkar

    2017-10-01

    Full Text Available With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC, an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

  17. Building a Billion Spatio-Temporal Object Search and Visualization Platform

    Science.gov (United States)

    Kakkar, D.; Lewis, B.

    2017-10-01

    With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC), an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

  18. The Spatio-Temporal Characteristics and Modeling Research of Inter-Provincial Migration in China

    Directory of Open Access Journals (Sweden)

    Xiaomei Fan

    2018-02-01

    Full Text Available The national census data during 1995 and 2000 and during 2005 and 2010 are selected in this paper to make an analysis of the spatio-temporal characteristics of the inter-provincial population migration in China. In addition, the general regression model, the extension regression model considering the historical dependent variable and the spatial lag model are established based on the gravity model to make the regression model on China’s inter-provincial population migration over two periods of time. The results show that: (1 the inter-provincial population migration increases rapidly in size with strong geographical proximity; (2 China’s inter-provincial population migration is still in the primary stage of the general process of population migration. In other words, the inter-provincial population emigration and immigration levels have increased greatly with the economic development; (3 Statistically, the inter-provincial population migration is negatively correlated with the level of economic development in the emigrant place and the migration distance and positively correlated with the level of economic development in the immigrant place and the population scale in the emigrant and immigrant places; and (4 The spatio-temporal factor is an important explanatory variable of population migration. The introduction of the historical dependent variable and the spatial lag factor can improve the regression effect of the gravity model greatly, and the historical variable and the spatial factor have strong explanatory power for the inter-provincial population migration.

  19. Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation

    International Nuclear Information System (INIS)

    Martins, Anabela; Figueira, Rui; Sousa, António Jorge; Sérgio, Cecília

    2012-01-01

    Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area. - Highlights: ► We estimated copper contamination in mosses by spatio-temporal kriging between 1992 and 2006. ► We determined local distribution functions to define variation intervals at each location. ► Significance of temporal changes is assessed using an indicator based on uncertainty interval. ► There is general decrease in copper contamination, but spatial patterns are not uniform. - The contamination of copper in mosses was estimated by spatio-temporal kriging, with determination of uncertainty classes in the temporal variation.

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

    Science.gov (United States)

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

    2016-11-15

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

  1. Spatio-Temporal Parameters\\' Changes in Gait of Male Elderly Subjects

    Directory of Open Access Journals (Sweden)

    Heydar Sadeghi

    2010-03-01

    Full Text Available Objectives: The purpose of this study was to compare spatio-temporal gait parameters between elderly and young male subjects. Methods & Materials: 57 able-bodied elderly (72±5.5 years and 57 healthy young (25±8.5 years subjects participated in this study. A four segment model consist of trunk, hip, shank, and foot with 10 reflective markers were used to define lower limbs. Kinematic data collected using four high speed video based cameras at a sampling frequency of 90 Hz.The t-testfor independent samples (α≤0.05 applied for statistical analysis. Results: Significant differences showed longer stance phase (2%, longer push-of time (4%, slower cadence (13%, slower speed (28% and shorter step length (15% for elderly in comparison with young subjects, though no significant differences were seen in double supporttime between two groups. Conclusion: Due to results, spatio-temporal changes are mainly attributed to the age-related decreases in muscular flexibility, joints>ranges of motion and neuromuscular control in elderly people.

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

    Science.gov (United States)

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

    2012-10-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL

    2013-01-01

    We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. We observe that the target and interference spectra are inherently sparse in the spatio-temporal domain. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data and produces an equivalent performance as the other existing STAP techniques. In addition, the use of an OFDM signal increases the frequency diversity of our system, as different scattering centers of a target resonate at different frequencies, and thus improves the target detectability. First, we formulate a realistic sparse-measurement model for an OFDM radar considering both the clutter and jammer as the interfering sources. Then, we apply a residual sparse-recovery technique based on the LASSO estimator to estimate the target and interference covariance matrices, and subsequently compute the optimal STAP-filter weights. Our numerical results demonstrate a comparative performance analysis of the proposed sparse-STAP algorithm with four other existing STAP methods. Furthermore, we discover that the OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.

  4. Spatio-temporal distribution of fecal indicators in three rivers of the Haihe River Basin, China.

    Science.gov (United States)

    Wang, Yawei; Chen, Yanan; Zheng, Xiang; Gui, Chengmin; Wei, Yuansong

    2017-04-01

    Because of their significant impact on public health, waterborne pathogens, especially bacteria and viruses, are frequently monitored in surface water to assess microbial quality of water bodies. However, more than one billion people worldwide currently lack access to safe drinking water, and a diversity of waterborne outbreaks caused by pathogens is reported in nations at all levels of economic development. Spatio-temporal distribution of conventional pollutants and five pathogenic microorganisms were discussed for the Haihe River Basin. Land use and socio-economic assessments were coupled with comprehensive water quality monitoring. Physical, chemical, and biological parameters were measured at 20 different sites in the watershed for 1 year, including pH, temperature, conductivity, dissolved oxygen, turbidity, chemical oxygen demand, ammonia-N, total and fecal coliforms, E. coli, and Enterococcus. The results highlighted the high spatio-temporal variability in pathogen distribution at watershed scale: high concentration of somatic coliphages and fecal indicator bacteria in March and December and their very low concentration in June and September. All pathogens were positively correlated to urban/rural residential/industrial land and negatively correlated to other four land use types. Microbial pollution was greatly correlated with population density, urbanization rate, and percentage of the tertiary industry in the gross domestic product. In the future, river microbial risk control strategy should focus more on the effective management of secondary effluent of wastewater treatment plant and land around rivers.

  5. Measurement of traffic parameters in image sequence using spatio-temporal information

    International Nuclear Information System (INIS)

    Lee, Daeho; Park, Youngtae

    2008-01-01

    This paper proposes a novel method for measurement of traffic parameters, such as the number of passed vehicles, velocity and occupancy rate, by video image analysis. The method is based on a region classification followed by spatio-temporal image analysis. Local detection region images in traffic lanes are classified into one of four categories: the road, the vehicle, the reflection and the shadow, by using statistical and structural features. Misclassification at a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. This capability of error correction results in the accurate estimation of traffic parameters even in high traffic congestion. Also headlight detection is employed for nighttime operation. Experimental results show that the accuracy is more than 94% in our test database of diverse operating conditions such as daytime, shadowy daytime, highway, urban way, rural way, rainy day, snowy day, dusk and nighttime. The average processing time is 30 ms per frame when four traffic lanes are processed, and real-time operation could be realized while ensuring robust detection performance even for high-speed vehicles up to 150 km h −1

  6. Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clustering models.

    Science.gov (United States)

    Ebrahimian, Hossein; Jalayer, Fatemeh

    2017-08-29

    In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.

  7. Spatio-Temporal Distribution of Landslides in Java and the Triggering Factors

    Directory of Open Access Journals (Sweden)

    Danang Sri Hadmoko

    2017-07-01

    Full Text Available Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1 the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2 their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %, Central Java (29 % and East Java (4 %. Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.

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

    Science.gov (United States)

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

    2016-08-15

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

  9. Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

    Science.gov (United States)

    Luan, Hui; Law, Jane; Quick, Matthew

    2015-12-30

    Obesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density. This research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas. For the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps. This research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

  10. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Science.gov (United States)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

    This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  11. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Directory of Open Access Journals (Sweden)

    Medyńska-Gulij Beata

    2016-06-01

    Full Text Available This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

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

    Energy Technology Data Exchange (ETDEWEB)

    Hilbert, V.; Rödel, C.; Zastrau, U., E-mail: ulf.zastrau@uni-jena.de [Institut für Optik und Quantenelektronik, Friedrich-Schiller-Universität, Max-Wien-Platz 1, 07743 Jena (Germany); Brenner, G.; Düsterer, S.; Dziarzhytski, S.; Harmand, M.; Przystawik, A.; Redlin, H.; Toleikis, S. [Deutsches Elektronen-Synchrotron DESY, Notkestrasse 85, 22607 Hamburg (Germany); Döppner, T.; Ma, T. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550 (United States); Fletcher, L. [Department of Physics, University of California, Berkeley, California 94720 (United States); Förster, E. [Institut für Optik und Quantenelektronik, Friedrich-Schiller-Universität, Max-Wien-Platz 1, 07743 Jena (Germany); Helmholtz-Institut Jena, Fröbelstieg 3, 07743 Jena (Germany); Glenzer, S. H.; Lee, H. J. [SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Hartley, N. J. [Department of Physics, Clarendon Laboratory, University of Oxford, Parks Road, Oxford OX1 3PU (United Kingdom); Kazak, L.; Komar, D.; Skruszewicz, S. [Institut für Physik, Universität Rostock, 18051 Rostock (Germany); and others

    2014-09-08

    A key feature of extreme ultraviolet (XUV) radiation from free-electron lasers (FELs) is its spatial and temporal coherence. We measured the spatio-temporal coherence properties of monochromatized FEL pulses at 13.5 nm using a Michelson interferometer. A temporal coherence time of (59±8) fs has been determined, which is in good agreement with the spectral bandwidth given by the monochromator. Moreover, the spatial coherence in vertical direction amounts to about 15% of the beam diameter and about 12% in horizontal direction. The feasibility of measuring spatio-temporal coherence properties of XUV FEL radiation using interferometric techniques advances machine operation and experimental studies significantly.

  13. Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    2010-01-01

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  14. Spatio-temporal foreshock activity during stick-slip experiments of large rock samples

    Science.gov (United States)

    Tsujimura, Y.; Kawakata, H.; Fukuyama, E.; Yamashita, F.; Xu, S.; Mizoguchi, K.; Takizawa, S.; Hirano, S.

    2016-12-01

    Foreshock activity has sometimes been reported for large earthquakes, and has been roughly classified into the following two classes. For shallow intraplate earthquakes, foreshocks occurred in the vicinity of the mainshock hypocenter (e.g., Doi and Kawakata, 2012; 2013). And for intraplate subduction earthquakes, foreshock hypocenters migrated toward the mainshock hypocenter (Kato, et al., 2012; Yagi et al., 2014). To understand how foreshocks occur, it is useful to investigate the spatio-temporal activities of foreshocks in the laboratory experiments under controlled conditions. We have conducted stick-slip experiments by using a large-scale biaxial friction apparatus at NIED in Japan (e.g., Fukuyama et al., 2014). Our previous results showed that stick-slip events repeatedly occurred in a run, but only those later events were preceded by foreshocks. Kawakata et al. (2014) inferred that the gouge generated during the run was an important key for foreshock occurrence. In this study, we proceeded to carry out stick-slip experiments of large rock samples whose interface (fault plane) is 1.5 meter long and 0.5 meter wide. After some runs to generate fault gouge between the interface. In the current experiments, we investigated spatio-temporal activities of foreshocks. We detected foreshocks from waveform records of 3D array of piezo-electric sensors. Our new results showed that more than three foreshocks (typically about twenty) had occurred during each stick-slip event, in contrast to the few foreshocks observed during previous experiments without pre-existing gouge. Next, we estimated the hypocenter locations of the stick-slip events, and found that they were located near the opposite end to the loading point. In addition, we observed a migration of foreshock hypocenters toward the hypocenter of each stick-slip event. This suggests that the foreshock activity observed in our current experiments was similar to that for the interplate earthquakes in terms of the

  15. Spatio-temporal transmission patterns of black-band disease in a coral community.

    Directory of Open Access Journals (Sweden)

    Assaf Zvuloni

    Full Text Available BACKGROUND: Transmission mechanisms of black-band disease (BBD in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease. METHODOLOGY/PRINCIPAL FINDINGS: 3,175 susceptible and infected corals were mapped over an area of 10x10 m in Eilat (northern Gulf of Aqaba, Red Sea and the distribution of the disease was examined monthly throughout almost two full disease cycles (June 2006-December 2007. Spatial and spatio-temporal analyses were applied to infer the transmission pattern of the disease and to calculate key epidemiological parameters such as (basic reproduction number. We show that the prevalence of the disease is strongly associated with high water temperature. When water temperatures rise and disease prevalence increases, infected corals exhibit aggregated distributions on small spatial scales of up to 1.9 m. Additionally, newly-infected corals clearly appear in proximity to existing infected corals and in a few cases in direct contact with them. We also present and test a model of water-borne infection, indicating that the likelihood of a susceptible coral becoming infected is defined by its spatial location and by the relative spatial distribution of nearby infected corals found in the site. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence that local transmission, but not necessarily by direct contact, is likely to be an important factor in the spread of the disease over the tested spatial scale. In the absence of potential disease vectors with limited mobility (e.g., snails, fireworms in the studied site, water-borne infection is likely to be a significant transmission mechanism of BBD. Our suggested model of water-borne transmission supports this hypothesis. The spatio-temporal analysis also points

  16. Challenges for modelling spatio-temporal variations of malaria risk in Malawi

    Science.gov (United States)

    Lowe, R.; Chirombo, J.; Tompkins, A. M.

    2012-04-01

    Malaria is the leading cause of morbidity and mortality in Malawi with more than 6 million episodes reported each year. Malaria poses a huge economic burden to Malawi in terms of the direct cost of treating malaria patients and also indirect costs resulting from workdays lost in agriculture and industry and absenteeism from school. Malawi implements malaria control activities within the Roll Back Malaria framework, with the objective to provide those most at risk (i.e. children under five years, pregnant woman and individuals with suppressed immune systems) access to personal and community protective measures. However, at present there is no mechanism by which to target the most 'at risk' populations ahead of an impending epidemic. Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the mosquito and the availability of breeding sites, but also socio-economic conditions such as levels of urbanisation, poverty and education, which influence human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for modelling of malaria risk in space and time. Using an age-stratified spatio-temporal dataset of malaria cases at the district level from July 2004 - June 2011, we use a spatio-temporal modelling framework to model variations in malaria risk in Malawi. Climatic and topographic variations are accounted for using an interpolation method to relate gridded products to administrative districts. District level data is tested in the model to account for confounding factors, including the proportion of the population living in urban areas; residing in traditional housing; with no toilet facilities; who do not attend school, etc, the number of health facilities per population and yearly estimates of insecticide-treated mosquito net distribution. In order to account for

  17. Spatio-temporal modelling of rainfall in the Murray-Darling Basin

    Science.gov (United States)

    Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

    2018-02-01

    The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

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

    International Nuclear Information System (INIS)

    Jing, Ha; He, Shoujie

    2015-01-01

    The characteristics of self-pulse in hollow cathode discharge at low pressure have been investigated. The voltage-current (V-I) curves, the influence of ballast resistor on the self-pulses, and the evolution of current and voltage are measured. Both the axial and radial spatio-temporal discharge images of self-pulse are recorded. The results show that there exists the hysteresis effect in the present hollow cathode discharge. The high value of ballast resistors is favourable for the observation of self-pulses. The process of the self-pulse can be divided into three stages from the temporal discharge images, i.e., the pre-discharge, the transition from mainly axial electric field to mainly radial electric field, and the decaying process. The self-pulse is suggested to originate from the mode transition of the discharge in essence

  19. Spatio-temporal chaos and thermal noise in Josephson junction series arrays

    International Nuclear Information System (INIS)

    Dominguez, D.; Cerdeira, H.A.

    1995-01-01

    We study underdamped Josephson junction series arrays that are globally coupled through a resistive shunting load and driven by an rf bias current. We find that they can be an experimental realization of many phenomena currently studied in globally coupled logistic map. Depending on the bias current the array can show Shapiro steps but also spatio-temporal chaos or ''turbulence'' in the IV characteristics. In the turbulent phase there is a saturation of the broad band noise for a large number of junctions. This corresponds to a break down of the law of large numbers as seen in globally coupled maps. We study this phenomenon as a function of thermal noise. We find that when increasing the temperature the broad band noise decreases. (author). 8 refs, 1 fig

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

    Directory of Open Access Journals (Sweden)

    Matthias Rieckher

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

  1. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

    Science.gov (United States)

    Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

    2014-01-01

    We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  4. Laser-Based Spatio-Temporal Characterisation of Port Fuel Injection (PFI Sprays

    Directory of Open Access Journals (Sweden)

    C. T. N. Anand

    2010-06-01

    Full Text Available In the present work, detailed laser-based diagnostic experiments were conducted to characterise the spray from low pressure 2-hole and 4-hole Port Fuel Injection (PFI injectors. The main objective of the work included obtaining quantitative information of the spatio-temporal spray structure of such low-pressure gasoline sprays. A novel approach involving a combination of techniques such as Mie scattering, Granulometry, and Laser Sheet Dropsizing (LSD was used to study the spray structure. The droplet sizes, distributions with time, Sauter Mean Diameters (SMD, droplet velocities, cone angles and spray tip penetrations of the sprays from the injectors were determined. The spray from these injectors is found to be ‘pencil like’ and not dispersed as in high pressure sprays. The application of the above mentioned techniques provides two-dimensional SMD contours of the entire spray at different instants of time, with reasonable accuracy.

  5. FACILITATING INTEGRATED SPATIO-TEMPORAL VISUALIZATION AND ANALYSIS OF HETEROGENEOUS ARCHAEOLOGICAL AND PALAEOENVIRONMENTAL RESEARCH DATA

    Directory of Open Access Journals (Sweden)

    C. Willmes

    2012-07-01

    Full Text Available In the context of the Collaborative Research Centre 806 "Our way to Europe" (CRC806, a research database is developed for integrating data from the disciplines of archaeology, the geosciences and the cultural sciences to facilitate integrated access to heterogeneous data sources. A practice-oriented data integration concept and its implementation is presented in this contribution. The data integration approach is based on the application of Semantic Web Technology and is applied to the domains of archaeological and palaeoenvironmental data. The aim is to provide integrated spatio-temporal access to an existing wealth of data to facilitate research on the integrated data basis. For the web portal of the CRC806 research database (CRC806-Database, a number of interfaces and applications have been evaluated, developed and implemented for exposing the data to interactive analysis and visualizations.

  6. VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

    Science.gov (United States)

    Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

    2017-10-02

    Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

  7. Spatio-temporal model based optimization framework to design future hydrogen infrastructure networks

    International Nuclear Information System (INIS)

    Konda, N.V.S.; Shah, N.; Brandon, N.P.

    2009-01-01

    A mixed integer programming (MIP) spatio-temporal model was used to design hydrogen infrastructure networks for the Netherlands. The detailed economic analysis was conducted using a multi-echelon model of the entire hydrogen supply chain, including feed, production, storage, and transmission-distribution systems. The study considered various near-future and commercially available technologies. A multi-period model was used to design evolutionary hydrogen supply networks in coherence with growing demand. A scenario-based analysis was conducted in order to account for uncertainties in future demand. The study showed that competitive hydrogen networks can be designed for any conceivable scenario. It was concluded that the multi-period model presented significant advantages in relation to decision-making over long time-horizons

  8. The spatio-temporal Development of Copenhagen's bicycle infrastructure 1912-2013

    DEFF Research Database (Denmark)

    Carstensen, Trine Agervig; Olafsson, Anton Stahl; Bech, Nynne Marie

    2015-01-01

    Cycling plays an important role in low-carbon transitions. Around the globe, cities are constructing bicycle infrastructure. The city of Copenhagen has a bicycle-friendly infrastructure celebrated for its fine-meshed network. This study documents the spatio-temporal development of Copenhagen......’s bicycle infrastructure and explores how the development corresponds to other processes of urban transformation. The study builds on historical maps of bicycle infrastructure that are digitised into geographical information, which allows for a comprehensive analysis of the formation of the network....... In search for identifying drivers, the study analyses the city’s spatial growth pattern, migration pattern, development of road network and changes in the transport culture. Analyses reveal that the bicycle infrastructure expanded at a relatively constant pace during distinct periods of urban transformation...

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

    DEFF Research Database (Denmark)

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

    2018-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Viktor Beneš

    2011-05-01

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  12. Estimating Activity Patterns Using Spatio-temporal Data of Cellphone Networks

    Directory of Open Access Journals (Sweden)

    Zahedi Seyedmostafa

    2016-01-01

    Full Text Available The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years, but these models have suffered insufficient data for calibration. This paper discusses ways to process the cellphone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. Movements of each subscriber is described by a sequence of stays and trips and each stay is labeled by an activity. The type of activities are estimated using features such as land use, duration of stay, frequency of visit, arrival time to that activity and its distance from home. Finally, the chains of trips are identified and different patterns that citizens follow to participate in activities are determined. The data comprises 144 million records of the location of 300,000 citizens of Shiraz at five-minute intervals.

  13. Spatio-temporal features for tracking and quadruped/biped discrimination

    Science.gov (United States)

    Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

    2012-05-01

    Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

  14. Spatio-Temporal Gene Expression Profiling during In Vivo Early Ovarian Folliculogenesis: Integrated Transcriptomic Study and Molecular Signature of Early Follicular Growth.

    Directory of Open Access Journals (Sweden)

    Agnes Bonnet

    Full Text Available The successful achievement of early ovarian folliculogenesis is important for fertility and reproductive life span. This complex biological process requires the appropriate expression of numerous genes at each developmental stage, in each follicular compartment. Relatively little is known at present about the molecular mechanisms that drive this process, and most gene expression studies have been performed in rodents and without considering the different follicular compartments.We used RNA-seq technology to explore the sheep transcriptome during early ovarian follicular development in the two main compartments: oocytes and granulosa cells. We documented the differential expression of 3,015 genes during this phase and described the gene expression dynamic specific to these compartments. We showed that important steps occurred during primary/secondary transition in sheep. We also described the in vivo molecular course of a number of pathways. In oocytes, these pathways documented the chronology of the acquisition of meiotic competence, migration and cellular organization, while in granulosa cells they concerned adhesion, the formation of cytoplasmic projections and steroid synthesis. This study proposes the involvement in this process of several members of the integrin and BMP families. The expression of genes such as Kruppel-like factor 9 (KLF9 and BMP binding endothelial regulator (BMPER was highlighted for the first time during early follicular development, and their proteins were also predicted to be involved in gene regulation. Finally, we selected a data set of 24 biomarkers that enabled the discrimination of early follicular stages and thus offer a molecular signature of early follicular growth. This set of biomarkers includes known genes such as SPO11 meiotic protein covalently bound to DSB (SPO11, bone morphogenetic protein 15 (BMP15 and WEE1 homolog 2 (S. pombe(WEE2 which play critical roles in follicular development but other biomarkers

  15. Participatory Bluetooth Sensing: A Method for Acquiring Spatio-Temporal Data about Participant Mobility and Interactions at Large Scale Events

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Larsen, Jakob Eg; Jørgensen, Sune Lehmann

    2013-01-01

    for collecting spatio-temporal data about participant mobility and social interactions uses the capabilities of Bluetooth capable smartphones carried by participants. As a proof-of-concept we present a field study with deployment of the method in a large music festival with 130 000 participants where a small...

  16. Clonal mobility and its implications for spatio-temporal patterns of plant communities: what do we need to know next?

    Czech Academy of Sciences Publication Activity Database

    Zobel, M.; Moora, M.; Herben, Tomáš

    2010-01-01

    Roč. 119, č. 5 (2010), s. 802-806 ISSN 0030-1299 Institutional research plan: CEZ:AV0Z60050516 Keywords : clonal mobility * spatio-temporal patterns * plant communities Subject RIV: EF - Botanics Impact factor: 3.393, year: 2010

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

    Science.gov (United States)

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

    2012-01-01

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

  18. Characteristics of juvenile survivors reveal spatio-temporal differences in early life stage survival of Baltic cod

    DEFF Research Database (Denmark)

    Huwer, Bastian; Hinrichsen, H.H.; Böttcher, U.

    2014-01-01

    with previous modeling studies on the survival chances of early-stage larvae and with general spatio-temporal patterns of larval prey availability suggests that differences in survival are related to food availability during the early larval stage. Results are discussed in relation to the recruitment process...

  19. Spatio-temporal encoding using narrow-band linear frequency modulated signals in synthetic aperture ultrasound imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jensen, Jørgen Arendt

    2005-01-01

    In this paper a method for spatio-temporal encoding is presented for synthetic transmit aperture ultrasound imaging (STA). The purpose is to excite several transmitters at the same time in order to transmit more acoustic energy in every single transmission. When increasing the transmitted acousti...

  20. Spatio-temporal spectra in the logarithmic layer of wall turbulence: large-eddy simulations and simple models

    NARCIS (Netherlands)

    Wilczek, Michael; Stevens, Richard Johannes Antonius Maria; Meneveau, Charles

    2015-01-01

    Motivated by the need to characterize the spatio-temporal structure of turbulence in wall-bounded flows, we study wavenumber–frequency spectra of the streamwise velocity component based on large-eddy simulation (LES) data. The LES data are used to measure spectra as a function of the two

  1. Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

    Science.gov (United States)

    Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

    2014-10-01

    Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

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

    Directory of Open Access Journals (Sweden)

    A. V. Zhukov

    2016-01-01

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

  3. Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.

    Directory of Open Access Journals (Sweden)

    Delphine Nicolas

    Full Text Available The North Sea cod (Gadus morhua, L. stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature and/or indirect (i.e. changes in the quantity and quality of zooplankton prey effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability.

  4. Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

    Science.gov (United States)

    Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

    2017-06-01

    The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

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

    Science.gov (United States)

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

    2013-10-01

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

  6. Spatio-temporal Variability of Albedo and its Impact on Glacier Melt Modelling

    Science.gov (United States)

    Kinnard, C.; Mendoza, C.; Abermann, J.; Petlicki, M.; MacDonell, S.; Urrutia, R.

    2017-12-01

    Albedo is an important variable for the surface energy balance of glaciers, yet its representation within distributed glacier mass-balance models is often greatly simplified. Here we study the spatio-temporal evolution of albedo on Glacier Universidad, central Chile (34°S, 70°W), using time-lapse terrestrial photography, and investigate its effect on the shortwave radiation balance and modelled melt rates. A 12 megapixel digital single-lens reflex camera was setup overlooking the glacier and programmed to take three daily images of the glacier during a two-year period (2012-2014). One image was chosen for each day with no cloud shading on the glacier. The RAW images were projected onto a 10m resolution digital elevation model (DEM), using the IMGRAFT software (Messerli and Grinsted, 2015). A six-parameter camera model was calibrated using a single image and a set of 17 ground control points (GCPs), yielding a georeferencing accuracy of accounting for possible camera movement over time. The reflectance values from the projected image were corrected for topographic and atmospheric influences using a parametric solar irradiation model, following a modified algorithm based on Corripio (2004), and then converted to albedo using reference albedo measurements from an on-glacier automatic weather station (AWS). The image-based albedo was found to compare well with independent albedo observations from a second AWS in the glacier accumulation area. Analysis of the albedo maps showed that the albedo is more spatially-variable than the incoming solar radiation, making albedo a more important factor of energy balance spatial variability. The incorporation of albedo maps within an enhanced temperature index melt model revealed that the spatio-temporal variability of albedo is an important factor for the calculation of glacier-wide meltwater fluxes.

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

    Science.gov (United States)

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

    2017-12-01

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

  8. Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

    Science.gov (United States)

    Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

    2017-04-01

    Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

  9. Spatio-Temporal Simulation and Analysis of Regional Ecological Security Based on Lstm

    Science.gov (United States)

    Gong, C.; Qi, L.; Heming, L.; Karimian, H.; Yuqin, M.

    2017-10-01

    Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP), atmospheric optical depth (AOD), moderate-resolution imaging spectrometer (MODIS), Normalized Difference Vegetation Index (NDVI), landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

  10. SPATIO-TEMPORAL SIMULATION AND ANALYSIS OF REGIONAL ECOLOGICAL SECURITY BASED ON LSTM

    Directory of Open Access Journals (Sweden)

    C. Gong

    2017-10-01

    Full Text Available Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP, atmospheric optical depth (AOD, moderate-resolution imaging spectrometer (MODIS, Normalized Difference Vegetation Index (NDVI, landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

  11. Adaptive OFDM Waveform Design for Spatio-Temporal-Sparsity Exploited STAP Radar

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL

    2017-11-01

    In this chapter, we describe a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of-freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully adaptive OFDM-STAP, we develop a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain, as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we optimally design the transmit OFDM signals by maximizing the output signal-to-interference-plus-noise ratio (SINR) in order to improve the STAP performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity-based technique and adaptive waveform design.

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

    Science.gov (United States)

    Willis, Gary; Pruessner, Gunnar

    2018-02-01

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

  13. a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

    Science.gov (United States)

    Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

    2017-09-01

    Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

  14. Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

    Science.gov (United States)

    Ironi, Liliana; Tentoni, Stefania

    2007-02-01

    This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.

  15. Spatio-temporal changes in total annual rainfall and the annual number of rainy days

    International Nuclear Information System (INIS)

    Limjirakan, Sangchan; Limsakul, Atsamon

    2007-01-01

    Full text: Full text: Rainfall variability is a critical factor for Thailand's socioeconomic development. Thus, enhancing understanding of rainfall mechanisms and variability is of paramount importance for effective strategies in tackling the severe droughts/floods which are memorable and a recurring problem in Thailand. Through this study, we have examined the variability of total annual rainfall (R,otai) and the annual number of rainy days (Rday) in Thailand during 1951-2003, using an Empirical Orthogonal Function (EOF) analysis. The primary objective is to determine the dominant spatio-temporal patterns, and to illustrate their connection with the El Nino-Southern Oscillation (ENSO). The results reveal that the first two EOF modes, which explain nearly half of the total variance, show a good coherence of spatio-temporal structures. A salient feature of the leading modes of R,otal and Rday in Thailand is that their temporal coefficients exhibit significant relations to the ENSO. On an interannual timescale, the leading modes tended to be greater (lower) than normal during the La Nina (El Nino) phase of the ENSO. Changes in the Walker circulation appear to be the dominant mechanism whereby the ENSO exerts its influence on rainfall variability in Thailand. For an interdecadal timescale, there is evidence of the unusual and persistent deficit in Rtar accompanied by a concomitant reduction of Ranrd over the last three decades. The recent drought-like condition has been closely associated with the shift in the ENSO towards more El Nino events since the late 1970s, and coincided with the high global mean temperature. These natural/anthropogenic-induced climatic changes have important implications for rainfall forecasting, and consequently for water resource and agricultural planning and management in Thailand

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

    Directory of Open Access Journals (Sweden)

    Anne eSchlottmann

    2013-07-01

    Full Text Available 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.

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

    Science.gov (United States)

    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

  18. A realistic large-scale model of the cerebellum granular layer predicts circuit spatio-temporal filtering properties

    Directory of Open Access Journals (Sweden)

    Sergio Solinas

    2010-05-01

    Full Text Available The way the cerebellar granular layer transforms incoming mossy fiber signals into new spike patterns to be related to Purkinje cells is not yet clear. Here, a realistic computational model of the granular layer was developed and used to address four main functional hypotheses: center-surround organization, time-windowing, high-pass filtering in responses to spike bursts and coherent oscillations in response to diffuse random activity. The model network was activated using patterns inspired by those recorded in vivo. Burst stimulation of a small mossy fiber bundle resulted in granule cell bursts delimited in time (time windowing and space (center-surround by network inhibition. This burst-burst transmission showed marked frequency-dependence configuring a high-pass filter with cut-off frequency around 100 Hz. The contrast between center and surround properties was regulated by the excitatory-inhibitory balance. The stronger excitation made the center more responsive to 10-50 Hz input frequencies and enhanced the granule cell output (with spike occurring earlier and with higher frequency and number compared to the surround. Finally, over a certain level of mossy fiber background activity, the circuit generated coherent oscillations in the theta-frequency band. All these processes were fine-tuned by NMDA and GABA-A receptor activation and neurotransmitter vesicle cycling in the cerebellar glomeruli. This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillations.

  19. Spatio-temporal variability in hydro-chemical characteristics of coastal waters of Salimpur, Chittagong along the Bay of Bengal

    Directory of Open Access Journals (Sweden)

    Avijit Talukder

    2016-04-01

    Full Text Available Diverse seasonal characteristics of hydro-chemical parameters in the coastal zone are significantly related to aquaculture development. In this paper, general water quality condition derived from laboratory analysis from the coastal waters of Salimpur, Chittagong is presented. Samples were collected from onshore and offshore site of two adjacent coastal locations named as North Salimpur (experimental location and South Kattoli (control during a monsoon and a dry season spanning 2013-14. The spatio-temporal variability of studied parameters were found as air temperature 26.5-32.5 ˚C, water temperature 23-33 °C, pH 7.1-7.9, DO 4.29-7.11 mg/L, BOD 1.10-3.25 mg/L, salinity 1.6-21 ppt, EC 3.40-35.68 mS/cm, TDS 2.02-21.99 g/L, TSS 0.62-2.76 g/L, transparency 4.5-14 cm, precipitation 64-1992 mm, NO2-N 1.94-2.58 µg/L, PO4-P 0.45-1.84 µg/L, SiO3-Si 130.46-956.31 µg/L during investigation period. Average values of physicochemical parameters were found to be in compliance with standard guidelines. The ship breaking activities near experimental location possess negative impacts on local geomorphology, freshwater inputs, precipitation and aquatic environment as well. Moreover, wind driven forces, tidal action, wave characteristics and changes in monsoon pattern regulate the coastal processes. This research suggests the importance of regular monitoring to assess present status of water quality and future prospect of aquaculture in the Chittagong coastal zone.

  20. A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom

    Science.gov (United States)

    Page, Benjamin P.; Kumar, Abhishek; Mishra, Deepak R.

    2018-04-01

    As the frequency of cyanobacterial harmful algal blooms (CyanoHABs) become more common in recreational lakes and water supply reservoirs, demand for rapid detection and temporal monitoring will be imminent for effective management. The goal of this study was to demonstrate a novel and potentially operational cross-satellite based protocol for synoptic monitoring of rapidly evolving and increasingly common CyanoHABs in inland waters. The analysis involved a novel way to cross-calibrate a chlorophyll-a (Chl-a) detection model for the Landsat-8 OLI sensor from the relationship between the normalized difference chlorophyll index and the floating algal index derived from Sentinel-2A on a coinciding overpass date during the summer CyanoHAB bloom in Utah Lake. This aided in the construction of a time-series phenology of the Utah Lake CyanoHAB event. Spatio-temporal cyanobacterial density maps from both Sentinel-2A and Landsat-8 sensors revealed that the bloom started in the first week of July 2016 (July 3rd, mean cell count: 9163 cells/mL), reached peak in mid-July (July 15th, mean cell count: 108176 cells/mL), and reduced in August (August 24th, mean cell count: 9145 cells/mL). Analysis of physical and meteorological factors suggested a complex interaction between landscape processes (high surface runoff), climatic conditions (high temperature, high rainfall followed by negligible rainfall, stable wind), and water quality (low water level, high Chl-a) which created a supportive environment for triggering these blooms in Utah Lake. This cross satellite-based monitoring methods can be a great tool for regular monitoring and will reduce the budget cost for monitoring and predicting CyanoHABs in large lakes.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    Science.gov (United States)

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

    2016-04-01

    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

  4. Zebrafish: an exciting model for investigating the spatio-temporal pattern of enteric nervous system development.

    LENUS (Irish Health Repository)

    Doodnath, Reshma

    2012-02-01

    AIM: Recently, the zebrafish (Danio rerio) has been shown to be an excellent model for human paediatric research. Advantages over other models include its small size, externally visually accessible development and ease of experimental manipulation. The enteric nervous system (ENS) consists of neurons and enteric glia. Glial cells permit cell bodies and processes of neurons to be arranged and maintained in a proper spatial arrangement, and are essential in the maintenance of basic physiological functions of neurons. Glial fibrillary acidic protein (GFAP) is expressed in astrocytes, but also expressed outside of the central nervous system. The aim of this study was to investigate the spatio-temporal pattern of GFAP expression in developing zebrafish ENS from 24 h post-fertilization (hpf), using transgenic fish that express green fluorescent protein (GFP). METHODS: Zebrafish embryos were collected from transgenic GFP Tg(GFAP:GFP)(mi2001) adult zebrafish from 24 to 120 hpf, fixed and processed for whole mount immunohistochemistry. Antibodies to Phox2b were used to identify enteric neurons. Specimens were mounted on slides and imaging was performed using a fluorescent laser confocal microscope. RESULTS: GFAP:GFP labelling outside the spinal cord was identified in embryos from 48 hpf. The patterning was intracellular and consisted of elongated profiles that appeared to migrate away from the spinal cord into the periphery. At 72 and 96 hpf, GFAP:GFP was expressed dorsally and ventrally to the intestinal tract. At 120 hpf, GFAP:GFP was expressed throughout the intestinal wall, and clusters of enteric neurons were identified using Phox2b immunofluorescence along the pathway of GFAP:GFP positive processes, indicative of a migratory pathway of ENS precursors from the spinal cord into the intestine. CONCLUSION: The pattern of migration of GFAP:GFP expressing cells outside the spinal cord suggests an organized, early developing migratory pathway to the ENS. This shows for the

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

    Science.gov (United States)

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

    2014-05-01

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

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

    Science.gov (United States)

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

    2014-09-18

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

  7. Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images

    Science.gov (United States)

    Hengl, Tomislav; Heuvelink, Gerard B. M.; Perčec Tadić, Melita; Pebesma, Edzer J.

    2012-01-01

    A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations (159) in Croatia. The input data set contains 57,282 ground measurements of daily temperature for the year 2008. Temperature was modeled as a function of latitude, longitude, distance from the sea, elevation, time, insolation, and the MODIS LST images. The original rasters were first converted to principal components to reduce noise and filter missing pixels in the LST images. The residual were next analyzed for spatio-temporal auto-correlation; sum-metric separable variograms were fitted to account for zonal and geometric space-time anisotropy. The final predictions were generated for time-slices of a 3D space-time cube, constructed in the R environment for statistical computing. The results show that the space-time regression model can explain a significant part of the variation in station-data (84%). MODIS LST 8-day (cloud-free) images are unbiased estimator of the daily temperature, but with relatively low precision (±4.1°C); however their added value is that they systematically improve detection of local changes in land surface temperature due to local meteorological conditions and/or active heat sources (urban areas, land cover classes). The results of 10-fold cross-validation show that use of spatio-temporal regression-kriging and incorporation of time-series of remote sensing images leads to significantly more accurate maps of temperature than if plain spatial techniques were used. The average (global) accuracy of mapping temperature was ±2.4°C. The regression-kriging explained 91% of variability in daily temperatures, compared to 44% for ordinary kriging. Further software advancement—interactive space-time variogram exploration and automated retrieval

  8. Spatio-temporal analyses of impacts of multiple climatic hazards in a savannah ecosystem of Ghana

    Directory of Open Access Journals (Sweden)

    Gerald A.B. Yiran, PhD

    2016-01-01

    Full Text Available Ghana’s savannah ecosystem has been subjected to a number of climatic hazards of varying severity. This paper presents a spatial, time-series analysis of the impacts of multiple hazards on the ecosystem and human livelihoods over the period 1983–2012, using the Upper East Region of Ghana as a case study. Our aim is to understand the nature of hazards (their frequency, magnitude and duration and how they cumulatively affect humans. Primary data were collected using questionnaires, focus group discussions, in-depth interviews and personal observations. Secondary data were collected from documents and reports. Calculations of the standard precipitation index (SPI and crop failure index used rainfall data from 4 weather stations (Manga, Binduri, Vea and Navrongo and crop yield data of 5 major crops (maize, sorghum, millet, rice and groundnuts respectively. Temperature and windstorms were analysed from the observed weather data. We found that temperatures were consistently high and increasing. From the SPI, drought frequency varied spatially from 9 at Binduri to 13 occurrences at Vea; dry spells occurred at least twice every year and floods occurred about 6 times on average, with slight spatial variations, during 1988–2012, a period with consistent data from all stations. Impacts from each hazard varied spatio-temporally. Within the study period, more 70% of years recorded severe crop losses with greater impacts when droughts and floods occur in the same year, especially in low lying areas. The effects of crop losses were higher in districts with no/little irrigation (Talensi, Nabdam, Garu-Tempane, Kassena-Nankana East. Frequency and severity of diseases and sicknesses such as cerebrospinal meningitis, heat rashes, headaches and malaria related to both dry and wet conditions have increased steadily over time. Other impacts recorded with spatio-temporal variations included destruction to housing, displacement, injury and death of people. These

  9. Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking

    KAUST Repository

    Huang, Huang

    2017-07-16

    This thesis focuses on two topics, computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data. The first topic is motivated by the prohibitive computational burden in fitting Gaussian process models to large and irregularly spaced spatial datasets. Various approximation methods have been introduced to reduce the computational cost, but many rely on unrealistic assumptions about the process and retaining statistical efficiency remains an issue. We propose a new scheme to approximate the maximum likelihood estimator and the kriging predictor when the exact computation is infeasible. The proposed method provides different types of hierarchical low-rank approximations that are both computationally and statistically efficient. We explore the improvement of the approximation theoretically and investigate the performance by simulations. For real applications, we analyze a soil moisture dataset with 2 million measurements with the hierarchical low-rank approximation and apply the proposed fast kriging to fill gaps for satellite images. The second topic is motivated by rank-based outlier detection methods for functional data. Compared to magnitude outliers, it is more challenging to detect shape outliers as they are often masked among samples. We develop a new notion of functional data depth by taking the integration of a univariate depth function. Having a form of the integrated depth, it shares many desirable features. Furthermore, the novel formation leads to a useful decomposition for detecting both shape and magnitude outliers. Our simulation studies show the proposed outlier detection procedure outperforms competitors in various outlier models. We also illustrate our methodology using real datasets of curves, images, and video frames. Finally, we introduce the functional data ranking technique to spatio-temporal statistics for visualizing and assessing covariance properties, such as

  10. Spatio-temporal analysis of smear-positive tuberculosis in the Sidama Zone, southern Ethiopia.

    Directory of Open Access Journals (Sweden)

    Mesay Hailu Dangisso

    Full Text Available Tuberculosis (TB is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs. However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia.A retrospective space-time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB. Scan statistics, Global Moran's I, and Getis and Ordi (Gi* statistics were all used to help analyze the spatial distribution and clusters of the disease across settings.A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001, with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001, with 7,584 observed and 4,738 expected cases in 2003-2012.The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas

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

    KAUST Repository

    Houborg, Rasmus

    2018-03-19

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

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

    International Nuclear Information System (INIS)

    Nasser, Hassan; Cessac, Bruno; Marre, Olivier

    2013-01-01

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

  13. Understanding the Spatio-Temporal Pattern of Fire Disturbance in the Eastern Mongolia Using Modis Product

    Science.gov (United States)

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-04-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2) The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3) Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4) The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

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

    Science.gov (United States)

    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. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  15. Spatio-Temporal Variability of the Phase of Total Ozone Quasi-Decennial Oscillations

    Science.gov (United States)

    Visheratin, K. N.

    2017-12-01

    The SBUV/SBUV2 (65° S-65° N) and Bodeker Scientific (90° S-90° N) satellite databases have been used for composite and cross-wavelet analyses of the spatio-temporal variability of phase relations between a 11-year cycle of solar activity (SA) and quasi-decennial oscillations (QDOs) of total ozone content (TOC). For globally average TOC values, the QDO maxima coincide in phase with the solar-activity maxima, and amplitude variations of TOC correlate with those of the 11-year solar cycle. According to the analysis of amplitude and phase of QDOs for the zonal average TOC fields, a QDO amplitude is about 6-7 Dobson Units (DU) in the high northern and southern latitudes, and it does not exceed 2-3 DU in the tropic regions. The latitudinal TOC variations are distinguished by a delay of the quasi-decennial oscillation phase in the southern latitudes in comparison with the northern latitudes. The TOC maxima phase coincides with the SA maxima phase in the tropic regions; the TOC variations go ahead of the SA variations, on average, in moderate and high latitudes of the Northern Hemisphere; the TOC variations are behind the SA variations in the Southern Hemisphere. The phase delay between TOC QDO maxima in the northern and southern latitudes appears to increase in the course of time, and the TOC quasi-decennial variations in the Arctic and Antarctic subpolar regions occur approximately in an antiphase over the last two decades.

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

    Directory of Open Access Journals (Sweden)

    Poh-Chin Lai

    2013-11-01

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

  17. Hierarchical Bayesian Spatio Temporal Model Comparison on the Earth Trapped Particle Forecast

    International Nuclear Information System (INIS)

    Suparta, Wayan; Gusrizal

    2014-01-01

    We compared two hierarchical Bayesian spatio temporal (HBST) results, Gaussian process (GP) and autoregressive (AR) models, on the Earth trapped particle forecast. Two models were employed on the South Atlantic Anomaly (SAA) region. Electron of >30 keV (mep0e1) from National Oceanic and Atmospheric Administration (NOAA) 15-18 satellites data was chosen as the particle modeled. We used two weeks data to perform the model fitting on a 5°x5° grid of longitude and latitude, and 31 August 2007 was set as the date of forecast. Three statistical validations were performed on the data, i.e. the root mean square error (RMSE), mean absolute percentage error (MAPE) and bias (BIAS). The statistical analysis showed that GP model performed better than AR with the average of RMSE = 0.38 and 0.63, MAPE = 11.98 and 17.30, and BIAS = 0.32 and 0.24, for GP and AR, respectively. Visual validation on both models with the NOAA map's also confirmed the superior of the GP than the AR. The variance of log flux minimum = 0.09 and 1.09, log flux maximum = 1.15 and 1.35, and in successively represents GP and AR

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  19. Spatio-temporal evolution of apparent resistivity during coal-seam hydraulic flushing

    Science.gov (United States)

    Li, Dexing; Wang, Enyuan; Song, Dazhao; Qiu, Liming; Kong, Xiangguo

    2018-06-01

    Hydraulic flushing in gas predrainage is widely used, but the hydraulic-flushing effect is evaluated in a traditional way, by determining the desorption volume, moisture content, gas drainage rate and other conventional indices. To verify the rationality and feasibility of the multielectrode resistivity method in the evaluation of coal-seam hydraulic flushing and to research the spatio-temporal evolution of apparent resistivity during hydraulic flushing, a field test was conducted in 17# coal seam at Nuodong Mine, Guizhou. During hydraulic flushing, four stages were defined according to the variation in coal rock resistivity with time, namely, the preparation stage, the sharply decreasing stage, the rapidly increasing stage and the steady stage. The apparent resistivity of the coal rock mass is affected mainly by its own degree of fragmentation and flushing volume. A more serious rupture and a greater flushing volume yield a smaller apparent resistivity during the sharply decreasing stage and a higher resistivity during the stable stage. After three months of gas predrainage, the residual gas content and the gas pressure at different points in the expected affected area decrease below the critical value. Changes in the residual gas content and gas pressure at these points are consistent with the apparent resistivity, which validates the rationality and feasibility of the multielectrode resistivity method in evaluating coal-seam hydraulic flushing.

  20. Spatio Temporal Expression Pattern of an Insecticidal Gene (cry2A in Transgenic Cotton Lines

    Directory of Open Access Journals (Sweden)

    Allah BAKHSH

    2012-11-01

    Full Text Available The production of transgenic plants with stable, high-level transgene expression is important for the success of crop improvement programs based on genetic engineering. The present study was conducted to evaluate genomic integration and spatio temporal expression of an insecticidal gene (cry2A in pre-existing transgenic lines of cotton. Genomic integration of cry2A was evaluated using various molecular approaches. The expression levels of cry2A were determined at vegetative and reproductive stages of cotton at regular intervals. These lines showed a stable integration of insecticidal gene in advance lines of transgenic cotton whereas gene expression was found variable with at various growth stages as well as in different plant parts throughout the season. The leaves of transgenic cotton were found to have maximum expression of cry2A gene followed by squares, bolls, anthers and petals. The protein level in fruiting part was less as compared to other parts showing inconsistency in gene expression. It was concluded that for culturing of transgenic crops, strategies should be developed to ensure the foreign genes expression efficient, consistent and in a predictable manner.

  1. Local overfishing may be avoided by examining parameters of a spatio-temporal model.

    Science.gov (United States)

    Carson, Stuart; Shackell, Nancy; Mills Flemming, Joanna

    2017-01-01

    Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time), connectivity (coherence of temporal pattern over space), and spatial variance (variation across the seascape). The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua) in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.

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

    Science.gov (United States)

    Memiş, Abbas; Albayrak, Songül

    2013-12-01

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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

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

    Science.gov (United States)

    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.

  5. Spatio-temporal evaluation of emerging contaminants and their partitioning along a Brazilian watershed.

    Science.gov (United States)

    de Sousa, Diana Nara Ribeiro; Mozeto, Antonio Aparecido; Carneiro, Renato Lajarim; Fadini, Pedro Sergio

    2018-02-01

    The occurrence, partitioning, and spatio-temporal distribution of seven pharmaceuticals for human use, three steroid hormones and one personal care product were determined in surface water, suspended particulate matter (SPM), and sediment of Piraí Creek and Jundiaí River (Jundiaí River Basin, São Paulo, Brazil). The maximum average detected concentrations of the compounds in the Piraí River samples were contaminants most frequently detected in sediment and SPM samples. Triclosan had the highest average proportion of SPM as opposed to in the aqueous phase (> 75%). Contaminants with acid functional groups showed, in general, a lower tendency to bind to particulate matter and sediments. In addition, hydrophobicity had an important effect on their environmental partitioning. The spatial distribution of contaminants along the Jundiaí River was mainly affected by the higher concentration of contaminants in water samples collected downstream from a sewage treatment plant (STP). The results obtained here clearly showed the importance of the analysis of some contaminants in the whole water, meaning both dissolved and particulate compartments in the water, and that the partitioning is ruled by a set of parameters associated to the physicochemical characteristics of contaminants and the matrix properties of the studied, which need be considered in an integrated approach to understand the fate of emerging chemical contaminants in aquatic environments.

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

    Directory of Open Access Journals (Sweden)

    Yi Lu

    2016-11-01

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

  7. Optimal spatio-temporal filter for the reduction of crosstalk in surface electromyogram

    Science.gov (United States)

    Mesin, Luca

    2018-02-01

    Objective. Crosstalk can pose limitations to the applications of surface electromyogram (EMG). Its reduction can help in the identification of the activity of specific muscles. The selectivity of different spatial filters was tested in the literature both in simulations and experiments: their performances are affected by many factors (e.g. anatomy, conduction properties of the tissues and dimension/location of the electrodes); moreover, they reduce crosstalk by decreasing the detection volume, recording data that represent only the activity of a small portion of the muscle of interest. In this study, an alternative idea is proposed, based on a spatio-temporal filter. Approach. An adaptive method is applied, which filters both in time and among different channels, providing a signal that maximally preserves the energy of the EMG of interest and discards that of nearby muscles (increasing the signal to crosstalk ratio, SCR). Main results. Tests with simulations and experimental data show an average increase of the SCR of about 2 dB with respect to the single or double differential data processed by the filter. This allows to reduce the bias induced by crosstalk in conduction velocity and force estimation. Significance. The method can be applied to few channels, so that it is useful in applicative studies (e.g. clinics, gate analysis, rehabilitation protocols with EMG biofeedback and prosthesis control) where limited and not selective information is usually available.

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

    Directory of Open Access Journals (Sweden)

    Yu-Jen Lee

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

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

    Science.gov (United States)

    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.

  10. Spatio-temporal evolution of water-related ecosystem services: Taihu Basin, China

    Directory of Open Access Journals (Sweden)

    Junyu Chen

    2018-06-01

    Full Text Available Water-related ecosystem services (WESs arise from the interaction between water ecosystems and their surrounding terrestrial ecosystems. They are critical for human well-being as well as for the whole ecological circle. An urgent service-oriented reform for the utilization and supervision of WESs can assist in avoiding ecological risks and achieving a more sustainable development in the Taihu Basin, China (THB. Spatially distributed models allow the multiple impacts of land use/land cover conversion and climate variation on WESs to be estimated and visualized efficiently, and such models can form a useful component in the toolbox for integrated water ecosystem management. The Integrated Valuation of Ecosystem Services and Tradeoffs model is used here to evaluate and visualize the spatio-temporal evolution of WESs in the THB from 2000 to 2010. Results indicate that water retention service experienced a decline from 2000 to 2005 with a recovery after 2005, while there was ongoing water scarcity in urban areas. Both the water purification service and the soil retention service underwent a slight decrease over the study period. Nutrients export mainly came from developed land and cultivated land, with the hilly areas in the south of the THB forming the primary area for soil loss. The quantity and distribution of WESs were impacted significantly by the shrinkage of cultivated land and the expansion of developed land. These findings will lay a foundation for a service-oriented management of WESs in the THB and support evidence-based decision making.

  11. Spatio-Temporal Variability of Urban Heat Island and Urban Mobility

    Science.gov (United States)

    Kar, B.; Omitaomu, O.

    2017-12-01

    A 2016 report by the U.S. Census stated that while the rural areas cover 97% of the U.S. landmass, these areas house only 19.7% of the nation's population. Given that the U.S. coastal counties are home to more than 50% of the U.S. population, these urban areas are clustered along the coast that is susceptible to sea level rise induced impacts. In light of increasing climate variability and extreme events, it is pertinent to understand the Urban Heat Island (UHI) effect that results from increasing population density and mobility in the urban areas, and that contributes to increased energy consumption and temperature as well as unmitigated flooding events. For example, in Illinois, warmer summers contribute to heavy precipitation that overwhelms the region's drainage capacity. This study focuses on understanding the spatio-temporal variability of the relationship between population density and mobility distribution, and creation of UHI due to temperature change in selected cities across the U.S. This knowledge will help us understand the role of UHI in energy-water nexus in urban areas, specifically, energy consumption.

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

    Science.gov (United States)

    Cybulski, Paweł

    2014-12-01

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

  13. Spatio-temporal variance and meteorological drivers of the urban heat island in a European city

    Science.gov (United States)

    Arnds, Daniela; Böhner, Jürgen; Bechtel, Benjamin

    2017-04-01

    Urban areas are especially vulnerable to high temperatures, which will intensify in the future due to climate change. Therefore, both good knowledge about the local urban climate as well as simple and robust methods for its projection are needed. This study has analysed the spatio-temporal variance of the mean nocturnal urban heat island (UHI) of Hamburg, with observations from 40 stations from different suppliers. The UHI showed a radial gradient with about 2 K in the centre mostly corresponding to the urban densities. Temporarily, it has a strong seasonal cycle with the highest values between April and September and an inter-annual variability of approximately 0.5 K. Further, synoptic meteorological drivers of the UHI were analysed, which generally is most pronounced under calm and cloud-free conditions. Considered were meteorological parameters such as relative humidity, wind speed, cloud cover and objective weather types. For the stations with the highest UHI intensities, up to 68.7 % of the variance could be explained by seasonal empirical models and even up to 76.6 % by monthly models.

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

    Directory of Open Access Journals (Sweden)

    Euro Beinat

    2012-11-01

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

  15. Bayesian spatio-temporal discard model in a demersal trawl fishery

    Science.gov (United States)

    Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.

    2014-07-01

    Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.

  16. A data science approach for quantifying spatio-temporal effects to graft failures in organ transplantation.

    Science.gov (United States)

    Pinheiro, Diego; Hamad, Farag; Cadeiras, Martin; Menezes, Ronaldo; Nezamoddini-Kachouie, Nezamoddin

    2016-08-01

    The transplantation of solid organs is one of the most important accomplishments of modern medicine. Yet, organ shortage is a major public health issue; 8,000 people died while waiting for an organ in 2014. Meanwhile, the allocation system currently implemented can lead to organs being discarded and the medical community still investigates factors that affects early graft failure such as distance and ischemic time. In this paper, we investigate early graft failure under a spatio-temporal perspective using a data science unified approach for all six organs that is based on complementary cumulative analysis of both distance and ischemic time. Interestingly, although distance seems to highly affect some organs (e.g. liver), it appears to have no effect on others (e.g. kidney). Similarly, the results on ischemic time confirm it affects early graft failure with higher influence for some organs such as (e.g. heart) and lower influence for others such as (e.g. kidney). This poses the question whether the allocation policies should be individually designed for each organ in order to account for their particularities as shown in this work.

  17. Spatio-temporal coherence of dengue, chikungunya and Zika outbreaks in Merida, Mexico.

    Directory of Open Access Journals (Sweden)

    Donal Bisanzio

    2018-03-01

    Full Text Available Response to Zika virus (ZIKV invasion in Brazil lagged a year from its estimated February 2014 introduction, and was triggered by the occurrence of severe congenital malformations. Dengue (DENV and chikungunya (CHIKV invasions tend to show similar response lags. We analyzed geo-coded symptomatic case reports from the city of Merida, Mexico, with the goal of assessing the utility of historical DENV data to infer CHIKV and ZIKV introduction and propagation. About 42% of the 40,028 DENV cases reported during 2008-2015 clustered in 27% of the city, and these clustering areas were where the first CHIKV and ZIKV cases were reported in 2015 and 2016, respectively. Furthermore, the three viruses had significant agreement in their spatio-temporal distribution (Kendall W>0.63; p<0.01. Longitudinal DENV data generated patterns indicative of the resulting introduction and transmission patterns of CHIKV and ZIKV, leading to important insights for the surveillance and targeted control to emerging Aedes-borne viruses.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  20. Spatio-temporal Analysis of suspended sediment Concentration in the Yongjiang Estuary Based on GOCI

    Science.gov (United States)

    Kang, Yanyan; Dong, Chuan

    2018-01-01

    The concentration and spatio-temporal variation of suspended sediment concentration in the estuary area are of great significance to the nearshore engineering, port construction and coastal evolution. Based on multi-period GOCI images and corresponding measured suspended sediment concentration (SSC) data, three inversion models (the linear regression model, the power exponent model and the neural network model) were established after rapid atmospheric correction. The results show that the absolute error of the three models is 0.20, 0.16 and 0.10kg/m3 respectively, and the relative errors are 38%, 23% and 18% respectively. The accuracy of the neural network (8-17-17-1) is the best. The SSC distribution diagrams in an ebb and flow cycle are obtained using this ANN model. The results show that with Yongjiang estuary for segmentation, the high concentration area is located in the north and the lower is in the south around Jintang Island deeper water area. When the tide rises, the water flow disturbs a large amount of sediment, and then the sediment concentration increases and high area high concentrations water body moves along the SE-NW. When the tide falls, flow rate decreases and the sediment concentration decreases. However, with the falling tide, the concentration of suspended sediment in the northern sea areas gradually increases, and is higher than 1kg/m3, and gradually moves along the NW-SE until to the estuary.

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

    Directory of Open Access Journals (Sweden)

    Stefanie Keller

    Full Text Available 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Riecke, H.

    1994-05-01

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

  3. Local overfishing may be avoided by examining parameters of a spatio-temporal model.

    Directory of Open Access Journals (Sweden)

    Stuart Carson

    Full Text Available Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time, connectivity (coherence of temporal pattern over space, and spatial variance (variation across the seascape. The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.

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

    Directory of Open Access Journals (Sweden)

    Francisco J. Escobedo

    2016-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-12-15

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

  6. Spatio-temporal cerebral blood flow perfusion patterns in cortical spreading depression

    Science.gov (United States)

    Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

    2017-04-01

    Cortical spreading depression (CSD) is an example of one of the most common abnormalities in biophysical brain functioning. Despite the fact that there are many mathematical models describing the cortical spreading depression (CSD), most of them do not take into consideration the role of redistribution of cerebral blood flow (CBF), that results in the formation of spatio-temporal patterns. The paper presents a mathematical model, which successfully explains the CBD role in the CSD process. Numerical study of this model has revealed the formation of stationary dissipative structures, visually analogous to Turing structures. However, the mechanism of their formation is not diffusion. We show these structures occur due to another type of spatial coupling, that is related to tissue perfusion rate. The proposed model predicts that at similar state of neurons the distribution of blood flow and oxygenation may by different. Currently, this effect is not taken into account when the Blood oxygen-level dependent (BOLD) contrast imaging used in functional magnetic resonance imaging (fMRI). Thus, the diagnosis on the BOLD signal can be ambiguous. We believe that our results can be used in the future for a more correct interpretation of the data obtained with fMRI, NIRS and other similar methods for research of the brain activity.

  7. Spatio-temporal expression patterns of Wnt signaling pathway during the development of temporomandibular condylar cartilage.

    Science.gov (United States)

    Chen, Kan; Quan, Huixin; Chen, Gang; Xiao, Di

    2017-11-01

    There is a growing body of evidence supporting the involvement of the Wnt signaling pathway in various aspects of skeletal and joint development; however, it is unclear whether it is involved in the process of temporomandibular joint development. In order to clarify this issue, we examined the spatio-temporal distribution of mRNAs and proteins of the Wnt family during the formation of the mandibular condylar cartilage at the prenatal and postnatal stages. An in situ hybridization test revealed no mRNAs of β-catenin and Axin2 during early mesenchymal condensation; the ligands surveyed in this study (including Wnt-4, 5a, and 9a) were clearly detected at various ranges of expression, mainly in the condylar blastema and later distinct cartilaginous layers. Apart from β-catenin and Axin2, the Wnt family members surveyed in this study, including Lef-1, were found to be immunopositive during early chondrogenesis in the condylar cartilage at E14.5. After distinct chondrocyte layers were identified within the cartilage at E16.5, the expression of the Wnt signaling members was different and mainly restricted to proliferating cells and mineralized hypertrophic chondrocytes. In the adult mandibular condylar cartilage, the Wnt-4 mRNA, as well as the Wnt-4 and Wnt-9a proteins, was not observed. Our findings demonstrated that the Wnt signaling pathway was associated with the development of mandibular condylar cartilage. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    Directory of Open Access Journals (Sweden)

    Wurihan

    2018-04-01

    Full Text Available Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1 The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2 The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3 Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4 The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

  9. Management of Uncertainty and Spatio-Temporal Aspects for Monitoring and Diagnosis in a Smart Home

    Directory of Open Access Journals (Sweden)

    Juan Carlos Augusto

    2008-12-01

    Full Text Available The health system in developed countries is facing a problem of scalability in order to accommodate the increased proportion of the elderly population. Scarce resources cannot be sustained unless innovative technology is considered to provide health care in a more effective way. The Smart Home provides pre- ventive and assistive technology to vulnerable sectors of the population. Much research and development has been focused on the technological side (e.g., sensors and networks but less effort has been invested in the capability of the Smart Home to intelligently monitor situations of interest and act in the best in- terest of the occupants. In this article we model a Smart Home scenario, using knowledge in the form of Event-Condition-Action rules together with a new inference scheme which incorporates spatio-temporal reasoning and uncertainty. A reasoning system called RIMER, has been extended to permit the monitoring of situations according to the place where they occur and the specific order and duration of the activities. The system allows for the specification of uncertainty both in terms of knowledge representation and credibility of the conclusions that can be achieved in terms of the evidence available.

  10. ANALISIS KETERKAITAN PERUBAHAN LAHAN PERTANIAN TERHADAP KETAHANAN PANGAN KABUPATEN MAGELANG BERBASIS MODEL SPATIO TEMPORAL SIG

    Directory of Open Access Journals (Sweden)

    Rifki Destianto

    2014-04-01

    Full Text Available As mandated by the 1945 Constitution of the Republic of Indonesia, agricultural land is part of the earth as a gift from God that is controlled by the state and utilized for the prosperity and welfare of the people. The agricultural land can provide great benefits in terms of economic, social, and environmental benefits. Land use conversion from agricultural to non-agricultural use can cause productivity decrease in agriculture, so it triggers a hypothesis that the decrease of agricultural land will negatively affect food security. Based on the problem, the research is conducted to assess the relationship between conversion in agricultural land use with food security using a case study of Magelang Regency (Kabupaten in the 2009-11 period. The methods used are spatio-temporal GIS, quantitative analysis, and field calibration. The results have shown that the agricultural land area has decreased (6.31% but the food security has not declined. It is because the food sources for Magelang Regency come from several adjacent areas. It can then be concluded that the reduction of agricultural land does not significantly affect the food security status of the study area. However, in the long run the decrease of the agricultural land will affect national food security. So, to maintain food security, agricultural land use control is necessary to prevent the unnecessary conversion of agricultural land.

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

    Science.gov (United States)

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

    2016-09-01

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

  12. Compressing an Ensemble with Statistical Models: An Algorithm for Global 3D Spatio-Temporal Temperature

    KAUST Repository

    Castruccio, Stefano

    2015-04-02

    One of the main challenges when working with modern climate model ensembles is the increasingly larger size of the data produced, and the consequent difficulty in storing large amounts of spatio-temporally resolved information. Many compression algorithms can be used to mitigate this problem, but since they are designed to compress generic scientific data sets, they do not account for the nature of climate model output and they compress only individual simulations. In this work, we propose a different, statistics-based approach that explicitly accounts for the space-time dependence of the data for annual global three-dimensional temperature fields in an initial condition ensemble. The set of estimated parameters is small (compared to the data size) and can be regarded as a summary of the essential structure of the ensemble output; therefore, it can be used to instantaneously reproduce the temperature fields in an ensemble with a substantial saving in storage and time. The statistical model exploits the gridded geometry of the data and parallelization across processors. It is therefore computationally convenient and allows to fit a non-trivial model to a data set of one billion data points with a covariance matrix comprising of 10^18 entries.

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

    Science.gov (United States)

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

    2018-02-01

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

  14. Compressing an Ensemble with Statistical Models: An Algorithm for Global 3D Spatio-Temporal Temperature

    KAUST Repository

    Castruccio, Stefano; Genton, Marc G.

    2015-01-01

    One of the main challenges when working with modern climate model ensembles is the increasingly larger size of the data produced, and the consequent difficulty in storing large amounts of spatio-temporally resolved information. Many compression algorithms can be used to mitigate this problem, but since they are designed to compress generic scientific data sets, they do not account for the nature of climate model output and they compress only individual simulations. In this work, we propose a different, statistics-based approach that explicitly accounts for the space-time dependence of the data for annual global three-dimensional temperature fields in an initial condition ensemble. The set of estimated parameters is small (compared to the data size) and can be regarded as a summary of the essential structure of the ensemble output; therefore, it can be used to instantaneously reproduce the temperature fields in an ensemble with a substantial saving in storage and time. The statistical model exploits the gridded geometry of the data and parallelization across processors. It is therefore computationally convenient and allows to fit a non-trivial model to a data set of one billion data points with a covariance matrix comprising of 10^18 entries.

  15. Ecological Pressure of Carbon Footprint in Passenger Transport: Spatio-Temporal Changes and Regional Disparities

    Directory of Open Access Journals (Sweden)

    Fei Ma

    2018-01-01

    Full Text Available Passenger transport has become a significant producer of carbon emissions in China, thus strongly contributing to climate change. In this paper, we first propose a model of ecological pressure of the carbon footprint in passenger transport (EPcfpt. In the model, the EPcfpt values of all the provinces and autonomous regions of China are calculated and analyzed during the period of 2006–2015. For the outlier EPcfpt values of Beijing, Shanghai and Tianjin, the research areas are classified into two scenarios: the first scenario (all the provinces and autonomous regions and the second scenario (not including Beijing, Shanghai and Tianjin. The global spatial autocorrelation analysis of the first scenario shows that the EPcfpt might be randomly distributed, while it shows positive spatial autocorrelation in the second scenario. Furthermore, we carry out the local spatial autocorrelation analysis of the second scenario, and find that the low aggregation areas are the most common type and are mainly located in the west of China. Then the disparities in EPcfpt between China’s Eight Comprehensive Economic Zones are further analyzed. Finally, we put forward a number of policy recommendations in relation to the spatio-temporal changes and the regional disparities of EPcfpt in China. This study provides related references for proposing effective policy measures to reduce the ecological pressure of carbon emissions from the passenger transport sector.

  16. Building, Sharing and Exploiting Spatio-Temporal Aggregates in Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Dorsaf Zekri

    2014-01-01

    Full Text Available This article focuses on data aggregation in vehicular ad hoc networks (VANETs. In such networks, data produced by sensors or crowdsourcers are exchanged between vehicles in order to warn or inform drivers when an event occurs (e.g., an accident, a traffic congestion, a parking space released, a vehicle with non-functioning brake lights, etc.. In the following, we propose to generate spatio-temporal aggregates containing these data in order to keep a summary of past events. We therefore use Flajolet-Martin sketches. Our goal is then to exploit these aggregates to better assist the drivers. These aggregates may indeed produce additional knowledge that may be useful when no event has been recently transmitted by surrounding vehicles or when some knowledge about the global demand may improve the decision that need to be taken at the vehicle level. To prove the effectiveness of our approach, an extensive experimental evaluation has been performed considering vehicles looking for an available parking space, that proves the interest of our proposal. The experimentations indeed show that the use of our aggregation structure significantly reduces the time needed to actually find a parking space. It also increases the percentage of vehicles finding such a resource in a bounded time in congested situations.

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

    Science.gov (United States)

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

    2009-04-01

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

  18. X-ray fluoroscopy spatio-temporal filtering with object detection

    International Nuclear Information System (INIS)

    Aufrichtig, R.; Wilson, D.L.; University Hospitals of Cleveland, OH

    1995-01-01

    One potential way to reduce patient and staff x-ray fluoroscopy dose is to reduce the quantum exposure to the detector and compensate the additional noise with digital filtering. A new filtering method, spatio-temporal filtering with object detection, is described that reduces noise while minimizing motion and spatial blur. As compared to some conventional motion-detection filtering schemes, this object-detection method incorporates additional a priori knowledge of image content; i.e. much of the motion occurs in isolated long thin objects (catheters, guide wires, etc.). The authors create object-likelihood images and use these to control spatial and recursive temporal filtering such as to reduce blurring the objects of interest. They use automatically computed receiver operating characteristic (ROC) curves to optimize the object-likelihood enhancement method and determine that oriented matched filter kernels with 4 orientations are appropriate. The matched filter kernels are simple projected cylinders. The authors demonstrate the method on several representative x-ray fluoroscopy sequences to which noise is added to simulate very low dose acquisitions. With processing, they find that noise variance is significantly reduced with slightly less noise reduction near moving objects. They estimate an effective exposure reduction greater than 80%

  19. Economic Development And Transfrontier Shipments Of Waste In Poland – Spatio-Temporal Analysis

    Directory of Open Access Journals (Sweden)

    Antczak Elżbieta

    2014-12-01

    Full Text Available The aim of the paper is to apply the spatio-temporal Environmental Kuznets Curve (SpEKC to test the relationship between economic growth and the amount of collected mixed municipal waste. The analysis was conducted at the level of sixty-six Polish sub-regions. The study contained selected environmental indicators. The dependent variable - the amount of municipal waste generated in kilograms per capita characterized the state of the environment. The GDP per capita in constant prices (as an explanatory variable presented the level of economic development of the sub-regions. In the empirical part of the research there were used spatial panel data models based on EKCs. It determined the levels of economic development, at which the amount of produced wastes has fallen or increased, depending on the wealth of the region. The application of different types of spatial weight matrices was an important element of this modelling. Data obtained the years 2005-2012. Models were estimated in the RCran package.

  20. Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

    Science.gov (United States)

    Matsubara, Takashi

    2017-01-01

    Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

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

    Directory of Open Access Journals (Sweden)

    Patrick Fried

    2016-09-01

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

  2. Spatio-temporal Analysis of the Genetic Diversity of Arctic Rabies Viruses and Their Reservoir Hosts in Greenland

    DEFF Research Database (Denmark)

    Hanke, Dennis; Freuling, Conrad M.; Fischer, Susanne

    2016-01-01

    There has been limited knowledge on spatio-temporal epidemiology of zoonotic arctic fox rabies among countries bordering the Arctic, in particular Greenland. Previous molecular epidemiological studies have suggested the occurrence of one particular arctic rabies virus (RABV) lineage (arctic-3...... of RABV in different arctic fox lineages. These data are invaluable to support future initiatives for arctic fox rabies control and elimination in Greenland....

  3. Spatio-Temporal Analysis of Urban Crime Pattern and its Implication for Abuja Municipal Area Council, Nigeria

    OpenAIRE

    Taiye Oluwafemi Adewuyi; Patrick Ali Eneji; Anthonia Silas Baduku; Emmanuel Ajayi Olofin

    2017-01-01

    This study examined the spatio-temporal analysis of urban crime pattern and its implication for Abuja Municipal Area Council of the Federal Capital Territory of Nigeria; it has the aim of using Geographical Information System to improve criminal justice system. The aim was achieved by establishing crime incident spots, types of crime committed, the time it occurred and factors responsible for prevailing crime. The methods for data collection involved Geoinformatics through the use of remote s...

  4. Spatio-temporal variations in biochemical composition, condition index and percentage edibility of the clam, Paphia malabarica (Chemnitz) from estuarine regions of Goa

    Digital Repository Service at National Institute of Oceanography (India)

    Nagvenkar, S.S.; Jagtap, T.G.

    and ambient environmental parameters were also established. Significant (P <0.001) spatio-temporal changes in biochemical composition, CI and PE were noticed. Protein content was higher (15.64-86.79%) round the year, followed by carbohydrate (4...

  5. Normalization Strategies for Enhancing Spatio-Temporal Analysis of Social Media Responses during Extreme Events: A Case Study based on Analysis of Four Extreme Events using Socio-Environmental Data Explorer (SEDE)

    Science.gov (United States)

    Ajayakumar, J.; Shook, E.; Turner, V. K.

    2017-10-01

    With social media becoming increasingly location-based, there has been a greater push from researchers across various domains including social science, public health, and disaster management, to tap in the spatial, temporal, and textual data available from these sources to analyze public response during extreme events such as an epidemic outbreak or a natural disaster. Studies based on demographics and other socio-economic factors suggests that social media data could be highly skewed based on the variations of population density with respect to place. To capture the spatio-temporal variations in public response during extreme events we have developed the Socio-Environmental Data Explorer (SEDE). SEDE collects and integrates social media, news and environmental data to support exploration and assessment of public response to extreme events. For this study, using SEDE, we conduct spatio-temporal social media response analysis on four major extreme events in the United States including the "North American storm complex" in December 2015, the "snowstorm Jonas" in January 2016, the "West Virginia floods" in June 2016, and the "Hurricane Matthew" in October 2016. Analysis is conducted on geo-tagged social media data from Twitter and warnings from the storm events database provided by National Centers For Environmental Information (NCEI) for analysis. Results demonstrate that, to support complex social media analyses, spatial and population-based normalization and filtering is necessary. The implications of these results suggests that, while developing software solutions to support analysis of non-conventional data sources such as social media, it is quintessential to identify the inherent biases associated with the data sources, and adapt techniques and enhance capabilities to mitigate the bias. The normalization strategies that we have developed and incorporated to SEDE will be helpful in reducing the population bias associated with social media data and will be useful

  6. Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

    Science.gov (United States)

    Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

    2015-10-20

    It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

  7. User requirements for geo-collaborative work with spatio-temporal data in a web-based virtual globe environment.

    Science.gov (United States)

    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. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  8. Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

    Directory of Open Access Journals (Sweden)

    Qing Gu

    2015-10-01

    Full Text Available It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes. According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

  9. Spatio-temporal variability of ichthyophagous bird assemblage around western Mediterranean open-sea cage fish farms.

    Science.gov (United States)

    Aguado-Giménez, Felipe; Eguía-Martínez, Sergio; Cerezo-Valverde, Jesús; García-García, Benjamín

    2018-06-14

    Ichthyophagous birds aggregate at cage fish farms attracted by caged and associated wild fish. Spatio-temporal variability of such birds was studied for a year through seasonal visual counts at eight farms in the western Mediterranean. Correlation with farm and location descriptors was assessed. Considerable spatio-temporal variability in fish-eating bird density and assemblage structure was observed among farms and seasons. Bird density increased from autumn to winter, with the great cormorant being the most abundant species, also accounting largely for differences among farms. Grey heron and little egret were also numerous at certain farms during the coldest seasons. Cattle egret was only observed at one farm. No shags were observed during winter. During spring and summer, bird density decreased markedly and only shags and little egrets were observed at only a few farms. Season and distance from farms to bird breeding/wintering grounds helped to explain some of the spatio-temporal variability. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Spatio-Temporal Multiway Data Decomposition Using Principal Tensor Analysis on k-Modes: The R Package PTAk

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    Didier G. Leibovici

    2010-10-01

    Full Text Available The purpose of this paper is to describe the R package {PTAk and how the spatio-temporal context can be taken into account in the analyses. Essentially PTAk( is a multiway multidimensional method to decompose a multi-entries data-array, seen mathematically as a tensor of any order. This PTAk-modes method proposes a way of generalizing SVD (singular value decomposition, as well as some other well known methods included in the R package, such as PARAFAC or CANDECOMP and the PCAn-modes or Tucker-n model. The example datasets cover different domains with various spatio-temporal characteristics and issues: (i~medical imaging in neuropsychology with a functional MRI (magnetic resonance imaging study, (ii~pharmaceutical research with a pharmacodynamic study with EEG (electro-encephaloegraphic data for a central nervous system (CNS drug, and (iii~geographical information system (GIS with a climatic dataset that characterizes arid and semi-arid variations. All the methods implemented in the R package PTAk also support non-identity metrics, as well as penalizations during the optimization process. As a result of these flexibilities, together with pre-processing facilities, PTAk constitutes a framework for devising extensions of multidimensional methods such ascorrespondence analysis, discriminant analysis, and multidimensional scaling, also enabling spatio-temporal constraints.

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

    Science.gov (United States)

    Zuluaga-Arias, Manuel D.

    2011-12-01

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

  12. A Spatio-Temporal Analysis of Heatwave Climatology in Three Major US Cities

    Science.gov (United States)

    Hulley, G. C.; Malakar, N.

    2016-12-01

    Heatwaves are one form of severe weather expected to become worse under a warming planet. The impacts of severe heatwaves, particularly in urban areas, can have detrimental and often deadly consequences across key socio-economic urban sectors.These effects are exacerbated by the urban heat island effect, and an overall increase in the number of city dwellers during the 21st century. For example it is projected that nearly 80% of the world's population will live in cities by 2025. In this study we use a combination of in situ and remote sensing measured surface temperatures to investigate the spatio-temporal variations of heatwaves in three major U.S. cities; Los Angeles, Chicago, and Washington D.C. Air temperature data from the NCDC US COOP network stations are used to first detect severe heatwave events using two new excess heat indices, and secondly to assess climatological changes in heatwave frequency, duration, and intensity since the 1950's. For example, in Los Angeles there has been a steady increase in the duration and frequency of heatwaves, while nighttime heatwave temperatures have shown a rapid warming since the start of the 21st century. The second part of the study uses a new land surface temperature product (MOD21) derived from the MODIS Aqua sensor to analyze the spatial variations of heatwave temperatures within urban environments, as a goal to help better understand and predict what areas may be more vulnerable to the effects of extreme temperatures in an effort to advise local councils on effective adaption and mitigation techniques.

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

    Directory of Open Access Journals (Sweden)

    Ansa W Fiaz

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

  14. Spatio-Temporal Characteristics of Rural Economic Development in Eastern Coastal China

    Directory of Open Access Journals (Sweden)

    Guogang Wang

    2015-01-01

    Full Text Available Although the regional differences of rural economic development can be easily determined, a challenging problem for research studies regarding rural economic development has been the inter-relatedness between different areas, and this challenge has been noted remarkably little in research data to date. As an empirical investigation, this study analyzes the spatio-temporal characteristics of rural economic development from a period beginning in 1978 to the year 2012, in the eastern coastal region of China. In order to determine the special differentiation characteristics of rural economic development, three indexes, namely the Gini coefficient (G, Tsui–Wang index (TW and Theil index (T, were employed. To explore the inter-relatedness among the different areas, we selected a spatial autocorrelation model. The results indicated that, to a large extent, rural economic development from 1978 to 2012 in the eastern coastal region of China was greatly influenced, and the per capita annual net income changed significantly, due to the process of rapid urbanization and industrialization. Generally speaking, the annual net income constantly increased, from 87.7 USD in 1978 to 1628.1 USD in 2012. However, the calculation results indicated that the per capita income gap in the same province decreased, while the gap between the provinces presented an aggregate trend. The regional polarization widened continuously. It was also found that the spatial positive autocorrelation for the regional economy was significant, with a waving and ascending trend, and the neighbor effect of regional economic growth was continuously strengthened. Qualitative analysis of the driving mechanism was applied, and it was determined that there are three primary factors affecting the development of the rural regions, namely resource endowments, economic location and policies.

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

    International Nuclear Information System (INIS)

    Prinja, Anil K.

    2015-01-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

  17. Analysis of Correlation Tendency between Wind and Solar from Various Spatio-temporal Perspectives

    Science.gov (United States)

    Wang, X.; Weihua, X.; Mei, Y.

    2017-12-01

    Analysis of correlation between wind resources and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by the fossil energy. In this paper, we discuss the correlation between wind and solar from various spatio-temporal perspectives (from east to west, in terms of plain, plateau, hill, and mountain, from hourly to daily, ten days and monthly) with observed data and modeled data from NOAA (National Oceanic and Atmospheric Administration) and NERL (National Renewable Energy Laboratory). With investigation of wind speed time series and solar radiation time series (period: 10 years, resolution: 1h) of 72 stations located in various landform and distributed dispersedly in USA, the results show that the correlation coefficient, Kendall's rank correlation coefficient, changes negative to positive value from east coast to west coast of USA, and this phenomena become more obvious when the time scale of resolution increases from daily to ten days and monthly. Furthermore, considering the differences of landforms which influence the local meteorology the Kendall coefficients of diverse topographies are compared and it is found that the coefficients descend from mountain to hill, plateau and plain. However, no such evident tendencies could be found in daily scale. According to this research, it is proposed that the complementary feature of wind resources and solar resources in the east or in the mountain area of USA is conspicuous. Subsequent study would try to further verify this analysis by investigating the operation status of wind power station and solar power station.

  18. Spatio-temporal changes in biomass carbon sinks in China's forests from 1977 to 2008.

    Science.gov (United States)

    Guo, Zhaodi; Hu, Huifeng; Li, Pin; Li, Nuyun; Fang, Jingyun

    2013-07-01

    Forests play a leading role in regional and global carbon (C) cycles. Detailed assessment of the temporal and spatial changes in C sinks/sources of China's forests is critical to the estimation of the national C budget and can help to constitute sustainable forest management policies for climate change. In this study, we explored the spatio-temporal changes in forest biomass C stocks in China between 1977 and 2008, using six periods of the national forest inventory data. According to the definition of the forest inventory, China's forest was categorized into three groups: forest stand, economic forest, and bamboo forest. We estimated forest biomass C stocks for each inventory period by using continuous biomass expansion factor (BEF) method for forest stands, and the mean biomass density method for economic and bamboo forests. As a result, China's forests have accumulated biomass C (i.e., biomass C sink) of 1896 Tg (1 Tg=10(12) g) during the study period, with 1710, 108 and 78 Tg C in forest stands, and economic and bamboo forests, respectively. Annual forest biomass C sink was 70.2 Tg C a(-1), offsetting 7.8% of the contemporary fossil CO2 emissions in the country. The results also showed that planted forests have functioned as a persistent C sink, sequestrating 818 Tg C and accounting for 47.8% of total C sink in forest stands, and that the old-, mid- and young-aged forests have sequestrated 930, 391 and 388 Tg C from 1977 to 2008. Our results suggest that China's forests have a big potential as biomass C sink in the future because of its large area of planted forests with young-aged growth and low C density.

  19. Associations of dragonflies (Odonata) to habitat variables within the Maltese Islands: a spatio-temporal approach.

    Science.gov (United States)

    Balzan, Mario V

    2012-01-01

    Relatively little information is available on environmental associations and the conservation of Odonata in the Maltese Islands. Aquatic habitats are normally spatio-temporally restricted, often located within predominantly rural landscapes, and are thereby susceptible to farmland water management practices, which may create additional pressure on water resources. This study investigates how odonate assemblage structure and diversity are associated with habitat variables of local breeding habitats and the surrounding agricultural landscapes. Standardized survey methodology for adult Odonata involved periodical counts over selected water-bodies (valley systems, semi-natural ponds, constructed agricultural reservoirs). Habitat variables relating to the type of water body, the floristic and physiognomic characteristics of vegetation, and the composition of the surrounding landscape, were studied and analyzed through a multivariate approach. Overall, odonate diversity was associated with a range of factors across multiple spatial scales, and was found to vary with time. Lentic water-bodies are probably of high conservation value, given that larval stages were mainly associated with this habitat category, and that all species were recorded in the adult stage in this habitat type. Comparatively, lentic and lotic seminatural waterbodies were more diverse than agricultural reservoirs and brackish habitats. Overall, different odonate groups were associated with different vegetation life-forms and height categories. The presence of the great reed, Arundo donax L., an invasive alien species that forms dense stands along several water-bodies within the Islands, seems to influence the abundance and/or occurrence of a number of species. At the landscape scale, roads and other ecologically disturbed ground, surface water-bodies, and landscape diversity were associated with particular components of the odonate assemblages. Findings from this study have several implications for the

  20. Spatio-temporal seasonal drought patterns in Europe from 1950 to 2015

    Science.gov (United States)

    Spinoni, Jonathan; Naumann, Gustavo; Vogt, Jürgen

    2016-04-01

    Drought is one of the natural disasters with severe impacts in Europe, not only in areas which frequently experience water scarcity such as the Mediterranean, but also in temperate or continental climates such as Central and Eastern Europe and even in cold regions such as Scandinavia and Iceland. In this study the spatio-temporal patterns of seasonal meteorological droughts in Europe between 1950 and 2015 are investigated using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). Since the focus is on the analysis of seasonal drought trends, indicators were calculated for 3 monthly accumulation periods. The input variables of precipitation and temperature were derived from E-OBS grids (v11-v12) at a spatial resolution of 0.25°x0.25°. Seasonal trends of drought frequency and severity were analyzed for moderate (SPI or SPEI 2.0) events during the periods 1950-2015 and 1981-2015. For the moderate events, results of the SPI analysis (precipitation driven) demonstrate a significant tendency towards less frequent and severe droughts in Northern Europe and Russia, especially in winter and spring; oppositely, an increasing trend is visible in Southern Europe, mainly in spring and summer. According to the SPEI analysis (precipitation and temperature driven) Northern Europe shows wetting patterns, while Southern and Eastern Europe show a more remarkable drying tendency, especially in summer and autumn for drought frequency and in every season for drought severity. The evolution towards drier conditions is more relevant from 1981 onwards, both in terms of frequency and severity. This is especially true for Central Europe in spring, for the Mediterranean in summer, and for Eastern Europe in autumn. Extreme events follow similar patterns, but in autumn no spatially coherent trend can be found.

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

    Directory of Open Access Journals (Sweden)

    Yali Si

    2009-11-01

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

  2. Spatio-Temporal Variation and Monsoon Effect on the Temperature Lapse Rate of a Subtropical Island

    Directory of Open Access Journals (Sweden)

    Ching-An Chiu

    2014-01-01

    Full Text Available Temperature lapse rate (TLR has been widely used in the prediction of mountain climate and vegetation and in many ecological models. The aims of this paper are to explore the spatio-temporal variations and monsoon effects on the TLR in the subtropical island of Taiwan with its steep Central Mountain Region (CMR. A TLR analysis using the 32-year monthly mean air temperatures and elevations from 219 weather stations (sea level to 3852 m a.s.l. was performed based on different geographical regions and monsoon exposures. The results revealed that the average TLR for all of Taiwan is -5.17°C km-1, with a general tendency to be steeper in summer and shallower in winter. The results are also shallower than the typical or global average TLR of -6.5°C km-1. During the prevailing northeast monsoon season (winter, the TLR exhibits a contrast between the windward side (steeper, -5.97°C km-1 and the leeward side (shallower, -4.51°C km-1. From the diagnosis on spatial characteristics of monthly cloud amount and vertical atmospheric profiles, this contrasting phenomenon may be explained by the warming effect of onshore stratus clouds (500 - 2500 m depth on cold and dry Siberian monsoon air on the windward side of the CMR. On the southwestern leeward side of the CMR, the low-level (1500 m, the weak ventilation atmosphere and temperature inversion make the TLR shallower than on the windward side.

  3. Spatio-temporal distribution patterns of the epibenthic community in the coastal waters of Suriname

    Science.gov (United States)

    Willems, Tomas; De Backer, Annelies; Wan Tong You, Kenneth; Vincx, Magda; Hostens, Kris

    2015-10-01

    This study aimed to characterize the spatio-temporal patterns of the epibenthic community in the coastal waters of Suriname. Data were collected on a (bi)monthly basis in 2012-2013 at 15 locations in the shallow (turbid-water zone (6-20 m depth), dominated by Atlantic seabob shrimp Xiphopenaeus kroyeri (Crustacea: Penaeoidea). Near the 30 m isobath, sediments were much coarser (median grain size on average 345±103 μm vs. 128±53 μm in the coastal assemblage) and water transparency was much higher (on average 7.6±3.5 m vs. 2.4±2.1 m in the coastal assemblage). In this zone, a diverse offshore assemblage was found, characterized by brittle stars (mainly Ophioderma brevispina and Ophiolepis elegans) and a variety of crabs, sea stars and hermit crabs. In between both zones, a transition assemblage was noted, with epibenthic species typically found in either the coastal or offshore assemblages, but mainly characterized by the absence of X. kroyeri. Although the epibenthic community was primarily structured in an on-offshore gradient related to depth, sediment grain size and sediment total organic carbon content, a longitudinal (west-east) gradient was apparent as well. The zones in the eastern part of the Suriname coastal shelf seemed to be more widely stretched along the on-offshore gradient. Although clear seasonal differences were noted in the environmental characteristics (e.g. dry vs. rainy season), this was not reflected in the epibenthic community structure. X. kroyeri reached very high densities (up to 1383 ind 1000 m-²) in the shallow coastal waters of Suriname. As X. kroyeri is increasingly exploited throughout its range, the current study provides the ecological context for its presence and abundance, which is crucial for an ecosystem approach and the sustainable management of this commercially important species and its habitat.

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

    Science.gov (United States)

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

    2017-06-01

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

  5. Spatio-temporal radiation biology with conventionally or laser-accelerated particles for ELIMED

    International Nuclear Information System (INIS)

    Ristić-Fira, A.; Bulat, T.; Keta, O.; Petrović, I.; Romano, F.; Cirrone, P.; Cuttone, G.

    2013-01-01

    The aim of this study is to investigate the behavior of radio-resistant human malignant cells, thus enabling better understanding of radiobiological effects of ions in such a case. Radiation sources such as accelerated continuous ion beams and laser technology-based ultra short radiation sources with energy of around 10 MeV will be used. The HTB140 melanoma cells are chosen since it has been shown that they represent the limit case of cellular radio-resistance among the studied tumor cell lines. These cells are particularly interesting as they provide data on the very edge of inactivation capacity of each beam line that is tested. After exposing the cell monolayers to continuous radiations of low (γ-rays) and high (protons) linear energy transfer, the kinetics of disappearance of the phosphorylated histone H2AX (γ-H2AX) foci per cell will be determined. The same procedure will be performed with the pulsed high dose rate protons. Detection and quantification of γ-H2AX foci will be performed by immunohistochemical 3D time-dependent imaging analyses using laser scanning confocal microscopy. Immunoblotting will enable the follow-up of the relation between γ-H2AX and cell cycle arrest via the p53/p21 pathway. In such a way the spatio-temporal changes on sub-cellular level will be visualized, quantified and compared. These results will show whether there is a difference in the effects on cells between continuous and pulsed irradiation mode. Therefore, they will contribute to the data base that might promote pulsed sources for medical treatments of malignant growths

  6. Spatio-temporal changes in precipitation over Beijing-Tianjin-Hebei region, China

    Science.gov (United States)

    Zhao, Na; Yue, Tianxiang; Li, Han; Zhang, Lili; Yin, Xiaozhe; Liu, Yi

    2018-04-01

    Changes in precipitation have a large effect on human society and are of primary importance for many scientific fields such as hydrology, agriculture and eco-environmental sciences. The present study intended to investigate the spatio-temporal characteristics of precipitation in Beijing-Tianjin-Hebei (BTH) region by using 316 meteorological stations during the period 1965-2014. Geographical Weighted Regression (GWR) method and High Accuracy Surface Modeling (HASM) method were applied to produce the precipitation patterns at different time scales. Mann-Kendall (MK) statistical test was applied to analyze the precipitation temporal variations. Results indicated that annual precipitation over the past 50 years appeared to be a non-periodic oscillation phenomenon; the number of wet years was approximately the same as that of dry years; significant positive trends were observed in spring during 1978-2014 and summer during 1996-2014; on the whole, precipitation in May, June, September, and December showed increasing trends at the 95% confidence level; and significant positive trends were also identified in July during 2000-2013 and August during 1997-2010, while slight decreasing trends were observed in February and November. Summer (June, July, and August) was the wettest season, accounting for 68.73% of annual totals in BTH. In general, northeastern BTH received the highest range of precipitation while northwestern area had the lowest. It was found that precipitation variation in this region had been closely linked to latitude, Digital Elevation Model (DEM), distance to the sea, and urbanization rate. In addition, land use played an important role in the decadal precipitation changes in BTH.

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

    Directory of Open Access Journals (Sweden)

    Phaisarn Jeefoo

    2010-12-01

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

  8. Spatio-temporal variation in chemical characteristics of PM10 over Indo Gangetic Plain of India.

    Science.gov (United States)

    Sharma, S K; Mandal, T K; Srivastava, M K; Chatterjee, A; Jain, Srishti; Saxena, M; Singh, B P; Saraswati; Sharma, A; Adak, A; K Ghosh, S

    2016-09-01

    The paper presents the spatio-temporal variation of chemical compositions (organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ionic components (WSIC)) of particulate matter (PM10) over three locations (Delhi, Varanasi, and Kolkata) of Indo Gangetic Plain (IGP) of India for the year 2011. The observational sites are chosen to represent the characteristics of upper (Delhi), middle (Varanasi), and lower (Kolkata) IGP regions as converse to earlier single-station observation. Average mass concentration of PM10 was observed higher in the middle IGP (Varanasi 206.2 ± 77.4 μg m(-3)) as compared to upper IGP (Delhi 202.3 ± 74.3 μg m(-3)) and lower IGP (Kolkata 171.5 ± 38.5 μg m(-3)). Large variation in OC values from 23.57 μg m(-3) (Delhi) to 12.74 μg m(-3) (Kolkata) indicating role of formation of secondary aerosols, whereas EC have not shown much variation with maximum concentration over Delhi (10.07 μg m(-3)) and minimum over Varanasi (7.72 μg m(-3)). As expected, a strong seasonal variation was observed in the mass concentration of PM10 as well as in its chemical composition over the three locations. Principal component analysis (PCA) identifies the contribution of secondary aerosol, biomass burning, fossil fuel combustion, vehicular emission, and sea salt to PM10 mass concentration at the observational sites of IGP, India. Backward trajectory analysis indicated the influence of continental type aerosols being transported from the Bay of Bengal, Pakistan, Afghanistan, Rajasthan, Gujarat, and surrounding areas to IGP region.

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

    Science.gov (United States)

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

    2015-10-01

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

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

    Science.gov (United States)

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

    2017-05-01

    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 ( P0.05). 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 higher when the elevation is above 3 308 m. On the other hand, the Shannon-Wiener diversity index and Pielou's evenness index would be lower when pH and ammoniacal nitrogen have lower or higher values. Finally yet importantly, close attention should be paid to periphytic protozoa and its environment to ensure sustainable development

  11. Spatio Temporal EEG Source Imaging with the Hierarchical Bayesian Elastic Net and Elitist Lasso Models.

    Science.gov (United States)

    Paz-Linares, Deirel; Vega-Hernández, Mayrim; Rojas-López, Pedro A; Valdés-Hernández, Pedro A; Martínez-Montes, Eduardo; Valdés-Sosa, Pedro A

    2017-01-01

    The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions. Both models have been addressed within the penalized regression approach, where the regularization parameters are selected heuristically, leading usually to non-optimal and computationally expensive solutions. The existing Bayesian formulation of ENET allows hyperparameter learning, but using the computationally intensive Monte Carlo/Expectation Maximization methods, which makes impractical its application to the EEG IP. While the ELASSO have not been considered before into the Bayesian context. In this work, we attempt to solve the EEG IP using a Bayesian framework for ENET and ELASSO models. We propose a Structured Sparse Bayesian Learning algorithm based on combining the Empirical Bayes and the iterative coordinate descent procedures to estimate both the parameters and hyperparameters. Using realistic simulations and avoiding the inverse crime we illustrate that our methods are able to recover complicated source setups more accurately and with a more robust estimation of the hyperparameters and behavior under different sparsity scenarios than classical LORETA, ENET and LASSO Fusion solutions. We also solve the EEG IP using data from a visual attention experiment, finding more interpretable neurophysiological patterns with our methods. The Matlab codes used in this work, including Simulations, Methods

  12. Wildlife in the Matrix: Spatio-Temporal Patterns of Herbivore Occurrence in Karnataka, India

    Science.gov (United States)

    Karanth, Krithi K.

    2016-01-01

    Wildlife reserves are becoming increasingly isolated from the surrounding human-dominated landscapes particularly in Asia. It is imperative to understand how species are distributed spatially and temporally in and outside reserves, and what factors influence their occurrence. This study surveyed 7500 km2 landscape surrounding five reserves in the Western Ghats to examine patterns of occurrence of five herbivores: elephant, gaur, sambar, chital, and pig. Species distributions are modeled spatio-temporally using an occupancy approach. Trained field teams conducted 3860 interview-based occupancy surveys in a 10-km buffer surrounding these five reserves in 2012. I found gaur and wild pig to be the least and most wide-ranging species, respectively. Elephant and chital exhibit seasonal differences in spatial distribution unlike the other three species. As predicted, distance to reserve, the reserve itself, and forest cover were associated with higher occupancy of all species, and higher densities of people negatively influenced occurrence of all species. Park management, species protection, and conflict mitigation efforts in this landscape need to incorporate temporal and spatial understanding of species distributions. All species are known crop raiders and conflict prone locations with resources (such as water and forage) have to be monitored and managed carefully. Wildlife reserves and adjacent areas are critical for long-term persistence and habitat use for all five herbivores and must be monitored to ensure wildlife can move freely. Such a large-scale approach to map and monitor species distributions can be adapted to other landscapes to identify and monitor critical habitats shared by people and wildlife.

  13. Spatio-temporal dimension of lightning flashes based on three-dimensional Lightning Mapping Array

    Science.gov (United States)

    López, Jesús A.; Pineda, Nicolau; Montanyà, Joan; Velde, Oscar van der; Fabró, Ferran; Romero, David

    2017-11-01

    3D mapping system like the LMA - Lightning Mapping Array - are a leap forward in lightning observation. LMA measurements has lead to an improvement on the analysis of the fine structure of lightning, allowing to characterize the duration and maximum extension of the cloud fraction of a lightning flash. During several years of operation, the first LMA deployed in Europe has been providing a large amount of data which now allows a statistical approach to compute the full duration and horizontal extension of the in-cloud phase of a lightning flash. The "Ebro Lightning Mapping Array" (ELMA) is used in the present study. Summer and winter lighting were analyzed for seasonal periods (Dec-Feb and Jun-Aug). A simple method based on an ellipse fitting technique (EFT) has been used to characterize the spatio-temporal dimensions from a set of about 29,000 lightning flashes including both summer and winter events. Results show an average lightning flash duration of 440 ms (450 ms in winter) and a horizontal maximum length of 15.0 km (18.4 km in winter). The uncertainties for summer lightning lengths were about ± 1.2 km and ± 0.7 km for the mean and median values respectively. In case of winter lightning, the level of uncertainty reaches up to 1 km and 0.7 km of mean and median value. The results of the successful correlation of CG discharges with the EFT method, represent 6.9% and 35.5% of the total LMA flashes detected in summer and winter respectively. Additionally, the median value of lightning lengths calculated through this correlative method was approximately 17 km for both seasons. On the other hand, the highest median ratios of lightning length to CG discharges in both summer and winter were reported for positive CG discharges.

  14. Spatio-temporal footprints of urbanisation in Surat, the Diamond City of India (1990-2009).

    Science.gov (United States)

    Sharma, Richa; Ghosh, Aniruddha; Joshi, Pawan Kumar

    2013-04-01

    Urbanisation is a ubiquitous phenomenon with greater prominence in developing nations. Urban expansion involves land conversions from vegetated moisture-rich to impervious moisture-deficient land surfaces. The urban land transformations alter biophysical parameters in a mode that promotes development of heat islands and degrades environmental health. This study elaborates relationships among various environmental variables using remote sensing dataset to study spatio-temporal footprint of urbanisation in Surat city. Landsat Thematic Mapper satellite data were used in conjugation with geo-spatial techniques to study urbanisation and correlation among various satellite-derived biophysical parameters, [Normalised Difference Vegetation Index, Normalised Difference Built-up Index, Normalised Difference Water Index, Normalised Difference Bareness Index, Modified NDWI and land surface temperature (LST)]. Land use land cover was prepared using hierarchical decision tree classification with an accuracy of 90.4 % (kappa = 0.88) for 1990 and 85 % (kappa = 0.81) for 2009. It was found that the city has expanded over 42.75 km(2) within a decade, and these changes resulted in elevated surface temperatures. For example, transformation from vegetation to built-up has resulted in 5.5 ± 2.6 °C increase in land surface temperature, vegetation to fallow 6.7 ± 3 °C, fallow to built-up is 3.5 ± 2.9 °C and built-up to dense built-up is 5.3 ± 2.8 °C. Directional profiling for LST was done to study spatial patterns of LST in and around Surat city. Emergence of two new LST peaks for 2009 was observed in N-S and NE-SW profiles.

  15. Spatio-temporal trends in monthly pan evaporation in Aguascalientes, Mexico

    Science.gov (United States)

    Ruiz-Alvarez, Osias; Singh, Vijay P.; Medina, Juan Enciso; Munster, Clyde; Kaiser, Ronald; Ontiveros-Capurata, Ronald Ernesto; Diaz-Garcia, Luis Antonio; dos Santos, Carlos Antonio Costa

    2018-05-01

    Emission of greenhouse gases is being alleged to be causing climate change in different regions of the world. The objective of this study was to analyze the spatio-temporal trends of monthly evaporation at 52 weather stations in the state of Aguascalientes (Mexico) which have hydrometeorological records of long periods. The autocorrelation was eliminated with an auto-regressive model, and the trend was determined using the Spearman (S) and Kendall (K) tests. The statistical significance of the trend was determined with the Spearman correlation coefficient (r s) and the Z statistic (the test statistic of the normal distribution) both indicated that that there were statistically significant trends in 107 time series, of these 88 series had negative trends and 19 series had positive trends. Negative trends were present in all months of the year, while positive trends occurred from February to May and from October to December only. The reduction of evaporation from - 4.10 to - 20.50 mm/month/year from June to September showed a hopeful future scenario for rainfed agriculture. Irrigated agriculture during dry months could have a reduction of irrigation requirements as a consequence of the reduction in reference and crop evapotranspiration. The evaporation increase during dry months could increase irrigation requirements and pumping, mainly in March, April, and November when there are trends with increases of about 26.90, 24.60, and 23.90 mm/month/year, respectively. The spatial variability of evaporation trend means that other effects of climate change could vary in different parts of the state. Results of this study will be useful for farmers and institutions in charge of the administration of water resources for developing adaptation and mitigation strategies to climate change.

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

    Directory of Open Access Journals (Sweden)

    Karin Gorzolka

    Full Text Available 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.

  17. Fine-scale hydrodynamics influence the spatio-temporal distribution of harbour porpoises at a coastal hotspot

    Science.gov (United States)

    Jones, A. R.; Hosegood, P.; Wynn, R. B.; De Boer, M. N.; Butler-Cowdry, S.; Embling, C. B.

    2014-11-01

    The coastal Runnelstone Reef, off southwest Cornwall (UK), is characterised by complex topography and strong tidal flows and is a known high-density site for harbour porpoise (Phocoena phocoena); a European protected species. Using a multidisciplinary dataset including: porpoise sightings from a multi-year land-based survey, Acoustic Doppler Current Profiling (ADCP), vertical profiling of water properties and high-resolution bathymetry; we investigate how interactions between tidal flow and topography drive the fine-scale porpoise spatio-temporal distribution at the site. Porpoise sightings were distributed non-uniformly within the survey area with highest sighting density recorded in areas with steep slopes and moderate depths. Greater numbers of sightings were recorded during strong westward (ebbing) tidal flows compared to strong eastward (flooding) flows and slack water periods. ADCP and Conductivity Temperature Depth (CTD) data identified fine-scale hydrodynamic features, associated with cross-reef tidal flows in the sections of the survey area with the highest recorded densities of porpoises. We observed layered, vertically sheared flows that were susceptible to the generation of turbulence by shear instability. Additionally, the intense, oscillatory near surface currents led to hydraulically controlled flow that transitioned from subcritical to supercritical conditions; indicating that highly turbulent and energetic hydraulic jumps were generated along the eastern and western slopes of the reef. The depression and release of isopycnals in the lee of the reef during cross-reef flows revealed that the flow released lee waves during upslope currents at specific phases of the tidal cycle when the highest sighting rates were recorded. The results of this unique, fine-scale field study provide new insights into specific hydrodynamic features, produced through tidal forcing, that may be important for creating predictable foraging opportunities for porpoises at a

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

    Science.gov (United States)

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

    2015-01-01

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

  19. Global spatio-temporal patterns in human migration: a complex network perspective.

    Science.gov (United States)

    Davis, Kyle F; D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

    2013-01-01

    Migration is a powerful adaptive strategy for humans to navigate hardship and pursue a better quality of life. As a universal vehicle facilitating exchanges of ideas, culture, money and goods, international migration is a major contributor to globalization. Consisting of countries linked by multiple connections of human movements, global migration constitutes a network. Despite the important role of human migration in connecting various communities in different parts of the world, the topology and behavior of the international migration network and its changes through time remain poorly understood. Here we show that the global human migration network became more interconnected during the latter half of the twentieth century and that migrant destination choice partly reflects colonial and postcolonial histories, language, religion, and distances. From 1960 to 2000 we found a steady increase in network transitivity (i.e. connectivity between nodes connected to the same node), a decrease in average path length and an upward shift in degree distribution, all of which strengthened the 'small-world' behavior of the migration network. Furthermore, we found that distinct groups of countries preferentially interact to form migration communities based largely on historical, cultural and economic factors.

  20. Global spatio-temporal patterns in human migration: a complex network perspective.

    Directory of Open Access Journals (Sweden)

    Kyle F Davis

    Full Text Available Migration is a powerful adaptive strategy for humans to navigate hardship and pursue a better quality of life. As a universal vehicle facilitating exchanges of ideas, culture, money and goods, international migration is a major contributor to globalization. Consisting of countries linked by multiple connections of human movements, global migration constitutes a network. Despite the important role of human migration in connecting various communities in different parts of the world, the topology and behavior of the international migration network and its changes through time remain poorly understood. Here we show that the global human migration network became more interconnected during the latter half of the twentieth century and that migrant destination choice partly reflects colonial and postcolonial histories, language, religion, and distances. From 1960 to 2000 we found a steady increase in network transitivity (i.e. connectivity between nodes connected to the same node, a decrease in average path length and an upward shift in degree distribution, all of which strengthened the 'small-world' behavior of the migration network. Furthermore, we found that distinct groups of countries preferentially interact to form migration communities based largely on historical, cultural and economic factors.

  1. Stochastic and deterministic processes regulate spatio-temporal variation in seed bank diversity

    Science.gov (United States)

    Alejandro A. Royo; Todd E. Ristau

    2013-01-01

    Seed banks often serve as reservoirs of taxonomic and genetic diversity that buffer plant populations and influence post-disturbance vegetation trajectories; yet evaluating their importance requires understanding how their composition varies within and across spatial and temporal scales (α- and β-diversity). Shifts in seed bank diversity are strongly...

  2. Spatio-temporal modelling of zero-inflated deep-sea shrimp data by Tweedie generalized additive

    Directory of Open Access Journals (Sweden)

    Simona Arcuti

    2013-10-01

    Full Text Available In theMediterrean Sea the population features of demersal resources fluctuate over spatial and temporal scales due to the variability of abiotic and biotic factors as well as to human activities. The two shrimps Parapenaeus longirostris and Aristaeomorpha foliacea are among the most important deep-sea demersal resources in the North-Western Ionian Sea. Their changes in terms of density, biomass andmedian length induced by anthropogenic and environmental variables (fishing effort, sea surface temperature, precipitations, Winter North Atlantic Oscillation (NAO and Annual MediterraneanOscillation (MO indices were investigated. Biological data were collected during trawl surveys carried out from 1995 to 2006 as part of the international program MEDITS (International Bottom Trawl Survey in the Mediterranean. Generalized AdditiveModels were used to evaluate the spatio-temporal variation of both species, together with the possible nonlinear effects of biotic and abiotic factors. Density and biomass were assumed to be distributed according to a member of the Tweedie family in order to account for zero-inflation in the relative data. Spacetime interaction was consideredwithin a non-separablemodel with smooth spatio-temporal component based on tensor product splines. The results show significant spatio-temporal and depth effects in the three population parameters of these resources. Winter NAO index significantly influenced the density, biomass and length of P. longirostris. Sea surface temperature significantly influenced the size of this species and the three population features of A. foliacea. The size of this shrimp resulted also influenced negatively by fishing effort and positively by the MO index.

  3. Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

    Science.gov (United States)

    Deilami, Kaveh; Kamruzzaman, Md.; Liu, Yan

    2018-05-01

    Despite research on urban heat island (UHI) effect has increased exponentially over the last few decades, a systematic review of factors contributing to UHI effect has scarcely been reported in the literature. This paper provides a systematic and overarching review of different spatial and temporal factors affecting the UHI effect. UHI is a phenomenon when urban areas experience a higher temperature than their surrounding non-urban areas and is considered as a critical factor contributing to global warming, heat related mortalities, and unpredictable climatic changes. Therefore, there is a pressing need to identify the spatio-temporal factors that contribute to (or mitigate) the UHI effect in order to develop a thorough understanding of their causal mechanism so that these are addressed through urban planning policies. This paper systematically identified 75 eligible studies on UHI effect and reviews the nature and type of satellite images used, the techniques applied to classify land cover/use changes, the models to assess the link between spatio-temporal factors and UHI effect, and the effects of these factors on UHI. The review results show that: a) 54% of the studies used Landsat TM images for modelling the UHI effect followed by Landsat ETM (34%), and MODIS (28%); b) land cover indices (46%), followed by supervised classification (17%) were the dominant methods to derive land cover/use changes associated with UHI effect; c) ordinary least square regression is the most commonly applied method (68%) to investigate the link between different spatio-temporal factors and the UHI effect followed by comparative analysis (33%); and d) the most common factors affecting the UHI effect as reported in the reviewed studies, include vegetation cover (44%), season (33%), built-up area (28%), day/night (25%), population density (14%), water body (12%) together with others. This research discusses the findings in policy terms and provides directions for future research.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Science.gov (United States)

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

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

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

    Directory of Open Access Journals (Sweden)

    Eva Gulikova

    2008-06-01

    Full Text Available 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

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt.

    Science.gov (United States)

    Kühling, Insa; Broll, Gabriele; Trautz, Dieter

    2016-02-15

    The Western Siberian grain belt covers 1millionkm² in Asiatic Russia and is of global importance for agriculture. Massive land-use changes took place in that region after the dissolution of the Soviet Union and the collapse of the state farm system. Decreasing land-use intensity (LUI) in post-Soviet Western Siberia was observed on grassland due to declining livestock whilst on cropland trends of land abandonment reversed in the early 2000s. Recultivation of abandoned cropland as well as increasing fertilizer inputs and narrowing crop rotations led to increasing LUI on cropland during the last two decades. Beyond that general trend, no information is available about spatial distribution and magnitude but a crucial precondition for the development of strategies for sustainable land management. To quantify changes and patterns in LUI, we developed an intensity index that reflects the impacts of land-based agricultural production. Based on subnational yearly statistical data, we calculated two separate input-orientated indices for cropland and grassland, respectively. The indices were applied on two spatial scale: at seven provinces covering the Western Siberian grain belt (Altay Kray, Chelyabinsk, Kurgan, Novosibirsk, Omsk, Sverdlovsk and Tyumen) and at all districts of the central province Tyumen. The spatio-temporal analysis clearly showed opposite trends for the two land-use types: decreasing intensity on grassland (-0.015 LUI units per year) and intensification on cropland (+0.014 LUI units per year). Furthermore, a spatial concentration towards intensity centres occurred during transition from a planned to a market economy. A principal component analysis enabled the individual calculations of both land-use types to be combined and revealed a strong link between biophysical conditions and LUI. The findings clearly showed the need for having a different strategy for future sustainable land management for grassland (predominantly used by livestock of households

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

    Directory of Open Access Journals (Sweden)

    Jimmy Martínez-Ortiz

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

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

    Science.gov (United States)

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

    2015-01-01

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

  11. Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing

    Directory of Open Access Journals (Sweden)

    Valentina Ciullo

    2018-05-01

    Full Text Available The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition or onset (temporal condition were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation.Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between

  12. Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing.

    Science.gov (United States)

    Ciullo, Valentina; Vecchio, Daniela; Gili, Tommaso; Spalletta, Gianfranco; Piras, Federica

    2018-01-01

    The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition) or onset (temporal condition) were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation. Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between explicit and

  13. The spatio-temporal structure of electrostatic turbulence in the WEGA stellarator

    International Nuclear Information System (INIS)

    Marsen, Stefan

    2008-03-01

    The main object of this work is to provide a detailed characterisation of electrostatic turbulence in WEGA and to identify the underlying instability mechanism driving turbulence. The spatio-temporal structure of turbulence is studied using multiple Langmuir probes providing a sufficiently high spatial and temporal resolution. Turbulence in WEGA is dominated by drift wave dynamics. The phase shift between density and potential fluctuations is close to zero, fluctuations are mainly driven by the density gradient, and the phase velocity of turbulent structures points in the direction of the electron diamagnetic drift. The structure of turbulence is studied mainly in the plasma edge region inside the last closed flux surface. WEGA can be operated in two regimes differing in the magnetic field strength by almost one order of magnitude (57 mT and 500 mT, respectively). At 57 mT large structures with a poloidal extent comparable to the machine dimensions are observed, whereas at 500 mT turbulent structures are much smaller. The poloidal structure size scales nearly linearly with the inverse magnetic field strength. This scaling may be argued to be related to the drift wave dispersion scale, ρ s =√(m i k B T e )/(qB). However, the structure size remains unchanged when the ion mass is changed by using different discharge gases. Inside the last closed flux surface the poloidal E x B drift in WEGA is negligible. The three-dimensional structure is studied in detail using probes which are toroidally separated but aligned along connecting magnetic field lines. A small but finite parallel wavenumber is found. The ratio between the average parallel and perpendicular wavenumber is in the order of anti κ parallel / anti κ θ ∼ 10 -2 . The parallel phase velocity of turbulent structures is in-between the ion sound velocity and the Alfven velocity. In the parallel dynamics a fundamental difference between the two operational regimes at different magnetic field strength is

  14. Mechanistic spatio-temporal point process models for marked point processes, with a view to forest stand data

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad; Rubak, Ege Holger

    We show how a spatial point process, where to each point there is associated a random quantitative mark, can be identified with a spatio-temporal point process specified by a conditional intensity function. For instance, the points can be tree locations, the marks can express the size of trees......, and the conditional intensity function can describe the distribution of a tree (i.e., its location and size) conditionally on the larger trees. This enable us to construct parametric statistical models which are easily interpretable and where likelihood-based inference is tractable. In particular, we consider maximum...

  15. Transition from complete synchronization to spatio-temporal chaos in coupled chaotic systems with nonhyperbolic and hyperbolic attractors

    Science.gov (United States)

    Rybalova, Elena; Semenova, Nadezhda; Strelkova, Galina; Anishchenko, Vadim

    2017-06-01

    We study the transition from coherence (complete synchronization) to incoherence (spatio-temporal chaos) in ensembles of nonlocally coupled chaotic maps with nonhyperbolic and hyperbolic attractors. As basic models of a partial element we use the Henon map and the Lozi map. We show that the transition to incoherence in a ring of coupled Henon maps occurs through the appearance of phase and amplitude chimera states. An ensemble of coupled Lozi maps demonstrates the coherence-incoherence transition via solitary states and no chimera states are observed in this case.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    International Nuclear Information System (INIS)

    Hamelin, Stéphanie; Planas, Dolors; Amyot, Marc

    2015-01-01

    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. - Highlights: • Epiphytes and macrophytes are sites of Hg accumulation in a large temperate river. • Epiphytic biofilms are ten fold more contaminated than their macrophyte host. • Physico-chemical variables influences Hg levels in epiphytes and macrophytes. • Up to 74% of total Hg is in the methylated form in epiphytes. • Epiphytes, should be included in Hg foodweb modeling. - Epiphytic biofilms are key sites of methylmercury accumulation in large river wetlands

  18. Assessment of the pseudo-tracking approach for the calculation of material acceleration and pressure fields from time-resolved PIV: part II. Spatio-temporal filtering

    Science.gov (United States)

    van Gent, P. L.; Schrijer, F. F. J.; van Oudheusden, B. W.

    2018-04-01

    The present study characterises the spatio-temporal filtering associated with pseudo-tracking. A combined theoretical and numerical assessment is performed that uses the relatively simple flow case of a two-dimensional Taylor vortex as analytical test case. An additional experimental assessment considers the more complex flow of a low-speed axisymmetric base flow, for which time-resolved tomographic PIV measurements and microphone measurements were obtained. The results of these assessments show how filtering along Lagrangian tracks leads to amplitude modulation of flow structures. A cut-off track length and spatial resolution are specified to support future applications of the pseudo-tracking approach. The experimental results show a fair agreement between PIV and microphone pressure data in terms of fluctuation levels and pressure frequency spectra. The coherence and correlation between microphone and PIV pressure measurements were found to be substantial and almost independent of the track length, indicating that the low-frequency behaviour of the flow could be reproduced regardless of the track length. It is suggested that a spectral analysis can be used inform the selection of a suitable track length and to estimate the local error margin of reconstructed pressure values.

  19. Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

    Science.gov (United States)

    Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

    2017-09-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

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

    Science.gov (United States)

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

    2015-12-30

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

  1. Earthquake Clusters and Spatio-temporal Migration of earthquakes in Northeastern Tibetan Plateau: a Finite Element Modeling

    Science.gov (United States)

    Sun, Y.; Luo, G.

    2017-12-01

    Seismicity in a region is usually characterized by earthquake clusters and earthquake migration along its major fault zones. However, we do not fully understand why and how earthquake clusters and spatio-temporal migration of earthquakes occur. The northeastern Tibetan Plateau is a good example for us to investigate these problems. In this study, we construct and use a three-dimensional viscoelastoplastic finite-element model to simulate earthquake cycles and spatio-temporal migration of earthquakes along major fault zones in northeastern Tibetan Plateau. We calculate stress evolution and fault interactions, and explore effects of topographic loading and viscosity of middle-lower crust and upper mantle on model results. Model results show that earthquakes and fault interactions increase Coulomb stress on the neighboring faults or segments, accelerating the future earthquakes in this region. Thus, earthquakes occur sequentially in a short time, leading to regional earthquake clusters. Through long-term evolution, stresses on some seismogenic faults, which are far apart, may almost simultaneously reach the critical state of fault failure, probably also leading to regional earthquake clusters and earthquake migration. Based on our model synthetic seismic catalog and paleoseismic data, we analyze probability of earthquake migration between major faults in northeastern Tibetan Plateau. We find that following the 1920 M 8.5 Haiyuan earthquake and the 1927 M 8.0 Gulang earthquake, the next big event (M≥7) in northeastern Tibetan Plateau would be most likely to occur on the Haiyuan fault.

  2. Analyzing Local Spatio-Temporal Patterns of Police Calls-for-Service Using Bayesian Integrated Nested Laplace Approximation

    Directory of Open Access Journals (Sweden)

    Hui Luan

    2016-09-01

    Full Text Available This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA. Temporal patterns for two-hour time periods, spatial patterns at the small-area scale, and space-time interaction (i.e., unusual departures from overall spatial and temporal patterns were estimated. Temporally, calls-for-service were found to be lowest in the early morning (02:00–03:59 and highest in the evening (20:00–21:59, while high levels of calls-for-service were spatially located in central business areas and in areas characterized by major roadways, universities, and shopping centres. Space-time interaction was observed to be geographically dispersed during daytime hours but concentrated in central business areas during evening hours. Interpreted through the routine activity theory, results are discussed with respect to law enforcement resource demand and allocation, and the advantages of modeling spatio-temporal datasets with Bayesian INLA methods are highlighted.

  3. Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China.

    Science.gov (United States)

    Ye, Zirong; Xu, Li; Zhou, Zi; Wu, Yafei; Fang, Ya

    2018-01-02

    Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial-temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women.

  4. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    Directory of Open Access Journals (Sweden)

    N. Mou

    2017-09-01

    Full Text Available Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.. In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method – based on grid density, which is used to cluster the OD (origin and destination data of taxi at different times. Then,combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion – spatial aggregation – spatial relative dispersion" in one day.

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

    Directory of Open Access Journals (Sweden)

    Zhaoyuan Yu

    2015-12-01

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

  6. Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico

    Science.gov (United States)

    Rychlik, Igor; Mao, Wengang

    2018-02-01

    The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.

  7. Spatio-temporal variability of the deposited radioactive materials in forest environments after the Fukushima Daiichi NPP accident

    Science.gov (United States)

    Kato, H.; Onda, Y.; Komatsu, Y.; Yoda, H.

    2012-12-01

    Soil, vegetation and other ecological compartments are expected to be highly contaminated by the deposited radionuclides after the Fukushima Daiichi nuclear power plant (NPP) accident triggered by a magnitude 9.1 earthquake and the resulting tsunami on Marchi 11, 2011. Study site have been established in Yamakiya district, Kawamata Town, Fukushima prefecture, located about 35 km from Fukushima power plant, and designated as the evacuated zone. The total deposition of radioactive materials at the study site ranged from 0.02to >10 M Bq/m2 for Cs-137. The mature cedar, young cedar, and broad-leaf stands were selected as experimental site for the monitoring of spatio-temporal variability of the deposited radionuclides after the accidental release of radioactive materials. In order to measure the vertical distribution of radioactivity in forest, a tower with the same height of tree have been established at each experimental site. The measurement of radioactivity by using a portable Ge gamma-ray detector (Detective-DX-100, Ortec) and radionuclide analysis of leaf samples at different height revealed that a large proportion of radionuclides which deposited on forest were trapped by canopies of the cedar forests. In contrast, in the broad-leaf forest highest radioactivity was found at the forest floor. Furthermore, spatio-temporal variability of radioactivity at the forest floor indicated that huge amount of caesium still remains on the canopy of coniferous forest, and subsequently transfers to forest floor in association with throughfall, stemflow, and litter fall.

  8. Efficient Streaming Mass Spatio-Temporal Vehicle Data Access in Urban Sensor Networks Based on Apache Storm.

    Science.gov (United States)

    Zhou, Lianjie; Chen, Nengcheng; Chen, Zeqiang

    2017-04-10

    The efficient data access of streaming vehicle data is the foundation of analyzing, using and mining vehicle data in smart cities, which is an approach to understand traffic environments. However, the number of vehicles in urban cities has grown rapidly, reaching hundreds of thousands in number. Accessing the mass streaming data of vehicles is hard and takes a long time due to limited computation capability and backward modes. We propose an efficient streaming spatio-temporal data access based on Apache Storm (ESDAS) to achieve real-time streaming data access and data cleaning. As a popular streaming data processing tool, Apache Storm can be applied to streaming mass data access and real time data cleaning. By designing the Spout/bolt workflow of topology in ESDAS and by developing the speeding bolt and other bolts, Apache Storm can achieve the prospective aim. In our experiments, Taiyuan BeiDou bus location data is selected as the mass spatio-temporal data source. In the experiments, the data access results with different bolts are shown in map form, and the filtered buses' aggregation forms are different. In terms of performance evaluation, the consumption time in ESDAS for ten thousand records per second for a speeding bolt is approximately 300 milliseconds, and that for MongoDB is approximately 1300 milliseconds. The efficiency of ESDAS is approximately three times higher than that of MongoDB.

  9. Efficient Streaming Mass Spatio-Temporal Vehicle Data Access in Urban Sensor Networks Based on Apache Storm

    Directory of Open Access Journals (Sweden)

    Lianjie Zhou

    2017-04-01

    Full Text Available The efficient data access of streaming vehicle data is the foundation of analyzing, using and mining vehicle data in smart cities, which is an approach to understand traffic environments. However, the number of vehicles in urban cities has grown rapidly, reaching hundreds of thousands in number. Accessing the mass streaming data of vehicles is hard and takes a long time due to limited computation capability and backward modes. We propose an efficient streaming spatio-temporal data access based on Apache Storm (ESDAS to achieve real-time streaming data access and data cleaning. As a popular streaming data processing tool, Apache Storm can be applied to streaming mass data access and real time data cleaning. By designing the Spout/bolt workflow of topology in ESDAS and by developing the speeding bolt and other bolts, Apache Storm can achieve the prospective aim. In our experiments, Taiyuan BeiDou bus location data is selected as the mass spatio-temporal data source. In the experiments, the data access results with different bolts are shown in map form, and the filtered buses’ aggregation forms are different. In terms of performance evaluation, the consumption time in ESDAS for ten thousand records per second for a speeding bolt is approximately 300 milliseconds, and that for MongoDB is approximately 1300 milliseconds. The efficiency of ESDAS is approximately three times higher than that of MongoDB.

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

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    Ram K Raghavan

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2009-12-01

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

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

    Science.gov (United States)

    Sarkar, Ram Rup; Malchow, Horst

    2005-12-01

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

  14. Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset

    Science.gov (United States)

    Qin, Y.; Xiao, X.; Dong, J.

    2016-12-01

    Large-scale deforestation and forest degradation in the tropical region have resulted in extensive carbon emissions and biodiversity loss. However, restricted by the availability of good-quality observations, large uncertainty exists in mapping the spatial distribution of forests and their spatio-temporal changes. In this study, we proposed a pixel- and phenology-based algorithm to identify and map annual tropical forests from 2000 to 2014, using the 8-day, 500-m MOD09A1 (v005) product, under the support of Google cloud computing (Google Earth Engine). A temporal filter was applied to reduce the random noises and to identify the spatio-temporal changes of forests. We then built up a confusion matrix and assessed the accuracy of the annual forest maps based on the ground reference interpreted from high spatial resolution images in Google Earth. The resultant forest maps showed the consistent forest/non-forest, forest loss, and forest gain in the pan-tropical zone during 2000 - 2014. The proposed algorithm showed the potential for tropical forest mapping and the resultant forest maps are important for the estimation of carbon emission and biodiversity loss.

  15. A Comparison of Spatio-Temporal Disease Mapping Approaches Including an Application to Ischaemic Heart Disease in New South Wales, Australia

    Directory of Open Access Journals (Sweden)

    Craig Anderson

    2017-02-01

    Full Text Available The field of spatio-temporal modelling has witnessed a recent surge as a result of developments in computational power and increased data collection. These developments allow analysts to model the evolution of health outcomes in both space and time simultaneously. This paper models the trends in ischaemic heart disease (IHD in New South Wales, Australia over an eight-year period between 2006 and 2013. A number of spatio-temporal models are considered, and we propose a novel method for determining the goodness-of-fit for these models by outlining a spatio-temporal extension of the Moran’s I statistic. We identify an overall decrease in the rates of IHD, but note that the extent of this health improvement varies across the state. In particular, we identified a number of remote areas in the north and west of the state where the risk stayed constant or even increased slightly.

  16. An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City

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    Lianjie Zhou

    2016-10-01

    Full Text Available The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems.

  17. Spatio-Temporal Variations of Microphytobenthos in the Botafogo and Siri estuaries (norteast - Brazil

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    Priscila Porchat de Assis Murolo

    2006-03-01

    Full Text Available Spatio-temporal variations of microphytobenthic biomass were investigated in the Botafogo and Siri estuaries, Pernambuco - Brazil. Samples were taken during low water (bi-monthly from February to December, 2003. Three sampling stations were located in each estuary, in both midlittoral and sublittoral areas. Clear spatial and temporal variations were found for both chlorophyll-a and phaeopigment concentrations. In Botafogo, chlorophyll-a had 34% of total variation explained by MRA from nitrogen and phosphorus concentrations, while only 16% of total variation was thus explained from nitrogen concentration in the Siri estuary. Phaeopigments had 39% of total variation explained by MRA from nitrogen concentration and salinity in the Botafogo estuary and 58% of total variation was similarly explained from nitrogen concentration in the Siri estuary. Nitrogen was discriminated by the b coefficients as the most important facto