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1

Overlapping Linear Quadtrees and Spatio-Temporal Query Processing  

Microsoft Academic Search

In this paper, indexing in spatio-temporal databases by using the technique of overlapping is investigated. Overlapping has been previously applied in various access methods to combine consecutive structure instances into a single structure, without storing identical sub-structures. In this way, space is saved without sacrificing time performance. A new access method, overlapping linear quadtrees is introduced. This structure is able

Theodoros Tzouramanis; Michael Vassilakopoulos; Yannis Manolopoulos

2000-01-01

2

Modeling sediment transport as a spatio-temporal Markov process.  

NASA Astrophysics Data System (ADS)

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

Heyman, Joris; Ancey, Christophe

2014-05-01

3

Photonic Zitterbewegung effect: Asymmetric spatio-temporal filtering near the Dirac point  

NASA Astrophysics Data System (ADS)

We present a classical explanation of the photonic Zitterbewegung (ZB) effect near the Dirac point in this paper. Due to the asymmetric transmitted spectrums near the Dirac point, a material with the Dirac point actually can function as a spatio-temporal filter. When an optical pulse with its spectrum centered near the Dirac point passing through the "filter", its spatio-temporal spectrum will be modified dramatically. As a result, the temporal shape of the transmitted pulse is distorted with tailed oscillations, i.e., the photonic ZB effect. The influence of the temporal and spatial widths of the input pulse on the tailed oscillations of the transmitted pulse has also been discussed. Our results may pave the way to the experimental research of the photonic ZB effect and provide a viewpoint for investigating other abnormal transmission properties near the Dirac point.

Ling, Xiaohui; Tang, Zhixiang; Chen, Liezun

2014-06-01

4

Spatio-temporal correlation analysis of turbulent flows using global and single-point measurements  

Microsoft Academic Search

A method to extract whole-field spatio-temporal correlations by combining global and single-point measurement techniques of different time resolutions is proposed. For fluid mechanics applications, the emphasis is on the combination of low repetition rate particle image velocimetry (PIV) results with experimental data obtained at largely higher sampling frequencies. The experimental feasibility of the procedure is established from results obtained in

Ludovic Chatellier; John Fitzpatrick

2005-01-01

5

The spatio-temporal brain dynamics of processing and integrating sound localization cues in humans  

Microsoft Academic Search

Interaural intensity and time differences (IID and ITD) are two binaural auditory cues for localizing sounds in space. This study investigated the spatio-temporal brain mechanisms for processing and integrating IID and ITD cues in humans. Auditory-evoked potentials were recorded, while subjects passively listened to noise bursts lateralized with IID, ITD or both cues simultaneously, as well as a more frequent

Eric Tardif; Micah M. Murray; Raphaël Meylan; Lucas Spierer; Stephanie Clarke

2006-01-01

6

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

7

Spatio-temporal processing of femtosecond laser pulses with thin film micro-optics  

Microsoft Academic Search

For spatio-temporal processing of ultrashort-pulse laser beams, design constraints arise from dispersion and diffraction. In sub-10-fs region, temporal and spatial coordinates of propagating wavepackets get non-separable. To enable controlled shaping and detection with spatial resolution, specific advantages of thin-film microoptical arrays are exploited. Transmitting and reflecting components of extremely small conical angles were used to generate multiple nondiffracting beams and

Rüdiger Grunwald; Volker Kebbel; Uwe Neumann; Uwe Griebner; Michel Piché

2003-01-01

8

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

NASA Astrophysics Data System (ADS)

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

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

2007-02-01

9

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

NASA Astrophysics Data System (ADS)

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

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

2012-09-01

10

Spatio-Temporal Process Variability in Watershed Scale Wetland Restoration Planning  

NASA Astrophysics Data System (ADS)

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

Evenson, G. R.

2012-12-01

11

Spatio-temporal analyses of sediment transport processes in an alpine catchment a scales oriented approach  

NASA Astrophysics Data System (ADS)

Increasing morphological problems are being encountered with water courses in Austria, related to the impacts of sediment regime with lack and surplus of material. River bed degradation and aggradation are enhanced by human intervention. On a scaling perspective the boundary conditions and major processes in a catchment, like the geomorphological setting, are given by longterm developments. On the basis of field mapping these effects are discusssed with respect to sediment availability, being affected e. g. by deep-seated gravitational slope deformations and slope creeping. Within these longterm processes, short-term unsteady sediment supply, erosion, transfer, deposition and remobilisation processes determine catchment sedimentation and management. At the moment the analysis of sediment regime is restricted to specific scales. Measurements of sediment transport are performed at limited spatial scales of a few meters or even individual points. These measurements are often not typical for the whole vertical or the whole cross section. The temporal resolution allows mostly no detailed analysis of e.g. the hysteretic behaviour of a flood wave. Furthermore it is questionable whether these data are characteristic for a longer reach which consists of individual sub-reaches of degradation, aggregation or equilibrium conditions. Finally the catchment wide analysis of sediment regime is restricted by the information given at these smaller scales and it is sensitive to the representativeness of these data with respect to spatial and temporal significance. With the help of a River Scaling Concept we discuss different scales in the alpine catchment Sölk for developing and testing a scale oriented procedure to investigate the catchment wide sediment regime in a spatio-temporal frame. It is shown that this methodology improves the quality of results derived from geometrical properties for the subbasins and gives good ideas for the solution of morphological problems.

Schober, S.; Habersack, H. M.

2003-04-01

12

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

SciTech Connect

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.

Sen, Satyabrata [ORNL

2013-01-01

13

A sensitivity analysis of the point reference global correlation (PRGC) technique for spatio-temporal correlations in turbulent flows  

Microsoft Academic Search

The point reference global correlation (PRGC) technique which combines single and global measurements as proposed by Chatellier\\u000a and Fitzpatrick (Exp Fluids 38(5):563–757, 2005) is of significant interest for the analysis of the turbulent statistics for noise source modeling in jet flows as it allows\\u000a the 2D spatio-temporal correlation functions to be obtained over a region of the flow. This enables

F. Kerhervé; J. Fitzpatrick; Ludovic Chatellier

2008-01-01

14

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

PubMed

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

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

2014-04-16

15

Spatio-temporal clustering  

Microsoft Academic Search

\\u000a Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively\\u000a new subfield of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness\\u000a of all kinds of location-based or environmental devices that record position, time or\\/and environmental properties of an object\\u000a or set of objects in real-time.

Slava Kisilevich; Florian Mansmann; Mirco Nanni; Salvatore Rinzivillo

2010-01-01

16

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

PubMed

Capturing the functionality of active dendritic processing into abstract mathematical models will help us to understand the role of complex biophysical neurons in neuronal computation and to build future useful neuromorphic analog Very Large Scale Integrated (aVLSI) neuronal devices. Previous work based on an aVLSI multi-compartmental neuron model demonstrates that the compartmental response in the presence of either of two widely studied classes of active mechanisms, is a nonlinear sigmoidal function of the degree of either input temporal synchrony OR input clustering level. Using the same silicon model, this work expounds the interaction between both active mechanisms in a compartment receiving input patterns of varying temporal AND spatial clustering structure and demonstrates that this compartmental response can be captured by a combined sigmoid and radial-basis function over both input dimensions. This paper further shows that the response to input spatio-temporal patterns in a one-dimensional multi-compartmental dendrite, can be described by a radial-basis like function of the degree of temporal synchrony between the inter-compartmental inputs. PMID:23853330

Wang, Yingxue; Liu, Shih-Chii

2013-06-01

17

A sensitivity analysis of the point reference global correlation (PRGC) technique for spatio-temporal correlations in turbulent flows  

NASA Astrophysics Data System (ADS)

The point reference global correlation (PRGC) technique which combines single and global measurements as proposed by Chatellier and Fitzpatrick (Exp Fluids 38(5):563-757, 2005) is of significant interest for the analysis of the turbulent statistics for noise source modeling in jet flows as it allows the 2D spatio-temporal correlation functions to be obtained over a region of the flow. This enables the statistical characteristics including inhomogeneous and anisotropic features to be determined. The sensitivity of the technique is examined in some detail for the specific case of laser doppler velocimetry (LDV) and particle image velocimetry (PIV). Simulated data are used to enable a parametric study of the accuracy of the PRGC technique to be determined as a function of the various measurement parameters. The sample frequencies and the number of samples of both the LDV and PIV signals are shown to be critical to errors associated with the estimated spatio-temporal correlations and that low data rates can lead to significant errors in the estimates. Measurements performed in single stream and co-axial jet flows at Mach 0.24 using PIV and LDV systems are reported and the 2D space-time correlation functions for these flows are determined using the PRGC technique. The results are discussed in the context of noise source modeling for jet flows.

Kerhervé, F.; Fitzpatrick, J.; Chatellier, Ludovic

2008-04-01

18

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

PubMed

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

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

2012-03-01

19

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

PubMed Central

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.

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

2012-01-01

20

One-channel inverse filter: Spatio-temporal control of a complex wave-field from a single point  

NASA Astrophysics Data System (ADS)

Can we make good use of the degrees of freedom of a wave-field trapped in a cavity to perform complete spatio-temporal inversion from a single emitter? To answer these questions, we used experiments conducted in the ultrasonic regime to investigate the wave-field in a water cavity where the energy was not homogeneously distributed over all of the degrees of freedom. While the time reversal from a single emitter gives poor results, we show the possibility to recover optimal spatio-temporal focusing by converting the multi-channel focusing technique of the spatio-temporal inverse filter into a single-channel method that we call the one-channel inverse filter. In particular, this method has the advantage of leaving the choice open for the duration of the time window for the inversion of the wave-field. We, thus, demonstrate that the shorter the time window, the better optimized the inversion. We believe that in addition to demonstrating the possibility of controlling the waves in a cavity, this method might have an interesting role in the improvement of solid imaging devices that are based on the exploitation of reverberations in cavities.

Rupin, Matthieu; Roux, Philippe; Catheline, Stefan

2014-06-01

21

Formally grounding spatio-temporal thinking.  

PubMed

To navigate through daily life, humans use their ability to conceptualize spatio-temporal information, which ultimately leads to a system of categories. Likewise, the spatial sciences rely heavily on conceptualization and categorization as means to create knowledge when they process spatio-temporal data. In the spatial sciences and in related branches of artificial intelligence, an approach has been developed for processing spatio-temporal data on the level of coarse categories: qualitative spatio-temporal representation and reasoning (QSTR). Calculi developed in QSTR allow for the meaningful processing of and reasoning with spatio-temporal information. While qualitative calculi are widely acknowledged in the cognitive sciences, there is little behavioral assessment whether these calculi are indeed cognitively adequate. This is an astonishing conundrum given that these calculi are ubiquitous, are often intended to improve processes at the human-machine interface, and are on several occasions claimed to be cognitively adequate. We have systematically evaluated several approaches to formally characterize spatial relations from a cognitive-behavioral perspective for both static and dynamically changing spatial relations. This contribution will detail our framework, which is addressing the question how formal characterization of space can help us understand how people think with, in, and about space. PMID:22806649

Klippel, Alexander; Wallgrün, Jan Oliver; Yang, Jinlong; Li, Rui; Dylla, Frank

2012-08-01

22

An allometric interpretation of the spatio-temporal organization of molecular and cellular processes.  

PubMed

Different levels of organization distinguished by characteristics spatial dimensions, Ec, and relaxation times, Tr, of biological processes ranging from electron transport in energy transduction to growth of microbial and plant cells, are shown to be related through a relation that may be interpreted as allometric and characterized by two different slopes. Processes, at levels of organization occurring in spatial dimensions of micrometers and relaxing in the order of minutes, delimit a 'transition point' between the two curves, that we interpret as a limit for the emergence of macroscopic coherence. The characteristic spatial dimension, Ec, and the relaxation time, Tr, contain dynamical information about the processes occurring at a given level of organization. When a steady state of a biological process at a certain level of organization becomes unstable, the system undergoes a transition to another level of organization. To exemplify the appearance of macroscopic order at levels of organization further from the 'transition point' we present in this report various experimental systems involving many levels of organization allometrically related that exhibit different kinds of self-organized behavior, i.e. bi-stability, oscillations, changes in (a)symmetry. PMID:8459799

Aon, M A; Cortassa, S

1993-03-10

23

Noise-induced re-entrant spatio-temporal intermittency  

NASA Astrophysics Data System (ADS)

We investigate the influence of noise on the spatio-temporal behavior of a simple model which has a subcritical bifurcation. We find that with increasing noise strength the spatio-temporal intermittency is first replaced by a low-amplitude noisy regime followed by spatio-temporal intermittency embedded into a noisy background. At sufficiently high noise intensity high-amplitude noise prevails. We point out that the transition from spatio-temporal intermittency to low-amplitude noise can be traced back to the conversion of a saddle point at zero amplitude for the deterministic system to a noise-stabilized fixed point. As the noise grows further, the noisy state around zero starts to communicate with a noisy limit cycle leading to noise-induced spatio-temporal intermittency. At high enough noise strength, high-amplitude noise is left over wiping out all details of the underlying deterministic dynamical system.

Hayase, Y.; Brand, H. R.

2004-06-01

24

Spatio-temporally resolved detection on a microfluidic chip for monitoring the dynamic processes of molecular events.  

PubMed

Detection is an essential aspect in analytical approaches. In liquid phase separations, many attempts have been focused on the capability to detect a partial or an entire column. However, detection in both spatial and temporal resolutions has not gained much attention yet. Here we present the concept of spatio-temporally resolved detection (STRD) and a proof-of-the-concept microchip electrophoresis (MCE)-STRD system. The MCE-STRD system was mainly composed of a microchip and an STRD unit, which were designed completely based on the requirements for spatial and temporal resolutions. In the STRD unit, a linear light beam expanded from a UV LED light source was employed to illuminate the whole separation channel of the microchip while a linear CCD sensor that has an identical effective length as the separation channel and more pixels per unit length was used to detect the absorbance signals through the separation channel. As each pixel of the CCD sensor can detect a corresponding channel space in real time, the CCD provides both spatial and temporal resolutions. A significant advantage of STRD over conventional detection schemes is its capability for monitoring the dynamic processes of molecular events occurring in the separation channel. This was demonstrated through the monitoring of the dynamic processes of protein-DNA and protein-drug interactions in chip isoelectric focusing (chip IEF). The MCE-STRD system provided not only whole pictures of the entire dynamic processes at-a-glance but also quantitative kinetic information (dissociation rate constants) of the dynamic processes. With further development, we anticipate that STRD could be a promising tool for the characterization of biomolecular interactions and the observation of migration behaviours of analytes. PMID:22785350

Bi, Xiaodong; Yu, Jianzhao; Li, Li; Jiang, Hancheng; Huang, Fengliang; Liu, Zhen

2012-09-01

25

GEDS: GPU Execution of Continuous Queries on Spatio-Temporal Data Streams  

Microsoft Academic Search

Much research exists for the efficient processing of spatio-temporal data streams. However, all methods ultimately rely on an ill-equipped processor, namely a CPU, to evaluate concurrent, continuous spatio-temporal queries over these data streams. This paper presents GEDS, a scalable, Graphics Processing Unit (GPU)-based framework for the evaluation of continuous spatio-temporal queries over spatio-temporal data streams. GEDS employs the computation sharing

Jonathan Cazalas; Ratan Guha

2010-01-01

26

An allometric interpretation of the spatio-temporal organization of molecular and cellular processes  

Microsoft Academic Search

Different levels of organization distinguished by characteristics spatial dimensions, Ec, and relaxation times, Tr, of biological processes ranging from electron transport in energy transduction to growth of microbial and plant cells, are shown to be related through a relation that may be interpreted as allometric and characterized by two different slopes. Processes, at levels of organization occurring in spatial dimensions

Miguel Antonio Aon; Sonia Cortassa

1993-01-01

27

Spatio-temporal dynamics of processing non-symbolic number: An ERP source localization study  

PubMed Central

Coordinated studies with adults, infants, and nonhuman animals provide evidence for two distinct systems of non-verbal number representation. The ‘parallel individuation’ system selects and retains information about 1–3 individual entities and the ‘numerical magnitude’ system establishes representations of the approximate cardinal value of a group. Recent ERP work has demonstrated that these systems reliably evoke functionally and temporally distinct patterns of brain response that correspond to established behavioral signatures. However, relatively little is known about the neural generators of these ERP signatures. To address this question, we targeted known ERP signatures of these systems, by contrasting processing of small versus large non-symbolic numbers, and used a source localization algorithm (LORETA) to identify their cortical origins. Early processing of small numbers, showing the signature effects of parallel individuation on the N1 (?150 ms), was localized primarily to extrastriate visual regions. In contrast, qualitatively and temporally distinct processing of large numbers, showing the signatures of approximate number representation on the mid-latency P2p (?200–250 ms), was localized primarily to right intraparietal regions. In comparison, mid-latency small number processing was localized to the right temporal-parietal junction and left-lateralized intraparietal regions. These results add spatial information to the emerging ERP literature documenting the process by which we represent number. Furthermore, these results substantiate recent claims that early attentional processes determine whether a collection of objects will be represented through parallel individuation or as an approximate numerical magnitude by providing evidence that downstream processing diverges to distinct cortical regions.

Hyde, Daniel C.; Spelke, Elizabeth S.

2013-01-01

28

Design of ETL Process on Spatio-temporal Data and Study of Quality Control  

Microsoft Academic Search

\\u000a In order to use the space-time data mining technology to conduct operation research in WuLiangSuHai Eutrophication, the water\\u000a quality sensor parameters of heterogeneous data which reflect the characteristics should set up a spatial data warehouse through\\u000a ETL process, and water quality sensors for quality control of spatial and temporal data plays a vital role in building an\\u000a effective analytical environment.

Buyu Wang; Changyou Li; Xueliang Fu; Meian Li; Dongqing Wang; Huibin Du; Yajuan Xing

2010-01-01

29

Integrating Population Genetics with Landscape Ecology to Infer Spatio-temporal Processes  

Microsoft Academic Search

The last decade has seen the rise of the research fields of DNA analysis and population or ecological genetics.They have the\\u000a potential to allow the revision of landscape ecological concepts such as habitat connectivity or fragmentation. In this chapter,\\u000a we first ask how population genetics can support and extend landscape ecological research from analysing patterns to understanding\\u000a processes, and we

Rolf Holderegger; Felix Gugerli; Christoph Scheidegger; Pierre Taberlet

30

Exploiting Spatio-temporal Correlations for Data Processing in Sensor Networks  

Microsoft Academic Search

Recent advances in microelectronics have made feasible the deployment of sensor networks for a variety of monitoring and surveillance\\u000a tasks. In such tasks the state of the network is evaluated either at regular intervals at a base-station, which constitutes\\u000a a centralized location where the data collected by the sensor nodes can be collected and processed, or continuously through\\u000a the use

Antonios Deligiannakis; Yannis Kotidis

2006-01-01

31

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

NASA Astrophysics Data System (ADS)

Process-based models, such as land surface models (LSMs), allow insight in the spatio-temporal distribution of stocks and the exchange of nutrients, trace gases etc. among environmental compartments. More recently, LSMs also become capable of assimilating time-series of in-situ reference observations. This enables calibrating the underlying functional relationships to site-specific characteristics, or to constrain the model results after each time-step in an attempt to minimize drift. The spatial resolution of LSMs is typically on the order of 10^2-10^4 km2, which is suitable for linking regional to continental scales and beyond. However, continuous in-situ observations of relevant stock and exchange variables, such as tower-based eddy-covariance (EC) fluxes, represent orders of magnitude smaller spatial scales (10^-6-10^1 km2). During data assimilation, this significant gap in spatial representativeness is typically either neglected, or side-stepped using simple tiling approaches. Moreover, at ';coarse' resolutions, a single LSM evaluation per time-step implies linearity among the underlying functional relationships as well as among the sub-grid land cover fractions. This, however, is not warranted for land-atmosphere exchange processes over more complex terrain. Hence, it is desirable to explicitly consider spatial variability at LSM sub-grid scales. Here we present a procedure that determines from a single EC tower the spatially integrated probability density function (PDF) of the surface-atmosphere exchange for individual land covers. These PDFs allow quantifying the expected value, as well as spatial variability over a target domain, can be assimilated in tiling-capable LSMs, and mitigate linearity assumptions at ';coarse' resolutions. The procedure is based on the extraction and extrapolation of environmental response functions (ERFs), for which a technical-oriented companion poster is submitted. In short, the subsequent steps are: (i) Time-frequency decomposition of tower EC data, (ii) Quantification of biophysical land cover properties in the flux footprint, (iii) Extraction of ERFs according to the information inherent in the observations, (iv) Extrapolation of the surface-atmosphere exchange from the ERF to a gridded target domain, and (v) Summarizing the PDFs for all grid cells of similar land cover. Metzger et al. (2013) have demonstrated the efficacy of this technique for airborne EC measurements. The results are spatial patterns of evapotranspiration that are highly similar to high-resolution LSM results, accurate to ?18% and precise to ?5%. Evapotranspiration differs by up to ?90% among land covers, and varies by up to ?40% across space within the same land cover. Here, we show for the first time results from applying this procedure to tower-based EC measurements (AmeriFlux Park Falls tower, Wisconsin, U.S.A.). Furthermore, we report the potential of this method for consistently informing LSMs on the in-situ fluxes of heat, water vapor, CO2 and CH4. Reference Metzger, S., Junkermann, W., Mauder, M., Butterbach-Bahl, K., Trancón y Widemann, B., Neidl, F., Schäfer, K., Wieneke, S., Zheng, X. H., Schmid, H. P., and Foken, T.: Spatially explicit regionalization of airborne flux measurements using environmental response functions, Biogeosciences, 10, 2193-2217, doi:10.5194/bg-10-2193-2013, 2013.

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

2013-12-01

32

Data assimilation using spatio-temporal descriptors  

NASA Astrophysics Data System (ADS)

Data assimilation is the process by which numerical model output is fused with observations in order to provide consensus estimates. In a Bayesian framework, this typically consists of constructing a 'process model prior' centred on the numerical model output and an 'observation model' which describes the relationship between the observed variable and the process of interest. This approach, while straightforward and ubiquitous in the geophysical sciences, can lead to erroneous inferences when the numerical output is biased (both spatially and temporally) in an undefined way. Here we show an alternative way in which to carry out data assimilation, whereby only the spatial and temporal properties of the numerical model are fused with the data. The method, couched in a spatio-temporal Bayesian framework, follows a two-stage approach: (i) Spatio-temporal modelling of the numerical model outputs in order to extract spectral spatio-temporal characteristics which are deemed faithful to the processes of interest (e.g. length scales and marginal variances), and (ii) Spatio-temporal modelling of the processes of interest with informative priors (based on (i)) in order to provide updated estimates. We apply this method to estimating the mass balance of Antarctic ice-sheet processes from multiple observations sources: GRACE, ICESat, ENVISat and GPS data. We show that although this problem is under-determined due to lack of observation diversity, spectral characterisation using the two-stage approach allows us to tease out the individual processes and reduce confounding between the processes whilst concurrently providing inferences which are largely data-driven.

Zammit-Mangion, Andrew; Schoen, Nana; Rougier, Jonathan; Bamber, Jonathan

2014-05-01

33

What Is Spatio-Temporal Data Warehousing?  

NASA Astrophysics Data System (ADS)

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.

Vaisman, Alejandro; Zimányi, Esteban

34

Bilinear Models for Spatio-Temporal Point Distribution Analysis: Application to Extrapolation of Whole Heart Cardiac Dynamics  

Microsoft Academic Search

In this work we introduce the usage of bilinear models as a means of factorising the shape variation induced by subject variability and the contraction of the human heart. We show that it is feasible to reconstruct the shape of the heart at a certain point in the cardiac cycle if we are given a small number of shapes representing

Corné Hoogendoorn; Federico M. Sukno; Sebastián Ordas; Alejandro F. Frangi

2007-01-01

35

Hybridizing Daphnia communities from ten neighbouring lakes: spatio-temporal dynamics, local processes, gene flow and invasiveness  

PubMed Central

Background In natural communities of cyclical parthenogens, rapid response to environmental change is enabled by switching between two reproduction modes. While long periods of asexual reproduction allow some clones to outcompete others, and may result in “clonal erosion”, sexual reproduction restores genetic variation in such systems. Moreover, sexual reproduction may result in the formation of interspecific hybrids. These hybrids can then reach high abundances, through asexual clonal reproduction. In the present study, we explored genetic variation in water fleas of the genus Daphnia. The focus was on the short-term dynamics within several clonal assemblages from the hybridizing Daphnia longispina complex and the impact of gene flow at small spatial scales. Results Daphnia individuals belonged either to the parental species D. galeata and D. longispina, or to different hybrid classes, as identified by 15 microsatellite markers. The distribution and genotypic structure of parental species, but not hybrids, corresponded well with the geographical positions of the lakes. Within parental species, the genetic distance among populations of D. galeata was lower than among populations of D. longispina. Moreover, D. galeata dominance was associated with higher phosphorous load. Finally, there was no evidence for clonal erosion. Conclusions Our results suggest that the contemporary structure of hybridizing Daphnia communities from ten nearby lakes is influenced by colonization events from neighbouring habitats as well as by environmental factors. Unlike the parental species, however, there was little evidence for successful dispersal of hybrids, which seem to be produced locally. Finally, in contrast to temporary Daphnia populations, in which a decrease in clonal diversity was sometimes detectable over a single growing season, the high clonal diversity and lack of clonal erosion observed here might result from repeated hatching of sexually produced offspring. Overall, our study provides insights into spatio-temporal dynamics in a hybridizing Daphnia species complex in a recently established lake system, and relates genetic similarities of populations to a scenario of secondary invasion enhanced by environmental factors.

2014-01-01

36

Spatio-temporal oscillations in the Keller-Segel system with logistic growth  

NASA Astrophysics Data System (ADS)

The Keller-Segel system with the logistic growth term is discussed from the spatio-temporal-oscillation point of view. This system exhibits two different types of spatio-temporal oscillations in certain distinct parameter regimes. In this paper, we study the difference between the two types of spatio-temporal oscillations. In particular, the characteristic properties of the behaviors become clear in a limiting system when a certain parameter value tends to zero. Moreover, we demonstrate that the onset of one of the spatio-temporal oscillatory patterns is an infinite-dimensional relaxation oscillation that consists of slow and fast dynamics.

Ei, Shin-Ichiro; Izuhara, Hirofumi; Mimura, Masayasu

2014-06-01

37

Annotating spatio-temporal datasets for meaningful analysis in the Web  

NASA Astrophysics Data System (ADS)

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.

Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

38

Optical Flow by Plane-based Spatio-Temporal Correlation  

NASA Astrophysics Data System (ADS)

The approach of spatio-temporal correlaton (STC) in which the object's flow is supposed to be point-symmetry for the searching point(pixel) has been proposed to improve the flow estimation of moving object. However, in the STC the shape of object becomes complex as Tree, the flows causes many errors. In this paper, we propose a plane-based spatio-temporal correlaton (PSTC) to cope with this. We show that the PSTC effectively estimates the flows of blurred “Tree" with Gaussian function through the experiments.

Kim, Jinwoo; Funato, Kazuteru; Wang, Rong-Long; Okazaki, Kozo

39

Spatio-temporal behavior of spiral vortex flow  

NASA Astrophysics Data System (ADS)

Experimental realizations of Taylor-Couette flow often include rigid end plates at bottom and top of the system. As a consequence of such end plates the bifurcation behavior of the basic laminar flow as well as the spatio-temporal properties of the emerging pattern, such as e.g. spiral vortex flow, can change. The latter point is in the focus of our present experimental study. The spatio-temporal behavior of spiral vortex flow in a Taylor-Couette system with rigid end plates is analyzed by a measurement technique based on Doppler-shift. This enables us to determine the spatial amplitude profile of up- and downward propagating spiral vortices within oscillatory flow states. Our study confirms experimentally recent numerical results of Hoffmann et al. [1] on the spatio-temporal properties of the spiral vortex state in finite systems with rigid end plates.

Heise, M.; Külter, D.; Abshagen, J.; Pfister, G.

2008-11-01

40

Real-time spatio-temporal analysis of dynamic scenes  

Microsoft Academic Search

We propose a set of tools for spatio-temporal real-time analysis of dynamic scenes. It is designed to improve the grounding\\u000a situation of autonomous agents in (simulated) physical domains. We introduce a knowledge processing pipeline ranging from\\u000a relevance-driven compilation of a qualitative scene description to a knowledge-based detection of complex event and action\\u000a sequences, conceived as a spatio-temporal pattern-matching problem. A

Tobias Warden; Ubbo Visser

41

Spatio-temporal laplacian pyramid coding for action recognition.  

PubMed

We present a novel descriptor, called spatio-temporal Laplacian pyramid coding (STLPC), for holistic representation of human actions. In contrast to sparse representations based on detected local interest points, STLPC regards a video sequence as a whole with spatio-temporal features directly extracted from it, which prevents the loss of information in sparse representations. Through decomposing each sequence into a set of band-pass-filtered components, the proposed pyramid model localizes features residing at different scales, and therefore is able to effectively encode the motion information of actions. To make features further invariant and resistant to distortions as well as noise, a bank of 3-D Gabor filters is applied to each level of the Laplacian pyramid, followed by max pooling within filter bands and over spatio-temporal neighborhoods. Since the convolving and pooling are performed spatio-temporally, the coding model can capture structural and motion information simultaneously and provide an informative representation of actions. The proposed method achieves superb recognition rates on the KTH, the multiview IXMAS, the challenging UCF Sports, and the newly released HMDB51 datasets. It outperforms state of the art methods showing its great potential on action recognition. PMID:23912503

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

2014-06-01

42

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

ERIC Educational Resources Information Center

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

Minai, Asghar Talaye

43

Spatio-temporal signal twice-whitening algorithms on the hx3100™ ultra-low power multicore processor  

Microsoft Academic Search

While modern signal detection theory fully accounts for spatially distributed sensors, exploiting these techniques for real-time sensing using large, underwater acoustic arrays requires advances in the spatio-temporal signal processing algorithms. In particular, the computational complexity of many spatio-temporal processing techniques is so large that conventional computer processors lack sufficient throughput to provide real-time processing of large spatio-temporal data sets. These

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

2010-01-01

44

Characterizing the state and processes of change in a dynamic forest environment using hierarchical spatio-temporal segmentation  

Microsoft Academic Search

Discrete changes in forest abundance, distribution, and productivity are readily detectable using a number of remotely sensed data sources; however, continuous changes such as growth and succession processes are more difficult to monitor. In this research we explore the potential of spectral trajectories generated from a 35-year (1973–2008) time-series of Landsat imagery to characterize change processes in a dynamic forest

Cristina Gómez; Joanne C. White; Michael A. Wulder

2011-01-01

45

Spatio-temporal saliency perception via hypercomplex frequency spectral contrast.  

PubMed

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. PMID:23482090

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

2013-01-01

46

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

PubMed

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

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

2014-01-01

47

Automatic real-time generalized phase-shifting interferometry to process interferograms with spatio-temporal visibility  

NASA Astrophysics Data System (ADS)

A faster and robust generalized phase-shifting interferometry suitable to automatic real-time applications is presented. The proposal is based on the parameter estimation by the least squares method. The algorithm can retrieve the wrapped phase from two or more phase shifted interferograms with unknown phase steps between 0 and ? rad. Moreover, by the multiple or single parameter estimation approach of this algorithm, interferograms with variable visibility both spatial and temporally can be processed, overcoming the restrictions and drawbacks from usual variable spatial visibility approaches. By both computer simulation and a optical experiment, the algorithm's feasibility is illustrated.

Juarez-Salazar, Rigoberto; Robledo-Sanchez, Carlos; Meneses-Fabian, Cruz; Rodriguez-Zurita, Gustavo; Guerrero Sanchez, Fermin; Barcelata-Pinzon, Antonio

2013-11-01

48

A framework about flow measurements by LDA-PDA as a spatio-temporal average: application to data post-processing  

NASA Astrophysics Data System (ADS)

Phase Doppler anemometry (PDA) is a well-established technique to study two-phase flows and its principles are also used in laser Doppler anemometry (LDA) for measurements of fluid velocity. Raw measurements of individual particle data require post-processing to obtain useful and consistent information (moments of velocity, particle concentration and flux, velocity autocorrelation, etc). This is called in this paper the reconstruction of statistical information. In the 1970s, several basic algorithms to perform the statistical reconstruction were developed for LDA measurements (such as the transit time method, the inverse velocity method, etc). With the advent of PDA, the scientific community developed reconstruction algorithms to obtain mean variables of the dispersed phase. All these basic algorithms were expounded as unconnected methods, following independent threads not integrated into a general framework. Assuming that the PDA works under ideal conditions (all particles that cross the probe volume are validated), this paper provides a general formulation and fully systematizes a large set of previous statistical reconstruction methods. In this paper, the statistical reconstruction of both the dispersed and the continuous phase is unified: the continuous phase post-processing emerges as the same reconstruction method of the dispersed phase. The general framework proposed offers many advantages. First, some previous calculation methods of particle concentration turn out to be particular cases of this general formulation. Second, it provides an easy way to deduce unbiased estimators of any statistical parameter of the flow. Third, a wide set of new post-processing methods are proposed to be tested by any member of the scientific community. In the fourth place, the generalized integral method to compute the particle concentration also gives information about the probe volume geometry and two new auto-calibration algorithms are proposed: the integral calibration method and the cross-section integral calibration method. Finally, a physical interpretation of the statistical reconstruction process is provided: it is a spatio-temporal averaging of the detected particle data, and some of the algorithms used are related to the Eulerian-Eulerian mathematical description of multiphase flows.

Calvo, Esteban; García, Juan A.; Santolaya, José Luis; García, Ignacio; Aísa, Luis

2012-05-01

49

Real-Time Spatio-Temporal Analysis of Dynamic Scenes in 3D Soccer Simulation  

Microsoft Academic Search

We propose a framework for spatio-temporal real-time analysis of dynamic scenes. It is designed to improve the grounding situation\\u000a of autonomous agents in (simulated) physical domains. We introduce a knowledge processing pipeline ranging from relevance-driven\\u000a compilation of a qualitative scene description to a knowledge-based detection of complex event and action sequences, conceived\\u000a as a spatio-temporal pattern matching problem. A methodology

Tobias Warden; Andreas D. Lattner; Ubbo Visser

2008-01-01

50

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

NASA Astrophysics Data System (ADS)

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

Dasgupta, Udayan; Ali, Murtaza

2011-03-01

51

Spatio-temporal dynamics in the origin of genetic information  

NASA Astrophysics Data System (ADS)

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

Kim, Pan-Jun; Jeong, Hawoong

2005-04-01

52

Spatio-temporal chaos: A solvable model  

NASA Astrophysics Data System (ADS)

A solvable coupled map lattice model exhibiting spatio-temporal chaos is studied. Exact expressions are obtained for the spectra of Lyapunov exponents as a function of the model parameters. Although the model has spatio-temporal structure, the time series measured at a single lattice site are shown to consist of independent, identically distributed samples for several values of the model parameters. For these parameter values, the spatial series measured at a fixed time also consist of independent, identically distributed samples. In these cases, the information dimension density is 1, but the information entropy density depends on the model parameters. Thus, the model is an example where the information entropy density can be obtained neither from a time series measured at a single lattice site nor from a spatial series measured at a fixed time. We conclude that in studying only a time series or a spatial series without any knowledge of the system, one could be easily led into thinking that there is no spatio-temporal structure. For a full characterization of the system, structure in time and space will have to be considered simultaneously.

Diks, C.; Takens, F.; DeGeode, J.

1997-02-01

53

Forecasting the Spatio-Temporal Dynamics of the Magnetosphere  

NASA Astrophysics Data System (ADS)

The spatio-temporal dynamics of the magnetosphere is a crucial component of effective space weather forecasting. The extensive data of the solar wind-magnetosphere interaction has been used to build predictive models of the magnetosphere based on nonlinear dynamical approaches. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the magnetic field variations at the ground stations as the magnetospheric response. The magnetic field perturbation at the ground and the corresponding solar wind data stations during the solar maximum period are compiled for these studies. The ground magnetometer data are from from CANOPUS, IMAGE and WDC magnetometer chain of stations. This new data set is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. In order to understand the predictability of space weather, the correlated database is used to study the causal relationships based on information theoretic approaches. This yields the mutual information between the solar wind variables and the ground magnetic field variations, and among the ground stations themselves. The information flow within the coupled system is analyzed by computing the transfer entropy among them.

Chen, J.; Sharma, A.; Veeramani, T.

2007-12-01

54

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

PubMed

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection. PMID:19550494

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

2009-06-22

55

Large scale stochastic spatio-temporal modelling with PCRaster  

NASA Astrophysics Data System (ADS)

PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model builders as Python functions. The software comes with Python framework classes providing control flow for spatio-temporal modelling, Monte Carlo simulation, and data assimilation (Ensemble Kalman Filter and Particle Filter). Models are built by combining the spatial operations in these framework classes. This approach enables modellers without specialist programming experience to construct large, rather complicated models, as many technical details of modelling (e.g., data storage, solving spatial operations, data assimilation algorithms) are taken care of by the PCRaster toolbox. Exploratory modelling is supported by routines for prompt, interactive visualisation of stochastic spatio-temporal data generated by the models. The high computational requirements for stochastic spatio-temporal modelling, and an increasing demand to run models over large areas at high resolution, e.g. in global hydrological modelling, require an optimal use of available, heterogeneous computing resources by the modelling framework. Current work in the context of the eWaterCycle project is on a parallel implementation of the modelling engine, capable of running on a high-performance computing infrastructure such as clusters and supercomputers. Model runs will be distributed over multiple compute nodes and multiple processors (GPUs and CPUs). Parallelization will be done by parallel execution of Monte Carlo realizations and sub regions of the modelling domain. In our approach we use multiple levels of parallelism, improving scalability considerably. On the node level we will use OpenCL, the industry standard for low-level high performance computing kernels. To combine multiple nodes we will use software from the eScience Technology Platform (eSTeP), developed at the Netherlands eScience Center. This will allow us to scale up to hundreds of machines, with thousands of compute cores. A key requirement is not to change the user experience of the software. PCRaster operations and the use of the Python framework classes should work in a similar manner on machines ranging from a laptop to a supercomputer. This enables a seamless transfer of models from small machines, where model development is done, to large machines used for large-scale model runs. Domain specialists from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies, currently use the PCRaster Python software within research projects. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows, Linux operating systems, and OS X.

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

2013-04-01

56

Proposal for a Non-Interceptive Spatio-Temporal Correlation Monitor  

SciTech Connect

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

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

2009-05-01

57

Efficient Index Structures for Spatio-Temporal Objects  

Microsoft Academic Search

In this article we present a family of four tree-based access structures for indexing spatio-temporal objects. Our indexing methods support spatio-temporal, as well as purely spatial and purely temporal queries. In order to han-dle sets of extended spatio-temporal objects we propose to specialize generalized search trees by combining the advan-tages of the well-known spatial structures R*-tree ([1]) and SS-tree ([18]).

Carsten Kleiner; Udo W. Lipeck

2000-01-01

58

Regularized feature reconstruction for spatio-temporal saliency detection.  

PubMed

Multimedia applications such as image or video retrieval, copy detection, and so forth can benefit from saliency detection, which is essentially a method to identify areas in images and videos that capture the attention of the human visual system. In this paper, we propose a new spatio-temporal saliency detection framework on the basis of regularized feature reconstruction. Specifically, for video saliency detection, both the temporal and spatial saliency detection are considered. For temporal saliency, we model the movement of the target patch as a reconstruction process using the patches in neighboring frames. A Laplacian smoothing term is introduced to model the coherent motion trajectories. With psychological findings that abrupt stimulus could cause a rapid and involuntary deployment of attention, our temporal model combines the reconstruction error, regularizer, and local trajectory contrast to measure the temporal saliency. For spatial saliency, a similar sparse reconstruction process is adopted to capture the regions with high center-surround contrast. Finally, the temporal saliency and spatial saliency are combined together to favor salient regions with high confidence for video saliency detection. We also apply the spatial saliency part of the spatio-temporal model to image saliency detection. Experimental results on a human fixation video dataset and an image saliency detection dataset show that our method achieves the best performance over several state-of-the-art approaches. PMID:23743773

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

2013-08-01

59

Spatio-temporal data dynamic visualization based on temporal tree structure  

NASA Astrophysics Data System (ADS)

This paper reviews the characteristics of spatio-temporal data and existing techniques for visualizing them, and then proposes a temporal tree structure which used to record and manipulates spatio-temporal object's predecessors and successors for the data source of dynamic visualization by algorithms of multi-temporal vector data correlation. Then, dynamic visualization methods of geometry shape and thematic were proposed with the support of temporal tree structure and case study were used to verify the methods proposed. The results and conclusion show that our method of dynamic visualization is an effective and generic way to implement dynamic modeling and visualization processes of spatio-temporal objects with various states along time.

Wang, Huibing; Liu, Yaolin; Tang, Xinming

2009-10-01

60

A spatio-temporal analysis of US station temperature trends over the last century  

NASA Astrophysics Data System (ADS)

This study presents a nonlinear spatio-temporal analysis of 1167 station temperature records from the United States Historical Climatology Network covering the period from 1898 through 2008. We use the Empirical Mode Decomposition (EMD) method to extract the generally nonlinear trends of each station. The statistical significance of each trend is assessed against three null models of the background climate variability, represented by stochastic processes of increasing temporal correlation length. We find strong evidence that more than 50 percent of all stations experienced a significant trend over the last century with respect to all three null models. A spatio-temporal analysis reveals a significant cooling trend in the South-East and significant warming trends in the rest of the contiguous US. It also shows that the warming trend appears to have migrated equatorward and possibly also in altitude. This shows the complex spatio-temporal evolution of climate change at local scales

Capparelli, Vincenzo; Franzke, Christian; Vecchio, Antonio; Freeman, Mervyn P.; Watkins, Nicholas W.; Carbone, Vincenzo

2013-04-01

61

Stochastic spatio-temporal modelling with PCRaster Python  

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

62

Spatio-temporal associative memories-the role of inhibitory neurons in building synfire chains  

Microsoft Academic Search

Associative memories are of paramount importance for any system that must compute on real world data. Famous fixed point recurrent networks of the Hopfield type have shown their limits in both storage capacities and computational capabilities. Recent extensions to dynamic attractors seem to be able to increase both. A study of such a spatio-temporal memory model based on Abeles' synfire

Christian Lehmann; Nirina Razafinimanana

1996-01-01

63

A METHODOLOGY OF MODELLING OBJECT HISTORY ORIENTED TO SPATIO- TEMPORAL REASONING  

Microsoft Academic Search

Spatio-Temporal Data Model (STDM) is the kernel and a critical point of the temporal difficulties in Geographical Information Systems. In recent years it has become an important research direction to explore STDM based on event and several relative models have been published. Which indicates that the emphasis of the research has transferred from the method of managing the historical data

LIN Guangfa; HUANG Wanli; JIANG Huixian; CHEN Youfei

64

Estimation of the trend function for spatio-temporal models  

Microsoft Academic Search

Spatiotemporal models have been applied in several scientific disciplines. A crucial problem is estimation of the trend function. Although nonparametric regression for spatial data has been studied in many papers, it is not the case for spatio-temporal data. In this article, we propose a local linear fitting method for spatio-temporal data and investigate the problem under what conditions the proposed

Hongxia Wang; Jinde Wang

2009-01-01

65

Spatio-Temporal Pattern Recognition Using Hidden Markov Models.  

National Technical Information Service (NTIS)

A new spatio-temporal method for identifying 3D objects found in 2D image sequences is presented. The Hidden Markov Model technique is used as a spatio-temporal classification algorithm to identify 3D objects by the temporal changes in observed shape feat...

K. H. Fielding

1994-01-01

66

A New Spatio-Temporal Fast Motion Estimation Algorithm  

Microsoft Academic Search

A new spatio-temporal approach is proposed for fast block motion estimation in video coding. The approach exploits the existing correlation of the spatio- temporal block neighborhood by utilizing the frequency of appearance of the neighborhood's motion vectors. Extensive simulations show that the proposed algorithm performs close to the full search algorithm (in terms of quality) with a significant computational gain.

V. Fotopoulos; A. N. Skodras

2007-01-01

67

High-Zoom Video Hallucination by Exploiting Spatio-Temporal Regularities  

Microsoft Academic Search

In this paper, we consider the problem of super-resolving a human face video by a very high ( 16) zoom factor. In- spired by recent literature on hallucination and example- based learning, we formulate this task using a graphical model that encodes 1) spatio-temporal consistencies, and 2) image formation & degradation processes. A video database of facial expressions is used

Göksel Dedeoglu; Takeo Kanade; Jonas August

2004-01-01

68

Groupwise Shape Registration on Raw Edge Sequence via A Spatio-Temporal Generative Model  

Microsoft Academic Search

Groupwise shape registration of raw edge sequence is addressed. Automatically extracted edge maps are treated as noised input shape of the deformable object and their registration are considered, results can be used to build statistical shape models without laborious manual labeling process. Dealing with raw edges poses several challenges, to fight against them a novel spatio-temporal generative model is proposed

Huijun Di; Rao Naveed Iqbal; Guangyou Xu; Linmi Tao

2007-01-01

69

I want my coffee hot! Learning to find people under spatio-temporal constraints  

Microsoft Academic Search

In this paper we present a probabilistic model for spatio-temporal patterns of human activities that enable robots to blend themselves into the work- ows and daily routines of people. The model, called spatial aordance map , is a non-homogeneous spatial Poisson process that relates space, time and occurrence probability of activity events. We describe how learning and inference is made

Gian Diego Tipaldi; Kai O. Arras

2011-01-01

70

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

NASA Astrophysics Data System (ADS)

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.

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

2009-10-01

71

Numerical spatio-temporal characterization of Listeria monocytogenes biofilms.  

PubMed

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

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

2014-07-16

72

Collaborative Assistance with Spatio-temporal Planning Problems  

NASA Astrophysics Data System (ADS)

The paper describes a collaborative assistance approach with spatio-temporal planning, which requires user's active participation in the problem solving task. The proposed collaborative assistance system operates on a region-based representation structure, which allows for partial specification of constraints at different levels of granularity. Weakly specified constraints contribute on the one hand to high computational complexity when generating alternative solutions and on the other hand to large solution spaces. The paper introduces Partial Order, Neighboring Regions and Partial Order of Neighboring Regions heuristics, which allow for pruning of significant parts of the search space, and produce hierarchical structuring of the solution space. Resulting hierarchical organization of the solution space reflects human mental processing of geographic information. To reduce cognitive load during observation of solution space, filtering of certain aspects, set-oriented structuring and case-based reasoning approaches are introduced.

Seifert, Inessa

73

A spatio-temporal extension to the map cube operator  

NASA Astrophysics Data System (ADS)

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.

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

2012-09-01

74

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

PubMed Central

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

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

2011-01-01

75

Sensor Web for Spatio-Temporal Monitoring of a Hydrological Environment  

NASA Technical Reports Server (NTRS)

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

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

2004-01-01

76

Spatio-temporal population estimates for risk management  

NASA Astrophysics Data System (ADS)

Accurate estimation of population at risk from hazards and effective emergency management of events require not just appropriate spatio-temporal modelling of hazards but also of population. While much recent effort has been focused on improving the modelling and predictions of hazards (both natural and anthropogenic), there has been little parallel advance in the measurement or modelling of population statistics. Different hazard types occur over diverse temporal cycles, are of varying duration and differ significantly in their spatial extent. Even events of the same hazard type, such as flood events, vary markedly in their spatial and temporal characteristics. Conceptually and pragmatically then, population estimates should also be available for similarly varying spatio-temporal scales. Routine population statistics derived from traditional censuses or surveys are usually static representations in both space and time, recording people at their place of usual residence on census/survey night and presenting data for administratively defined areas. Such representations effectively fix the scale of population estimates in both space and time, which is unhelpful for meaningful risk management. Over recent years, the Pop24/7 programme of research, based at the University of Southampton (UK), has developed a framework for spatio-temporal modelling of population, based on gridded population surfaces. Based on a data model which is fully flexible in terms of space and time, the framework allows population estimates to be produced for any time slice relevant to the data contained in the model. It is based around a set of origin and destination centroids, which have capacities, spatial extents and catchment areas, all of which can vary temporally, such as by time of day, day of week, season. A background layer, containing information on features such as transport networks and landuse, provides information on the likelihood of people being in certain places at specific times. Unusual patterns associated with special events can also be modelled and the framework is fully volume preserving. Outputs from the model are gridded population surfaces for the specified time slice, either for total population or by sub-groups (e.g. age). Software to implement the models (SurfaceBuilder247) has been developed and pre-processed layers for typical time slices for England and Wales in 2001 and 2006 are available for UK academic purposes. The outputs and modelling framework from the Pop24/7 programme provide significant opportunities for risk management applications. For estimates of mid- to long-term cumulative population exposure to hazards, such as in flood risk mapping, populations can be produced for numerous time slices and integrated with flood models. For applications in emergency response/ management, time-specific population models can be used as seeds for agent-based models or other response/behaviour models. Estimates for sub-groups of the population also permit exploration of vulnerability through space and time. This paper outlines the requirements for effective spatio-temporal population models for risk management. It then describes the Pop24/7 framework and illustrates its potential for risk management through presentation of examples from natural and anthropogenic hazard applications. The paper concludes by highlighting key challenges for future research in this area.

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

2013-04-01

77

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

Microsoft Academic Search

BACKGROUND: While there is a general agreement that picture-plane inversion is more detrimental to face processing than to other seemingly complex visual objects, the origin of this effect is still largely debatable. Here, we address the question of whether face inversion reflects a quantitative or a qualitative change in processing mode by investigating the pattern of event-related potential (ERP) response

Boutheina Jemel; Julie Coutya; Caroline Langer; Sylvain Roy

2009-01-01

78

A LANGUAGE FOR MODULAR SPATIO-TEMPORAL SIMULATION (R824766)  

EPA Science Inventory

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

79

VISUALIZATION OF SPATIO-TEMPORAL PATTERNS IN PUBLIC TRANSPORT DATA  

Microsoft Academic Search

In this paper, we discuss geovisualization techniques to explore spatio-temporal patterns formed by people traveling through public transport system (PTS). The Spatio-temporal reasoning by PTS operators\\/policy makers to extract patterns from public transport system data is studied. The resulting questions are related to basic visual tasks like locate, identify, associate and compare. These visual tasks are incorporated in a set

Menno-Jan Kraak

80

[Spatio-temporal changes in the metabolic processes in the blood-tissue system in the terminal states of the organism].  

PubMed

The role of synergism in diffusion of oxygen from erythrocyte into interstitial liquid and water filtration through the capillary wall was studied on the model using the following parameters: hydrostatic pressure on arterial and venous ends of the capillary (Pa and Pb), oncotic blood and tissue pressure (Pob and Pot), pore radius in the capillary (r), the number of pores in the capillary (n) per m2, amount of the liquid released from the capillary (q(x)), gas diffusion coefficient (D), time of erythrocyte movement in the capillary (T), speed of oxygen consumption (V), maximal distance with adequate V (Xmax), characteristic time of diffusion (Topt). It is shown that diffuse and convective components of the metabolic process have their own contribution and in changed conditions they redistribute. In increased number and diameter of hydravlic pores the greatest role in tissue saturation with oxygen belongs to convective metabolism, but in this situation tissues contain areas lacking oxygen. PMID:15052873

Kozlova, E K; Fomina, U A; Moroz, V V; Bogushevich, M S; Chernysh, A M

2004-01-01

81

Spatio-temporal mapping and modeling of a new forest disease spread using remote sensing and spatial statistics  

NASA Astrophysics Data System (ADS)

In central coastal California, a recently discovered pathogen Phytophthora ramorum has been killing hundreds of thousands of tanoak, coast live oak, and black oak trees. This forest disease referred to as Sudden Oak Death (SOD) has attracted attention from the public, government and academia. Monitoring the disease distribution and understanding the disease mechanisms are important for disease control and management. In this dissertation, I developed a spatio-temporal approach to mapping and modeling the SOD spread in California using remote sensing and spatial statistics. This dissertation seeks to quantify the disease spread over a range of scales using multi-temporal high spatial resolution airborne imagery. The work has three components: multi-temporal image registration, spatio-temporal classification, and spatial pattern analysis of disease dynamics. First, I developed an automated algorithm to register multi-temporal airborne images, which are characterized by complex geometric distortion with respect to one another. In this algorithm, large amounts of evenly distributed control points on regular grids were first derived from area-based methods. The control points with outliers removed were then applied to local transformation models. The results showed that the combination of area-based control point extraction with local transformation models is successful for geometric registration of airborne images with complex local distortion. Second, I developed a spatio-temporal classification algorithm to map mortality patterns from the accurately co-registered multi-temporal images. This algorithm is based on Markov Random Fields and Support Vector Machines and explicitly integrates spectral, spatial and temporal information in multi-temporal high-spatial resolution images. The results indicated that the algorithm achieved significant improvements over non-contextual classifications. Third, I applied both univariate and multivariate spatial point pattern analysis methods to quantify the mortality patterns using the mapped point patterns. The results from the univariate point pattern analysis showed that all the SOD point patterns are significantly clustered at different scales and spatial extents, revealing that the underlying mortality process consists of both first order trend and second order clustering. The results from the multivariate point pattern analysis showed that there exist strong attractions within multi-temporal SOD point patterns and between SOD and its major foliar host, California bay.

Liu, Desheng

82

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

USGS Publications Warehouse

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

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

2005-01-01

83

Initial spatio-temporal domain expansion of the Modelfest database  

NASA Astrophysics Data System (ADS)

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 preliminary expansion of the Modelfest dataset needs the participation of additional laboratories to evaluate the impact of different methods on threshold estimates and increase the subject base. We eagerly await the addition of new data from interested researchers. It remains to be seen how accurately general HVS models will predict thresholds across both Modelfest datasets.

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

2013-03-01

84

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

NASA Astrophysics Data System (ADS)

The spatial distribution of uncontrolled hazardous events, such as forest fires, is largely investigated from the scientific community with the purpose of finding out the more vulnerable areas. Mapping the location of spatio-temporal sequences for a given environmental dataset is of great impact; however, the majority of the studies miss the analysis of the aggregation over time. Nonetheless discovering unusual temporal pattern for a given time sequence is fundamental to understand the phenomena and underlying processes. The present study aims investigating both the spatial and the temporal cluster behaviour of forest fires occurrences registered in Canton Ticino (Switzerland) over a period of about 40 years and testing if space and time interact in generate clusters. To do this, the purely spatial, the time and the space-time extensions of the Ripley's K-function were applied. The Ripley's K-function is a statistic exploratory method which enables detecting whether or not a point process (e.g. the location of the ignition points) is randomly distributed. The purely spatial K-function K(r) is defined as the expected number of further events within an area of radius r around an arbitrary point of the pattern, divided by the intensity of the phenomenon. Under completely spatial randomness, the value of the K(r) is equal to the area around the point (=?r2), while observations above this theoretical value imply a clustering behaviour at the corresponding distance r. For the purely time analysis, the Ripley's K-function K(t) can be taught as a reformulation of the spatial version to detect unexpected aggregation of events over the temporal scale. For its computation, the value of the intensity used in K(r) is replaced by the total duration of the time sequence divided by the total number of observed events, and the distance r is replaced by the time interval t. Under time-regularity, K(t) equals 2t, whereas, observed measures above this theoretical value indicate a temporal cluster behaviour at the corresponding temporal scale t. For the analysis of the space-time clustering, we applied the spatio-temporal (bivariate) K-function K(r,t), which evaluates if events are closer in both space and time. Intuitively, if there is no space-time interaction K(r,t) = K(r) * K(t). Accordingly, if K(r,t) minus K(r) * K(t) is positive, this indicates an interaction between space and time in producing clusters, which arise from a well detectable spatial and temporal scales. This study allowed detecting: 1) the purely spatial and the purely temporal scales at which the registered forest fires events are clustered, given by the results of the K(r) and the K(t) computations; and 2) the time period where spatial clusters take place at a given distance scale, exhibited by the results of the K(r,t) computation. Key words: spatio-temporal sequences, cluster, Ripley's K-function, forest fires. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Bivand R., Rowlingson B., and Diggle P. (2012) - splancs package in R project - Diggle P., Chetwynd A., Haggkvist R. and Morris S. (1995) Second-order analysis of space-time clustering. Statistical Methods in Medical Research, vol. 4(2): 124-136. - R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/. - Vega Orozco C., Tonini M., Conedera M., Kanveski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, GeoInformatica, vol. 16(4): 653-673.

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

2013-04-01

85

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

Microsoft Academic Search

Low dose X-ray image sequences, as obtained in fluoroscopy, exhibit high levels of noise that must be suppressed in real-time, while preserving diagnostic structures. Multi-step adaptive filtering approaches, often involving spatio-temporal filters, are typically used to achieve this goal. In this work typical fluoroscopic image sequences, corrupted with Poisson noise, were processed using various filtering schemes. The noise suppression of

Udayan Dasgupta; Murtaza Ali

2011-01-01

86

Scalable 2Pass Data Mining Technique for Large Scale Spatio-temporal Datasets  

Microsoft Academic Search

In this paper we present a system for mining very large spatio-temporal datasets. The system comprises two main layers: the\\u000a mining layer and the visualization layer. The mining layer implements a new approach based on a 2-pass strategy to efficiently\\u000a support the data-mining process, address the spatial and temporal dimensions of the dataset, and visualize and interpret results.\\u000a In the

M. Tahar Kechadi; Michela Bertolotto

2007-01-01

87

A distributed spatio-temporal EEG/MEG inverse solver.  

PubMed

We propose a novel l1l2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard l1-norm inverse solver, the proposed sparse distributed inverse solver integrates the l1-norm spatial model with a temporal model of the source signals in order to avoid unstable activation patterns and "spiky" reconstructed signals often produced by the original solvers. The joint spatio-temporal model leads to a cost function with an l1l2-norm regularizer whose minimization can be reduced to a convex second-order cone programming problem and efficiently solved using the interior-point method. Validation with simulated and real MEG data shows that the proposed solver yields source time course estimates qualitatively similar to those obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. Furthermore, the l1l2-norm solver achieves fewer false positives and a better representation of the source locations than the conventional l2 minimum-norm estimates. PMID:18979728

Ou, Wanmei; Golland, Polina; Hämäläinen, Matti

2008-01-01

88

A distributed spatio-temporal EEG/MEG inverse solver.  

PubMed

We propose a novel l(1)l(2)-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard l(1)-norm inverse solvers, this sparse distributed inverse solver integrates the l(1)-norm spatial model with a temporal model of the source signals in order to avoid unstable activation patterns and "spiky" reconstructed signals often produced by the currently used sparse solvers. The joint spatio-temporal model leads to a cost function with an l(1)l(2)-norm regularizer whose minimization can be reduced to a convex second-order cone programming (SOCP) problem and efficiently solved using the interior-point method. The efficient computation of the SOCP problem allows us to implement permutation tests for estimating statistical significance of the inverse solution. Validation with simulated and human MEG data shows that the proposed solver yields source time course estimates qualitatively similar to those obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. Furthermore, the l(1)l(2)-norm solver achieves fewer false positives and a better representation of the source locations than the conventional l(2) minimum-norm estimates. PMID:18603008

Ou, Wanmei; Hämäläinen, Matti S; Golland, Polina

2009-02-01

89

Spatio-temporally smoothed coherence factor for ultrasound imaging.  

PubMed

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

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

2014-01-01

90

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

NASA Astrophysics Data System (ADS)

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

Smith, Tony E.; Wu, Peggy

2009-12-01

91

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

PubMed

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. PMID:19027230

Külahci, Fatih; Sen, Zekâi

2009-06-15

92

Spatio-temporal diffusion of dynamic PET images  

NASA Astrophysics Data System (ADS)

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.

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

2011-10-01

93

Spatio-temporal diffusion of dynamic PET images.  

PubMed

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. PMID:21937774

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

2011-10-21

94

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

NASA Astrophysics Data System (ADS)

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

Iwaniak, A.; ?ukowicz, J.; Strzelecki, M.; Kaczmarek, I.

2013-10-01

95

[Spatio-temporal change and gradient differentiation of landscape pattern in Guangzhou City during its urbanization].  

PubMed

Guangzhou City is a rapidly urbanizing city in China, and a constructed city with holistic planning. By using the remote sensing images of 1985, 1990, 1995, 2000 and 2004, this paper studied the 20 years spatio-temporal changes of landscape pattern in Guangzhou, and analyzed the relationships between these changes and urbanization. The landscape and class-level pattern indices of whole Guangzhou City and its five districts were compared, and the results indicated that the landscape pattern in Guangzhou had an obvious spatio-temporal variation, and an increase of diversity and fractal dimension. The landscape structural complexity and fragmentation increased gradually from 1985 to 2004, and the variation intensity and tendency varied during four comparative stages 1985-1990, 1990-1995, 1995-2000, and 2000-2004. It was a rapid development period from 1985 to 1995 in Guangzhou. The represents of ten districts varied in their spatio-temporal landscape pattern, because of the different development progress and planning motive. The urbanization of Panyu was from 1990 to 2000, and its natural landscape was seriously disturbed by human activities. The represents of Conghua and Zengcheng districts were of integrative disturbance, and also, the urbanization process mainly took place during 1990-2000. In the city center consisting of 8 official constructed districts, the urbanization process happened earlier. In Huadu district, the landscape change revealed the frequent and severe human disturbance. PMID:17147179

Guo, Luo; Xia, Beicheng; Liu, Weiqiu; Jiang, Xueding

2006-09-01

96

Time reversal and the spatio-temporal matched filter  

SciTech Connect

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

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

2004-03-08

97

Spatio-Temporal Representation of the Pitch of Harmonic Complex Tones in the Auditory Nerve  

PubMed Central

The pitch of harmonic complex tones plays an important role in speech and music perception and the analysis of auditory scenes, yet traditional rate-place and temporal models for pitch processing provide only an incomplete description of the psychophysical data. In order to test physiologically a model based on spatio-temporal pitch cues created by the cochlear traveling wave (Shamma, J Acoust Soc Am 78: 1622–1632), we recorded from single fibers in the auditory nerve of anesthetized cat in response to harmonic complex tones with missing fundamentals and equal-amplitude harmonics. We used the principle of scaling invariance in cochlear mechanics to infer the spatiotemporal response pattern to a given stimulus from a series of measurements made in a single fiber as a function of fundamental frequency F0. We found that spatio-temporal cues to resolved harmonics are available for F0s between 350 Hz and 1100 Hz and that these cues are more robust than traditional rate-place cues at high stimulus levels. The lower F0-limit is determined by the limited frequency selectivity of the cochlea, while the upper limit is caused by the degradation of phase-locking to the stimulus fine structure at high frequencies. The spatio-temporal representation is consistent with the upper F0-limit to the perception of the pitch of complex tones with a missing fundamental, and its effectiveness does not depend on the relative phase between resolved harmonics. The spatio-temporal representation is thus consistent with key trends in human psychophysics.

Cedolin, Leonardo; Delgutte, Bertrand

2010-01-01

98

Complex background subtraction by pursuing dynamic spatio-temporal models.  

PubMed

Although it has been widely discussed in video surveillance, background subtraction is still an open problem in the context of complex scenarios, e.g., dynamic backgrounds, illumination variations, and indistinct foreground objects. To address these challenges, we propose an effective background subtraction method by learning and maintaining an array of dynamic texture models within the spatio-temporal representations. At any location of the scene, we extract a sequence of regular video bricks, i.e., video volumes spanning over both spatial and temporal domain. The background modeling is thus posed as pursuing subspaces within the video bricks while adapting the scene variations. For each sequence of video bricks, we pursue the subspace by employing the auto regressive moving average model that jointly characterizes the appearance consistency and temporal coherence of the observations. During online processing, we incrementally update the subspaces to cope with disturbances from foreground objects and scene changes. In the experiments, we validate the proposed method in several complex scenarios, and show superior performances over other state-of-the-art approaches of background subtraction. The empirical studies of parameter setting and component analysis are presented as well. PMID:24876126

Lin, Liang; Xu, Yuanlu; Liang, Xiaodan; Lai, Jianhuang

2014-07-01

99

Two bilateral sources of the late AEP as identified by a spatio-temporal dipole model.  

PubMed

A new spatio-temporal dipole model is presented, which enables prediction and analysis of scalp potential wave forms due to spatio-temporal overlap of multiple generators. Each generator is thought to represent a local neural subset, the electric activity of which can be modelled by an equivalent dipole with stationary location and orientation closely related to the spatial organization of the neural subset. The temporal course of dipole magnitude is assumed to depict the external far field due to the compound discharge processes of the generator. Simulations of uni- and bilateral dipoles within the temporal lobe, oriented vertically and horizontally, demonstrate how spatio-temporal overlap mag bring about the 'vertex response' of the late AEP and the wave form changes observed over temporal sites. Analyses of late AEPs reported for a coronal chain of electrodes by Peronnet et al. (1974) and Vaughan et al. (1980) revealed that the wave forms in the 60-250 msec range could be perfectly matched at all electrodes by model wave forms due to 2 bilateral sources within the temporal lobe. Their locations, orientations and their latency difference of about 30 msec suggest consistently that the sequential activation of primary and secondary auditory cortices is the predominant source to the late AEPs. PMID:2578376

Scherg, M; Von Cramon, D

1985-01-01

100

Predictability of spatio-temporal patterns in a lattice of coupled FitzHugh-Nagumo oscillators  

PubMed Central

In many biological systems, variability of the components can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In pioneering work in the late 1990s, it was hypothesized that a drift of cellular parameters (along a ‘developmental path’), together with differences in cell properties (‘desynchronization’ of cells on the developmental path) can establish self-organized spatio-temporal patterns (in their example, spiral waves of cAMP in a colony of Dictyostelium discoideum cells) starting from a homogeneous state. Here, we embed a generic model of an excitable medium, a lattice of diffusively coupled FitzHugh–Nagumo oscillators, into a developmental-path framework. In this minimal model of spiral wave generation, we can now study the predictability of spatio-temporal patterns from cell properties as a function of desynchronization (or ‘spread’) of cells along the developmental path and the drift speed of cell properties on the path. As a function of drift speed and desynchronization, we observe systematically different routes towards fully established patterns, as well as strikingly different correlations between cell properties and pattern features. We show that the predictability of spatio-temporal patterns from cell properties contains important information on the pattern formation process as well as on the underlying dynamical system.

Grace, Miriam; Hutt, Marc-Thorsten

2013-01-01

101

A psychophysical and computational analysis of the spatio-temporal mechanisms underlying the flash-lag effect.  

PubMed

Several accounts put forth to explain the flash-lag effect (FLE) rely mainly on either spatial or temporal mechanisms. Here we investigated the relationship between these mechanisms by psychophysical and theoretical approaches. In a first experiment we assessed the magnitudes of the FLE and temporal-order judgments performed under identical visual stimulation. The results were interpreted by means of simulations of an artificial neural network, that was also employed to make predictions concerning the FLE. The model predicted that a spatio-temporal mislocalisation would emerge from two, continuous and abrupt-onset, moving stimuli. Additionally, a straightforward prediction of the model revealed that the magnitude of this mislocalisation should be task-dependent, increasing when the use of the abrupt-onset moving stimulus switches from a temporal marker only to both temporal and spatial markers. Our findings confirmed the model's predictions and point to an indissoluble interplay between spatial facilitation and processing delays in the FLE. PMID:19227376

Cravo, André M; Baldo, Marcus V C

2008-01-01

102

Spatio-temporal soil moisture distribution in a Maize field  

Microsoft Academic Search

The spatio-temporal distribution of water content is important for predicting water flow and solute transport in the unsaturated zone. In a cropped field, this distribution is affected by the interception and redistribution of water by the plants, by surface runoff, by root water uptake, and by the distribution of soil hydraulic properties and boundary conditions of the system. This study

Laure Beff; Valentin Couvreur; Mathieu Javaux

2010-01-01

103

Efficient motion weighted spatio-temporal video SSIM index  

NASA Astrophysics Data System (ADS)

Recently, Seshadrinathan and Bovik proposed the Motion-based Video Integrity Evaluation (MOVIE) index for VQA.1, 2 MOVIE utilized a multi-scale spatio-temporal Gabor filter bank to decompose the videos and to compute motion vectors. Apart from its psychovisual inspiration, MOVIE is an interesting option for VQA owing to its performance. However, the use of MOVIE in a practical setting may prove to be difficult owing to the presence of the multi-scale optical flow computation. In order to bridge the gap between the conceptual elegance of MOVIE and a practical VQA algorithm, we propose a new VQA algorithm - the spatio-temporal video SSIM based on the essence of MOVIE. Spatio-temporal video SSIM utilizes motion information computed from a block-based motion-estimation algorithm and quality measures using a localized set of oriented spatio-temporal filters. In this paper we explain the algorithm and demonstrate its conceptual similarity to MOVIE; we explore its computational complexity and evaluate its performance on the popular VQEG dataset. We show that the proposed algorithm allows for efficient FR VQA without compromising on the performance while retaining the conceptual elegance of MOVIE.

Moorthy, Anush K.; Bovik, Alan C.

2010-02-01

104

Fast Spatio-Temporal Data Mining from Large Geophysical Datasets  

NASA Technical Reports Server (NTRS)

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

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

1995-01-01

105

Finding Spatio-Temporal Patterns in Large Sensor Datasets  

ERIC Educational Resources Information Center

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

McGuire, Michael Patrick

2010-01-01

106

Kernel Averaged Predictors for Spatio-Temporal Regression Models  

PubMed Central

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

Gelfand, Alan E.

2013-01-01

107

KNN-kernel based clustering for spatio-temporal database  

Microsoft Academic Search

Extracting and analyzing the interesting patterns from spatio-temporal databases, have drawn a great interest in various fields of research. Recently, a number of experiments have explored the problem of spatial or temporal data mining, and some clustering algorithms have been proposed. However, not many studies have been dealing with the integration of spatial data mining and temporal data mining. Moreover,

A. Musdholifah; S. Z. B. M. Hashim; Ito Wasito

2010-01-01

108

Cubic map algebra functions for spatio-temporal analysis  

USGS Publications Warehouse

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

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

2005-01-01

109

Spatio-temporal decomposition of the EEG: a general approach to the isolation and localization of sources  

Microsoft Academic Search

The principal-component method of source localization for the background EEG is generalized to arbitrary spatio-temporal decompositions. It is shown that as long as the spatial patterns of the decomposition span the same signal space as the principal spatial components, the computational process of attempting to localize the sources is the same. Decompositions other than the principal components are shown to

Z. J. Koles; J. C. Lind; A. C. K. Soong

1995-01-01

110

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

USGS Publications Warehouse

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

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

2012-01-01

111

Network architecture and spatio-temporally symmetric dynamics  

NASA Astrophysics Data System (ADS)

We examine the relation between the structure of a network and the spatio-temporally symmetric periodic dynamics it can support. For solutions in which no cell is stationary, we show that only networks in which all cells interact with each other, or which contain a single group of interacting cells which drive the remainder of the network can exhibit such dynamics robustly. These characteristics of network architecture are not captured by the typical statistical quantities used to describe network structure. We illustrate the existence of spatio-temporally periodic solutions through a direct construction using ideas from coupled cell theory and the theory of weakly coupled oscillators, and show that these solutions can be stable in a very large region of parameter space. While we consider only a special type of network behavior, these ideas extend to more general architectures and dynamics.

Josi?, Krešimir; Török, Andrei

2006-12-01

112

Spatio-temporal analysis of Salmonella surveillance data in Thailand.  

PubMed

SUMMARY 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 isolates from Thailand was analysed. Data was grouped into human and non-human categories and the analysis was performed for the top five occurring serovars for each year of the study period. A total 91 human and 39 non-human significant spatio-temporal clusters were observed, accounting for 11% and 16% of the isolates, respectively. Serovar-specific associations between human and non-human clusters were also evaluated. Results show that these statistical tools can provide information for use in outbreak prevention and detection, in countries where only limited data is available. Moreover, it is suggested that monitoring non-human reservoirs can be relevant in predicting future Salmonella human cases. PMID:24103334

Domingues, A R; Vieira, A R; Hendriksen, R S; Pulsrikarn, C; Aarestrup, F M

2014-08-01

113

Spatio-temporal dynamics in a Turing model  

NASA Astrophysics Data System (ADS)

In this paper we study numerically two-dimensional spatio-temporal pattern formation in a generic Turing model, by investigating the dynamical behavior of a monostable system in the presence of Turing-Hopf bifurcation. In addition, we study the interaction of instabilities in a tristable system. We speculate that the interaction of spatial and temporal instabilities in Turing systems might bring some insight to a recent biological finding of temporal patterns on animal skin.

Leppänen, T.; Karttunen, M.; Barrio, R. A.; Kaski, K.

114

Spatio-Temporal Tracking of Faces by Stereo Vision  

Microsoft Academic Search

This report contributes a new approach for the robust tracking of humans’ heads and faces based on a spatio-temporal scene\\u000a analysis. The framework comprises aspects of structure and motion problems, as there are feature extraction, spatial and temporal\\u000a matching, re-calibration, tracking, and reconstruction. The scene is acquired through a calibrated stereo sensor. A cue processor\\u000a extracts invariant features in both

Markus Steffens; Werner Krybus; Christine Kohring; Danny Morton

2009-01-01

115

Time-Aggregated Graphs for Modeling Spatio-temporal Networks  

Microsoft Academic Search

Given applications such as location based services and the spatio-temporal queries they may pose on a spatial network (e.g.,\\u000a road networks), the goal is to develop a simple and expressive model that honors the time dependence of the road network.\\u000a The model must support the design of efficient algorithms for computing the frequent queries on the network. This problem\\u000a is

Betsy George; Shashi Shekhar

116

Finding Spatio-Temporal Patterns in Earth Science Data  

Microsoft Academic Search

This paper presents preliminary work in using data mining techniques to find interesting spatio-temporal patterns from Earth Science data. The data consists of time series measurements for various Earth science and climate variables (e.g. soil moisture, temperature, and precipitation), along with additional data from existing ecosystem models (e.g. Net Primary Production). The ecological patterns of interest include associations, clusters, predictive

Pang-Ning Tan; Michael Steinbach; Vipin Kumar; Christopher Potter; Steven Klooster; Alicia Torregrosa

2001-01-01

117

Improved inversion of MR elastography images by spatio-temporal directional filtering  

NASA Astrophysics Data System (ADS)

MR elastography can visualize and measure propagating shear waves in tissue-like materials subjected to harmonic mechanical excitation. This allows the calculation of local values of material parameters such as shear modulus and attenuation. Various inversion algorithms to perform such calculations have been proposed, but they are sensitive to areas of low displacement amplitude (and hence low SNR) that result from interference patterns due to reflection and refraction. A spatio-temporal directional filter applied as a pre-processing step can separate interfering waves so they can be processed separately. Weighted combinations of inversions from such directionally separated data sets can significantly improve reconstructions of shear modulus and attenuation.

Manduca, Armando; Lake, David S.; Ehman, Richard L.

2003-05-01

118

Spatio-temporal regularization for range imaging with high photon efficiency  

NASA Astrophysics Data System (ADS)

Conventional depth imagers using time-of-flight methods collect hundreds to thousands of detected photons per pixel to form high-quality depth images of a scene. Through spatio-temporal regularization achieved with maximum a posteriori probability estimation under a scene prior and an inhomogeneous Poisson process likelihood function, we form depth images with dramatically higher photon efficiency even as low as one detected photon per pixel. Simulations demonstrate the combination of high accuracy and high photon efficiency of our method, compared to the traditional maximum likelihood estimate of the depth image and other popular denoising algorithms.

Kirmani, Ahmed; Colaço, Andrea; Shin, Dongeek; Goyal, Vivek K.

2013-09-01

119

Retrieving Human Actions Using Spatio-Temporal Features and Relevance Feedback  

NASA Astrophysics Data System (ADS)

In this paper, we extend the idea of 2D objects retrieval to 3D human action retrieval and present the solution of action retrieval with spatio-temporal features. The framework of this action retrieval engine is based on the spatio-temporal interest point detector and the bag-of-words representation. For description of action features, we observe that appearance feature and structural feature from interest points can provide complementary information to each other. Then, we propose to combine brightness gradient and 3D shape context together to increase the discriminative power of descriptors. The experiments carried on the KTH dataset prove the advantage of this method. The extension of this work is applying the interest points based action retrieval technique to realistic actions in movies. As actions in movies are very complex due to the background variation, scale difference and performers' appearance, etc., it is a difficult target to localize and describe the actions. The results show that our method is very efficient computationally and achieves a reasonable accuracy for those challenging scenarios. We believe that our work is helpful for further research on action retrieval techniques.

Jin, Rui; Shao, Ling

120

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

NASA Astrophysics Data System (ADS)

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

Kornelsen, K. C.; Coulibaly, P.

2012-12-01

121

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

PubMed Central

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

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

2011-01-01

122

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

NASA Astrophysics Data System (ADS)

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.

Kornelsen, K. C.; Coulibaly, P.

2013-04-01

123

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

PubMed Central

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

Wang, Grace I.

2012-01-01

124

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

USGS Publications Warehouse

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 nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

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

2010-01-01

125

Spatio temporal Dynamics of Face Recognition  

Microsoft Academic Search

To better understand face recognition, it is necessary to identify not only which brain structures are implicated but also the dynamics of the neuronal activity in these structures. Latencies can then be compared to unravel the temporal dynamics of information processing at the distributed network level. To achieve high spatial and temporal resolution, we used intracerebral recordings in epileptic subjects

Emmanuel J. Barbeau; Margot J. Taylor; Jean Regis; Patrick Marquis; Patrick Chauvel; Catherine Liegeois-Chauvel

2008-01-01

126

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

NASA Astrophysics Data System (ADS)

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

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

2013-10-01

127

Working with Spatio-Temporal Data Type  

NASA Astrophysics Data System (ADS)

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

Raza, A.

2012-07-01

128

Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data  

NASA Astrophysics Data System (ADS)

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.

Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.

2011-11-01

129

Spatio-temporal topological relationships between land parcels in cadastral database  

NASA Astrophysics Data System (ADS)

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

Song, W.; Zhang, F.

2014-04-01

130

Quantifying human sensitivity to spatio-temporal information in dynamic faces.  

PubMed

A great deal of perceptual and social information is conveyed by facial motion. Here, we investigated observers' sensitivity to the complex spatio-temporal information in facial expressions and what cues they use to judge the similarity of these movements. We motion-captured four facial expressions and decomposed them into time courses of semantically meaningful local facial actions (e.g., eyebrow raise). We then generated approximations of the time courses which differed in the amount of information about the natural facial motion they contained, and used these and the original time courses to animate an avatar head. Observers chose which of two animations based on approximations was more similar to the animation based on the original time course. We found that observers preferred animations containing more information about the natural facial motion dynamics. To explain observers' similarity judgments, we developed and used several measures of objective stimulus similarity. The time course of facial actions (e.g., onset and peak of eyebrow raise) explained observers' behavioral choices better than image-based measures (e.g., optic flow). Our results thus revealed observers' sensitivity to changes of natural facial dynamics. Importantly, our method allows a quantitative explanation of the perceived similarity of dynamic facial expressions, which suggests that sparse but meaningful spatio-temporal cues are used to process facial motion. PMID:24784699

Dobs, Katharina; Bülthoff, Isabelle; Breidt, Martin; Vuong, Quoc C; Curio, Crist?bal; Schultz, Johannes

2014-07-01

131

Dissecting spatio-temporal protein networks driving human heart development and related disorders  

PubMed Central

Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems-level insight into the underlying processes is very limited. Using heart morphogenesis as general model for dissecting the functional architecture of organ development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages of a developing organ identifying several novel signaling modules. Our results show that organ development relies on surprisingly few, extensively recycled, protein modules that integrate into complex higher-order networks. This design allows the formation of a complicated organ using simple building blocks, and suggests how mutations in the same genes can lead to diverse phenotypes. We observe a striking temporal correlation between organ complexity and the number of discrete functional modules coordinating morphogenesis. Our analysis elucidates the organization and composition of spatio-temporal protein networks that drive the formation of organs, which in the future may lay the foundation of novel approaches in treatments, diagnostics, and regenerative medicine.

Lage, Kasper; M?llgard, Kjeld; Greenway, Steven; Wakimoto, Hiroko; Gorham, Joshua M; Workman, Christopher T; Bendsen, Eske; Hansen, Niclas T; Rigina, Olga; Roque, Francisco S; Wiese, Cornelia; Christoffels, Vincent M; Roberts, Amy E; Smoot, Leslie B; Pu, William T; Donahoe, Patricia K; Tommerup, Niels; Brunak, S?ren; Seidman, Christine E; Seidman, Jonathan G; Larsen, Lars A

2010-01-01

132

Spatio-temporal skin strain distributions evoke low variability spike responses in cuneate neurons  

PubMed Central

A common method to explore the somatosensory function of the brain is to relate skin stimuli to neurophysiological recordings. However, interaction with the skin involves complex mechanical effects. Variability in mechanically induced spike responses is likely to be due in part to mechanical variability of the transformation of stimuli into spiking patterns in the primary sensors located in the skin. This source of variability greatly hampers detailed investigations of the response of the brain to different types of mechanical stimuli. A novel stimulation technique designed to minimize the uncertainty in the strain distributions induced in the skin was applied to evoke responses in single neurons in the cat. We show that exposure to specific spatio-temporal stimuli induced highly reproducible spike responses in the cells of the cuneate nucleus, which represents the first stage of integration of peripheral inputs to the brain. Using precisely controlled spatio-temporal stimuli, we also show that cuneate neurons, as a whole, were selectively sensitive to the spatial and to the temporal aspects of the stimuli. We conclude that the present skin stimulation technique based on localized differential tractions greatly reduces response variability that is exogenous to the information processing of the brain and hence paves the way for substantially more detailed investigations of the brain's somatosensory system.

Hayward, Vincent; Terekhov, Alexander V.; Wong, Sheng-Chao; Geborek, Pontus; Bengtsson, Fredrik; Jorntell, Henrik

2014-01-01

133

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

NASA Astrophysics Data System (ADS)

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

Sampson, K. M.; Wilhelmi, O.

2009-12-01

134

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

PubMed Central

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

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

2008-01-01

135

Event Detection using Twitter: A Spatio-Temporal Approach  

PubMed Central

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

Cheng, Tao; Wicks, Thomas

2014-01-01

136

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

SciTech Connect

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

Mosher, J.C. (TRW Defense Systems Group, Redondo Beach, CA (USA). Systems Engineering and Development Div. University of Southern California, Los Angeles, CA (USA). Signal and Image Processing Inst.); Lewis, P.S. (Los Alamos National Lab., NM (USA)); Leahy, R. (University of Southern California, Los Angeles, CA (USA). Signal and Image Processing Inst.); Singh, M. (University of Southern Californi

1990-01-01

137

Spatio-temporal avalanche forecasting with Support Vector Machines  

NASA Astrophysics Data System (ADS)

This paper explores the use of the Support Vector Machine (SVM) as a data exploration tool and a predictive engine for spatio-temporal forecasting of snow avalanches. Based on the historical observations of avalanche activity, meteorological conditions and snowpack observations in the field, an SVM is used to build a data-driven spatio-temporal forecast for the local mountain region. It incorporates the outputs of simple physics-based and statistical approaches used to interpolate meteorological and snowpack-related data over a digital elevation model of the region. The interpretation of the produced forecast is discussed, and the quality of the model is validated using observations and avalanche bulletins of the recent years. The insight into the model behaviour is presented to highlight the interpretability of the model, its abilities to produce reliable forecasts for individual avalanche paths and sensitivity to input data. Estimates of prediction uncertainty are obtained with ensemble forecasting. The case study was carried out using data from the avalanche forecasting service in the Locaber region of Scotland, where avalanches are forecast on a daily basis during the winter months.

Pozdnoukhov, A.; Matasci, G.; Kanevski, M.; Purves, R. S.

2011-02-01

138

Spatio-temporal topography of saccadic overestimation of time.  

PubMed

Rapid eye movements (saccades) induce visual misperceptions. A number of studies in recent years have investigated the spatio-temporal profiles of effects like saccadic suppression or perisaccadic mislocalization and revealed substantial functional similarities. Saccade induced chronostasis describes the subjective overestimation of stimulus duration when the stimulus onset falls within a saccade. In this study we aimed to functionally characterize saccade induced chronostasis in greater detail. Specifically we tested if chronostasis is influenced by or functionally related to saccadic suppression. In a first set of experiments, we measured the perceived duration of visual stimuli presented at different spatial positions as a function of presentation time relative to the saccade. We further compared perceived duration during saccades for isoluminant and luminant stimuli. Finally, we investigated whether or not saccade induced chronostasis is dependent on the execution of a saccade itself. We show that chronostasis occurs across the visual field with a clear spatio-temporal tuning. Furthermore, we report chronostasis during simulated saccades, indicating that spurious retinal motion induced by the saccade is a prime origin of the phenomenon. PMID:23458677

Knöll, Jonas; Morrone, M Concetta; Bremmer, Frank

2013-05-01

139

Adaptive spatio-temporal filtering of multichannel surface EMG signals.  

PubMed

A motor unit (MU) is defined as an anterior horn cell, its axon, and the muscle fibres innervated by the motor neuron. A surface electromyogram (EMG) is a superposition of many different MU action potentials (MUAPs) generated by active MUs. The objectives of this study were to introduce a new adaptive spatio-temporal filter, here called maximum kurtosis filter (MKF), and to compare it with existing filters, on its performance to detect a single MUAP train from multichannel surface EMG signals. The MKF adaptively chooses the filter coefficients by maximising the kurtosis of the output. The proposed method was compared with five commonly used spatial filters, the weighted low-pass differential filter (WLPD) and the marginal distribution of a continuous wavelet transform. The performance was evaluated using simulated EMG signals. In addition, results from a multichannel surface EMG measurement fro from a subject who had been previously exposed to radiation due to cancer were used to demonstrate an application of the method. With five time lags of the MKF, the sensitivity was 98.7% and the highest sensitivity of the traditional filters was 86.8%, which was obtained with the WLPD. The positive predictivities of these filters were 87.4 and 80.4%, respectively. Results from simulations showed that the proposed spatio-temporal filtration technique significantly improved performance as compared with existing filters, and the sensitivity and the positive predictivity increased with an increase in number of time lags in the filter. PMID:16937162

Ostlund, Nils; Yu, Jun; Karlsson, J Stefan

2006-03-01

140

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

Microsoft Academic Search

A spatio-temporal model of housing price trends is developed that focuses on individual housing sales over time. The model allows for both the spatio-temporal lag effects of previous sales in the vicinity of each housing sale, and for general autocorrelation effects over time. A key feature of this model is the recognition of the unequal spacing between individual housing sales

Tony E. Smith; Peggy Wu

2009-01-01

141

Spatio-temporal evaluation of neck muscle activation during postural perturbations in healthy subjects  

Microsoft Academic Search

The purpose of this study was to examine the spatio-temporal activation of the sternocleidomastoid (SCM) and cervical extensor (CE) muscles with respect to the deltoid muscle onset during rapid voluntary upper limb movement in healthy volunteers. The repeatability and reliability of the spatio-temporal aspects of the myoelectric signals were also examined. Ten subjects performed bilateral and unilateral rapid upper limb

D. Falla; A. Rainoldi; R. Merletti; G. Jull

2004-01-01

142

Geostatistical Analysis of Spatio-Temporal Forest Fire Data  

NASA Astrophysics Data System (ADS)

Forest fire is one of the major phenomena causing degradation of environment, landscape, natural ecosystems, human health and economy. One of the main topic in forest fire data studies deals with the detection, analysis and modelling of spatio-temporal patterns of clustering. Spatial patterns of forest fire locations, their sizes and their sequence in time are of great interest for fire prediction and for forest fire management planning and distribution in optimal way necessary resources. Currently, fires can be analyzed and monitored by using different statistical tools, for example, Ripley's k-function, fractals, Allan factor, scan statistics, etc. Some of them are adapted to temporal or spatial data and are either local or global. In the present study the main attention is paid to the application of geostatistical tools - variography and methods for the analysis of monitoring networks (MN) clustering techniques (topological, statistical and fractal measures), in order to detect and to characterize spatio-temporal forest fire patterns. The main studies performed include: a) analysis of forest fires temporal sequences; b) spatial clustering of forest fires; c) geostatistical spatial analysis of burnt areas. Variography was carried out both for temporal and spatial data. Real case study is based on the forest-fire event data from Canton of Ticino (Switzerland) for a period of 1969 to 2008. The results from temporal analysis show the presence of clustering and seasonal periodicities. Comprehensive analysis of the variograms shows an anisotropy in the direction 30° East-North where smooth changes are detected, while on the direction 30° North-West a greater variability was identified. The research was completed with an application of different MN analysis techniques including, analysis of distributions of distances between events, Morisita Index (MI), fractal dimensions (sandbox counting and box counting methods) and functional fractal dimensions, adapted and applied to characterize spatio-temporal events. The results are compared with the reference patterns (no spatial clustering) simulated within the natural validity domains (forests). The research was partly supported by SNSF projects IZAIZO-12777 and 200020-121835.

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

2010-05-01

143

Spatio-Temporal Chaos in Yttrium Iron Garnet Films  

NASA Astrophysics Data System (ADS)

The spatio-temporal chaotic behavior of magnet spin wave states in thin films of Yttrium Iron Garnet is experimentally studied. Samples (12-37 ?m thick rectangular films) are placed in DC magnetic fields to align the atomic spins, which are then excited at resonant frequencies. Chaotic spin wave states result when surface modes of the film begin to interact above an excitation power threshold. We study the spatial correlation of the chaotic states of the sample by monitoring the magnetic moment at two positions on the film surface. The magnetic moments are detected by using coaxial loops mounted near the film surface and we can obtain time series corresponding to the signals at each position. We have analyzed the correlation between the two signals using both linear and nonlinear analysis techniques.

Goodridge, Chris; Rachford, Fred; Carroll, Tom; Pecora, Lou

1999-11-01

144

Inferring Synaptic Connectivity from Spatio-Temporal Spike Patterns  

PubMed Central

Networks of well-known dynamical units but unknown interaction topology arise across various fields of biology, including genetics, ecology, and neuroscience. The collective dynamics of such networks is often sensitive to the presence (or absence) of individual interactions, but there is usually no direct way to probe for their existence. Here we present an explicit method for reconstructing interaction networks of leaky integrate-and-fire neurons from the spike patterns they exhibit in response to external driving. Given the dynamical parameters are known, the approach works well for networks in simple collective states but is also applicable to networks exhibiting complex spatio-temporal spike patterns. In particular, stationarity of spiking time series is not required.

Van Bussel, Frank; Kriener, Birgit; Timme, Marc

2011-01-01

145

Spatio-Temporal Structure of Hooded Gull Flocks  

PubMed Central

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

Yomosa, Makoto; Mizuguchi, Tsuyoshi; Hayakawa, Yoshinori

2013-01-01

146

Spatio-temporal operator formalism for holographic recording and diffraction in a photorefractive-based true-time-delay phased-array processor.  

PubMed

We present a spatio-temporal operator formalism and beam propagation simulations that describe the broadband efficient adaptive method for a true-time-delay array processing (BEAMTAP) algorithm for an optical beamformer by use of a photorefractive crystal. The optical system consists of a tapped-delay line implemented with an acoustooptic Bragg cell, an accumulating scrolling time-delay detector achieved with a traveling-fringes detector, and a photorefractive crystal to store the adaptive spatio-temporal weights as volume holographic gratings. In this analysis, linear shift-invariant integral operators are used to describe the propagation, interference, grating accumulation, and volume holographic diffraction of the spatio-temporally modulated optical fields in the system to compute the adaptive array processing operation. In addition, it is shown that the random fluctuation in time and phase delays of the optically modulated and transmitted array signals produced by fiber perturbations (temperature fluctuations, vibrations, or bending) are dynamically compensated for through the process of holographic wavefront reconstruction as a byproduct of the adaptive beam-forming and jammer-excision operation. The complexity of the cascaded spatial-temporal integrals describing the holographic formation, and subsequent readout processes, is shown to collapse to a simple imaging condition through standard operator manipulation. We also present spatio-temporal beam propagation simulation results as an illustrative demonstration of our analysis and the operation of a BEAMTAP beamformer. PMID:14503701

Kiruluta, Andrew; Pati, Gour S; Kriehn, Gregory; Silveira, Paulo E X; Sarto, Anthony W; Wagner, Kelvin

2003-09-10

147

Patterns of Urban Violent Injury: A Spatio-Temporal Analysis  

PubMed Central

Objectives 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. Methodology/Principal Findings 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. Conclusions/Significance 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.

Cusimano, Michael; Marshall, Sean; Rinner, Claus; Jiang, Depeng; Chipman, Mary

2010-01-01

148

Spatio-temporal clustering of wildfires in Portugal  

NASA Astrophysics Data System (ADS)

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.

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

2012-04-01

149

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

SciTech Connect

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

Gaffney, S; Smyth, P

2001-01-10

150

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

NASA Astrophysics Data System (ADS)

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

Baumann, Peter

2014-05-01

151

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

NASA Astrophysics Data System (ADS)

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.

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

2014-01-01

152

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

153

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

PubMed Central

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

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

2013-01-01

154

Spatio-Temporal Downscaling of Precipitation by means of a Weather Generator  

NASA Astrophysics Data System (ADS)

Hydrological extremes like floods and droughts are causing severe socio-economic damages. Distributed well parameterized precipitation-runoff models are able to reproduce important hydrological state variables (observed hydrographs, soil moisture among others). To assess the impacts of climate change on the hydrological cycle, information about the future state of the climatological system has to be taken into account. A standard approach consists on downscaling climate projections provided by Regional Climate Models (RCMs). RCM data is often resolved at spatio-temporal scales coarser than required by hydrological applications. Therefore, multiple statistical downscaling schemes, incorporating various mathematical techniques, have been developed over the past decades. One class of Statistical Downscaling schemes are Weather Generators (WG). These algorithms provide meteorological time series as the realization of a stochastic process. First, single- and multi-site models were developed, whereas recently, the generation at sub-daily scales and on gridded spatial resolution has been of increasing interest. Most of the WG incorporate the monthly cycle of precipitation by deriving parameter sets for each calendar month of the year. Given these fixed parameters, it implies that precipitation variability at these scales are underestimated. An important subset of WG are Multi-Scale WG, for which the scaling laws have been revised, since finer resolved rainfall data has become available. This led to statistically more sound scaling procedures, such as copula-based downscaling schemes. In this work, a framework for a Multi-Scale WG is proposed, which exploits the statistical scaling behavior expressed by copulas. This methodology ensures that precipitation properties are matched at various spatial and temporal scales, ranging from 4km to 32km, and from days to seasons, respectively. The basic idea is to generate rainfall occurrences and intensities conditioned on the values at larger spatio-temporal scales, for which the strongest dependence was identified. Furthermore, it exploits the fact, that precipitation properties are easier to represent at resolutions being rather coarse than fine. For instance the probability of a dry time step is significant at daily and sub-daily scales, but decreases to zero as weekly or even monthly and seasonal time periods are considered (depending on the region). This study incorporates a gridded, daily data set for the domain of Germany, which was made available by the German Weather Service. This data set spans over the time period from 1961 to 2000 at a 1~km resolution and incorporates data from rain gauges under the assumption, that the elevation, location and aspect govern the main climatological properties of rainfall distribution. This data was aggregated to the different spatio-temporal scales investigated in this study. The proposed methodology provides statistically reasonable precipitation time series at the resolution required by hydrological applications. Moreover, it is able to realistically resemble rainfall variability at coarser spatio-temporal scales. Nevertheless, it remains an open question, whether rainfall extremes, which are not covered by RCMs, are satisfactorily represented.

Thober, S.; Samaniego, L. E.

2012-12-01

155

Yes/No Discrimination With Spatio-Temporal Characteristics of EEG.  

National Technical Information Service (NTIS)

Yes/No discrimination using spatio-temporal characteristics of EEG is investigated. For the correlation between EEG signals, we introduce two new representations useful in time domain calculation, synchronization rate and polarity. Using synchronization r...

M. Kim S. Shin Y. Song C. S. Ryu

2001-01-01

156

Workload induced spatio-temporal distortions and safety of flight  

SciTech Connect

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

Barrett, C.L.; Weisgerber, S.A. (Los Alamos National Lab., NM (USA); Naval Weapons Center, China Lake, CA (USA))

1989-01-01

157

A Synthetic Surface that Undergoes Spatio-temporal Remodeling  

PubMed Central

The ability to undergo spatially resolved remodeling within defined time domains is one of the ubiquitous features of nature. In fact, essentially any biological structure undergoes defined molecular interactions and exhibits lateral mobility within defined time domains. The impartment of surface mobility has therefore emerged as one of the key challenges, when engineering synthetic analogues of natural biointerfaces. Herein, we now report a synthetic analogue based on self-assembled monolayers that can undergo spatial remodeling on demand, thereby effectively mimicking nature’s spatio-temporally controlled biointerfaces. First, we created microstructured surfaces, where the structural differences between different regions originated from differences in the molecular density of the nanofilm, while the chemical composition of all regions remained identical. We then demonstrated thermally-controlled, lateral mobility of thiolates between different regions of density and found that there exists appropriate threshold temperatures, from where on continuous lateral diffusion of thiolates may occur within the plane of the gold surface until steady-state equilibrium with an average surface density is reached. The ability to remodel interfaces on demand is a key characteristic of natural systems, which we now begin to mimic through synthetic model systems. Engineered biointerfaces, which can undergo spatially and temporally controlled remodeling, will be of utmost importance for a range of applications including molecular devices, biosensors, and future biomaterials.

Peng, David K.; Ahmadi, Allen A.; Lahann, Joerg

2009-01-01

158

A Spatio-Temporal Speech Enhancement Technique Based on Generalized Eigenvalue Decomposition  

Microsoft Academic Search

We present a new spatio-temporal algorithm for speech enhancement using microphone arrays. Our technique uses an iterative method for computing the generalized eigenvectors of the multichannel data as measured from the microphone array. Coefficient adaptation is performed using the spatio-temporal correlation coefficient sequences of the observed data. The technique avoids large matrix-vector multiplications and has lower computational resource requirements as

Malay Gupta; Scott C. Douglas

2009-01-01

159

Self-organized development of behaviors in spatio-temporal dynamical systems  

Microsoft Academic Search

Nonlinear distributed modeling is applied to generate conditions for the emergence of intentional behaviors afforded by the environment. The models are based on a nondeterministic dynamical approach to self-organized formation of categories using chaotic principles. Continuous and discrete models of the spatio-temporal dynamics are shown to exhibit phase transitions manifested in the form of intermittent spatio-temporal structures, which are studied

Robert Kozma; Paul Balister; Bela Bollobas

2002-01-01

160

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

Microsoft Academic Search

This paper presents a set of methods and techniques for analysis and multidimensional visualisation of crime scenes in a German\\u000a city. As a first step the approach implies spatio-temporal analysis of crime scenes. Against this background a GIS-based application\\u000a is developed that facilitates discovering initial trends in spatio-temporal crime scene distributions even for a GIS untrained\\u000a user. Based on these

Markus Wolff; Hartmut Asche

2009-01-01

161

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

NASA Astrophysics Data System (ADS)

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.

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

162

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

PubMed Central

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

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

2013-01-01

163

Spatio-temporal drought forecasting within Bayesian networks  

NASA Astrophysics Data System (ADS)

Spatial variations of future droughts across the Gunnison River Basin in CO, USA, are evaluated in this study, using a recently developed probabilistic forecast model. The Standardized Runoff Index (SRI) is employed to analyze drought status across the spatial extent of the basin. The runoff generated at each spatial unit of the basin is estimated by a distributed-parameter and physically-based hydrologic model. Using the historical runoff at each spatial unit, a statistical forecast model is developed within Bayesian networks. The forecast model applies a family of multivariate distribution functions to forecast future drought conditions given the drought status in the past. Given the runoff in the past (January-June), the forecast model is applied in estimating the runoff across the basin in the forecast period (July-December). The main advantage of the forecast model is its probabilistic features in analyzing future droughts. It develops conditional probabilities of a given forecast variable, and returns the highest probable forecast along with an assessment of the uncertainty around that value. Bayesian networks can also estimate the probability of future droughts with different severities, given the drought status of the predictor period. Moreover, the model can be used to generate maps showing the runoff variation over the basin with the particular chance of occurrence in the future. Our results indicate that the statistical method applied in this study is a useful procedure in probabilistic forecast of future droughts given the spatio-temporal characteristics of droughts in the past. The techniques presented in this manuscript are suitable for probabilistic drought forecasting and have potential to improve drought characterization in different applications.

Madadgar, Shahrbanou; Moradkhani, Hamid

2014-05-01

164

Spatio-temporal coupling of EEG signals in epilepsy  

NASA Astrophysics Data System (ADS)

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.

Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

2011-05-01

165

Quantifying spatio-temporal variability of soil water storage and their controls at multiple scales  

NASA Astrophysics Data System (ADS)

Soil water is the primary limiting factor in semiarid ecosystems and determinant of environmental health. The distribution of soil water in space and time has important hydrologic applications. However, the spatio-temporal variability of soil water is a major challenge in hydrology as their distribution in the landscape is controlled many factors and processes acting in different intensities over a variety of scales. Quantification of these variability and their dominant controls at multiple scales can only lead to a better understanding on the soil water dynamics in space and time and on the underlying processes causing the variability. In order to quantify spatio-temporal variability, soil water content (later converted to soil water storage, SWS) was measured down to 1.4 m (0.2 m depth interval) at 128 regularly spaced locations along a transect of 576 m over a five-year period from the Hummocky landscape of central Canada. The spatial pattern of SWS was very similar (large values of Spearman's rank correlation coefficient) over the entire study period and was almost a mirror image of the spatial pattern of the relative elevation. The similarity was stronger within a season (intra-season) than the same season from different years (inter-annual) and between seasons (inter-season). The variability at multiple scales was quantified using the wavelet transform. The strongest large scale (>72 m) variability contributed from the macro-topography and a moderate medium scale (18-72 m) variability contributed from the landform elements were persistent over the entire measurement period (time stability). The locations and the scales of the most persistent spatial patterns over time and depth were quantified using the wavelet coherency. The changes in the persistent patterns indicated the changes in the scales and locations of underlying hydrological processes, which can be used to identify change in sampling domain. The similarities/dissimilarities in the spatial pattern between the surface and sub-surface measurements at different scales and locations were used to infer the whole profile hydrological dynamics (depth persistence). The variability in SWS spatial patterns was controlled by different factors at different scales. Scale specific dominant controls were identified after separating the variance contribution of each scale towards the overall variance using the Hilbert-Huang transform. The large scale macro-topographical control and medium scale landform control were much stronger than very large scale soil textural control on SWS. The scale-specific relationship with controlling factors improved the prediction of SWS.

Biswas, Asim

2014-05-01

166

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

PubMed Central

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.

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

2014-01-01

167

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

PubMed

Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME) infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS)], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER)], and socio-economic conditions (US Census Bureau) were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases. PMID:24992684

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

2014-01-01

168

Spatio-temporal correlations in human gamma band electrocorticograms.  

PubMed

Animal electrocorticogram (ECoG) studies have shown that spatial patterns in the gamma band (>20 Hz) reflect perceptual categorization. Spatio-temporal correlations were investigated in the 20-50 Hz range in search for similar phenomena in human ECoG. ECoGs were recorded in a somatosensory discrimination task from 64-electrode subdural grid arrays, with inter-electrode spacing of 1 cm, overlying somatosensory, motor and superior temporal cortices in 2 patients with intractable epilepsy. Bootstrap techniques were devised to analyze the spatial and temporal characteristics of the correlations. Despite an extensive search, no evidence was found for globally correlated activity related to behavior either in narrow (1.e., 35-45 Hz) or broad (i.e., 20-50 Hz) bands. Spatial patterns, extracted using principal component analysis, could not be classified with respect to stimulus type in any time interval. Instead, spatially and temporally intermittent synchronization was observed between pairs of electrodes in 1 cm X 1 cm regions with high variability within and across trials. The distribution of correlation coefficients differed substantially from background levels at inter-electrode distances of 1 cm and 1.4 cm but not 2 cm or more. The minimum duration of correlation, the decorrelation time, of the ECoG was about 50 msec; the average correlation duration at 1 cm inter-electrode distance was about 150 msec; and the recurrence rate of significant correlation peaks was about 1.3/sec. The findings suggest that the surface diameters of domains of spatially correlated activity underlying perceptual categorization in human gamma band ECoG are limited to less than 2 cm and that the intermittent synchronization observed across separations of 1 cm and 1.4 cm is not solely due to volume conduction. Thus, if such gamma band spatial patterns exist in the human brain, no existing technology would be capable of measuring them at the scalp, and subdural electrode arrays for cortical surface recording would have to have spacings under 5 mm. PMID:8598178

Menon, V; Freeman, W J; Cutillo, B A; Desmond, J E; Ward, M F; Bressler, S L; Laxer, K D; Barbaro, N; Gevins, A S

1996-02-01

169

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

NASA Astrophysics Data System (ADS)

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 numerical hydrological model. It appears that the outputs (maps of water depth and velocity) of the hydrological model exhibit a scaling behaviour both in space and time. Various sets of UM parameters are tested. The three UM parameters of the various processes at stake are then compared which enables to analyse how the extremes are either dampened or enhanced. This hints at innovative techniques to quantify the extremes at very high resolution (typically 1 m) without having to run the model at these resolutions which would require too much time especially for real time applications.

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

2014-05-01

170

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

NASA Astrophysics Data System (ADS)

Contemporary anthropogenic climatic warming is having an accelerated, and more pronounced effect upon Arctic regions than any other environment on Earth. Increased surface temperatures have led to widespread permafrost degradation and a shift in dynamics. One landscape manifestation of localised permafrost decay, seen to be ubiquitous across low-lying tundra regions of Alaska, Canada and Siberia, is the thermokarst lake - or 'thaw' lake. These features are seen to be truly dynamic, with a relatively rapid evolution and decay. The exact impacts of climatic perturbation on thaw lake development are in contention; however, recent studies have suggested an increased vulnerability of these features, owing to the susceptibility of the fundamental processes of initiation, expansion and drainage to climatic variation. It is often hypothesised that with current trends, thaw lakes will see a net increase in expansion rate, and areal extent, with a potential for increased drainage events. Increased permafrost thaw and thermokarst activity has also led to shifts in biogeochemical cycles, leading to an amplified release from large carbon reservoirs currently sequestered within permafrost. An example of carbon release exhibited from thaw lakes is that of methane ebullition (gas bubble formation); this has been theorised to have the potential to initiate a major positive climatic feedback leading to a continued rise in global temperatures. Due to the remote nature and large area over which these landforms occur, remotely sensed data has been widely used in order to both accurately classify features and measure change over spatially large and great temporal extents. As well as studies interpreting data collected in the visible and near-infrared spectra, studies have recently made use of radar or microwave products in order to capture imagery avoiding adverse atmospheric conditions, most notably cloud cover. Data from Envisat ASAR operating in Wide Swath Mode was acquired for this study region; however, the core of this research relied upon the analysis of the changing lake morphology using visible and near-infrared spectra from MODIS and Landsat products. This research explored: (1) intra-annual variability of freeze-thaw cycles and resultant effects on thaw lake development; and (2) the spatio-temporal trends and changing dynamism of thaw lake activity. Research presented here within suggests that although climatic trends do indeed influence widespread changes within thaw lake characteristics, site-specific phenomena of sediment type and ice-content and fluvial activity also play integral roles. Understanding and observing changing spatio-temporal dynamics, particularly on an intra-annual basis, has helped to gather more information concerning complex lake processes, and increase the understanding of permafrost decay and thaw lake development.

Cooper, Michael; Rees, Gareth; Bartsch, Annett

2014-05-01

171

Coherent spatio-temporal coupling in fractional wanderings. Renewed approach to continuous-time Lévy flights  

NASA Astrophysics Data System (ADS)

The one-dimensional continuous-time Lévy flights (CTLF) are reconsidered in the renewed framework of the nonseparable continuous-time random walk (CTRW) model in order to be able to treat the spatio-temporal relations in terms of the self-similar structure of the Lévy process. Hence, a novel spatio-temporal coupling is introduced by assuming that in each order of the structure the probability density for the flight and for waiting are joined. This (stochastic) structure is characterized by the spatial fractional dimension 1/? (representing the flights) and the temporal one 1/? (representing the waiting). Time was assumed here as the only independent truncation range. In the present work we study the asymptotic properties of our procedure. For example, by applying the method of steepest descents we obtained the particle propagator in the approximate scaling form, P(X, t) ˜ t -?(?,?)/2 F(?), where the scaling function {F}(? ) = ? bar v(&alpha,? ) exp(-const(?,?) ?v(??)) and the scaling variable ? =| X | /t ?(?,?)/2 is large. The principal result of our analysis is that the exponents ?, ? and bar \\upsilon depend on more fundamental, fractional dimensions ? and ?, what leads to a novel scaling. As a result of competition between exponents ? and ? an enhanced, dispersive or normal diffusion was recognized for a given topology of the structure in distinction from the prediction of the commonly used separable CTRW model where the enhanced diffusion is lost and the dispersive one is strongly limited. We compare here partially thermalized versions of both approaches where some initial fluctuations were also included in agreement with the spirit of the theory of the renewal processes. Having the propagator we calculated, for example, the mean-square displacement and found its novel scaling with time for enhanced particle diffusion, given by ˜ t 1+?(2/?-1), in distinction from its diverging for ?<2 within the separable CTRW model. This renewed CTLF approach offers a possibility to properly model the time-dependence for any fractional (critical) wandering of jump type.

Kutner, R.

172

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

PubMed

1.?Flows of nutrients and energy across ecosystem boundaries have the potential to subsidize consumer populations and modify the dynamics of food webs, but how spatio-temporal variations in autochthonous and allochthonous resources affect consumers' subsidization remains largely unexplored. 2.?We studied spatio-temporal patterns in the allochthonous subsidization of a predator living in a relatively simple ecosystem. We worked on Bylot Island (Nunavut, Canada), where arctic foxes (Vulpes lagopus L.) feed preferentially on lemmings (Lemmus trimucronatus and Dicrostonyx groenlandicus Traill), and alternatively on colonial greater snow geese (Anser caerulescens atlanticus L.). Geese migrate annually from their wintering grounds (where they feed on farmlands and marshes) to the Canadian Arctic, thus generating a strong flow of nutrients and energy across ecosystem boundaries. 3.?We examined the influence of spatial variations in availability of geese on the diet of fox cubs (2003-2005) and on fox reproductive output (1996-2005) during different phases of the lemming cycle. 4.?Using stable isotope analysis and a simple statistical routine developed to analyse the outputs of a multisource mixing model (SIAR), we showed that the contribution of geese to the diet of arctic fox cubs decreased with distance from the goose colony. 5.?The probability that a den was used for reproduction by foxes decreased with distance from the subsidized goose colony and increased with lemming abundance. When lemmings were highly abundant, the effect of distance from the colony disappeared. The goose colony thus generated a spatial patterning of reproduction probability of foxes, while the lemming cycle generated a strong temporal variation of reproduction probability of foxes. 6.?This study shows how the input of energy owing to the large-scale migration of prey affects the functional and reproductive responses of an opportunistic consumer, and how this input is spatially and temporally modulated through the foraging behaviour of the consumer. Thus, perspectives of both landscape and foraging ecology are needed to fully resolve the effects of subsidies on animal demographic processes and population dynamics. PMID:22268371

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

2012-05-01

173

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

NASA Astrophysics Data System (ADS)

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 autoregressive filter models are considered, for a prediction of EEG signal values. Thus Signal features values for successive, short, quasi stationary segments of brain electrical activity can be obtained, with the objective of detecting distinct changes prior to impending epileptic seizures. Furthermore long term recordings gained during presurgical diagnostics in temporal lobe epilepsy are analyzed and the predictive performance of the extracted features is evaluated statistically. Therefore a Receiver Operating Characteristic analysis is considered, assessing the distinguishability between distributions of supposed preictal and interictal periods.

Gollas, Frank; Tetzlaff, Ronald

2009-05-01

174

Effects of single pulse TMS on spatio-temporal integration in sequential isochronus movements.  

PubMed

This study was designed to investigate the effect of single pulse transcranial magnetic stimulation (TMS) on the isochronic performance of sequential movements which were recorded using a digitising pad. Magnetic stimulation was applied through an 8-shaped magnetic coil over primary motor and premotor cortex at a specific time point while executing the first of a three movement sequence. TMS applied to the premotor cortex showed an alteration effect on the first movement while stimulation of the primary motor cortex influenced the second movement in the sequence. Results suggest that the premotor cortex is involved in online monitoring and controlling of spatio-temporal features of trajectories while the motor cortex contributes to the execution of movements. Isochrony is maintained to a high degree under TMS which has been found in other studies to delay reaction times. The results show that although TMS has a significant influence on motor performance, isochrony is a robust component of motor programs, not readily to be disturbed. PMID:15313035

Suchan, Boris; Wist, Eugene R; Hömberg, Volker

2004-10-01

175

Spatio-temporal variability of anions in wet precipitation of Cuiabá, Brazil  

NASA Astrophysics Data System (ADS)

Spatio-temporal variability in the ionic chemical composition of atmospheric precipitation samples was investigated at twenty-six points in Cuiabá city, Brazil, during three rainfall events from October 2009 to February 2010. All samples were analyzed for pH, electrical conductivity and ions: chloride (Cl-), fluoride (F-), nitrate (NO3-), sulfate (SO42 -) and phosphate (PO43 -). The spatial dependence and variability of the rainwater's ionic composition were evaluated through semivariograms and kriging. A large proportion of the samples were characterized as acid rain: 80.77% of samples in October, 80.77% in December, and 65.38% in February. The average concentrations of Cl-, F-, NO3-, SO42 -and PO43 - were 4.43, 0.29, 3.78, 1.00 and 0.02 ?eq L- 1, respectively. A strong correlation was observed between NO3-and SO42 - indicating a common anthropogenic origin of these anions. Maps generated by geostatistical techniques indicated that the highest anion concentrations occurred at the beginning of the rainy season in the industrial district and during periods of lower rainfall in the city center, indicating the important role of local emission sources.

Dias, Vanessa Rakel de Moraes; Sanches, Luciana; Alves, Marcelo de Carvalho; Nogueira, José de Souza

2012-04-01

176

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

NASA Astrophysics Data System (ADS)

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

Wolff, Markus; Asche, Hartmut

177

Spatio-temporal spread of competitive innovations: An ecological approach  

Microsoft Academic Search

This study proposes the continuous deterministic interaction model of the spread of a set of competitive innovations in space and time, and presents the Volterra-Lotka type vectorial differential equation of the diffusion process. Three major themes are considered: i) the competitive exclusion principle and the Markov chain's approximation of the diffusion process in the neighbourhood of equilibrium points, ii) the

Michael Sonis

1983-01-01

178

The spatio-temporal pattern of testis organogenesis in mammals - insights from the mole.  

PubMed

Some cellular events are crucial in testis organogenesis, including Sertoli and Leydig cell differentiation, mesonephric cell migration and testis cord formation. These processes are controlled by transcription factors, paracrine signalling and hormones. Using the mole species Talpa occidentalis as an alternative animal model, we report the expression patterns of nine genes during testis differentiation and analyse their implications in the above-mentioned cellular processes. We show that: 1) Sertoli cell differentiation occurs very early and precedes mesonephric cell migration, indicating that the latter is not needed for the endocrine cytodifferentiation of Sertoli cells; 2) the time of Leydig cell differentiation is consistent with the participation of PDGFR-alpha in promoting the migration and/or proliferation of Leydig cell precursors, and with that of WNT4 signalling in inhibiting Leydig cell differentiation and 3) the formation of the tunica albuginea involves intragonadal cell migration/movement. These results demonstrate that testicular organogenesis in the mole differs from that in the mouse in some particular aspects, thus providing evidence that the spatio-temporal pattern of testis development is not highly conserved during mammalian evolution. PMID:19598120

Carmona, Francisco D; Lupiáñez, Darío G; Martín, José-Ezequiel; Burgos, Miguel; Jiménez, Rafael; Zurita, Federico

2009-01-01

179

Radio-frequency discharges in oxygen: II. Spatio-temporally resolved optical emission pattern  

NASA Astrophysics Data System (ADS)

Axially and temporally resolved optical emission structures were investigated in the rf sheath region of a parallel plate capacitively coupled rf discharge (13.56 MHz) in pure oxygen and tetrafluoromethane. The rf discharge was driven at total pressures of between 10 and 100 Pa, gas flow rate of 3 sccm and rf power in the range 5-100 W. In particular, the emission of the atomic oxygen at 844.6 nm (3p3P ? 3s3S0) and the atomic carbon at 193 nm (3s1P0 ? 2p1D) were imaged with a lens onto the entrance slit of a spectrometer and detected by a fast ICCD-camera. The spatio-temporally resolved analysis of the emission intensity during the rf cycle (73.75 ns) provides two significant excitation processes inside the rf sheath: the electron impact excitation at the sheath edge, and heavy particle impact excitation in front of the powered electrode. In oxygen plasma the emission of atomic oxygen was found in both regions whereas in tetrafluoromethane the emission of atomic carbon was observed only in front of the powered electrode. The experimental results reveal characteristic dependence of the emission pattern in front of the powered electrode on plasma process parameters (self-bias voltage, pressure) and allow an estimation of the excitation threshold energy and effective cross section of energetic heavy particle loss.

Dittmann, K.; Drozdov, D.; Krames, B.; Meichsner, J.

2007-11-01

180

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

NASA Astrophysics Data System (ADS)

Integrated risk management consists of risk prevention, early warning, intervention during an event and restoration/re-construction after an event. The prevention phase consists of land use planning measures with a long-term time horizon and of structural measures that sometimes have a lifespan of more than 30-50 years. In this case, it is important to analyse the long-term evolvement of natural risks due to climate changes or land use changes. Besides of this, the spatial and temporal variability of a natural hazard process during the course of an event is also important. The shift from "static" hazard and risk assessment towards a "dynamic" assessment offers benefits for improving the intervention phase in risk management. This contribution describes some examples and points out the benefits of this shift for risk management. One example is the variable disposition of small alpine catchments for runoff and its relevance for early warning. The disposition for runoff depends on the actual status of environmental variables such as soil moisture and the snowpack characteristics. A feasibility study showed how the monitoring of soil moisture and the status of the snowpack can be incorporated into a rule base for describing the temporal variability of the disposition for high runoff in alpine catchments. The study showed that this information about the system state of alpine catchments can be used to improve the assessment of the consequences of a weather forecast for risk management. Another example is the use of snowpack and weather monitoring and traffic intensity measurements for avalanche risk management on alpine roads. Here, the information about the spatio-temporal variability of the snow avalanches and the presence of vehicles can be used for improving the procedures for road closure and re-opening. Another example is the preparation of intervention plans for fire brigades and other relief units during urban floods. The simulation of the temporal evolvement of a single flood event (time horizon of 0-24 hours) provides information for the elaboration of the intervention tactic. The following questions can be answered only by knowing the temporal and spatial evolvement during an event itself: Which intervention priorities have to be set if the resources of the relief units are limited? Which early interventions could be turn out to be unhelpful because in a later step the object to be protected will be flooded anyway? What is the time available for setting up object protection measures and other flood protection measures? The most important factor to implement the theory in practice is the focus on the interlinkages between the simulation of all possible scenarios in advance (scenario techniques, analysing the time-steps in flood simulation), the monitoring system (now-casting, real-time-data), the scenarios of intervention measures and their interdependency with the hazard scenarios. The interlinkages can be set up and described with the expert system approach.

Zischg, Andreas

2013-04-01

181

Directly measuring the spatio-temporal electric field of focusing ultrashort pulses.  

PubMed

We present the first technique for directly measuring (without assumptions) the spatio-temporal intensity and phase of a train of ultrashort pulses at and near a focus. Our method uses an experimentally simple and high-spectral resolution variant of spectral interferometry (SEA TADPOLE). To illustrate our technique, we measured the spatio-temporal electric field in and around the foci of several different types of lenses. To confirm our results, we also simulated these measurements by numerically propagating a pulse through each of the lenses used. From one set of measurements, we made a movie showing a focusing pulse with severe chromatic aberration. PMID:19547371

Bowlan, Pamela; Gabolde, Pablo; Trebino, Rick

2007-08-01

182

X-ray fluoroscopy spatio-temporal filtering with object detection  

SciTech Connect

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%.

Aufrichtig, R. [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering] [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering; Wilson, D.L. [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering] [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering; [University Hospitals of Cleveland, OH (United States). Dept. of Radiology

1995-12-01

183

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

PubMed Central

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

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

2011-01-01

184

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

PubMed

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

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

2011-04-01

185

Interactive visual exploration of a large spatio-temporal dataset: reflections on a geovisualization mashup.  

PubMed

Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporaldatasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the dataset, the specific tools used and the 'mashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here. PMID:17968062

Wood, Jo; Dykes, Jason; Slingsby, Aidan; Clarke, Keith

2007-01-01

186

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

PubMed

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

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

2009-02-15

187

Bayesian spatio-temporal discard model in a demersal trawl fishery  

NASA Astrophysics Data System (ADS)

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.

Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.

2014-07-01

188

Identification of myocardial infarction (MI) using spatio-temporal heart dynamics.  

PubMed

Cardiovascular disorders, such as myocardial infarction (MI) are the leading causes of mortality in the world. This paper presents an approach that uses novel spatio-temporal patterns of the vectorcardiogram (VCG) signals for the identification of various types of MI. In contrast to the traditional electrocardiogram (ECG) approaches, the 3D cardiac VCG signal is partitioned into 8 octants for localized analysis of the heart's electrical activities. The proposed method was tested using the PhysioNet PTB database for 368 MIs and 80 healthy control (HC) recordings, each of which includes 12-lead ECG and 3-lead VCG. Significant differences are found in the VCG spatial distribution between MI and HC groups. Furthermore, classification and regression tree (CART) analysis was used to demonstrate that VCG octant features can distinguish MIs from HCs with a sensitivity (accuracy of MI identification) of 97.28% and a specificity (accuracy of HC identification) of 95.00%, which is promising compared to the previously reported results using other ECG databases. The results indicate that the present approach provides an effective way for monitoring, post-processing, and interpretation of ECG data, and hopefully can impact the current cardiac diagnostic practice. PMID:21940193

Yang, Hui; Bukkapatnam, Satish T S; Le, Trung; Komanduri, Ranga

2012-05-01

189

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

NASA Astrophysics Data System (ADS)

Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB heterogeneity over time was observed for heavy grazing intensity. All grazing intensities showed decrease in spatial range (patch size) over time indicating that grazing is a patchy process. The study demonstrates that cattle grazing with variable intensity can maintain and change the spatial patterns of vegetation in the studied region. Using a modelling approach, the relative degrees to which grazing intensity and soil properties affect grassland productivity and carbon dynamics at longer time-periods were investigated. Both grass productivity and carbon dynamics are sensitive to variability in soil texture and grazing intensity. Moderate grazing is predicted to be the best option in terms of maintaining sufficient heterogeneity to support species diversity, as well as for carbon management in the mixed grassland ecosystem.

Virk, Ravinder

190

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

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

191

Circles on pommel horse with a suspended aid: Spatio-temporal characteristics  

Microsoft Academic Search

A suspended aid is popular for learning circles and for refining circle technique on pommel horse. The aim of this study was to investigate the effect of using a suspended aid on the biomechanical characteristics of circles. This first study focused specifically on the spatio-temporal characteristics of circles. Eighteen gymnasts performed three sets of 10 circles with and without a

Toshiyuki Fujihara; Pierre Gervais

2012-01-01

192

Spatio-temporal relationship match: Video structure comparison for recognition of complex human activities  

Microsoft Academic Search

Human activity recognition is a challenging task, es- pecially when its background is unknown or changing, and when scale or illumination differs in each video. Approaches utilizing spatio-temporal local features have proved that they are able to cope with such difficulties, but they mainly focused on classifying short videos of simple periodic actions. In this paper, we present a new

Michael S. Ryoo; Jake K. Aggarwal

2009-01-01

193

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

NASA Astrophysics Data System (ADS)

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

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

2001-12-01

194

Spatio-temporal variation of vegetation in an arid and vulnerable coal mining region  

Microsoft Academic Search

Environmental assessment in an arid coal mining area requires an understanding of the influences of coal mining, the arid climate and ecological remediation. To that end, we selected vegetation as the key environmental factor to observe. Remote sensing approaches to monitoring the spatio-temporal variation of vegetation caused by mining activities, the arid climate and ecological remediation in the Shengdong coal

Shaogang LEI; Zhengfu BIAN; John L DANIELS; Xiao HE

2010-01-01

195

Hierarchical modeling of spatio-temporally misaligned data: relating traffic density to pediatric asthma hospitalizations  

Microsoft Academic Search

this paper we extend this hierarchical modeling approachto the spatio-temporal case, so that misalignment can arise either within a given timepoint,or across timepoints (as when the regional boundaries themselves evolve over time). Implementedusing Markov chain Monte Carlo computing methods, our approach sensibly combines the relevantdata sources and imposes the necessary constraints over the misaligned regional grids. Weillustrate the method through

Li Zhu; Bradley P. Carlin; Paul English; Russell Scalf

2000-01-01

196

Blind separation of spatio-temporal Synfire sources and visualization of neural cliques  

Microsoft Academic Search

A dominating paradigm in neuroscience attributes components of perception and behavior to synchronous spatio-temporal activities of subsets of neurons within neural networks { the so-called Synflre chains. Synflre chains cohere to generate neural cliques within the simultaneously active Synflres. The present study is con- cerned with blind separation of Synflre activities and identiflcation of neural cliques. Assuming stationarity and, to

Hilit Unger; Yehoshua Y. Zeevi

2006-01-01

197

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

Microsoft Academic Search

Effective drought planning and mitigation requires an understanding of water supply and demand, including historical biophysical and legal conditions that lead to water shortages among various end-users. With the goal of providing information that is useful for managing current drought risks and for adapting to changing climate, this project aims to fill the gaps in the knowledge about spatio-temporal variations

K. M. Sampson; O. Wilhelmi

2009-01-01

198

Shadowing - Tracking - Interviewing: How to Explore Human Spatio-Temporal Behaviour Patterns  

Microsoft Academic Search

The complexity of pedestrian spatio-temporal behaviour calls for the combination of several complementary empirical methods in order to comprehen- sively understand human motion behaviour patterns and underlying motives, habits and intentions. This is essential for the development of mobile spatial information technologies, as the huge amount of potentially available information has to be fil- tered and customised to individual needs.

Alexandra Millonig; Georg Gartner

2008-01-01

199

Spatio-temporal array (STAR) DS-CDMA systems: localized scattering channel estimation  

Microsoft Academic Search

This paper is concerned with the problem of channel estimation for asynchronous DS-CDMA systems in the presence of local scattering of the multipaths. Based on a first order Taylor series expansion, the manifold vector associated with a locally scattered multipath is formulated and a new channel estimation algorithm is proposed. The proposed algorithm hinges on the spatio-temporal array (STAR) manifold

T. S. Naveendra; A. Manikas

2002-01-01

200

A Fully Automated Content Based Video Search Engine Supporting Spatio-Temporal Queries  

Microsoft Academic Search

The rapidity with which digital information, particularlyvideo, is being gener- ated, has necessitated the development of tools for efficien t search of these media. Content based visual queries have been primarily focused on still image retrieval. In this paper, we propose a novel, interactive system on the W eb, based on the visual paradigm, with spatio-temporal attributes playinga key role

Shih-Fu Chang; William Chen; Horace J. Meng; Hari Sundaram

1997-01-01

201

Discussion on synthesis of non linear spatio-temporal systems with unstable zeros dynamics  

Microsoft Academic Search

This paper deals with multivariable control problem of spatio-temporal systems modelled by non linear partial differential equations (PDEs). SISO control of distributed parameter systems (DPS) can be achieved either by late or by early approaches. In practice, there are mainly two reasons why MIMO control of DPS, which can provide an analytical law of a distributed controller, could be impossible

Ova BOUBAKER; F. Cherif

2004-01-01

202

Improvement in Tile Quality of Vidio Signals by Spatio-Temporal Data-Dependent Filtering  

Microsoft Academic Search

The restoration of video signals corrupted by the additive noise is important for getting the high quality video and the high compression ratio of video signals. In this paper, we propose a novel restoration method for video signals corrupted by the Gaussian noise. Conventional methods use the spatio-temporal filtering after the motion compensation. However, the accuracy of the motion compensation

S. Saitoh; A. Taguchi; H.-B. Ryu

2006-01-01

203

Evaluating the impact of spatio-temporal scale on CPUE standardization  

NASA Astrophysics Data System (ADS)

This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE (catch per unit effort). We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales, with a combination of four levels of temporal scale (weekly, biweekly, monthly, and bimonthly) and six levels of spatial scale (longitude×latitude: 0.5°×0.5°, 0.5°×1°, 0.5°×2°, 1°×0.5°, 1°×1°, and 1°×2°). We applied generalized additive models and generalized linear models to analyze the 24 scenarios for CPUE standardization, and then the differences in the standardized CPUE among these scenarios were quantified. This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE. However, at a fine temporal scale (weekly) different spatial scales yielded similar results for standardized CPUE. The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management. To identify a cost-effective spatio-temporal scale for data collection, we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.

Tian, Siquan; Han, Chan; Chen, Yong; Chen, Xinjun

2013-09-01

204

The Auckland volcanic field, New Zealand: Geophysical evidence for structural and spatio-temporal relationships  

Microsoft Academic Search

Geophysical data from the monogenetic Auckland volcanic field reveal complex structural and spatio-temporal relationships at different scales. The volcanic field is coincident with regional magnetic and gravity anomalies that mark a major crustal suture and with a discontinuity marking a significant structural asperity. Here, the linear regional magnetic anomaly splays into a wide band of NNW-trending lineaments, arising from serpentinised

John Cassidy; Corinne A. Locke

2010-01-01

205

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

NASA Astrophysics Data System (ADS)

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.

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

2012-07-01

206

Developmental regulation of spatio-temporal patterns of cortical circuit activation  

PubMed Central

Neural circuits are refined in an experience-dependent manner during early postnatal development. How development modulates the spatio-temporal propagation of activity through cortical circuits is poorly understood. Here we use voltage-sensitive dye imaging (VSD) to show that there are significant changes in the spatio-temporal patterns of intracortical signals in primary visual cortex (V1) from postnatal day 13 (P13), eye opening, to P28, the peak of the critical period for rodent visual cortical plasticity. Upon direct stimulation of layer 4 (L4), activity spreads to L2/3 and to L5 at all ages. However, while from eye opening to the peak of the critical period, the amplitude and persistence of the voltage signal decrease, peak activation is reached more quickly and the interlaminar gain increases with age. The lateral spread of activation within layers remains unchanged throughout the time window under analysis. These developmental changes in spatio-temporal patterns of intracortical circuit activation are mediated by differences in the contributions of excitatory and inhibitory synaptic components. Our results demonstrate that after eye opening the circuit in V1 is refined through a progression of changes that shape the spatio-temporal patterns of circuit activation. Signals become more efficiently propagated across layers through developmentally regulated changes in interlaminar gain.

Griffen, Trevor C.; Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

2013-01-01

207

Classification of Traffic Events based on the Spatio-Temporal MRF Model and the Bayesian Network  

Microsoft Academic Search

In order to support safe and efficient driving, it is important to classify the behaviors of vehicles and to understand what is going on the traffic situations. For that purpose, our system employed a vision sensor rather than spot sensors because of its rich information. We then have developed a dedicated vehicle tracking algorithm based on the Spatio-Temporal MRF model

Shunsuke KAMIJO Masao SAKAUCHI

2002-01-01

208

Querying Spatio-temporal Patterns in Mobile Phone-Call Databases  

Microsoft Academic Search

Call Detail Record (CDR) databases contain many millions of records with information about mobile phone calls, including the users' location when the call was made\\/received. This huge amount of spatio-temporal data opens the door for the study of human trajectories on a large scale without the bias that other sources, like GPS or WLAN networks, introduce in the population studied.

Marcos R. Vieira; Enrique Frías-Martínez; Petko Bakalov; Vanessa Frías-Martínez; Vassilis J. Tsotras

2010-01-01

209

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

PubMed Central

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

Saglam, Bulent; Bilgili, Ertugrul; Durmaz, Bahar Dinc; Kad?ogullar?, Ali Ihsan; Kucuk, Omer

2008-01-01

210

Parameter Estimation for Spatio-Temporal Maximum Entropy Distributions: Application to Neural Spike Trains  

NASA Astrophysics Data System (ADS)

We propose a numerical method to learn Maximum Entropy (MaxEnt) distributions with spatio-temporal constraints from experimental spike trains. This is an extension of two papers [10] and [4] who proposed the estimation of parameters where only spatial constraints were taken into account. The extension we propose allows to properly handle memory effects in spike statistics, for large sized neural networks.

Nasser, Hassan; Cessac, Bruno

2014-04-01

211

Spectral element methods for nonlinear spatio-temporal dynamics of an Euler-Bernoulli beam  

NASA Astrophysics Data System (ADS)

Spectral element methods are high order accurate methods which have been successfully utilized for solving ordinary and partial differential equations. In this paper the space-time spectral element (STSE) method is employed to solve a simply supported modified Euler-Bernoulli nonlinear beam undergoing forced lateral vibrations. This system was chosen for analysis due to the availability of a reference solution of the form of a forced Duffing's equation. Two formulations were examined: i) a generalized Galerkin method with Hermitian polynomials as interpolants both in spatial and temporal discretization (HHSE), ii) a mixed discontinuous Galerkin formulation with Hermitian cubic polynomials as interpolants for spatial discretization and Lagrangian spectral polynomials as interpolants for temporal discretization (HLSE). The first method revealed severe stability problems while the second method exhibited unconditional stability and was selected for detailed analysis. The spatial h-convergence rate of the HLSE method is of order ?= p s+1 (where p s is the spatial polynomial order). Temporal p-convergence of the HLSE method is exponential and the h-convergence rate based on the end points (the points corresponding to the final time of each element) is of order 2 p T-1 ???2 p T+1 (where p T is the temporal polynomial order). Due to the high accuracy of the HLSE method, good results were achieved for the cases considered using a relatively large spatial grid size (4 elements for first mode solutions) and a large integration time step (1/4 of the system period for first mode solutions, with p T=3). All the first mode solution features were detected including the onset of the first period doubling bifurcation, the onset of chaos and the return to periodic motion. Two examples of second mode excitation produced homogeneous second mode and coupled first and second mode periodic solutions. Consequently, the STSE method is shown to be an accurate numerical method for simulation of nonlinear spatio-temporal dynamical systems exhibiting chaotic response.

Bar-Yoseph, P. Z.; Fisher, D.; Gottlieb, O.

1996-11-01

212

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

213

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

PubMed Central

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

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

2009-01-01

214

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

NASA Astrophysics Data System (ADS)

We present, for the first time, Ionospheric Total Electron Content (TEC) computed from dual frequency GPS data observed by Indian geodetic GPS network and neighboring IGS stations for more than a decade (2001-2012) (figure 1). Indian geodetic GPS network has more than 30 stations well spread across the Indian subcontinent, primarily, to study the tectonics of the Indian plate. Each station has geodetic grade dual frequency GPS receiver which are operated in continuous mode by making observations at every 30s since 2001. The ionospheric TEC presented here is computed from the code and phase GPS measurements using the software IONODETECT developed at CSIR 4PI. This decadal scale ionospheric data set covers from maxima of 23rd to maxima of 24th solar cycle with a broad spatial coverage from 35S to 56N and 38E to 134E (figure1). The GPS TEC computed at every 30 seconds over each sub-ionospheric point correlates well with International Reference Ionosphere(IRI) 2012 model in longer time scale, however, a strong spatio-temporal dependence in correlation is clearly observed. In addition a site specific, nearly systematic night time bias between GPS TEC and IRI-12 is noted. The advantage of using the systematic bias for correcting Differential Code Bias (DCB) in computing GPS TEC is discussed. We also discuss in detail the equatorial ionospheric processes and regional characteristics of Equatorial Ionization Anomaly (EIA) through latitudinal, diurnal, seasonal, and inter-annual variability of decadal scale GPS TEC computed over Indian subcontinent. EIA anomaly crust maxima during local noon on 30th November 2004 is clearly visible in the figure 1. The TEC variations associated with solar flares and solar maxima and minima during the solar cycles are also discussed to understand the impact of space weather on equatorial and mid latitude ionosphere as well as on navigation. Vertical TEC (VTEC) at each sub ionospheric pierce points (SIP) on 30th November 2004 from 0UTC to 2359UTC. The red triangles are GPS stations.

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

2013-12-01

215

Spatio-temporal Variability of Nitrate in Groundwater underneath Dairies with Irrigated Crops  

NASA Astrophysics Data System (ADS)

Nitrate contamination remains a ubiquitous groundwater pollution problem worldwide. Animal farming systems are among the major sources of groundwater nitrate. Little is known about the impact of dairy farming practices on water quality in the extensive alluvial aquifers underlying many animal farming regions in the United States and elsewhere. The objective of this work is to characterize and assess nitrate leaching across an array of potential point and nonpoint sources within dairy facilities. Sources are divided into three major groups (animal housing areas, liquid manure storage ponds, irrigated fields receiving liquid manure). A shallow groundwater monitoring network (79 wells) was installed on five representative dairy operations in the San Joaquin Valley, California. Nitrate and reduced nitrogen was measured over a four-year period at intervals of 4 - 7 weeks. Reduced N was only found near manure storage ponds. Total nitrogen (N) concentrations are found subject to large spatial and temporal variability within individual dairies, while the range of observed groundwater N was similar on all five investigated dairies. Average shallow groundwater N concentrations within the dairies was almost three times as high (64 mg/l) as immediately upgradient of these dairies (24 mg/l). Nitrogen may vary rapidly over time at individual observation wells. Temporal correlation is insignificant for measurements taken more than 4 to 6 months apart. Spatial distribution of shallow groundwater N across individual dairies is highly complex.Correlation scales are less than 100 m. High spatio-temporal variability severely limits the value of individual groundwater observation wells for compliance monitoring.

Harter, T.; Mathews, M. C.; Meyer, R. D.

2001-05-01

216

Mapping Ancient Forests: Bayesian Inference for Spatio-temporal Trends in Forest Composition Using the Fossil Pollen Proxy Record  

PubMed Central

Ecologists use the relative abundance of fossil pollen in sediments to estimate how tree species abundances change over space and time. To predict historical forest composition and quantify the available information, we build a Bayesian hierarchical model of forest composition in central New England, USA, based on pollen in a network of ponds. The critical relationships between abundances of taxa in the pollen record and abundances as actual vegetation are estimated for the modern and colonial periods, for which both pollen and direct vegetation data are available, based on a latent multivariate spatial process representing forest composition. For time periods in the past with only pollen data, we use the estimated model parameters to constrain predictions about the latent spatio-temporal process conditional on the pollen data. We develop an innovative graphical assessment of feature significance to help to infer which spatial patterns are reliably estimated. The model allows us to estimate the spatial distribution and relative abundances of tree species over the last 2500 years, with an assessment of uncertainty, and to draw inference about how these patterns have changed over time. Cross-validation suggests that our feature significance approach can reliably indicate certain large-scale spatial features for many taxa, but that features on scales smaller than 50 km are difficult to distinguish, as are large-scale features for some taxa. We also use the model to quantitatively investigate ecological hypotheses, including covariate effects on taxa abundances and questions about pollen dispersal characteristics. The critical advantages of our modeling approach over current ecological analyses are the explicit spatio-temporal representation, quantification of abundance on the scale of trees rather than pollen, and uncertainty characterization.

Paciorek, Christopher J.; McLachlan, Jason S.

2008-01-01

217

Spatio-temporal patterns of soil available nutrients following experimental disturbance in a pine forest.  

PubMed

Although disturbance is known to alter soil nutrient heterogeneity, it remains unclear whether spatial patterns in soil nutrients after disturbance follow predictable temporal changes that reflect underlying processes. This study examined the effects of tree harvesting and girdling on overall variability, geostatistical patterns, and resource congruence of soil available nutrients in a mature Pinus elliottii Engelm. forest. The two disturbances led to different patterns of vegetation removal, forest floor redistribution, and revegetation, but showed similar post-disturbance changes in overall soil nutrient variability. Soil nutrient variability increased after both disturbances by more than 5-fold, and then decreased, returning to the undisturbed level in 4 years. Spatial structures assessed using geostatistics did not show predictable temporal trends. However, girdled plots showed more persistent spatial structures in soil nutrients than harvested plots, and had semivariogram ranges mostly equal to or less than 10 m, reflecting effects of persistent and spatially stable patches of undisturbed hardwoods that had an average patch size of 10 m. Resource congruence examined with Spearman rank correlations was nil before disturbance, increased after disturbance and then became nil again by the 4th year post-disturbance. The timing of the increase was related to treatment, occurring in the 1st year after disturbance in the girdled plots, but not until the 2nd year in the harvested plots. These two patterns of congruence were potentially caused by different rates of nutrient patch formation and resource uptake by plants during early succession. Although temporal changes in soil heterogeneity have been documented previously, the present study indicates that temporal trends in nutrient variability after disturbance may be predictable, and that the marked changes in spatio-temporal patterns of soil nutrients as a result of disturbance are ephemeral. PMID:14689301

Guo, Dali; Mou, Pu; Jones, Robert H; Mitchell, Robert J

2004-03-01

218

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

PubMed Central

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

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

2013-01-01

219

Analysis of spatio-temporal brain imaging patterns by hidden markov models and serial MRI images.  

PubMed

Brain changes due to development and maturation, normal aging, or degenerative disease are continuous, gradual, and variable across individuals. To quantify the individual progression of brain changes, we propose a spatio-temporal methodology based on Hidden Markov Models (HMM), and apply it on four-dimensional structural brain magnetic resonance imaging series of older individuals. First, regional brain features are extracted in order to reduce image dimensionality. This process is guided by the objective of the study or the specific imaging patterns whose progression is of interest, for example, the evaluation of Alzheimer-like patterns of brain change in normal individuals. These regional features are used in conjunction with HMMs, which aim to measure the dynamic association between brain structure changes and progressive stages of disease over time. A bagging framework is used to obtain models with good generalization capability, since in practice the number of serial scans is limited. An application of the proposed methodology was to detect individuals with the risk of developing MCI, and therefore it was tested on modeling the progression of brain atrophy patterns in older adults. With HMM models, the state-transition paths corresponding to longitudinal brain changes were constructed from two completely independent datasets, the Alzheimer Disease Neuroimaging Initiative and the Baltimore Longitudinal Study of Aging. The statistical analysis of HMM-state paths among the normal, progressive MCI, and MCI groups indicates that, HMM-state index 1 is likely to be a predictor of the conversion from cognitively normal to MCI, potentially many years before clinical symptoms become measurable. Hum Brain Mapp 35:4777-4794, 2014. © 2014 Wiley Periodicals, Inc. PMID:24706564

Wang, Ying; Resnick, Susan M; Davatzikos, Christos

2014-09-01

220

Spatio-temporal variations in water quality of Nullah Aik-tributary of the river Chenab, Pakistan.  

PubMed

This study reports the spatio-temporal changes in water quality of Nullah Aik, tributary of the Chenab River, Pakistan. Stream water samples were collected at seven sampling sites on seasonal basis from September 2004 to April 2006 and were analyzed for 24 water quality parameters. Most significant parameters which contributed in spatio-temporal variations were assessed by statistical techniques such as Hierarchical Agglomerative Cluster Analysis (HACA), Factor Analysis/Principal Components Analysis (FA/PCA), and Discriminant Function Analysis (DFA). HACA identified three different classes of sites: Relatively Unimpaired, Impaired and Less Impaired Regions on the basis of similarity among different physicochemical characteristics and pollutant level between the sampling sites. DFA produced the best results for identification of main variables for temporal and spatial analysis and separated eight parameters (DO, hardness, sulphides, K, Fe, Pb, Cr and Zn) that accounted 89.7% of total variations of spatial analysis. Temporal analysis using DFA separated six parameters (E.C., TDS, salinity, hardness, chlorides and Pb) that showed more than 84.6% of total temporal variation. FA/PCA identified six significant factors (sources) which were responsible for major variations in water quality dataset of Nullah Aik. The results signify that parameters identified by statistical analyses were responsible for water quality change and suggest the possibility of industrial, municipal and agricultural runoff, parent rock material contamination. The results suggest dire need for proper management measures to restore the water quality of this tributary for a healthy and promising aquatic ecosystem and also highlights its importance for objective ecological policy and decision making process. PMID:17665141

Qadir, Abdul; Malik, Riffat Naseem; Husain, Syed Z

2008-05-01

221

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

SciTech Connect

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.

Kurt Derr; Milos Manic

2008-09-01

222

Identifying the dynamics of complex spatio-temporal systems by spatial recurrence properties  

PubMed Central

Complex spatio-temporal systems may exhibit irregular behaviors when driven far from equilibrium. Reaction-diffusion systems often lead to the formation of patterns and spatio-temporal chaos. When a limited number of observations is available, the reconstruction and identification of complex dynamical regimes become challenging problems. A method based on spatial recurrence properties is proposed to deal with this problem: generalized recurrence plots and generalized recurrence quantification analysis are exploited to show that detection of structural changes in spatially distributed systems can be performed by setting up appropriate diagrams accounting for different spatial recurrences. The method has been tested on two prototypical systems forming complex patterns: the complex Ginzburg–Landau equation and the Schnakenberg system. This work allowed us to identify changes in the stability of spiral wave solutions in the former system and to analyze the Turing bifurcations in the latter.

Mocenni, Chiara; Facchini, Angelo; Vicino, Antonio

2010-01-01

223

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

PubMed Central

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

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

2013-01-01

224

A haemodynamic response function model in spatio-temporal diffuse optical tomography  

NASA Astrophysics Data System (ADS)

Diffuse optical tomography (DOT) is a new and effective technique for functional brain imaging. It can detect local changes in both oxygenated and deoxygenated haemoglobin concentrations in tissue based on differential absorption at multiple wavelengths. Traditional methods in spatio-temporal analysis of haemoglobin concentrations in diffuse optical tomography first reconstruct the spatial distribution at different time instants independently, then look at the temporal dynamics on each pixel, without incorporating any temporal information as a prior in the image reconstruction. In this work, we present a temporal haemodynamic response function model described by a basis function expansion, in a joint spatio-temporal DOT reconstruction of haemoglobin concentration changes during simulated brain activation. In this joint framework, we simultaneously employ spatial regularization, spectral information and temporal assumptions. We also present an efficient algorithm for solving the associated large-scale systems. The expected improvements in spatial resolution and contrast-to-noise ratio are illustrated with simulations of human brain activation.

Zhang, Yiheng; Brooks, Dana H.; Boas, David A.

2005-10-01

225

Meteorological Factors-Based Spatio-Temporal Mapping and Predicting Malaria in Central China  

PubMed Central

Despite significant reductions in the overall burden of malaria in the 20th century, this disease still represents a significant public health problem in China, especially in central areas. Understanding the spatio-temporal distribution of malaria is essential in the planning and implementing of effective control measures. In this study, normalized meteorological factors were incorporated in spatio-temporal models. Seven models were established in WinBUGS software by using Bayesian hierarchical models and Markov Chain Monte Carlo methods. M1, M2, and M3 modeled separate meteorological factors, and M3, which modeled rainfall performed better than M1 and M2, which modeled average temperature and relative humidity, respectively. M7 was the best fitting models on the basis of based on deviance information criterion and predicting errors. The results showed that the way rainfall influencing malaria incidence was different from other factors, which could be interpreted as rainfall having a greater influence than other factors.

Huang, Fang; Zhou, Shuisen; Zhang, Shaosen; Zhang, Hongwei; Li, Weidong

2011-01-01

226

Statistical occurrence analysis and spatio-temporal distribution of earthquakes in the Apennines (Italy)  

NASA Astrophysics Data System (ADS)

We present two examples of statistical analysis of seismicity conducted by integrating geological, geophysical and seismological data with the aim to characterize the active stress field and to define the spatio-temporal distribution of large earthquakes. Moreover, our data will help to improve the knowledge of the "seismogenic behavior" of the areas and to provide useful information for seismic hazard evaluation. The earthquakes are described by two non-parametric statistical procedures integrating also tectonic-physical parameters to study the spatio-temporal variability. The results show that the areas are characterized by: 1) a stress regime with mainly extensional kinematics; 2) tectonic structures mainly oriented with the active stress field ( Shmin = N44° ± 18° in the southern Apennines and Shmin = N50° ± 17° in the central Apennines); 3) cluster distribution of seismicity and 4) a high probability of earthquake occurrence ( M > 5.5) in the next 10 years.

Faenza, L.; Pierdominici, S.

2007-07-01

227

Mechanisms for spatio-temporal pattern formation in highway traffic models  

Microsoft Academic Search

A key qualitative requirement for highway traffic models is the ability to replicate a type of traffic jam popularly referred to as a phantom jam, shock wave or stop-and-go wave. Despite over 50 years of modelling, the precise mechanisms for the generation and propagation of stop-and-go waves and the associated spatio-temporal patterns are in dispute. However, the increasing availability of

R. Eddie Wilson

2008-01-01

228

Spatio-temporal luminance contrast sensitivity and visual backward masking in schizophrenia  

Microsoft Academic Search

The aim of two experiments was to investigate the relationship between spatio-temporal contrast sensitivity and visual backward masking in normal observers and in subgroups with positive or negative symptoms in schizophrenia. Experiment 1 measured contrast sensitivity for stationary and counterphase-modulated sinusoidal gratings at four spatial (0.5, 2.0, 4.0, 8.0 cycles\\/degree) and four temporal frequencies (0, 4.0, 8.0, 16.0 Hz). The results showed

Walter L. Slaghuis

2004-01-01

229

CNN BASED SPATIO-TEMPORAL NONLINEAR FILTERING AND ENDOCARDIAL BOUNDARY DETECTION IN ECHOCARDIOGRAPHY  

Microsoft Academic Search

In this paper, a CNN based spatio-temporal approach is introduced for finding the endocardial (inner) boundary of the left ventricle from a sequence of echocardiogra phic images. The discussed analogic1 CNN algorithm combines optimal nonlinear filtering and constrained wave propagation in order to estimate the continuous contour of a moving object in a medium where the edges are ill-defined. In

Csaba Rekeczky; Ádám Tahy; Zoltán Végh; Tamás Roska

1997-01-01

230

Multiple-Scale Spatio Temporal Variability of Precipitation over the Coterminous United States  

Microsoft Academic Search

The spatio-temporal variability of precipitation over the United States using a 30-yr, gridded hourly precip- itation dataset is studied. Orthogonal wavelet transform is applied to the time series at each grid box to capture the temporal scales of fluctuation at 17 different timescales ranging fro m2ht o 15 yr.Rotated principal component analysis is then applied to the transformed series to

Renu Joseph; Mingfang Ting; Praveen Kumar

2000-01-01

231

A Spatio-temporal Representation Scheme for Modeling Moving Objects in Video Data  

Microsoft Academic Search

The trajectory of moving objects in video data plays an important role in video indexing for content-based retrieval. In this\\u000a paper, we propose a new spatio-temporal representation scheme for modeling moving objects’ trajectories in video data. In\\u000a order to support contentbased retrieval on video data very well, our representation scheme considers the moving distance of\\u000a an object during a given

Choon-Bo Shim; Jae-Woo Chang

232

Analysis of Spatio-Temporal Patterns in Associative Networks of Spiking Neurons  

Microsoft Academic Search

: A neural network is presentedthat stores spatio-temporal patterns (synfirechains)in associative networks of spikingneurons and replays them at a controlablespeed. An implicit equation is derived andsolved numerically which relates the averagespeed to the network parameters. The replayspeed can be controled by unspecific backgroundsignals and also depends on the numberof co-activated synfire-chains. Balancedinhibition can prevent the latter dependency.Simulation results confirm the...

Thomas Wennekers

1999-01-01

233

Characteristics and spatio-temporal variability of the Amazon River Basin Water Budget  

Microsoft Academic Search

The spatio-temporal variations of the water budget components in the Amazon region are investigated by using a combination of hydrometeorological observations and moisture fluxes derived from the NCEP\\/NCAR reanalyses, for the period 1970–1999. The key new finding of this study identifies the major differences in the water balance characteristics and variability between the northern and southern parts of the basin.

Jose A. Marengo

2005-01-01

234

Real-time spatio-temporal twice whitening for MIMO energy detectors  

Microsoft Academic Search

While many techniques exist for local spectrum sensing of a primary user, each represents a computationally demanding task to secondary user receivers. In software-defined radio, computational complexity lengthens the time for a cognitive radio to recognize changes in the transmission environment. This complexity is even more significant for spatially multiplexed receivers, e.g., in SIMO and MIMO, where the spatio-temporal data

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

2010-01-01

235

Space-time renormalization at the onset of spatio-temporal chaos in coupled maps.  

PubMed

The transition regime to spatio-temporal chaos via the quasiperiodic route as well as the period-doubling route is examined for coupled-map lattices. Space-time renormalization-group analysis is carried out and the scaling exponents for the coherence length, the Lyapunov exponent, and the size of the phase fluctuations are determined. Universality classes for the different types of coupling at various routes to chaos are identified. PMID:12779978

Alstrom, Preben; Stassinopoulos, Dimitris

1992-07-01

236

Spatio-temporal variations of soil nutrients influenced by an altered land tenure system in China  

Microsoft Academic Search

Initiated during the late 1970s in China, the Household Responsibility System (HRS) has brought a profound change to the rural economy. The shift from a collective farming system to individually-owned family farms has changed land management practices, affecting both soil quality and agro-environmental sustainability. The purpose of this study was to investigate spatio-temporal variability of soil nutrients influenced by the

Xingmei Liu; Weiwen Zhang; Minghua Zhang; Darren L. Ficklin; Fan Wang

2009-01-01

237

Spatio-temporal video error concealment with perceptually optimized mode selection  

Microsoft Academic Search

We propose a spatio-temporal error concealment algorithm for video transmission in an error-prone environment. The proposed technique employs motion vector estimation, edge-preserving interpolation, and texture analysis\\/synthesis. It has two main advantages with respect to existing methods, namely: (i) it aims at optimizing the visual quality of the restored video, and not only PSNR; and (ii) it employs an automatic mode

S. Belfiore; M. Grangetto; E. Magli; G. Olmo

2003-01-01

238

Spatio-temporal scalability-based motion-compensated 3-D subband\\/DCT video coding  

Microsoft Academic Search

The existing standard video coding schemes support spatial scalability because of its prospective applications. Unfortunately, spatial scalable codecs produce high bit rate overhead as compared to a single layer coder. In this paper, we propose a spatio-temporal scalable video coding system based on motion compensated (MC) three-dimensional subband\\/discrete cosine transform (3-D SBC\\/DCT). This coder is proposed as a solution to

Randa Atta; Mohammed Ghanbari

2006-01-01

239

Spatio-temporal analysis of stimuli-modulated spontaneous low frequency oscillations  

Microsoft Academic Search

In this paper, the spatio-temporal architecture of the stimulation-modulated spontaneous low frequency oscillation (LFO) in\\u000a the SD rat’s somatosensory cortex is studied by optical imaging (OI) technology. After the electrical stimulation, it is observed\\u000a that the phases of the LFO signals are changed, the amplitudes are increased, and most importantly, the signals in the bilateral\\u000a somatosensory cortex tend to be

Ming Li; YaDong Liu; DeWen Hu; YuCheng Wang; FaYi Liu; GuiYu Feng

2007-01-01

240

Projecting low and extensive dimensional chaos from spatio-temporal dynamics  

NASA Astrophysics Data System (ADS)

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

Ananthakrishna, G.; Sarmah, R.

2013-07-01

241

Convex spatio-temporal segmentation of the endocardium in ultrasound data using distribution and shape priors  

Microsoft Academic Search

We present a convex variational active contour model with shape priors, for spatio-temporal segmentation of the endocardium in 2D B-mode ultrasound sequences, which can be solved by Continuous Cuts. A four component (signal dropout, echocardiographic artifacts, blood and tissue) Rayleigh mixture model is proposed for modeling the inside and outside of the endocardium. The parameters of the mixture model are

Mattias Hansson; Ketut Fundana; Sami S. Brandt; Petri Gudmundsson

2011-01-01

242

Spatio-temporal pattern formation on spherical surfaces: numerical simulation and application to solid tumour growth  

Microsoft Academic Search

.   In this paper we examine spatio-temporal pattern formation in reaction-diffusion systems on the surface of the unit sphere\\u000a in 3D. We first generalise the usual linear stability analysis for a two-chemical system to this geometrical context. Noting\\u000a the limitations of this approach (in terms of rigorous prediction of spatially heterogeneous steady-states) leads us to develop,\\u000a as an alternative, a

M. A. J. Chaplain; M. Ganesh; I. G. Graham

2001-01-01

243

Type1 hybrid-ARQ using MTCM spatio-temporal vector coding for MIMO systems  

Microsoft Academic Search

A system that combines MTCM modified for type-I hybrid-ARQ error control with Spatio-Temporal Vector Coding (STVC) for use over a slowly varying MIMO channel is presented. An idealistic retransmission protocol is defined that maximizes the channel utilization is described and analyzed. Numerical examples, based on a set of simple 8-state trellis codes providing a granularity of 0.5 bit per 2-dimensional

Zhihong Ding; Michael Rice

2003-01-01

244

Hydroxyl spatio-temporal statistics for turbulent partially premixed opposed-jet flames  

NASA Astrophysics Data System (ADS)

Turbulent flows display fluctuations spanning a wide spectrum of both length and time scales. The most energetic fluctuations are typically contained in large-scale eddies characterized by integral length and time scales. In turbulent opposed-flows, the predominance of young turbulence and the influence of the stagnation plane complicate the interpretation of spatial and temporal structures. Therefore, it is essential to understand both the temporal and spatial behavior of large-scale structures in such opposed flows. In this context, two-point, picosecond time-resolved laser-induced fluorescence (PITLIF) has been used to resolve both integral length and time scales, thus providing unique spatial statistics in addition to temporal statistics. The interpretation of spatial and temporal structures is further complicated by their dependence on both local turbulent Reynolds number and equivalence ratio, as affected by changes in internal structure and flame thickness. Hence, simultaneous PLIF/PIV measurements were employed to investigate spatial OH structures and flame-velocity interactions. Hydroxyl single-point time-series measurements have been obtained in opposed-jet nonpremixed flames to study the independent effects of jet velocity (U) on Reynolds number (Re) and strain rate (SR) using time-scale correlations. The combined effect of Re and SR on the integral time scale behaves approximately as U-1.35 in these opposed-jet nonpremixed flames. Two-point, time-series experiments with associated PLIF/PIV measurements were employed to investigate flamelet spatio-temporal scales, extinction and reignition mechanisms, and flame-velocity interactions in turbulent opposed jet, partially premixed and double flames. Filtered OH length scales corresponding to radial OH fluctuations, were obtained from the spatial autocorrelation function. The axial change in length scale is more pronounced for flames with lower bulk Re and greater partial premixing. A stochastic time-series simulation, using a combined mixture-fraction and progress-variable approach and based on measured OH time scales, has been performed to extract scalar time scales in opposed jet double flames. In contrast to the partially-premixed and nonpremixed flames, where the ratio of OH to underlying scalar time scales is ˜0.3, the time-scale ratio for the double flames is ˜0.5. As compared to nonpremixed flames, OH in double flames is distributed across a broader spatial and mixture-fraction space, thereby inducing relatively slower OH fluctuations.

Venkatesan, Krishna Kumar

245

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities  

NASA Astrophysics Data System (ADS)

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

246

Spatio-temporal growth of disturbances in a boundary layer and energy based receptivity analysis  

NASA Astrophysics Data System (ADS)

In fluid dynamical systems, it is not known a priori whether disturbances grow either in space or in time or as spatio-temporal structures. However, for boundary layers, it is customary to treat it as a spatial problem and some limited comparison between prediction and laboratory experiments exist. In the present work, the receptivity problem of a zero pressure gradient boundary layer excited by a localized harmonic source is investigated under the general spatio-temporal framework, using the Bromwich contour integral method. While this approach has been shown to be equivalent to the spatial study, for unstable systems excited by a single frequency source [T. K. Sengupta, M. Ballav, and S. Nijhawan, Phys. Fluids 6, 1213 (1994)], here we additionally show, how the boundary layer behaves when it is excited (i) at a single frequency that corresponds to a stable condition (given by spatial normal-mode analysis) and (ii) by wideband frequencies, that shows the possibility of flow transition due to a spatio-temporally growing forerunner or wave front. An energy based receptivity analysis tool is also developed as an alternative to traditional instability theory. Using this, we reinterpret the concept of critical layer that was originally postulated to explain the mathematical singularity of inviscid disturbance field in traditional instability theory of normal modes.

Sengupta, T. K.; Rao, A. Kameswara; Venkatasubbaiah, K.

2006-09-01

247

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

NASA Astrophysics Data System (ADS)

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.

Serinaldi, F.; Kilsby, C. G.

2012-04-01

248

Spatio-temporal characterization techniques of high-power femtosecond laser chains  

NASA Astrophysics Data System (ADS)

In this letter, we propose two techniques capable of spatio-temporally characterizing high-power femtosecond laser chains. We demonstrate a new implementation of SEA TADPOLE. To avoid the problems induced by the the significant spatial jittering of the focal spot on high-power laser chains, our setup is adapted to collimated beams. In addition, a fibered light source is also used to correct the phase fluctuations. This experimental setup allows identifying any spatiotemporal distortions such as the pulse front tilt for instance. In this paper, to the best of our knowledge, we present the very first spatio-temporal characterization done on a TW laser. However, a SEA TADPOLE measurement is not immediate since it requires scanning the beam over the two transverse dimensions which prevent us from studying the shot-to-shot laser fluctuations. This is why, we developed MUFFIN, a single-shot technique capable of spatio-temporally characterizing a laser pulse along its two transverse dimensions. First experimental results obtained with this technique are presented here.

Gallet, Valentin; Pariente, Gustave; Kahaly, Subhendu; Gobert, Olivier; Quéré, Fabien

2014-03-01

249

Spatio-temporal variations in water quality of Nullah Aik-tributary of the river Chenab, Pakistan  

Microsoft Academic Search

This study reports the spatio-temporal changes in water quality of Nullah Aik, tributary of the Chenab River, Pakistan. Stream\\u000a water samples were collected at seven sampling sites on seasonal basis from September 2004 to April 2006 and were analyzed\\u000a for 24 water quality parameters. Most significant parameters which contributed in spatio-temporal variations were assessed\\u000a by statistical techniques such as Hierarchical

Abdul Qadir; Riffat Naseem Malik; Syed Z. Husain

2008-01-01

250

Estimation of 3D cardiac deformation using spatio-temporal elastic registration of non-scanconverted ultrasound data  

Microsoft Academic Search

Current ultrasound methods for measuring myocardial strain are often limited to measurements in one or two dimensions. Spatio-temporal elastic registration of 3D cardiac ultrasound data can however be used to estimate the 3D motion and full 3D strain tensor. In this work, the spatio-temporal elastic registration method was validated for both non-scanconverted and scanconverted images. This was done using simulated

An Elen; Dirk Loeckx; Hon Fai Choi; Hang Gao; Piet Claus; Frederik Maes; Paul Suetens; Jan D'hooge

2008-01-01

251

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

NASA Astrophysics Data System (ADS)

Geographic information systems form a core part of Earth Science education and teaching, allowing the ever-growing repositories of digital geo-data to be integrated and visualised in a unified fashion. These systems cope with the wide variety of spatial data types, each with their own properties and metadata, allowing for a better understanding of how Earth processes operate. A unique requirement for the Earth Sciences is to take into account plate motion and crustal deformation processes acting through time, thus altering the various spatial relationships. The open-source GPlates software (www.gplates.org) infrastructure has become a standard tool for this type of analysis, providing the ability to reconstruct various datasets through time interactively by attaching arbitrary data to tectonic plates. Combining vast datasets in this manner is increasing the analysis complexity, with traditional visualisation-based approaches becoming ineffective in extracting necessary information and discovering new insights. In addressing this, GPlates has been extended with two key technologies, manifesting itself as a powerful interactive knowledge-discovery platform. The first technology is a "data coregistration" tool, in which desired relationships between various datasets are recursively defined, thus providing the key link between a qualitative visualisation environment and a quantitative multivariate statistical analysis framework. The second technology is a data-mining environment (Orange, http://orange.biolab.si), better suited to coping with complexities due to large datasets, high dimensionality, spatial and temporal dynamics, different data types etc. The data-mining tool has a diverse library of components allowing for interactive filtering, combining, transforming and pattern analysis of incoming data. Attached to the data-mining tool is a visual-programming environment in which underlying software complexities are abstracted from the user, allowing for the rapid prototyping of analysis work-flows without requiring programming expertise. A plug-in framework allows for the construction of new spatio-temporal data processing components, which is seeing the functionality and flexibility of this environment increasing rapidly, aided by an open-source model. The resultant ensemble of technologies lends itself to becoming a frontier teaching and research tool, providing the necessary abstraction of complexity required to better understand how the various complex Earth processes acted through time resulting in the familiar spatial configuration we observe today.

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

2011-12-01

252

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

NASA Astrophysics Data System (ADS)

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

Ibrahim, Hesham M.; Huggins, David R.

2011-07-01

253

Spatio-Temporal Rainfall Patterns in Northern Ghana, West Africa  

Microsoft Academic Search

Rainfall reliability in West Africa has important societal consequences. However, our understanding of the rainfall generating processes in this region remains incomplete. This study aims at the detection of different rainfall producing processes and their characteristics during the later part of the rainy season in Northern Ghana. Rainfall in this region has three main origins: monsoonal advection, local convection, and

J. Friesen; N. van de Giesen

2002-01-01

254

Spatio-temporal characteristics of the Agulhas Current retroflection  

NASA Astrophysics Data System (ADS)

A 12.7-year series of weekly absolute sea surface height (SSH) data in the region south of Africa is used for a statistical characterization of the location of the Agulhas Current retroflection and its variations at periods up to 2 years. The highest probability of presence of the retroflection point is at ˜39.5°S/18-20°E. The longitudinal probability density is negatively skewed. A sharp eastward decrease at 22°E is related to detachments of the Agulhas Current from the continental slope at this longitude. The asymmetry in the central part of the distribution might reflect a westward increase of the zonal velocity of the retroflection point during its east-west pulsations. The western tail of the distribution reveals larger residence times of the retroflection at 14°E-15°E, possibly related to a slowing down of its westward motion by seamounts. While the averaged zonal velocity component of the retroflection point increases westward, its modulus exhibits an opposite trend, the result of southward velocity components more intense in the northeastern Agulhas Basin than farther west. These meridional motions likely reflect influences by cyclones adjacent to the Agulhas Current south of the Agulhas Bank, and farther west in the Cape Basin. In the latter area, variations of the meridional motions result in different positions of the westernmost retroflection patterns relative to the neighbouring seamounts, likely influencing the future behaviour of Agulhas rings shed at these locations. Agulhas ring formation at an average yearly rate of 5.8, similar to previous findings, was observed to occur west of ˜19°E, in the western half of the retroflection probability domain. A well-defined seasonal signal of the retroflection longitude was found throughout the first 5 years of the time series, characterized by amplitudes of 1-1.3° of longitude, and western (eastern) extremes during austral summer (winter). This annual cycle was strongly phase shifted during and after the upstream retroflection event of 2000-2001.

Dencausse, Guillaume; Arhan, Michel; Speich, Sabrina

2010-11-01

255

Spatio-temporal modelling of Antarctic mass balance from multi-satellite observations  

NASA Astrophysics Data System (ADS)

Quantifying ice mass changes, identifying its causes and determining rigorous error estimates, is important for estimating present-day sea-level rise. Yet this remains a challenging task: (i) estimates obtained from altimetry, gravimetry, and mass-budget methods can yield conflicting results with error estimates that do not always overlap, and (ii) the use of different forward models to separate the effects of GIA and surface mass balance (SMB) processes, as is generally done, introduces another source of uncertainty which is hard to quantify. We present a statistical modelling approach that tackles these issues. We combine the observational data together, including radar and laser altimetry, GRACE, GPS and InSAR, and use the different degrees of spatial and temporal smoothness to constrain the underlying geophysical processes. This is achieved via a spatio-temporal Bayesian hierarchical model, employing dimensionality reduction methods to allow the solution to remain tractable in the presence of the large number (> 10^6) of observations involved. The resulting trend estimates are only dependent on length and smoothness properties obtained from numerical models, but are otherwise data-driven. We present annual, time-varying trend fields of dynamic ice loss, SMB, firn compaction and GIA; using a combination of GRACE, ICESat, ENVISat, and GPS vertical uplift rates, for 2003-2009. The elastic flexure of the crust is also determined simultaneously. We estimate that, between 2003 and 2009, there has been an acceleration in ice loss, from balance in 2003/2004 to a rate of -200±50Gt/yr by 2009. This was predominantly driven by ice dynamic losses in West Antarctica and the Antarctic Peninsula. However, this has been partially compensated by an overall positive trend in SMB over the whole continent. We conclude that there was no statistically significant net loss or gain in the seven year period. Other data will be included to allow extension back to 1995 and forward to the present day using, for example, CryoSat 2, ice core records and accumulation radar data.

Schoen, Nana; Zammit-Mangion, Andrew; Bamber, Jonathan; Rougier, Jonathan; Luthcke, Scott; Rémy, Frédérique; Flament, Thomas; Petrie, Elizabeth

2014-05-01

256

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

PubMed Central

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

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

2008-01-01

257

Adaptive spatio-temporal models for satellite ecological data  

Microsoft Academic Search

This article develops models for environmental data recorded by meteorological satellites. In general, such data are continuously\\u000a available for suitable space and time units and are intrinsically nonstationary. Space-time auto-regression (STAR) is a class\\u000a of models that can be used in monitoring and forecasting, but it must be adapted to nonstationary processes. A set of adaptive\\u000a recursive estimators is then

Carlo Grillenzoni

2004-01-01

258

Integration of Remote Sensing with Ground-Based Measurements to Identify Year-Independent Spatio-Temporal Patterns of Snow Cover and their Potential Applications (Invited)  

NASA Astrophysics Data System (ADS)

Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products have been used successfully and are still appealing for a variety of hydrological applications due to their high spatial and temporal resolution coupled with the products' high accuracy based on comparisons with point ground-based measurements. Several researchers have observed that snow accumulation and ablation occur in reasonably regular patterns from one year to the next. Thus, snow cover information from satellite imagery across different years could be integrated with ground-based measurements with the aim of discovering general information about the temporal and spatial character of snowmelt and runoff processes over watersheds that can be used to answer both short-term questions, such as what are the stream flows likely to be over the next two weeks or month and what is the seasonal runoff likely to be, as well as long-term questions such as what are the likely impacts of various climate change scenarios on biome succession or streamflow and water supply from a basin given the discovered behavior of spatio-temporal snowmelt processes. In this study we utilized a collection of snow cover maps produced from MODIS data across multiple years (2001 to 2011) coupled with the melt-out date of a collection of Snowpack Telemetry (SNOTEL) stations within a region of study to synthesize the interannually repeatable pattern of snow depletion from the beginning to the end of melt seasons. The accuracy of this method has been evaluated over the headwaters of the Upper Snake River in Western Wyoming with very good results. This method has many applications including cloud removal, reconstruction of historical snow depletion curves, generation of snow cover maps for times predating the launch of the MODIS sensor, within-season snow cover ablation forecasting, climate change impacts on snow and runoff, and modeling climatology of snow. These applications can be extended for use in water management and water supply forecasting.

Qualls, R. J.; Arogundade, A. B.

2013-12-01

259

Spatio-Temporal Rainfall Patterns in Northern Ghana, West Africa  

NASA Astrophysics Data System (ADS)

Rainfall reliability in West Africa has important societal consequences. However, our understanding of the rainfall generating processes in this region remains incomplete. This study aims at the detection of different rainfall producing processes and their characteristics during the later part of the rainy season in Northern Ghana. Rainfall in this region has three main origins: monsoonal advection, local convection, and squall lines. Different processes dominate during different parts of the rainy season, which runs from May through October. Rainfall measurements were taken with tipping-bucket rain gages with high temporal resolution. A total of 16 rain gages were used, organized in two nested grids covering areas of 9x9 km and 3x3 km, respectively. The recorded rainfall events were classified according to their origin primarily on the basis of intensity, duration, and spatial pattern and distribution. As local convective and squall line rainfall show similar characteristics, TRMM Precipitation Radar imagery was analyzed visually to help further distinguish between these two types. The main result is a procedure that allows to differentiate rainfall origins and a set of characteristic rainfall events. Special attention is paid to squall line induced rainfall. Squall lines are crescent shaped atmospheric disturbances that move from East to West over the sub-continent and are associated with violent wind gusts and high rainfall intensities of up to 300 mm/h. These squall lines are mainly caused by interaction between the monsoonal air layer and the African Easterly Jet. In Northern Ghana, line squalls produce most of the annual rainfall. At the end of the wet season, rain almost exclusively originates from squall lines. Because of their high intensities, squall lines and convective storms are hydrologically important for understanding runoff generation.

Friesen, J.; van de Giesen, N.

2002-12-01

260

Spatio-temporal colour correction of strongly degraded movies  

NASA Astrophysics Data System (ADS)

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

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

2011-01-01

261

Spatio-temporal changes of seismic anisotropy in seismogenic zones  

NASA Astrophysics Data System (ADS)

Seismic anisotropy plays a key role in the study of stress and strain fields in the earth. Potential temporal change of seismic anisotropy can be interpreted as change of the orientation of cracks in seismogenic zones and thus change of the stress field. Such temporal changes have been observed in seismogenic zones before and after earthquakes (Durand et al. , 2011) but are still not well understood. In this study, from a numerical point of view, we investigate the variations of the polarization of surface waves in anisotropic media. These variations are related to the elastic properties of the medium, in particular to anisotropy. The technique used is based on the calculation of the whole cross-correlation tensor (CCT) of ambient seismic noise. If the sources are randomly distributed in homogeneous medium, it allows us to reconstruct the Green's tensor between two stations continuously and to monitor the region through the use of its fluctuations. Therefore, the temporal change of the Green's cross-correlation tensor enables the monitoring of stress and strain fields. This technique is applied to synthetic seismograms computed in a transversally isotropic medium with horizontal symmetry axis (hereafter referred to an HTI medium) using a code RegSEM (Cupillard et al. , 2012) based on the spectral element method. We designed an experiment in order to investigate the influence of anisotropy on the CCT. In homogeneous, isotropic medium the off-diagonal terms of the Green's tensor are null. The CCT is computed between each pair of stations and then rotated in order to approximate the Green's tensor by minimizing the off-diagonal components. This procedure permits the calculation of the polarization angle of quasi-Rayleigh and quasi-Love waves, and to observe the azimuthal variation of their polarization. The results show that even a small variation of the azimuth of seismic anisotropy with respect to a certain pair of stations can induce, in some cases, a large variation in the horizontal polarization of surface waves along the direction of this pair of stations. It depends on the relative azimuth angle between the pair of stations and the direction of anisotropy, on the amplitude of anisotropy and the frequency band of the signal. Therefore, it is now possible to explain the large, rapid and very localized variations of surface waves horizontal polarization observed by Durand et al. (2011) during the Parkfield earthquake of 2004. Furthermore, some preliminary results about the investigation of seismic anisotropy change caused by the June 13, 2008 Iwate-Miyagi Nairiku earthquake (Mw = 6.9) will be presented.

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

2013-12-01

262

Spatio-temporal Visualization for Environmental Decision Support  

SciTech Connect

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

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

2009-01-01

263

Spatio-temporal dynamics of pneumonia in bighorn sheep  

USGS Publications Warehouse

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

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

2013-01-01

264

Spatio-temporal evolution of the H --> L back transition  

NASA Astrophysics Data System (ADS)

Since ITER will operate close to threshold and with limited control, the H --> L back transition is a topic important for machine operations as well as physics. Using a reduced mesoscale model [Miki et al., Phys. Plasmas 19, 092306 (2012)], we investigate ELM-free H --> L back transition dynamics in order to isolate transport physics effects. Model studies indicate that turbulence spreading is the key process which triggers the back transition. The transition involves a feedback loop linking turbulence and profiles. The I-phase appears during the back transition following a slow power ramp down, while fast ramp-downs reveal a single burst of zonal flow during the back transition. The I-phase nucleates at the pedestal shoulder, as this is the site of the residual turbulence in H-mode. Hysteresis in the profile gradient scale length is characterized by the Nusselt number, where Nu=?i,turb/?i,neo. Relative hysteresis of temperature gradient vs density gradient is sensitive to the pedestal Prandtl number, where Prped=Dped/?i,neo. We expect the H-mode to be somewhat more resilient in density than in temperature.

Miki, K.; Diamond, P. H.; Schmitz, L.; McDonald, D. C.; Estrada, T.; Gürcan, Ö. D.; Tynan, G. R.

2013-06-01

265

Spatio-temporal evolution of the H ? L back transition  

SciTech Connect

Since ITER will operate close to threshold and with limited control, the H ? L back transition is a topic important for machine operations as well as physics. Using a reduced mesoscale model [Miki et al., Phys. Plasmas 19, 092306 (2012)], we investigate ELM-free H ? L back transition dynamics in order to isolate transport physics effects. Model studies indicate that turbulence spreading is the key process which triggers the back transition. The transition involves a feedback loop linking turbulence and profiles. The I-phase appears during the back transition following a slow power ramp down, while fast ramp-downs reveal a single burst of zonal flow during the back transition. The I-phase nucleates at the pedestal shoulder, as this is the site of the residual turbulence in H-mode. Hysteresis in the profile gradient scale length is characterized by the Nusselt number, where Nu=?{sub i,turb}/?{sub i,neo}. Relative hysteresis of temperature gradient vs density gradient is sensitive to the pedestal Prandtl number, where Pr{sub ped}=D{sub ped}/?{sub i,neo}. We expect the H-mode to be somewhat more resilient in density than in temperature.

Miki, K. [WCI Center for Fusion Theory, National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of) [WCI Center for Fusion Theory, National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of); Center for Computational Science and e-Systems, Japan Atomic Energy Agency, Chiba 277-8587 (Japan); Diamond, P. H. [WCI Center for Fusion Theory, National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of) [WCI Center for Fusion Theory, National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of); Center for Momentum Transport and Flow Organization, University of California, San Diego, California 92093 (United States); Schmitz, L. [University of California, Los Angeles, California 90095 (United States)] [University of California, Los Angeles, California 90095 (United States); McDonald, D. C. [JET-EFDA, Culham Centre for Fusion Energy, Arbingdon (United Kingdom)] [JET-EFDA, Culham Centre for Fusion Energy, Arbingdon (United Kingdom); Estrada, T. [Laboratorio Nacional de Fusión, Asociación Euratom-CIEMAT, Madrid (Spain)] [Laboratorio Nacional de Fusión, Asociación Euratom-CIEMAT, Madrid (Spain); Gürcan, Ö. D. [LPP, Ecole Polytechnique, CNRS (France)] [LPP, Ecole Polytechnique, CNRS (France); Tynan, G. R. [Center for Momentum Transport and Flow Organization, University of California, San Diego, California 92093 (United States)] [Center for Momentum Transport and Flow Organization, University of California, San Diego, California 92093 (United States)

2013-06-15

266

Spatio-Temporal Data Mining for Scalable Ocean Eddy Monitoring  

NASA Astrophysics Data System (ADS)

Rotating coherent structures of water, known as ocean eddies are the oceanic analog of storms in the atmosphere and a crucial component of ocean dynamics. In addition to dominating the ocean's kinetic energy, eddies play a significant role in the transport of water, salt, heat, nutrients, and carbon uptake. Therefore, understanding current and future eddy activity is a central climate challenge to address future sustainability of marine ecosystems. The emergence of sea surface height observations from satellite radar altimeter has recently enabled researchers to track eddies at a global scale. The majority of studies that identify eddies from observational data employ highly parametrized connected component algorithms using expert filtered data, effectively making reproducibility and scalability challenging. In this paper, we improve upon the state of the art connected component eddy monitoring algorithms to track eddies globally. This work makes three main contributions: first, we do not pre-process the data therefore minimizing the risk of wiping out important signals within the data. Second, we employ a physically-consistent convexity requirement on eddies based on theoretical and empirical studies to improve accuracy effectively reducing the computational complexity from quadratic to linear time in the size of each eddy. Finally, we are able to effectively break-up merged eddies, which existing methods cannot accomplish. We compare our results to those of the state-of-the-art method and discuss the impact of our improvements on the difference in results. Acknowledgments: This work was supported in part by the National Science Foundation under Grant IIS-1029711.

Steinhaeuser, K.; Faghmous, J.; Boriah, S.; Liess, S.; Vikebo, F.; Mesquita, M. D.; Kumar, V.

2012-12-01

267

Spatio-temporal mapping cortical neuroplasticity in carpal tunnel syndrome  

PubMed Central

Neuroimaging data demonstrate that carpal tunnel syndrome, a peripheral neuropathy, is accompanied by maladaptive central neuroplasticity. To further investigate this phenomenon, we collected magnetoencephalography data from 12 patients with carpal tunnel syndrome and 12 healthy control subjects undergoing somatosensory stimulation of the median nerve-innervated Digits 2 and 3, as well as Digit 5, which is innervated by the ulnar nerve. Nerve conduction velocity and psychophysical data were acquired to determine whether standard clinical measures correlated with brain response. In subjects with carpal tunnel syndrome, but not healthy controls, sensory nerve conduction velocity for Digits 2 and 3 was slower than Digit 5. However, somatosensory M20 latencies for Digits 2 and 3 were significantly longer than those of Digit 5. The extent of the M20 delay for median nerve-innervated Digit 2 was positively correlated with decreasing nerve conduction velocity and increasing pain severity. Thus, slower peripheral nerve conduction in carpal tunnel syndrome corresponds to greater delays in the first somatosensory cortical response. Furthermore, spectral analysis demonstrated weaker post-stimulus beta event-related desynchronization and earlier and shorter event-related synchronization in subjects with carpal tunnel syndrome. The extent of the decreased event-related desynchronization for median nerve-innervated digits was positively correlated with paraesthesia severity. We propose that ongoing paraesthesias in median nerve-innervated digits render their corresponding sensorimotor cortical areas ‘busy’, thus reducing their capacity to process external stimulation. Finally, subjects with carpal tunnel syndrome demonstrated a smaller cortical source separation for Digits 2 and 3 compared with healthy controls. This supports our hypothesis that ongoing paraesthesias promote blurring of median nerve-innervated digit representations through Hebbian plasticity mechanisms. In summary, this study reveals significant correlation between the clinical severity of carpal tunnel syndrome and the latency of the early M20, as well as the strength of long latency beta oscillations. These temporal magnetoencephalography measures are novel markers of neuroplasticity in carpal tunnel syndrome and could be used to study central changes that may occur following clinical intervention.

Ruzich, Emily; Witzel, Thomas; Maeda, Yumi; Malatesta, Cristina; Morse, Leslie R.; Audette, Joseph; Hamalainen, Matti; Kettner, Norman; Napadow, Vitaly

2012-01-01

268

A Spatio-Temporal Algorithmic Procedure for Environmental Policymaking in the Municipality of Arkalochori in the Greek Island of Crete  

NASA Astrophysics Data System (ADS)

This work deals with a methodological framework designed/developed under the form of a spatio-temporal algorithmic procedure for environmental policymaking at local level. The procedure includes 25 activity stages and 9 decision nodes, putting emphasis on (i) mapping on GIS layers water supply/demand and modeling of aquatic pollution coming from point and non-point sources, (ii) environmental monitoring by periodically measuring the main pollutants in situ and in the laboratory, (iii) design of environmental projects, decomposition of them into sub-projects and combination of the latter to form attainable alternatives, (iv) multicriteria ranking of alternatives, according to a modified Delphi method, by using as criteria the expected environmental benefit, the attitude of inhabitants, the priority within the programme of regional development, the capital required for the investment and the operating cost, and (v) knowledge Base (KB) operation/enrichment, functioning in combination with a data mining mechanism to extract knowledge/information/data from external Bases. An implementation is presented referring to the Municipality of Arkalochori in the Greek island of Crete.

Batzias, F. A.; Sidiras, D. K.; Giannopoulos, Ch.; Spetsidis, I.

2009-08-01

269

Spatio-temporal analysis to identify determinants of Oncomelania hupensis infection with Schistosoma japonicum in Jiangsu province, China  

PubMed Central

Background With the successful implementation of integrated measures for schistosomiasis japonica control, Jiangsu province has reached low-endemicity status. However, infected Oncomelania hupensis snails could still be found in certain locations along the Yangtze river until 2009, and there is concern that they might spread again, resulting in the possible re-emergence of infections among people and domestic animals alike. In order to establish a robust surveillance system that is able to detect the spread of infected snails at an early stage, sensitive and reliable methods to identify risk factors for the establishment of infected snails need to be developed. Methods A total of 107 villages reporting the persistent presence of infected snails were selected. Relevant data on the distribution of infected snails, and human and livestock infection status information for the years 2003 to 2008 were collected. Spatio-temporal pattern analysis including spatial autocorrelation, directional distribution and spatial error models were carried out to explore spatial correlations between infected snails and selected explanatory factors. Results The area where infected snails were found, as well as their density, decreased significantly between 2003 and 2008. Changes in human and livestock prevalences were less pronounced. Three statistically significant spatial autocorrelations for infected snails were identified. (i) The Moran’s I of infected snails increased from 2004 to 2007, with the snail density increasing and the area with infected snails decreasing. (ii) The standard deviations of ellipses around infected snails were decreasing and the central points of the ellipses moved from West to East. (iii) The spatial error models indicated no significant correlation between the density of infected snails and selected risk factors. Conclusions We conclude that the contribution of local infection sources including humans and livestock to the distribution of infected snails might be relatively small and that snail control may limit infected snails to increasingly small areas ecologically most suitable for transmission. We provide a method to identify these areas and risk factors for persistent infected snail presence through spatio-temporal analysis, and a suggested framework, which could assist in designing evidence based control strategies for schistosomiasis japonica elimination.

2013-01-01

270

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

USGS Publications Warehouse

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

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

2006-01-01

271

Predicting Intra-Urban Variation in Air Pollution Concentrations with Complex Spatio-Temporal Dependencies  

PubMed Central

We describe a methodology for assigning individual estimates of long-term average air pollution concentrations that accounts for a complex spatio-temporal correlation structure and can accommodate spatio-temporally misaligned observations. This methodology has been developed as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study funded by the U.S. EPA to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. Our hierarchical model decomposes the space-time field into a “mean” that includes dependence on covariates and spatially varying seasonal and long-term trends and a “residual” that accounts for spatially correlated deviations from the mean model. The model accommodates complex spatio-temporal patterns by characterizing the temporal trend at each location as a linear combination of empirically derived temporal basis functions, and embedding the spatial fields of coefficients for the basis functions in separate linear regression models with spatially correlated residuals (universal kriging). This approach allows us to implement a scalable single-stage estimation procedure that easily accommodates a significant number of missing observations at some monitoring locations. We apply the model to predict long-term average concentrations of oxides of nitrogen (NOx) from 2005–2007 in the Los Angeles area, based on data from 18 EPA Air Quality System regulatory monitors. The cross-validated R2 is 0.67. The MESA Air study is also collecting additional concentration data as part of a supplementary monitoring campaign. We describe the sampling plan and demonstrate in a simulation study that the additional data will contribute to improved predictions of long-term average concentrations.

Szpiro, Adam A.; Sampson, Paul D.; Sheppard, Lianne; Lumley, Thomas; Adar, Sara D.; Kaufman, Joel

2014-01-01

272

Distributed representation of tone frequency in highly decodable spatio-temporal activity in the auditory cortex.  

PubMed

Although the place code of tone frequency, or tonotopic map, has been widely accepted in the auditory cortex, tone-evoked activation becomes less frequency-specific at moderate or high sound pressure levels. This implies that sound frequency is not represented by a simple place code but that the information is distributed spatio-temporally irrespective of the focal activation. In this study, using a decoding-based analysis, we investigated multi-unit activities in the auditory cortices of anesthetized rats to elucidate how a tone frequency is represented in the spatio-temporal neural pattern. We attempted sequential dimensionality reduction (SDR), a specific implementation of recursive feature elimination (RFE) with support vector machine (SVM), to identify the optimal spatio-temporal window patterns for decoding test frequency. SDR selected approximately a quarter of the windows, and SDR-identified window patterns led to significantly better decoding than spatial patterns, in which temporal structures were eliminated, or high-spike-rate patterns, in which windows with high spike rates were selectively extracted. Thus, the test frequency is also encoded in temporal as well as spatial structures of neural activities and low-spike-rate windows. Yet, SDR recruited more high-spike-rate windows than low-spike-rate windows, resulting in a highly dispersive pattern that probably offers an advantage of discrimination ability. Further investigation of SVM weights suggested that low-spike-rate windows play significant roles in fine frequency differentiation. These findings support the hypothesis that the auditory cortex adopts a distributed code in tone frequency representation, in which high- and low-spike-rate activities play mutually complementary roles. PMID:21277165

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

2011-05-01

273

Spatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland  

NASA Astrophysics Data System (ADS)

Time series of satellite data have an important role in the monitoring of regional and global ecosystem properties. Satellite images often present missing data due to atmospheric aerosol, clouds or other atmospheric conditions. Most methods proposed to minimise the effects of degradation and to restore signal values do not take into account the spatial and temporal correlation of the values in the pixels. The aim of this study was to propose and test a spatio-temporal interpolation method to reconstruct pixel values in MODIS data time series that are missing due to cloud cover or other image noise. The method presented and tested is an example of a hybrid Generalised Additive Model (GAM)-geostatistical space-time model, including the fitting of a smoother spatio-temporal trend and a spatial component to account for local details supported by information in covariates. The method is not limited by the type of noise or degradation of pixels values, latitude, vegetation dynamics and land uses. The application of cloud masks on the target image provided the data for a quantitative validation through the comparison between the modelled EVI values and those from the MODIS product. The method was able to restore data providing very good to adequate responses in series of simulations of missing data. The comparison of distributions showed good agreement and predictive capabilities. The spatio-temporal method always performed better and the use of kriged residuals was helpful for situations with high percentages of missing data. The spatial pattern and the local features were well preserved for cloud coverage ?20%. For higher percentages of missing data, the results were smoother with less local detail retained, but still showing the general spatial pattern of the variable. The method has proved to be flexible and able to provide reconstructed images reproducing spatial patterns and local features of the measured product, even with substantial amounts of missing pixels.

Poggio, Laura; Gimona, Alessandro; Brown, Iain

2012-08-01

274

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

PubMed Central

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 (?2?=?7587, df?=?7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

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

2011-01-01

275

Spatio-temporal variation and prediction of ischemic heart disease hospitalizations in Shenzhen, China.  

PubMed

Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents) and the standardized rate (the observed cases standardized by the expected cases) of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013-2015) to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction using the GM (1,1). In addition, the combined analysis of the prediction of IHD hospital admissions and the general hospital distributions shows that Pingshan and Longgang might experience the most serious burden of IHD hospital services in the near future, although Futian would still have the greatest number and the highest incidence rate of hospital admissions for IHD. PMID:24806191

Wang, Yanxia; Du, Qingyun; Ren, Fu; Liang, Shi; Lin, De-nan; Tian, Qin; Chen, Yan; Li, Jia-jia

2014-05-01

276

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

PubMed Central

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

Wang, Yanxia; Du, Qingyun; Ren, Fu; Liang, Shi; Lin, De-nan; Tian, Qin; Chen, Yan; Li, Jia-jia

2014-01-01

277

Spatio-Temporal Organization of Replication in Bacteria and Eukaryotes (Nucleoids and Nuclei)  

PubMed Central

Here we discuss the spatio-temporal organization of replication in eubacteria and eukaryotes. Although there are significant differences in how replication is organized in cells that contain nuclei from those that do not, you will see that organization of replication in all organisms is principally dictated by the structured arrangement of the chromosome. We will begin with how replication is organized in eubacteria with particular emphasis on three well studied model organisms. We will then discuss spatial and temporal organization of replication in eukaryotes highlighting the similarities and differences between these two domains of life.

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

2012-01-01

278

Visualization of superluminal pulses inside a white light cavity using plane wave spatio temporal transfer functions.  

PubMed

In a white light cavity (WLC), the group velocity is superluminal over a finite bandwidth. For a WLC-based data buffering system we recently proposed, it is important to visualize the behavior of pulses inside such a cavity. The conventional plane wave transfer functions, valid only over space that is translationally invariant, cannot be used for the space inside WLC or any cavity, which is translationally variant. Here, we develop the plane wave spatio temporal transfer function (PWSTTF) method to solve this problem, and produce visual representations of a Gaussian input pulse incident on a WLC, for all times and positions. PMID:23038529

Yum, H N; Jang, Y J; Liu, X; Shahriar, M S

2012-08-13

279

Spatio-temporal clustering of firing rates for neural state estimation.  

PubMed

Characterizing the dynamics of neural data by a discrete state variable is desirable in experimental analysis and brain-machine interfaces. Previous successes have used dynamical modeling including Hidden Markov Models, but the methods do not always produce meaningful results without being carefully trained or initialized. We propose unsupervised clustering in the spatio-temporal space of neural data using time embedding and a corresponding distance measure. By defining performance measures, the method parameters are investigated for a set of neural and simulated data with promising results. Our investigations demonstrate a different view of how to extract information to maximize the utility of state estimation. PMID:21097115

Brockmeier, Austin J; Park, Il; Mahmoudi, Babak; Sanchez, Justin C; Principe, Jose C

2010-01-01

280

Spatio-temporal measurements of Trichel corona discharge using capacitive probe diagnostic  

NASA Astrophysics Data System (ADS)

A nonintrusive capacitive probe diagnostic is developed to estimate the spatio-temporal charge density variation of corona discharge. Tikhonov regularization is used to calculate the charge density from measured potential. A good time resolution and restricted space resolution in charge density is achieved. The axial electric field due to space charge is also estimated by considering the discharge to be of finite radius and with uniformly distributed charge density along the radial direction. Space charge wave front movement, as predicted by existing theories, is noticed. Constraints of present technique and scope for further improvements are discussed.

Gupta, Deepak K.; Ramachandran, H.; John, P. I.

2000-02-01

281

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

PubMed

Here we discuss the spatio-temporal organization of replication in eubacteria and eukaryotes. Although there are significant differences in how replication is organized in cells that contain nuclei from those that do not, you will see that organization of replication in all organisms is principally dictated by the structured arrangement of the chromosome. We will begin with how replication is organized in eubacteria with particular emphasis on three well studied model organisms. We will then discuss spatial and temporal organization of replication in eukaryotes highlighting the similarities and differences between these two domains of life. PMID:22855726

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

2012-08-01

282

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

NASA Astrophysics Data System (ADS)

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

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

2013-05-01

283

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification  

NASA Astrophysics Data System (ADS)

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

2013-10-01

284

Linking spatio-temporal patterns in land cover dynamics with regional climate factors and recent weather: Application to the Flint Hills of Kansas and Oklahoma  

SciTech Connect

A key obstacle to developing regional models of ecosystem dynamics is representation of spatio-temporal variation in constituent patterns and processes. Simple resealing of site-specific ecological data or simulations to broader spatial scales is unlikely to capture regional spatio-temporal dynamics. Yet logistical constraints usually require synoptic weather data to be synthesized from sparse data networks. We seek a simple top-down model that links remotely-sensed vegetation cover with antecedent meteorological forcings to generate boundary conditions for site-specific fine-resolution data and simulations of tallgrass prairie. We developed several candidate models using AVHRR NDVI maximum biweekly composites of the Flint Hills from 1990-1993 and data from a network of more than 60 weather stations across the 40,000 km2 region. Models combined parameters derived from exemplary land cover trajectories, spatial structure (lacunarity and correlation length), and running weighted sums of weather data. Spectral-temporal models were easier to fit; lacunarity was more sensitive than correlation length; compositing effects were strong.

Henebry, G.M.; Goodin, D.G. [Kansas State Univ., Manhattan, KS (United States); Su, H. [Argonne National Lab., IL (United States)] [and others

1995-06-01

285

A Spatio-Temporal Understanding of Growth Regulation during the Salt Stress Response in Arabidopsis[W  

PubMed Central

Plant environmental responses involve dynamic changes in growth and signaling, yet little is understood as to how progress through these events is regulated. Here, we explored the phenotypic and transcriptional events involved in the acclimation of the Arabidopsis thaliana seedling root to a rapid change in salinity. Using live-imaging analysis, we show that growth is dynamically regulated with a period of quiescence followed by recovery then homeostasis. Through the use of a new high-resolution spatio-temporal transcriptional map, we identify the key hormone signaling pathways that regulate specific transcriptional programs, predict their spatial domain of action, and link the activity of these pathways to the regulation of specific phases of growth. We use tissue-specific approaches to suppress the abscisic acid (ABA) signaling pathway and demonstrate that ABA likely acts in select tissue layers to regulate spatially localized transcriptional programs and promote growth recovery. Finally, we show that salt also regulates many tissue-specific and time point–specific transcriptional responses that are expected to modify water transport, Casparian strip formation, and protein translation. Together, our data reveal a sophisticated assortment of regulatory programs acting together to coordinate spatially patterned biological changes involved in the immediate and long-term response to a stressful shift in environment.

Geng, Yu; Wu, Rui; Wee, Choon Wei; Xie, Fei; Wei, Xueliang; Chan, Penny Mei Yeen; Tham, Cliff; Duan, Lina; Dinneny, Jose R.

2013-01-01

286

Spatio-temporal dynamics of dengue 2009 outbreak in Córdoba City, Argentina.  

PubMed

During 2009 the biggest dengue epidemic to date occurred in Argentina, affecting almost half the country. We studied the spatio-temporal dynamics of the outbreak in the second most populated city of the country, Córdoba city. Confirmed cases and the results of an Aedes aegypti monitoring during the outbreak were geolocated. The imported cases began in January, and the autochthonous in March. Thirty-three percent of the 130 confirmed cases were imported, and occurred mainly at the center of the city. The autochthonous cases were more frequent in the outskirts, specially in the NE and SE. Aedes aegypti infestation showed no difference between neighborhoods with or without autochthonous cases, neither between neighborhoods with autochthonous vs. imported cases. The neighborhoods with imported cases presented higher population densities. The majority of autochthonous cases occurred at ages between 25 and 44 years old. Cases formed a spatio-temporal cluster of up to 20 days and 12km. According to a mathematical model that estimates the required number of days needed for transmission according to daily temperature, the number of cases begun to fall when more than 15.5 days were needed. This may be a coarse estimation of mean mosquito survival in the area, provided that the study area is close to the global distribution limit of the vector, and that cases prevalence was very low. PMID:24795212

Estallo, E L; Carbajo, A E; Grech, M G; Frías-Céspedes, M; López, L; Lanfri, M A; Ludueña-Almeida, F F; Almirón, W R

2014-08-01

287

A geomatic methodology for spatio-temporal analysis of climatologic variables and water related diseases  

NASA Astrophysics Data System (ADS)

The main objective of this research is to propose, by the way of geomatic developments, an integrated tool to analyze and model the spatio-temporal pattern of human diseases related to environmental conditions, in particular the ones that are linked to water resources. The geomatic developments follows four generic steps : requirement analysis, conceptual modeling, geomatic modeling and implementation (in Idrisi GIS software). A first development consists of the preprocessing of water, population and health data in order to facilitate the conversion and validation of tabular data into the required structure for spatio-temporal analysis. Three parallel developments follow : water balance, demographic state and evolution, epidemiological measures (morbidity and mortality rates, diseases burden). The new geomatic modules in their actual state have been tested on various regions of Mexico Republic (Lerma watershed, Chiapas state) focusing on diarrhea and vector borne diseases (dengue and malaria) and considering records over the last decade : a yearly as well as seasonal spreading trend can be observed in correlation with precipitation and temperature data. In an ecohealth perspective, the geomatic approach results particularly appropriate since one of its purposes is the integration of the various spatial themes implied in the study problem, environmental as anthropogenic. By the use of powerful spatial analysis functions, it permits the detection of spatial trends which, combined to the temporal evolution, can be of particularly use for example in climate change context, if sufficiently valid historical data can be obtain.

Quentin, E.; Gómez Albores, M. A.; Díaz Delgado, C.

2009-04-01

288

Spatio-temporal dynamics in the phenology of croplands across the Indo-Gangetic Plains  

NASA Astrophysics Data System (ADS)

Spatio-temporal dynamics in land surface phenology parameters observed over croplands can inform on crop-climate interactions and, elucidate local to regional scale vulnerabilities either due to climate change or prevailing sub-optimal agricultural practices. Here, we observe spatio-temporal trends in land surface phenology parameters (cropping intensity, length of growing season and productivity) for kharif and rabi cropping seasons from satellite data across the Indo-Gangetic Plains from 1982 to 2006. The productivity of the Indo-Gangetic Plains croplands is of regional importance and is a vital component of Indian national food security efforts. Aside from local and intra-state heterogeneity in observed trends there was a clear west-to-east gradient in cropping intensity. Key observed trends include increasing cropping intensity in the eastern IGP, increasing number of growing days per year in Bihar, Uttar Pradesh and Haryana and increasing productivity in both cropping seasons across the IGP. This information is a crucial input to integrated assessments of the croplands to ensure management of the agricultural system shifts towards a trajectory of climate-resilience and environmental sustainability. To create spatially explicit time-series, at a spatial resolution of 8 km across the IGP of the following LSP parameters: (i) cropping intensity, (ii) LGS and (iii) agro-ecosystem productivity. To quantify normal conditions, inter-annual variation and long-term trends in these LSP parameters at an 8 km spatial resolution across the IGP croplands.

Duncan, John M. A.; Dash, Jadunandan; Atkinson, Peter M.

2014-08-01

289

Multiple dipole modeling and localization from spatio-temporal MEG data  

SciTech Connect

An array of biomagnetometers may be used to measure the spatio-temporal neuromagnetic field or magnetoencephalogram (MEG) produced by neural activity in the brain. A popular model for the neural activity produced in response to a given sensory stimulus is a set of current dipoles, where each dipole represents the primary current associated with the combined activation of a large number of neutrons located in a small volume of the brain. An important problem in the interpretation of MEG data from evoked response experiments is the localization of these neural current dipoles. The authors present here a linear algebraic framework for three common spatio-temporal dipole models: (i) unconstrained dipoles, (ii) dipoles with a fixed location, and (iii) dipoles with a fixed orientation and location. In all cases, they assume that the location, orientation, and magnitude of the dipoles are unknown. With a common model, they show how the parameter estimation problem may be decomposed into the estimation of the time invariant parameter using nonlinear least-squares minimization, followed by linear estimation of the associated time varying parameters. A subspace formulation is presented and used to derive a suboptimal least-squares subspace scanning method. The resulting algorithm is a special case of the well-known MUltiple SIgnal Classification (MUSIC) method, in which the solution (multiple dipole locations) is found by scanning potential locations using a simple one dipole model.

Mosher, J.C. (TRW Systems Engineering and Development Division, Redondo Beach, CA (United States)); Lewis, P.S. (Los Alamos National Laboratory, NM (United States)); Leahy, R. (University of Southern California, Los Angeles, CA (United States))

1992-06-01

290

Correlated spatio-temporal fluctuations in chromatin compaction states characterize stem cells.  

PubMed

Stem cells integrate signals from the microenvironment to generate lineage-specific gene expression programs upon differentiation. Undifferentiated cell nuclei are easily deformable, with an active transcriptome, whereas differentiated cells have stiffer nuclei and condensed chromatin. Chromatin organization in the stem cell state is known to be highly dynamic but quantitative characterizations of its plasticity are lacking. Using fluorescence imaging, we study the spatio-temporal dynamics of nuclear architecture and chromatin compaction in mouse embryonic stem (ES) cells and differentiated states. Individual ES cells exhibit a relatively narrow variation in chromatin compaction, whereas primary mouse embryonic fibroblasts (PMEF) show broad distributions. However, spatial correlations in chromatin compaction exhibit an emergent length scale in PMEFs, although they are unstructured and longer ranged in ES cells. We provide evidence for correlated fluctuations with large amplitude and long intrinsic timescales, including an oscillatory component, in both chromatin compaction and nuclear area in ES cells. Such fluctuations are largely frozen in PMEF. The role of actin and Lamin A/C in modulating these fluctuations is described. A simple theoretical formulation reproduces the observed dynamics. Our results suggest that, in addition to nuclear plasticity, correlated spatio-temporal structural fluctuations of chromatin in undifferentiated cells characterize the stem cell state. PMID:23442906

Talwar, Shefali; Kumar, Abhishek; Rao, Madan; Menon, Gautam I; Shivashankar, G V

2013-02-01

291

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

PubMed Central

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

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

2007-01-01

292

Hierarchical Bayesian spatio-temporal modeling and entropy-based network design  

NASA Astrophysics Data System (ADS)

Typical spatio-temporal data include temperature, precipitation, atmospheric pressure, ozone concentration, personal income, infection prevalence, mosquito populations, among others. To model such data in a given region by hierarchical Bayesian kriging is undertaken in this paper. In addition, an environmental network design problem is also explored. For demonstration, we consider the ozone concentrations in the Toronto region of Ontario, Canada. There are many missing observations in the data. To proceed, we first formulate the hierarchical spatio-temporal model in terms of observed data. We then fill in some missing observations such that the data has the staircase structure. Thus, in light of Le and Zidek (2006), we model the ozone concentrations in Toronto region by hierarchical Bayesian kriging and derive a conditional predictive distribution of the ozone concentrations over unknown locations. To decide if a new monitoring station needs to be added or an existing station can be closed down, we solve this environmental network design problem by using the principle of maximum entropy.

Wu, Y.; Jin, B.; Chan, E.

2012-12-01

293

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

PubMed

Carnivorous plants have evolved modified leaves into the traps which assist in nutrient uptake from captured prey. It is known that the traps of carnivorous plants have usually lower photosynthetic rates than assimilation leaves as a result of adaptation to carnivory. However a few recent studies have indicated that photosynthesis and respiration undergo spatio-temporal changes during prey capture and retention, especially in the genera with active trapping mechanisms. This study describes the spatio-temporal changes of effective quantum yield of photochemical energy conversion in photosystem II (? PSII) in response to ant-derived formic acid during its capture and digestion. PMID:20523127

Pavlovi?, Andrej

2010-11-01

294

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

PubMed Central

Carnivorous plants have evolved modified leaves into the traps that assist in nutrient uptake from captured prey. It is known that the traps of carnivorous plants usually have lower photosynthetic rates than assimilation leaves as a result of adaptation to carnivory. However, a few recent studies have indicated that photosynthesis and respiration undergo spatio-temporal changes during prey capture and retention, especially in the genera with active trapping mechanisms. This study describes the spatio-temporal changes of effective quantum yield of photochemical energy conversion in photosystem II (?PSII) in response to ant-derived formic acid during its capture and digestion.

2010-01-01

295

Investigation of amplitude spatio-temporal couplings at the focus of a 100 TW-25 fs laser  

NASA Astrophysics Data System (ADS)

We address the on target focal spot spatio-temporal features of an ultrashort, 100 TW class laser chain by using spectrally resolved imaging diagnostics. The observed spatio-spectral images, which we call rotating imaging spectrographs, are obtained single shot to reveal the essential information about the spatio-temporal couplings. We observe nontrivial effects in the focal plane due to compressor defects which significantly affect the maximum on target intensity. This diagnostic might become an essential tool for improving compressor alignment in many upcoming multi-petawatt short pulse laser facilities.

Kahaly, S.; Monchocé, S.; Gallet, V.; Gobert, O.; Réau, F.; Tcherbakoff, O.; D'Oliveira, P.; Martin, Ph.; Quéré, F.

2014-02-01

296

Comparison of spatio–temporal evolution of experimental particulate gravity flows at two different initial concentrations, based on velocity, grain size and density data  

Microsoft Academic Search

Flume experiments were conducted to investigate the spatio–temporal structure of subaqueous particulate gravity flows with an initial concentration of 14% by volume. Time series of downstream flow velocity and its calculated degree of turbulence, median grain size and sediment concentration at different positions along the path of nominally identical flows are analysed and combined to constrain the spatio–temporal evolution of

C. M. A. Choux; J. H. Baas; W. D. McCaffrey; P. D. W. Haughton

2005-01-01

297

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

NASA Astrophysics Data System (ADS)

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 the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a negative binomial generalised linear mixed model (GLMM) is adopted, which includes structured and unstructured spatial and temporal random effects. The parameters in this spatio-temporal Bayesian hierarchical model are estimated using Markov Chain Monte Carlo (MCMC). This allows posterior predictive distributions for disease risk to be derived for each spatial location and time period. A novel visualisation technique is then used to display seasonal probabilistic forecasts of malaria risk, derived from the developed model using pre-defined risk category thresholds, on a map. This technique allows decision makers to identify areas where the model predicts with certainty a particular malaria risk category (high, medium or low); in order to effectively target limited resources to those districts most at risk for a given season.

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

2012-04-01

298

Effect of vertebrate predation on the spatio-temporal distribution of cladocerans in a temperature eutrophic lake  

Microsoft Academic Search

We analysed the spatio-temporal distribution of zooplankton along a profile of 10 stations from the shore to the pelagic zone from April to September 1988, the period when the larvae and juveniles Rutilus rutilus, the most abundant species in the Lake, are in the littoral zone. The digestive tracts of the young roach were analysed. They fed essentially on rotifers

Hassan Taleb; Patricia Reyes-Marchant; Nicole Lair

1994-01-01

299

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

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

300

Spatio-temporal patterns of fishing pressure on UK marine landscapes, and their implications for spatial planning and management  

Microsoft Academic Search

The spatio-temporal distribution of fishing pressure on marine landscapes in offshore UK (England and Wales) waters is assessed, based on a time-series of fishing vessel monitoring system (VMS) data for UK and foreign fleets deploying beam and otter trawls, and scallop dredges. The results reveal that marine landscapes with coarse or mixed sediments and weak or moderate tide stress are

Vanessa Stelzenmuller; Stuart I. Rogers; Craig M. Mills

2008-01-01

301

Spatio-Temporal Weighting for High Resolution Direction-of-Arrival Estimation (Rums-Tidsviktning foer Hoegupploesande Estimering av Ankomstriktning).  

National Technical Information Service (NTIS)

A new spatio-temporal weighting scheme for high resolution direction-of-arrival (DOA) estimation of narrow-band, possibly multi-frequency, signals is proposed. It works on correlation data rather than directly on output data, as in the beamspace methods, ...

J. W. C. Robinson

1996-01-01

302

Anatomical co-registration using spatio-temporal features of a non-contact near-infrared optical scanner  

NASA Astrophysics Data System (ADS)

Non-contact based near-infrared (NIR) optical imaging devices are developed for non-invasive imaging of deep tissues in various clinical applications. Most of these devices focus on obtaining the spatial information for anatomical co-registration of blood vessels as in sub-surface vein localization applications. In the current study, the anatomical co-registration of blood vessels based on spatio-temporal features was performed using NIR optical imaging without the use of external contrast agents. A 710 nm LED source and a compact CCD camera system were employed during simple cuff (0 to 60 mmHg) experiment in order to acquire the dynamic NIR data from the dorsum of a hand. The spatio-temporal features of dynamic NIR data were extracted from the cuff experimental study to localize vessel according to blood dynamics. The blood vessels shape is currently reconstructed from the dynamic data based on spatio-temporal features. Demonstrating the spatio-temporal feature of blood dynamic imaging using a portable non-contact NIR imaging device without external contrast agents is significant for applications such as peripheral vascular diseases.

Jung, Young-Jin; Gonzalez, Jean; Rodriguez, Suset; Velez Mejia, Maximiliano; Clark, Gabrielle; Godavarty, Anuradha

2014-02-01

303

Spatio-temporal patterns of fish assemblages in coastal West African rivers: a self-organizing map approach  

Microsoft Academic Search

We investigated spatio-temporal patterns of fish assemblages in four small coastal rivers in South-East Ivory Coast. The samples were collected between July 2003 and March 2005 at 8 sampling sites (2 per river: 1 upstream and 1 downstream). A total of 59 fish species belonging to 39 genera, 23 families and 11 orders were captured. Perci- forms (30% of the

Félix Koffi Konan; Fabien Leprieur; Allassane Ouattara; Sébastien Brosse; Gaël Grenouillet; Germain Gourène; Peter Winterton; Sovan Lek

2006-01-01

304

Spatio-temporal Patterning of Small Area Low Birth Weight Incidence and Its Correlates: A Latent Spatial Structure Approach  

PubMed Central

Low birth weight (LBW) defined as infant weight at birth of less than 2500g is a useful health outcome for exploring spatio-temporal variation and the role of covariates. LBW is a key measure of population health used by local, national and international health organizations. Yet its spatio-temporal patterns and their dependence structures are poorly understood. In this study we examine the use of flexible latent structure models for the analysis of spatio-temporal variation in LBW. Beyond the explanatory capabilities of well-known predictors, we observe spatio-temporal effects, which are not directly observable using conventional modeling approaches. Our analysis shows that for county-level counts of LBW in Georgia and South Carolina the proportion of black population is a positive risk factor while high-income is a negative risk factor. Two dominant residual temporal components are also estimated. Finally our proposed method provides a better goodness-of-fit to these data than the conventional space-time models.

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

2011-01-01

305

Comparison of spatio temporal evolution of experimental particulate gravity flows at two different initial concentrations, based on velocity, grain size and density data  

NASA Astrophysics Data System (ADS)

Flume experiments were conducted to investigate the spatio-temporal structure of subaqueous particulate gravity flows with an initial concentration of 14% by volume. Time series of downstream flow velocity and its calculated degree of turbulence, median grain size and sediment concentration at different positions along the path of nominally identical flows are analysed and combined to constrain the spatio-temporal evolution of a single idealised flow. Comparison of the 14% flow with a flow of 5% initial concentration reveals similarities in the basic spatio-temporal structure of velocity, turbulence, grain size and concentration. Both flow types exhibit a velocity maximum at about 1 / 3 of the flow height above the flume floor. At that level, velocity decreases slowly in the flows' body and more rapidly in their tails. Moreover, turbulence intensity is highest in the head and at the base of the flows, whereas the level of maximum velocity and the tail of the flows typically are weakly turbulent. The zones of high turbulence are associated with shear at the front and base of the gravity flows. The flow of 5% and 14% initial concentration also agree in stratification patterns of median grain size and concentration. Grain populations are relatively well mixed in the head, show normal grading in the main part of the body and normal to inverse grading in the rear of the body and tail. The inverse grading is thought to originate from particles transported from the head upward and backward into the body of the flows, where they subsequently settle. The main difference between the flow of 5% and 14% initial concentration is that the higher-density flows appear to develop from a jet into a turbidity current closer to the inception point than the lower-density flow. This difference is interpreted from dimensionless vertical profiles of the flow parameters: horizontal velocity, concentration and grain size distribution. In the turbidity current phase of both flows, the dimensionless variables collapse well. This indicates that the flows behave in a dynamically similar manner and inspires confidence that the dimensionless variables can be used to predict the dynamic behaviour of particulate gravity flows across the measured concentration range in the flume, which due to dilution/sedimentation effects, was from ˜7 to < 1 vol.% concentration.

Choux, C. M. A.; Baas, J. H.; McCaffrey, W. D.; Haughton, P. D. W.

2005-08-01

306

Measurement of the spatio-temporal gas density profile of a supersonic jet  

NASA Astrophysics Data System (ADS)

Supersonic jets are important for many experiments in physics, chemistry, and engineering sciences. Characterization of the density profile of the gas released from the nozzle is crucial for many applications and generally requires complicated measurements. A method that uses a common microphone to characterize the spatio-temporal gas profile of the supersonic jet is demonstrated here. Calibrating the microphone signals with the pressure change in the stagnation chamber, it is shown that it is possible to measure the complete density profile of the conical gas emission from the supersonic jet. It is shown that any conical section has a gaussian radial profile and that the peak densities decrease as 1/z'2, where z' is the distance from the nozzle.

Rajeev, R.; Raja, S. V.; Madhu Trivikram, T.; Rishad, K. P. M.; Krishnamurthy, M.

2013-08-01

307

Facilitating Integrated Spatio-Temporal Visualization and Analysis of Heterogeneous Archaeological and Palaeoenvironmental Research Data  

NASA Astrophysics Data System (ADS)

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.

Willmes, C.; Brocks, S.; Hoffmeister, D.; Hütt, C.; Kürner, D.; Volland, K.; Bareth, G.

2012-07-01

308

Linear and Nonlinear Analysis of Spatio-Temporal Chaos in Yttrium Iron Garnet Films  

NASA Astrophysics Data System (ADS)

The spatio-temporal chaotic behavior of magnetic spin wave states in Yttrium Iron Garnet films is experimentally studied and analyzed. A 37 micron sample is placed in a DC magnetic field to align the atomic spins, which are then excited at resonant frequencies. Chaotic spin wave states result when surface modes of the film begin to interact above an excitation power threshold. We study the spatial correlation of the chaotic states of the sample by monitoring the magnetic moment at two positions on the film surface. The magnetic moments are detected by using coaxial loops mounted near the film surface and we can obtain time series corresponding to the signals at each position. We have analyzed the correlation between the two signals using both linear methods and a novel nonlinear analysis technique. This nonlinear analysis is non-parametric and is based solely on the statistics of the two time series.

Goodridge, Chris; Carroll, Tom; Pecora, Lou; Rachford, Fred

2000-03-01

309

The study of spatio-temporal reasoning model and application in the digital tobacco  

NASA Astrophysics Data System (ADS)

This paper combined the studied task and the project of "digital tobacco" and in the backgroun of completely analyzed the current various spatio-temporal reasoning models, and then advanced the technical route by combining the object-oriented technology, and applied this model in the management of tobacco planting of the "Digital tobacco 3S system in YunNan province". Through the application of management of rotating parcels, the mode of management of parcels in this area transferred from the traditional mode to the scientific and modern mode. Consequently, this mode would increase the rationality and scientific component in the planting, monitoring, maintenance and management etc, and then gained the maximal economic benefit.

Luo, Jing; Cui, Weihong

2007-08-01

310

Spatio-temporal memories for machine learning: a long-term memory organization.  

PubMed

Design of artificial neural structures capable of reliable and flexible long-term spatio-temporal memory is of paramount importance in machine intelligence. To this end, we propose a novel, biologically inspired, long-term memory (LTM) architecture. We intend to use it as a building block of a neuron-level architecture that is able to mimic natural intelligence through learning, anticipation, and goal-driven behavior. A mutual input enhancement and blocking structure is proposed, and its operation is discussed in detail. The paper focuses on a hierarchical memory organization, storage, recognition, and recall mechanisms. Simulation results of the proposed memory show its effectiveness, adaptability, and robustness. Accuracy of the proposed method is compared to other methods including Levenshtein distance method and a Markov chain. PMID:19336289

Starzyk, Janusz A; He, Haibo

2009-05-01

311

Hydrodynamic Model of Spatio-Temporal Evolution of Two-Plasmon Decay  

NASA Astrophysics Data System (ADS)

A hydrodynamic model of two-plasmon decay in a homogeneous plasma slab near the quarter-critical density is constructed in order to gain better insight into the spatio-temporal evolution of the daughter electron plasma waves in plasma in the course of the instability. The influence of laser and plasma parameters on the evolution of the amplitudes of the participating waves is discussed. The secondary coupling of two daughter electron plasma waves with an ion-acoustic wave is assumed to be the principal mechanism of saturation of the instability. The impact of the inherently nonresonant nature of this secondary coupling on the development of TPD is investigated and it is shown to significantly influence the electron plasma wave dynamics. Its inclusion leads to nonuniformity of the spatial profile of the instability and causes the burst-like pattern of the instability development, which should result in the burst-like hot-electron production in homogeneous plasma.

Dimitrijevi?, D. R.; Maluckov, A. A.

2010-01-01

312

Spatio-temporal development of the long and short-wave vortex-pair instabilities  

NASA Astrophysics Data System (ADS)

We consider the spatio-temporal development of the long-wave and short-wave instabilities in a pair of counter-rotating vortices in the presence of a uniform axial advection velocity. The stability properties depend upon the aspect ratio a/b of the vortex pair, where a is the core radius of the vortices and b their separation, and upon W0/U0 the ratio between the self-induced velocity of the pair and the axial advection velocity. For sufficiently small W0/U0, the instabilities are convective, but an increase of W0/U0 may lead to an absolute instability. Near the absolute instability threshold, spatial growth rates are larger than those predicted by temporal stability theory. Considering aeronautical applications, it is shown that instabilities of the type considered in this communication cannot become absolute in farfield wakes of high aspect ratio wings.

Fabre, David; Cossu, Carlo; Jacquin, Laurent

2000-05-01

313

Spatio-temporal video segmentation with shape growth or shrinkage constraint.  

PubMed

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. PMID:25020092

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

2014-09-01

314

Joint spatio-temporal registration and microvasculature segmentation of retinal angiogram sequences.  

PubMed

We discuss the problem of 2D+t intra- and inter-sequential registration of retinal angiograms. A joint spatio-temporal registration algorithm is presented based on a RANSAC (RANdom SAmple Consensus) approach incorporating a quadratic model to describe "pairwise" image homography. This is incorporated into a local-to-global hierarchical joint registration framework. After registration, vessel centrelines are segmented to subpixel accuracy by applying multi-scale steerable complex wavelet filters. Frame-by-frame microvascular centrelines in Regions-of-Interest (ROIs) are evaluated against segmented centrelines of the temporal average of the registered sequences. The microvascular centrelines in registered sequences can be compared intra-sequentially and inter-sequentially, allowing non-invasive clinical monitoring of micro-circulation. This has the potential to detect the presence of microemboli and pathological structural alterations. PMID:22254878

Cao, Shuoying; Bharath, Anil; Parker, Kim; Ng, Jeffrey; Arnold, John; McGregor, Alison; Hill, Adam

2011-01-01

315

New spatio-temporal instability scenarios in non-Boussinesq mixed convection  

NASA Astrophysics Data System (ADS)

Mixed convection flows in a tall vertical channel with differentially heated walls subject to large cross-channel temperature gradients are shown to exhibit enormous variety of instability scenarios which have two physically distinct origins: the shear and the buoyancy of the flow. In order to visualize the most typical spatio-temporal patterns and complement previous analytical stability studies the Fourier integrals representing linearised disturbances arising from an initially localised source are evaluated numerically. The disturbance fields are obtained for strongly non-Boussinesq high-temperature convection of air. They are contrasted to their counterparts in the Boussinesq limits of small temperature gradients. A drastic difference in disturbance evolution scenarios is found. In particular, it is shown that non-Boussinesq natural convection is convectively unstable while mixed convection flows can be absolutely unstable. These scenarios are opposite to the ones detected in the classical Boussinesq convection in the same geometry.

Suslov, Sergey A.

2007-11-01

316

Spatio-temporal variations of black carbon concentrations in the Megacity Beijing.  

PubMed

The spatial and temporal distribution and the flux of black carbon (BC) concentration in Beijing were continuously investigated over a two-year period at five sites to highlight the relative influence of contributing sources. The results demonstrate firstly that there is significant spatio-temporal variability of BC in Beijing. Highest concentrations occurred during winter primarily due to stagnant meteorological conditions, and seasonal BC sources, such as coal combustion for heating purposes. Biomass burning was identified as a minor seasonal source during the summer months. BC also varied spatially with higher concentrations in the SE of Beijing and lower concentrations in the NW, due to the differing emission intensity of various local BC sources such as traffic and industry. Frequently, overnight BC concentrations were higher due to specific meteorological conditions, such as the lower urban mixing layer height and various anthropogenic activities, such as exclusive night-time heavy duty vehicle traffic in the inner-city. PMID:23978522

Schleicher, Nina; Norra, Stefan; Fricker, Mathieu; Kaminski, Uwe; Chen, Yizhen; Chai, Fahe; Wang, Shulan; Yu, Yang; Cen, Kuang

2013-11-01

317

Spatio-temporal complexity analysis of the sea surface temperature in the Philippines  

NASA Astrophysics Data System (ADS)

A spatio-temporal complexity (STC) measure which has been previously used to analyze data from terrestrial ecosystems is employed to analyse 21 years of remotely sensed sea-surface temperature (SST) data from the Philippines. STC on the Philippine wide SST showed the monsoonal variability of the Philippine waters but did not show significant differences between El Niño, La Niña and normal years. The spatial domain was subsequently divided into six thermal regions computed via clustering of temperature means. The STC values of each thermal region showed variations corresponding to the monsoonal shifts - as well as - to ENSO events. STC characterized environmental heterogeneity over space and time has the potential to define limits of bio-regions. The same approach can be utilized for many long-term remotely sensed data.

Botin, Z. T.; David, L. T.; Del Rosario, R. C. H.; Parrott, L.

2009-11-01

318

Spatio-temporal Contrast Sensitivity in the Cardinal Directions of the Colour Space. A Review  

PubMed Central

We review the psychophysics of the spatio-temporal contrast sensitivity in the cardinal directions of the colour space and their correlation with those neural characteristics of the visual system that limit the ability to perform contrast detection or pattern-resolution tasks. We focus our attention particularly on the influence of luminance level, spatial extent and spatial location of the stimuli - factors that determine the characteristics of the physiological mechanisms underlying detection. Optical factors do obviously play a role, but we will refer to them only briefly. Contrast sensitivity measurements are often used in clinical practice as a method to detect, at their early stages, a variety of pathologies affecting the visual system, but their usefulness is very limited due to several reasons. We suggest some considerations about stimuli characteristics that should be taken into account in order to improve the performance of this kind of measurement.

Diez-Ajenjo, Maria Amparo; Capilla, Pascual

2010-01-01

319

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

PubMed Central

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

Roy, Priti; Bandyopadhyay, Amitabha

2014-01-01

320

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

NASA Astrophysics Data System (ADS)

In this paper, we review the state of the art of characterizing and analyzing spatio-temporal dynamics of soil moisture content at the field scale. We discuss measurement techniques that have become available in recent years and that provide unique opportunities to characterize field scale soil moisture variability with high spatial and/or temporal resolution. These include soil moisture sensor networks, hydrogeophysical measurement techniques, novel remote sensing platforms, and cosmic ray probes. Techniques and methods to analyze soil moisture fields are briefly discussed and include temporal stability analysis, wavelet analysis and empirical orthogonal functions. We revisit local and non-local controls on field scale soil moisture dynamics and discuss approaches to model these dynamics at the field scale. Finally, we address the topic of optimal measurement design and provide an outlook and future research perspectives.

Vereecken, H.; Huisman, J. A.; Pachepsky, Y.; Montzka, C.; van der Kruk, J.; Bogena, H.; Weihermüller, L.; Herbst, M.; Martinez, G.; Vanderborght, J.

2014-08-01

321

Spatio-temporal evolution of the L ? H and H ? L transitions  

NASA Astrophysics Data System (ADS)

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 (PT) 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 PT, (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.

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

2013-07-01

322

Predicted spatio-temporal dynamics of radiocesium deposited onto forests following the Fukushima nuclear accident.  

PubMed

The majority of the area contaminated by the Fukushima Dai-ichi nuclear power plant accident is covered by forest. To facilitate effective countermeasure strategies to mitigate forest contamination, we simulated the spatio-temporal dynamics of radiocesium deposited into Japanese forest ecosystems in 2011 using a model that was developed after the Chernobyl accident in 1986. The simulation revealed that the radiocesium inventories in tree and soil surface organic layer components drop rapidly during the first two years after the fallout. Over a period of one to two years, the radiocesium is predicted to move from the tree and surface organic soil to the mineral soil, which eventually becomes the largest radiocesium reservoir within forest ecosystems. Although the uncertainty of our simulations should be considered, the results provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident. PMID:23995073

Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji

2013-01-01

323

Assessing the spatio-temporal variations of the completeness magnitude for seismic events in Venezuela  

NASA Astrophysics Data System (ADS)

We investigate the spatio temporal variation of the completeness magnitude Mc, for a set of 18774 well localized earthquakes registered by the Venezuelan Seismological Network over the period 2000-2010. In the entire seismicity region we defined two-dimensional grids of different sizes in order to map the Mc: 11 km, 22 km, 55 km and 111 km. We calculated the completeness magnitude using the Maximum Curvature method (MAXC) for every particular cell taking at least 15 earthquakes to perform computations. The results show an overall variation from 2.0 to 3.6. We found different thresholds and ranges of Mc depending on the dimension of the seismicity zone: western region from 2.2 to 2.8, north central from 2.0 to 3.2 and eastern region from 2.2 to 3.2. We also include remarks in border seismicity, close to Colombia and Trinidad, where the largest Mc values are estimated.

Vasquez, R.; Bravo, L.

2013-05-01

324

Spatio-temporal simulation of first pass drug perfusion in the liver.  

PubMed

The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the liver in the future. PMID:24625393

Schwen, Lars Ole; Krauss, Markus; Niederalt, Christoph; Gremse, Felix; Kiessling, Fabian; Schenk, Andrea; Preusser, Tobias; Kuepfer, Lars

2014-03-01

325

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

PubMed

The North Sea cod (Gadus morhua, L.) stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS) data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature) and/or indirect (i.e. changes in the quantity and quality of zooplankton prey) effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST) from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability. PMID:24551103

Nicolas, Delphine; Rochette, Sébastien; Llope, Marcos; Licandro, Priscilla

2014-01-01

326

Spatio-temporal distribution of floating objects in the German Bight (North Sea)  

NASA Astrophysics Data System (ADS)

Floating objects facilitate the dispersal of marine and terrestrial species but also represent a major environmental hazard in the case of anthropogenic plastic litter. They can be found throughout the world's oceans but information on their abundance and the spatio-temporal dynamics is scarce for many regions of the world. This information, however, is essential to evaluate the ecological role of floating objects. Herein, we report the results from a ship-based visual survey on the abundance and composition of flotsam in the German Bight (North Sea) during the years 2006 to 2008. The aim of this study was to identify potential sources of floating objects and to relate spatio-temporal density variations to environmental conditions. Three major flotsam categories were identified: buoyant seaweed (mainly fucoid brown algae), natural wood and anthropogenic debris. Densities of these floating objects in the German Bight were similar to those reported from other coastal regions of the world. Temporal variations in flotsam densities are probably the result of seasonal growth cycles of seaweeds and fluctuating river runoff (wood). Higher abundances were often found in areas where coastal fronts and eddies develop during calm weather conditions. Accordingly, flotsam densities were often higher in the inner German Bight than in areas farther offshore. Import of floating objects and retention times in the German Bight are influenced by wind force and direction. Our results indicate that a substantial amount of floating objects is of coastal origin or introduced into the German Bight from western source areas such as the British Channel. Rapid transport of floating objects through the German Bight is driven by strong westerly winds and likely facilitates dispersal of associated organisms and gene flow among distant populations.

Thiel, Martin; Hinojosa, Iván A.; Joschko, Tanja; Gutow, Lars

2011-04-01

327

Stability of the spatio-temporal distribution and niche overlap in neotropical earthworm assemblages  

NASA Astrophysics Data System (ADS)

The spatial distribution of soil invertebrates is aggregated with high-density patches alternating with low-density zones. A high degree of spatio-temporal organization generally exists with identified patches of specific species assemblages, in which species coexist according to assembly rules related to competitive mechanisms for spatial and trophic resources occur. However, these issues have seldom been addressed. The spatio-temporal structure of a native earthworm community in a natural savanna and a grass-legume pasture in the Colombian "Llanos" was studied during a 2-year-period. A spatially explicit sampling design (regular grid) was used to discern the distribution pattern of species assemblages in both systems. Earthworms were collected from small soil pits at three different sampling dates. Data collected from 1 m 2 soil monoliths were also used in the present study. Data were analyzed with the partial triadic analysis (PTA) and correlograms, while niche overlap was computed with the Pianka index. The PTA and correlogram analysis revealed that earthworm communities displayed a similar stable spatial structure in both systems during the 2-year study period. An alternation of population patches where different species' assemblages dominated was common to all sampling dates. The medium-sized Andiodrilus sp. and Glossodrilus sp. exhibited a clear spatial opposition in natural savanna and the grass-legume pasture for the duration of the study. The Pianka index showed a high degree of niche overlapping in several dimensions (vertical distribution, seasonality of population density) between both species. The inclusion of space-time data analysis tools as the PTA and the use of classical ecological indices (Pianka) in soil ecology studies may improve our knowledge of earthworm assemblages' dynamics.

Jiménez, Juan-José; Decaëns, Thibaud; Rossi, Jean-Pierre

2006-11-01

328

Spatio-Temporal Variability of the North Sea Cod Recruitment in Relation to Temperature and Zooplankton  

PubMed Central

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.

Nicolas, Delphine; Rochette, Sebastien; Llope, Marcos; Licandro, Priscilla

2014-01-01

329

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

NASA Astrophysics Data System (ADS)

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.

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

2013-10-01

330

Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity  

PubMed Central

It has previously been shown that by using spike-timing-dependent plasticity (STDP), neurons can adapt to the beginning of a repeating spatio-temporal firing pattern in their input. In the present work, we demonstrate that this mechanism can be extended to train recognizers for longer spatio-temporal input signals. Using a number of neurons that are mutually connected by plastic synapses and subject to a global winner-takes-all mechanism, chains of neurons can form where each neuron is selective to a different segment of a repeating input pattern, and the neurons are feed-forwardly connected in such a way that both the correct input segment and the firing of the previous neurons are required in order to activate the next neuron in the chain. This is akin to a simple class of finite state automata. We show that nearest-neighbor STDP (where only the pre-synaptic spike most recent to a post-synaptic one is considered) leads to “nearest-neighbor” chains where connections only form between subsequent states in a chain (similar to classic “synfire chains”). In contrast, “all-to-all spike-timing-dependent plasticity” (where all pre- and post-synaptic spike pairs matter) leads to multiple connections that can span several temporal stages in the chain; these connections respect the temporal order of the neurons. It is also demonstrated that previously learnt individual chains can be “stitched together” by repeatedly presenting them in a fixed order. This way longer sequence recognizers can be formed, and potentially also nested structures. Robustness of recognition with respect to speed variations in the input patterns is shown to depend on rise-times of post-synaptic potentials and the membrane noise. It is argued that the memory capacity of the model is high, but could theoretically be increased using sparse codes.

Humble, James; Denham, Susan; Wennekers, Thomas

2012-01-01

331

Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity.  

PubMed

It has previously been shown that by using spike-timing-dependent plasticity (STDP), neurons can adapt to the beginning of a repeating spatio-temporal firing pattern in their input. In the present work, we demonstrate that this mechanism can be extended to train recognizers for longer spatio-temporal input signals. Using a number of neurons that are mutually connected by plastic synapses and subject to a global winner-takes-all mechanism, chains of neurons can form where each neuron is selective to a different segment of a repeating input pattern, and the neurons are feed-forwardly connected in such a way that both the correct input segment and the firing of the previous neurons are required in order to activate the next neuron in the chain. This is akin to a simple class of finite state automata. We show that nearest-neighbor STDP (where only the pre-synaptic spike most recent to a post-synaptic one is considered) leads to "nearest-neighbor" chains where connections only form between subsequent states in a chain (similar to classic "synfire chains"). In contrast, "all-to-all spike-timing-dependent plasticity" (where all pre- and post-synaptic spike pairs matter) leads to multiple connections that can span several temporal stages in the chain; these connections respect the temporal order of the neurons. It is also demonstrated that previously learnt individual chains can be "stitched together" by repeatedly presenting them in a fixed order. This way longer sequence recognizers can be formed, and potentially also nested structures. Robustness of recognition with respect to speed variations in the input patterns is shown to depend on rise-times of post-synaptic potentials and the membrane noise. It is argued that the memory capacity of the model is high, but could theoretically be increased using sparse codes. PMID:23087641

Humble, James; Denham, Susan; Wennekers, Thomas

2012-01-01

332

Quantifying the spatio-temporal dynamics of woody plant encroachment using an integrative remote sensing, GIS, and spatial modeling approach  

NASA Astrophysics Data System (ADS)

Despite a longstanding universal concern about and intensive research into woody plant encroachment (WPE)---the replacement of grasslands by shrub- and woodlands---our accumulated understanding of the process has either not been translated into sustainable rangeland management strategies or with only limited success. In order to increase our scientific insights into WPE, move us one step closer toward the sustainable management of rangelands affected by or vulnerable to the process, and identify needs for a future global research agenda, this dissertation presents an unprecedented critical, qualitative and quantitative assessment of the existing literature on the topic and evaluates the utility of an integrative remote sensing, GIS, and spatial modeling approach for quantifying the spatio-temporal dynamics of WPE. Findings from this research suggest that gaps in our current understanding of WPE and difficulties in devising sustainable rangeland management strategies are in part due to the complex spatio-temporal web of interactions between geoecological and anthropogenic variables involved in the process as well as limitations of presently available data and techniques. However, an in-depth analysis of the published literature also reveals that aforementioned problems are caused by two further crucial factors: the absence of information acquisition and reporting standards and the relative lack of long-term, large-scale, multi-disciplinary research efforts. The methodological framework proposed in this dissertation yields data that are easily standardized according to various criteria and facilitates the integration of spatially explicit data generated by a variety of studies. This framework may thus provide one common ground for scientists from a diversity of fields. Also, it has utility for both research and management. Specifically, this research demonstrates that the application of cutting-edge remote sensing techniques (Multiple Endmember Spectral Mixture Analysis, fuzzy logic-based change detection) to conventional medium spatial and spectral resolution imagery (Landsat Thematic Mapper, Landsat Enhanced Thematic Mapper Plus, ASTER) can be used to generate spatially explicit estimates of temporal changes in the abundance of woody plants and other surface materials. The research also shows that spatial models (Geographically Weighted Regression, Weights of Evidence, Weighted Logistic Regression) integrating this timely remotely sensed information with readily available GIS data can yield reasonably accurate estimates of an area's relative vulnerability to WPE and of the importance of anthropogenic and geoecological variables influencing the process. Such models may also be used for the testing of existing and generation of new scientific hypotheses about WPE, for evaluating the impact of natural or human-induced modifications of a landscape on the landscape's vulnerability to WPE, and for identifying target areas for conservation, restoration, or other management objectives. In sum, this dissertation demonstrates that integrative remote sensing, GIS, and spatial modeling approaches have enormous potential for addressing questions relevant to both rangelands research and management. However, it also suggests that much work remains to be done before we can translate our understanding of WPE into sustainable rangeland management strategies. In particular, we need to more fully explore the limitations and potentials of currently available data and techniques for quantifying WPE; build structures for data sharing and integration; develop a set of relevant standards; more actively engage in collaborative research efforts; and foster cross-cutting dialogues among researchers, managers, and communities.

Buenemann, Michaela

333

Usage of a Dense GPS Network to Analyze Spatio-Temporal Characteristics of Water Vapor during Local Downpours in the Seoul Metropolitan Area  

NASA Astrophysics Data System (ADS)

Recently, the local downpour occurs frequently in South Korea due to the global climate change. Korea Meteorological Administration (KMA) have used radiosondes and microwave radiometers to observe atmospheric water vapor. However, the observation network is not dense enough to analyze the rapid change in under-synoptic scale atmosphere. The network of Global Positioning System (GPS) is dense enough in Korea, and it can be an alternative to other upper air observation equipments. In this study, we analyzed spatio-temporal characteristics of atmospheric water vapor changes by calculating GPS precipitable water vapor (PWV) during locally severe weather periods. Fifteen GPS stations in the metropolitan Seoul area were used and the data was processed with GIPSY 5.0. We evaluated the GPS's ability as upper air observation system by comparing GPS estimates with measurement from radiosonde and radiometers. Also, we established the water vapor observation system by using GPS network in the Seoul metropolitan area.

Kim, D.; Won, J.; Park, K.

2011-12-01

334

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

PubMed

The brain functions as a spatio-temporal information processing machine. Spatio- and spectro-temporal brain data (STBD) are the most commonly collected data for measuring brain response to external stimuli. An enormous amount of such data has been already collected, including brain structural and functional data under different conditions, molecular and genetic data, in an attempt to make a progress in medicine, health, cognitive science, engineering, education, neuro-economics, Brain-Computer Interfaces (BCI), and games. Yet, there is no unifying computational framework to deal with all these types of data in order to better understand this data and the processes that generated it. Standard machine learning techniques only partially succeeded and they were not designed in the first instance to deal with such complex data. Therefore, there is a need for a new paradigm to deal with STBD. This paper reviews some methods of spiking neural networks (SNN) and argues that SNN are suitable for the creation of a unifying computational framework for learning and understanding of various STBD, such as EEG, fMRI, genetic, DTI, MEG, and NIRS, in their integration and interaction. One of the reasons is that SNN use the same computational principle that generates STBD, namely spiking information processing. This paper introduces a new SNN architecture, called NeuCube, for the creation of concrete models to map, learn and understand STBD. A NeuCube model is based on a 3D evolving SNN that is an approximate map of structural and functional areas of interest of the brain related to the modeling STBD. Gene information is included optionally in the form of gene regulatory networks (GRN) if this is relevant to the problem and the data. A NeuCube model learns from STBD and creates connections between clusters of neurons that manifest chains (trajectories) of neuronal activity. Once learning is applied, a NeuCube model can reproduce these trajectories, even if only part of the input STBD or the stimuli data is presented, thus acting as an associative memory. The NeuCube framework can be used not only to discover functional pathways from data, but also as a predictive system of brain activities, to predict and possibly, prevent certain events. Analysis of the internal structure of a model after training can reveal important spatio-temporal relationships 'hidden' in the data. NeuCube will allow the integration in one model of various brain data, information and knowledge, related to a single subject (personalized modeling) or to a population of subjects. The use of NeuCube for classification of STBD is illustrated in a case study problem of EEG data. NeuCube models result in a better accuracy of STBD classification than standard machine learning techniques. They are robust to noise (so typical in brain data) and facilitate a better interpretation of the results and understanding of the STBD and the brain conditions under which data was collected. Future directions for the use of SNN for STBD are discussed. PMID:24508754

Kasabov, Nikola K

2014-04-01

335

Spatio-Temporal Expression and Functional Involvement of Transient Receptor Potential Vanilloid 1 in Diabetic Mechanical Allodynia in Rats  

PubMed Central

Diabetic neuropathic pain (DNP) is one of the most common clinical manifestations of diabetes mellitus (DM), which is characterized by prominent mechanical allodynia (DMA). However, the molecular mechanism underlying it has not fully been elucidated. In this study, we examined the spatio-temporal expression of a major nociceptive channel protein transient receptor potential vanilloid 1 (TRPV1) and analyzed its functional involvement by intrathecal (i.t.) application of TRPV1 antagonists in streptozocin (STZ)-induced DMA rat models. Western blot and immunofluorescent staining results showed that TRPV1 protein level was significantly increased in the soma of the dorsal root ganglion (DRG) neurons on 14 days after STZ treatment (DMA 14 d), whereas those in spinal cord and skin (mainly from the central and peripheral processes of DRG neurons) had already been enhanced on DMA 7 d to peak on DMA 14 d. qRT-PCR experiments confirmed that TRPV1 mRNA level was significantly up-regulated in the DRG on DMA 7 d, indicating a preceding translation of TRPV1 protein in the soma but preferential distribution of this protein to the processes under the DMA conditions. Cell counting assay based on double immunostaining suggested that increased TRPV1-immunoreactive neurons were likely to be small-sized and CGRP-ergic. Finally, single or multiple intrathecal applications of non-specific or specific TRPV1 antagonists, ruthenium red and capsazepine, at varying doses, effectively alleviated DMA, although the effect of the former was more prominent and long-lasting. These results collectively indicate that TRPV1 expression dynamically changes during the development of DMA and this protein may play important roles in mechanical nociception in DRG neurons, presumably through facilitating the release of CGRP.

Wu, Huang-Hui; Qi, Jian; Shi, Juan; Li, Yun-Qing

2014-01-01

336

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

PubMed Central

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.

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

2013-01-01

337

Spatio-temporal expression and functional involvement of transient receptor potential vanilloid 1 in diabetic mechanical allodynia in rats.  

PubMed

Diabetic neuropathic pain (DNP) is one of the most common clinical manifestations of diabetes mellitus (DM), which is characterized by prominent mechanical allodynia (DMA). However, the molecular mechanism underlying it has not fully been elucidated. In this study, we examined the spatio-temporal expression of a major nociceptive channel protein transient receptor potential vanilloid 1 (TRPV1) and analyzed its functional involvement by intrathecal (i.t.) application of TRPV1 antagonists in streptozocin (STZ)-induced DMA rat models. Western blot and immunofluorescent staining results showed that TRPV1 protein level was significantly increased in the soma of the dorsal root ganglion (DRG) neurons on 14 days after STZ treatment (DMA 14 d), whereas those in spinal cord and skin (mainly from the central and peripheral processes of DRG neurons) had already been enhanced on DMA 7 d to peak on DMA 14 d. qRT-PCR experiments confirmed that TRPV1 mRNA level was significantly up-regulated in the DRG on DMA 7 d, indicating a preceding translation of TRPV1 protein in the soma but preferential distribution of this protein to the processes under the DMA conditions. Cell counting assay based on double immunostaining suggested that increased TRPV1-immunoreactive neurons were likely to be small-sized and CGRP-ergic. Finally, single or multiple intrathecal applications of non-specific or specific TRPV1 antagonists, ruthenium red and capsazepine, at varying doses, effectively alleviated DMA, although the effect of the former was more prominent and long-lasting. These results collectively indicate that TRPV1 expression dynamically changes during the development of DMA and this protein may play important roles in mechanical nociception in DRG neurons, presumably through facilitating the release of CGRP. PMID:25020137

Cui, Yuan-Yuan; Xu, Hao; Wu, Huang-Hui; Qi, Jian; Shi, Juan; Li, Yun-Qing

2014-01-01

338

Lipidomic and Spatio-Temporal Imaging of Fat by Mass Spectrometry in Mice Duodenum during Lipid Digestion  

PubMed Central

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

Seyer, Alexandre; Cantiello, Michela; Bertrand-Michel, Justine; Roques, Veronique; Nauze, Michel; Bezirard, Valerie; Touboul, David; Comera, Christine

2013-01-01

339

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

PubMed

Despite the fact that investigations of home range behaviour have exponentially evolved on theoretical, analytical and technological grounds, the factors that shape animal home range behaviour still represent an unsolved question and a challenging field of research. However, home range studies have recently begun to be approached under a new integrated conceptual framework, considering home range behaviour as the result of the simultaneous influences of temporal, spatial and individual-level processes, with potential consequences at the population level. Following an integrated approach, we studied the influence of both external and internal factors on variations in the home range behaviour of 34 radiotagged eagle owl (Bubo bubo) breeders. Home range behaviour was characterised through complementary analysis of space use, movement patterns and rhythms of activity at multiple spatio-temporal scales. The effects of the different phases of the biological cycle became considerably evident at the level of movement patterns, with males travelling longer distances than females during incubation and nestling periods. Both external (i.e. habitat structure and composition) and internal (i.e. sex and health state) factors explained a substantial amount of the variation in home range behaviour. At the broader temporal scale, home range and core area size were negatively correlated with landscape heterogeneity. Males showed (1) smaller home range and core area sizes, (2) more complex home range internal structure and (3) higher rates of movement. The better the physiological condition of the individuals, the simpler the internal home range structure. Finally, inter- and intra-individual effects contributed to shaping space use and movement patterns during the biological cycle. Because of the plurality of behavioural and ecological processes simultaneously involved in home range behaviour, we claim that an integrative approach is required for adequate investigation of its temporal and spatial variation. PMID:23086505

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

2013-06-01

340

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

NASA Astrophysics Data System (ADS)

In the context of proactive disaster risk as well as immediate situational crisis management knowledge of locational social aspects in terms of spatio-temporal population distribution dynamics is considered among the most important factors for disaster impact minimization (Aubrecht et al., 2013a). This applies to both the pre-event stage for designing appropriate preparedness measures and to acute crisis situations when an event chain actually unfolds for efficient situation-aware response. The presented DynaPop population dynamics model is developed at the interface of those interlinked crisis stages and aims at providing basic input for social impact evaluation and decision support in crisis management. The model provides the starting point for assessing population exposure dynamics - thus here labeled as DynaPop-X - which can either be applied in a sense of illustrating the changing locations and numbers of affected people at different stages during an event or as ex-ante estimations of probable and maximum expected clusters of affected population (Aubrecht et al., 2013b; Freire & Aubrecht, 2012). DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation (Ahola et al., 2007; Bhaduri, 2008; Cockings et al., 2010). We will present ongoing developments particularly focusing on the implementation logic of the model using the emikat software tool, a data management system initially designed for inventorying and analysis of spatially resolved regional air pollutant emission scenarios. This study was performed in the framework of the EU CRISMA project. CRISMA is funded from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552. REFERENCES Ahola, T., Virrantaus, K., Krisp, J.K., Hunter, G.J. (2007) A spatio-temporal population model to support risk assessment and damage analysis for decision-making. International Journal of Geographical Information Science, 21(8), 935-953. Aubrecht, C., Fuchs, S., Neuhold, C. (2013a) Spatio-temporal aspects and dimensions in integrated disaster risk management. Natural Hazards, 68(3), 1205-1216. Aubrecht, C., Özceylan, D., Steinnocher, K., Freire, S. (2013b) Multi-level geospatial modeling of human exposure patterns and vulnerability indicators. Natural Hazards, 68(1), 147-163. Bhaduri, B. (2008) Population distribution during the day. In S. Shekhar & X. Hui, eds., Encyclopedia of GIS. Springer US, 880-885. Cockings, S., Martin, D. & Leung, S. (2010) Population 24/7: building space-time specific population surface models. In M. Haklay, J. Morley, & H. Rahemtulla, eds., Proceedings of the GIS Research UK 18th Annual conference. GISRUK 2010. London, UK, 41-47. Freire, S., Aubrecht, C. (2012) Integrating population dynamics into mapping human exposure to seismic hazard. Natural Hazards and Earth System Sciences, 12(11), 3533-3543.

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

2014-05-01

341

Spatio-temporal Variability of the Relation between African Easterly Waves and West African Squall Lines in 1998 and 1999  

NASA Astrophysics Data System (ADS)

This study investigates the spatio-temporal variability of the relationship between African Easterly Waves (AEWs) and the lifecycle and characteristics of Squall Lines (SLs) over West Africa for the two six-month periods May-October 1998 and 1999. 81 AEWs have been tracked using analyses from the European Centre for Medium-Range Weather Forecasts and 344 SLs have been identified by localizing their leading edges mainly from passive microwave rain rate retrievals. It is found that the area west of the AEW trough is a favorable location for SL generation over the entire tropical West Africa. In the Sahel, a second peak around the region of maximum AEW-related southerlies is observed. 42% of all SLs identified were defined as "AEW-forced", since they formed in the aforementioned preferred genesis phases. This percentage is larger for the Sahel than for the Guinea Coast/Soudanian region. The contribution of AEWs to SL generation increases from 20% around 15°E to 68% at the West African coast (15°W). Furthermore, the impact of AEWs on SL genesis is larger at the height of the Sahelian rainy season (July-September) than in the remaining early and late monsoon months. Few SLs form after midnight and in the morning hours, but if so, they typically owe their existence to the wave forcing. Since AEW-forced SLs exhibit no extraordinary characteristics (lifetime, propagation speed, size, and rain rate) compared to the remaining SLs, it is suggested that the impact of AEWs is largely restricted to SL initiation and organization processes. Finally, some potential physical mechanisms responsible for the AEW-SL-genesis relationship are discussed.

Reiner, A.; Fink, A. H.

2003-04-01

342

Dynamic disordering of liposomal cocktails and the spatio-temporal favorable release of cargoes to circumvent drug resistance.  

PubMed

Multidrug resistance (MDR) has been a major impediment to the success of cancer chemotherapy. Extensive efforts have been devoted to the development of drug delivery systems using nanotechnology to reverse MDR in cancer. However, the spontaneous release of drug payloads was always a slow process, which leads to the low intracellular drug concentration resulting in consequent drug insensitivity. To circumvent this limitation, we described a liposomal cocktail (LMDHV) constructed by a pH-responsive molecule (i.e., malachite green carbinol base (MG)) and liposome conjugated with Her-2 antibody for codelivery of doxorubicin (DOX) and verapamil (VER) to suppress drug resistance in Her-2 positive breast cancer. MG inserted in the bilayer as pH responders greatly contributed to the destabilization of the vesicle membrane in low pH, followed by the rapid release of the payloads. LMDHV showed 6-fold reversal efficiency in DOX resistant breast cancer owing to the efficient tumor targeting delivery and rapid burst release of drug intracellularly. Compared to tumor inhibition ratio of treated groups by free DOX (32.4 ± 7.4%), our designed kinetically favorable drug release system exhibited significantly (P < 0.01) enhanced tumor inhibition ratio up to 83.9 ± 12.5%, which is attributed to the remarkably increased drug concentration in cells. The spatio-temporal favorable release of drugs resulted in synergistic inhibition of tumor growth in xenografts. We envision that this new type of liposomal cocktail might be potentially utilized to circumvent drug resistance in the future. PMID:24456605

Liu, Ya; Li, Li-Li; Qi, Guo-Bin; Chen, Xi-Guang; Wang, Hao

2014-03-01

343

Spatio-temporal analysis on enterovirus cases through integrated surveillance in Taiwan  

PubMed Central

Background Severe epidemics of enterovirus have occurred frequently in Malaysia, Singapore, Taiwan, Cambodia, and China, involving cases of pulmonary edema, hemorrhage and encephalitis, and an effective vaccine has not been available. The specific aim of this study was to understand the epidemiological characteristics of mild and severe enterovirus cases through integrated surveillance data. Methods All enterovirus cases in Taiwan over almost ten years from three main databases, including national notifiable diseases surveillance, sentinel physician surveillance and laboratory surveillance programs from July 1, 1999 to December 31, 2008 were analyzed. The Pearson’s correlation coefficient was applied for measuring the consistency of the trends in the cases between different surveillance systems. Cross correlation analysis in a time series model was applied for examining the capability to predict severe enterovirus infections. Poisson temporal, spatial and space-time scan statistics were used for identifying the most likely clusters of severe enterovirus outbreaks. The directional distribution method with two standard deviations of ellipse was applied to measure the size and the movement of the epidemic. Results The secular trend showed that the number of severe EV cases peaked in 2008, and the number of mild EV cases was significantly correlated with that of severe ones occurring in the same week [r?=?0.553, p?spatio-temporal clusters in June 2008, the mild cases had begun to rise since May 2008, and the outbreak spread from south to north. Conclusions Local public health professionals can monitor the temporal and spatial trends plus spatio-temporal clusters and isolation rate of EV-71 in mild and severe EV cases in a community when virus transmission is high, to provide early warning signals and to prevent subsequent severe epidemics.

2014-01-01

344

Identifying the spatio-temporal trends in snow cover in upper Euphrates basin using remote sensing  

NASA Astrophysics Data System (ADS)

The Euphrates and Tigris are the two major rivers which serve as the most important water resources in the Middle East. The precipitation falls mostly in the form of snow over higher elevations of Euphrates Basin and remains on the ground for nearly half of the year. Monitoring of this snow covered area (SCA) which is a key element for hydrological cycle is crucial for making accurate forecasts of snowmelt discharge especially for energy production, flood control, irrigation and reservoir operation optimization in the upper Euphrates basin. Remote sensing allows detection of spatio-temporal patterns of snow cover across large areas in inaccessible terrain like Eastern part of Turkey which is highly mountainous. In this study the seasonal evaluation of snow cover from 2000 to 2008 is performed by using eight-day snow cover products (MOD10C2). The MOD10C2 is a climate modeling grid product at a 0.05o resolution with global coverage and 8-day availability. The utility of the snow recognition product (SNOBS-1b) of EUMETSAT Hydrological Application Facility (HSAF) project in obtaining snow cover area is also analyzed. The SNOBS-1b snow cover product is a daily product having 0.05o resolution. The final version of SNOBS-1b product has started to be produced since January 2008 by the project team members (METU, AU). Therefore the comparison in retrieving snow cover area from MOD10C2 and SNOBS-1b was performed for the snow year 2007-2008 for eastern part of Turkey. In comparison of the snow cover area for the period of 2000-2008, an earlier melting was observed in the last three years compared to the previous years. This early melting was seen obviously at lower elevation zones (lower than 2000 m) of the basin. At elevation zones having higher elevations than 2000m, the spatio-temporal pattern of snow cover does not show too much variation among the years. In order to investigate the warming trend in the study area, the long term precipitation and temperature data collected at meteorological stations located in the basin were used. Using the snowmelt runoff model (SRM), the relationship among air temperature, precipitation, snow cover and runoff is analyzed. The potential effects of climate change on the runoff characteristics of the upper Euphrates basin are discussed.

Sürer, S.; Akyürek, Z.; Arda ?orman, A.; ?orman, A. ?.; Ünal ?orman, A.

2009-04-01

345

Spatio-temporal effects of low severity grassland fire on soil colour  

NASA Astrophysics Data System (ADS)

Fire changes soil properties directly, through temperature, or indirectly with ash deposition and the temporal elimination of vegetal cover. Both influences change soil colour and soil properties. The degree of changes depends on fire severity that has important implications on soil organic matter, texture, mineralogy and hydrological properties and type of ash produced. The ash colour is different according to the temperature of combustion and burned specie and this property will have implications on soil colour. In addition, ash properties have a strong spatial variability. The aim of this work is to study the spatio-temporal effects of a low severity grassland fire on soil colour occurred in Lithuania, near Vilnius city (54° 42' N, 25° 08' E, 158 m.a.s.l.). After the fire it was designed a plot of 20x20m in a burned and unburned flat area. Soil colour was analysed immediately after the fire, and 2, 5, 7 and 9 months after the fire. In each sampling 25 soil samples were collected, carried out to the laboratory, dried at room temperature (20-24° C) and sieved with the <2mm mesh. Soil colour was observed with the Munsell colour chart and the soil chroma value (CV) was observed. Since data did not respected the Gaussian distribution a neperian logarithmic (ln) transformation was applied. Differences among time and between plots were observed with the repeated measures ANOVA test, followed by a Tukey HSD test. Differences were significant at a p<0.05. The spatial variability (SV) was assessed with the coefficient of variation using non transformed data. The results showed differences among time at a p<0.001, treatment at a p<0.01 and time x treatment at a p<0.01. This means that fire during the first 9 months changed significantly soil colour. The CV of the burned plot was lower than the control plot (darker colour), that is attributed to the deposition of charred material and charcoal. This ash produced in this fire was mainly black coloured. With the time the soil of the burned plot became lighter, due the movement of charred material and charcoal in depth through soil profile. After the fire SV was higher in the burned plot (13.27%) than in the unburned plot (7.95%). This major variability might be attributed to ash influence, since this fire did nit had direct effects on soil. Despite the reduced CV, some patches burned at higher severity, and ash was dark and light grey and this might had influences on soil colour SV. In the following measurements SV was very similar, but always slightly higher in the control plot than in the burned plot. Two months, unburned 15.52% and burned, 14.70%. Five months, unburned, 14.78% and burned 14.42%, Seven months, unburned, 15.15% and burned, 14.67%. Nine months, unburned, 18.96% and burned 17.84%. After the fire ash can be (re)distributed uncountable times. In the immediate period after the fire, finner ash produced at higher severities is easily transported by wind and can remix (Pereira et al., 2013a, Pereira et al., 2013b) and change soil colour. In this fire, vegetation recovered very fast, thus this process might occurred only in the first weeks after the fire (Pereira et al., 2013c). Since vegetation recovered fast, soil colour SV depended on carbon and charred material movement in depth soil profile. Further studies are needed on the soil colour evolution after the fire, since can be an indicator of soil properties such as temperature reached with implications in other soil properties. Acknowledgements The authors appreciated the support of the project "Litfire", Fire effects in Lithuanian soils and ecosystems (MIP-048/2011) funded by the Lithuanian Research Council, Spanish Ministry of Science and Innovation for funding through the HYDFIRE project CGL2010-21670-C02-01, FUEGORED (Spanish Network of Forest Fire Effects on Soils http://grupo.us.es/fuegored/) and to Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya. References Pereira, P. Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2013a) Mod

Pereira, Paulo; Cerdà, Artemi; Bolutiene, Violeta; Pranskevicius, Mantas; Úbeda, Xavier; Jordán, Antonio; Zavala, Lorena; Mataix-Solera, Jorge

2013-04-01

346

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

PubMed Central

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

D'Angelo, Egidio

2008-01-01

347

Three-dimensional instabilities in a discretely heated annular flow: Onset of spatio-temporal complexity via defect dynamics  

NASA Astrophysics Data System (ADS)

The transition to three-dimensional and unsteady flow in an annulus with a discrete heat source on the inner cylinder is studied numerically. For large applied heat flux through the heater (large Grashof number Gr), there is a strong wall plume originating at the heater that reaches the top and forms a large scale axisymmetric wavy structure along the top. For Gr ? 6 × 109, this wavy structure becomes unstable to three-dimensional instabilities with high azimuthal wavenumbers m ˜ 30, influenced by mode competition within an Eckhaus band of wavenumbers. Coexisting with some of these steady three-dimensional states, solution branches with localized defects break parity and result in spatio-temporal dynamics. We have identified two such time dependent states. One is a limit cycle that while breaking spatial parity, retains spatio-temporal parity. The other branch corresponds to quasi-periodic states that have globally broken parity.

Lopez, Juan M.; Marques, Francisco

2014-06-01

348

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

NASA Astrophysics Data System (ADS)

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.

Nasser, Hassan; Marre, Olivier; Cessac, Bruno

2013-03-01

349

Robust line-of-sight stability and jitter compensation using spatio- temporal-filtering based control approaches  

Microsoft Academic Search

A spatio-temporal filter (STF) based active vibration suppression technique is presented. The STF approach is intended for use for stability and jitter compensation for the UltraLITE Precision Deployable Experiment - a ground demonstration of a sparse array, deployable, large aperture, optical space telescope concept. This technique is well suited for control of complex, real-world structures because it requires little model

Stuart J. Shelley; Thomas D. Sharp; Keith K. Denoyer

350

Spatio-temporal analysis of the role of climate in inter-annual variation of malaria incidence in Zimbabwe  

Microsoft Academic Search

BACKGROUND: On the fringes of endemic zones climate is a major determinant of inter-annual variation in malaria incidence. Quantitative description of the space-time effect of this association has practical implications for the development of operational malaria early warning system (MEWS) and malaria control. We used Bayesian negative binomial models for spatio-temporal analysis of the relationship between annual malaria incidence and

Musawenkoi LH Mabaso; Penelope Vounatsou; Stanely Midzi; Joaquim Da Silva; Thomas Smith

2006-01-01

351

Spatio-Temporal Regulation of Rac1 Localization and Lamellipodia Dynamics during Epithelial Cell-Cell Adhesion  

Microsoft Academic Search

Cadherin-dependent epithelial cell-cell adhesion is thought to be regulated by Rho family small GTPases and PI 3-kinase, but the mechanisms involved are poorly understood. Using time-lapse microscopy and quantitative image analysis, we show that cell-cell contact in MDCK epithelial cells coincides with a spatio-temporal reorganization of plasma membrane Rac1 and lamellipodia from noncontacting to contacting surfaces. Within contacts, Rac1 and

Jason S. Ehrlich; Marc D. H. Hansen; W. James Nelson

2002-01-01

352

Dispersal mechanisms of the narrow endemic Polygala vayredae : dispersal syndromes and spatio-temporal variations in ant dispersal assemblages  

Microsoft Academic Search

This study assesses the dispersal mechanisms of the narrow endemic Polygala vayredae, analysing the functioning of its dispersal syndromes (anemochory and myrmecochory), the spatio-temporal variability of the\\u000a disperser assemblage, foraging behaviour and dispersal ability, and the role of the elaiosome in ant attraction and seed germination.\\u000a The dispersion of diaspores begins when either (1) capsules or seeds fall beneath the

Sílvia Castro; Victoria Ferrero; João Loureiro; Xavier Espadaler; Paulo Silveira; Luis Navarro

2010-01-01

353

Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli  

Microsoft Academic Search

We present a generalized reverse correlation technique that can be used to estimate the spatio-temporal receptive fields (STRFs) of sensory neurons from their responses to arbitrary stimuli such as auditory vocalizations or natural visual scenes. The general solution for STRF estimation requires normalization of the stimulus-response cross-correlation by the stimulus auto- correlation matrix. When the second-order stimulus statistics are stationary,

eric E Theunissen; Stephen V David; Nandini C Singh; Anne Hsu; William E Vinje; Jack L Gallant

2001-01-01

354

Spatio-temporal Variability of the Relation between African Easterly Waves and West African Squall Lines in 1998 and 1999  

Microsoft Academic Search

This study investigates the spatio-temporal variability of the relationship between African Easterly Waves (AEWs) and the lifecycle and characteristics of Squall Lines (SLs) over West Africa for the two six-month periods May-October 1998 and 1999. 81 AEWs have been tracked using analyses from the European Centre for Medium-Range Weather Forecasts and 344 SLs have been identified by localizing their leading

A. Reiner; A. H. Fink

2003-01-01

355

Spatio-temporal evolution of velocity structure, concentration and grain-size stratification within experimental particulate gravity currents  

Microsoft Academic Search

We describe a flume study of the spatio-temporal evolution of particulate gravity currents. Time series of the vertical structure of flow in terms of the forward component of velocity, flow concentration and grain-size of suspended sediment were co-measured at a different position along the flume for each of a series of nominally identical flows. The data are combined to show

W. d. Mccaffrey; C. m. Choux; J. h. Baas; P. d. w. Haughton

2003-01-01

356

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

PubMed Central

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 to characterize the mode of motion of nanocarriers and to quantify 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 and DC-Chol-DOPE/DNA lipoplexes in CHO-K1 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). In the cytosol, the lipoplexes’ motion was characterized by active transport with average velocity ? ? 0.03 µm/s and random motion. The method permitted us to generate intracellular transport map showing several regions of concerted motion of lipoplexes.

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

2013-01-01

357

Wintertime spatio-temporal variation of ultrafine particles in a Belgian city.  

PubMed

Simultaneous measurements of ultrafine particles (UFPs) were carried out at four sampling locations situated within a 1 km(2) grid area in a Belgian city, Borgerhout (Antwerp). All sampling sites had different orientation and height of buildings and dissimilar levels of anthropogenic activities (mainly traffic volume). The aims were to investigate: (i) the spatio-temporal variation of UFP within the area, (ii) the effect of wind direction with respect to the volume of traffic on UFP levels, and (iii) the spatial representativeness of the official monitoring station situated in the study area. All sampling sites followed similar diurnal patterns of UFP variation, but effects of local traffic emissions were evident. Wind direction also had a profound influence on UFP concentrations at certain sites. The results indicated a clear influence of local weather conditions and the more dominant effect of traffic volumes. Our analysis indicated that the regional air quality monitoring station represented the other sampling sites in the study area reasonably well; temporal patterns were found to be comparable though the absolute average concentrations showed differences of up to 35%. PMID:22705865

Mishra, Vinit K; Kumar, Prashant; Van Poppel, Martine; Bleux, Nico; Frijns, Evelien; Reggente, Matteo; Berghmans, Patrick; Int Panis, Luc; Samson, Roeland

2012-08-01

358

Spatio-temporal variability of meteorological and hydrologic droughts in typical closed glacial basin  

NASA Astrophysics Data System (ADS)

An analysis of meteorological droughts from March 1961 to Feburary 2001 in Tarim Basin by using Reconnaissance Drought Index (RDI) incorporating potential evapotranspiration is presented, while hydrological droughts within the source region of Tarim River were also recognized based on Streamflow Drought Index (SDI). To assess spatio-temporal variability of meteorological droughts, a principal component analysis (PCA) were applied to the RDI series, four well-defined parts with different temporal evolution of droughts were identified (north, south, west and east parts of Tarim Basin). With a focus on the north and south part, where three most important headstreams including Aksu River, Yarkant River and Hotan River were distributed, the relationship between meteorological and hydrolgical droughts was investigated in multiple timescales (1,3,6,12 months) comparison between SDI series and the corresponding RDI principal components through the Fast Fourier Transform algorithm (FFT). This study aims to reveal complexities of hydrologic cycle over this closed basin where glacier melting plays a very active role and how the meteorological and hydrological droughts affect each other under regional climate change.

Li, Z.; Li, J.; Hao, Z.; Chen, S.

2012-04-01

359

An inducible, modular system for spatio-temporal control of gene expression in stomatal guard cells  

PubMed Central

Stomata, flanked by pairs of guard cells, are small pores on the leaf surfaces of plants and they function to control gas exchange between plants and the atmosphere. Stomata will open when water is available to allow for the uptake of carbon dioxide for photosynthesis. During periods of drought, stomata will close to reduce desiccation stress. As such, optimal functioning of stomata will impact on water use efficiency by plants. The development of an inducible, modular system for robust and targeted gene expression in stomatal guard cells is reported here. It is shown that application of ethanol vapour to activate the gene expression system did not affect the ability of stomata to respond to ABA in bioassays to determine the promotion of stomatal closure and the inhibition of stomatal opening. The system that has been developed allows for robust spatio-temporal control of gene expression in all cells of the stomatal lineage, thereby enabling molecular engineering of stomatal function as well as studies on stomatal development.

Xiong, Tou Cheu; Hann, Cliona M.; Chambers, John P.; Surget, Marie; Ng, Carl K.-Y.

2009-01-01

360

Spatio-temporal evolution of seismic clusters in southern and central California  

NASA Astrophysics Data System (ADS)

We examine evolutionary patterns of seismic clusters and their relations to (i) heat flow, rock types and seismogenic depth, (ii) structure of the regional fault network and (iii) occurrence times of large near-by earthquakes. The analyses are based on our recent methodology for detection and classification of seismic clusters, and new high-quality relocated catalogs of southern and central California. The novelty of this study is in systematic uniform analysis of thousands of robustly detected seismic clusters of small-to-medium magnitude events, as opposed to the handful of largest clusters analyzed in most studies. Our previous research established the existence of three types of earthquake clusters (burst-like, swarm-like, and singles) of small-to-medium magnitude, and demonstrated that the cluster type is closely related to the heat flow and other properties governing the effective viscosity of a region. The continuing work focuses on spatio-temporal evolution of different cluster types in relation to seasonal patterns, activity switching between different areas, and systematic patterns preceding large events. The results so far document (i) activity switching of small-to-medium magnitude earthquakes between different faults, (ii) mild seasonal fluctuations of intensity of such events, and (iii) several premonitory patterns that are seen most clearly near Parkfield.

Zaliapin, I. V.; Ben-Zion, Y.

2013-12-01

361

Unification of Bell, Leggett-Garg and Kochen-Specker inequalities: Hybrid spatio-temporal inequalities  

NASA Astrophysics Data System (ADS)

The Bell-type (spatial), Kochen-Specker (contextuality) or Leggett-Garg (temporal) inequalities are based on classically plausible but otherwise quite distinct assumptions. For any of these inequalities, satisfaction is equivalent to a joint probability distribution for all observables in the experiment. This implies a joint distribution for all pairs of observables, and is indifferent to whether or not they commute in the theory. This indifference underpins a unification of the above inequalities into a general framework of correlation inequalities. When the physical scenario is such that the correlated pairs are all compatible, the resulting correlation is nonsignaling, which may be local or multi-particle, corresponding to contextuality or Bell-type inequalities. If the pairs are incompatible, the resulting correlation corresponds to Leggett-Garg (LG) inequalities. That quantum mechanics (QM) violates all these inequalities suggests a close connection between the local, spatial and temporal properties of the theory. As a concrete manifestation of the unification, we extend the method due to Roy and Singh (J. Phys. A, 11 (1978) L167) to derive and study a new class of hybrid spatio-temporal inequalities, where the correlated pairs in the experiment are both compatible or incompatible. The implications for cryptography and monogamy inequalities of the unification are briefly touched upon.

Das, Siddhartha; Aravinda, S.; Srikanth, R.; Home, Dipankar

2013-12-01

362

Spatio-temporally Multiplexed Multiphoton Calcium Imaging for Monitoring Neuronal Networks In Vivo  

NASA Astrophysics Data System (ADS)

Calcium imaging using 2-photon laser scanning microscopy is an ideal tool for interrogating large ensembles of neurons in the intact brain, but suffers from poor temporal resolution when using conventional raster scanning. Using multiple laser beams can increase image acquisition rates. Unfortunately, this approach is highly sensitive to light scattering in brain tissue, which precludes the use of camera-type detectors necessary to distinguish fluorescence from different beams. To circumvent this problem, one can introduce a spatio-temporal multiplexing approach separating multiple beams in time by the fluorescence lifetime of the calcium dye. The scattered fluorescence emission from individual beams is distinguished by a state-of-the-art single-channel hybrid photomultiplier. By combining this method with fast raster scanning, millisecond acquisition rates are achieved for high-resolution in vivo calcium imaging of ˜100 layer 2/3 neurons in barrel cortex. Additionally, recording of neuronal activity in multiple axial planes at rates of tens of milliseconds is achieved, by scanning individual beams at different tissue depths. This is the first time multiple plane calcium imaging has been achieved in-vivo.

Cheng, Adrian

363

Spatio-temporal analysis of brain MRI images using hidden Markov models.  

PubMed

A rapidly increasing number of medical imaging studies is longitudinal, i.e. involves series of repeated examinations of the same individuals. This paper presents a methodology for analysis of such 4D images, with brain aging as the primary application. An adaptive regional clustering method is first adopted to construct a spatial pattern, in which a measure of correlation between morphological measurements and a continuous patient's variable (age in our case) is used to group brain voxels into regions; Secondly, a dynamic probabilistic Hidden Markov Model (HMM) is created to statistically analyze the relationship between spatial brain patterns and hidden states; Thirdly, parametric HMM models under a bagging framework are used to capture the changes occurring with time by decoding the hidden states longitudinally. We apply this method to datasets from elderly individuals, and test the effectiveness of this spatio-temporal model in analyzing the temporal dynamics of spatial aging patterns on an individual basis. Experimental results show this method could facilitate the early detection of pathological brain change. PMID:20879311

Wang, Ying; Resnick, Susan M; Davatzikos, Christos

2010-01-01

364

Spatio-temporal analysis of tamoxifen-induced bystander effects in breast cancer cells using microfluidics  

PubMed Central

The bystander effect in cancer therapy is the inhibition or killing of tumor cells that are adjacent to those directly affected by the agent used for treatment. In the case of chemotherapy, little is known as to how much and by which mechanisms bystander effects contribute to the elimination of tumor cells. This is mainly due to the difficulty to distinguish between targeted and bystander cells since both are exposed to the pharmaceutical compound. We here studied the interaction of tamoxifen-treated human breast cancer MCF-7 cells with their neighboring counterparts by exploiting laminar flow patterning in a microfluidic chip to ensure selective drug delivery. The spatio-temporal evolution of the bystander response in non-targeted cells was analyzed by measuring the mitochondrial membrane potential under conditions of free diffusion. Our data show that the bystander response is detectable as early as 1 hour after drug treatment and reached effective distances of at least 2.8?mm. Furthermore, the bystander effect was merely dependent on diffusible factors rather than cell contact-dependent signaling. Taken together, our study illustrates that this microfluidic approach is a promising tool for screening and optimization of putative chemotherapeutic drugs to maximize the bystander response in cancer therapy.

Rios-Mondragon, Ivan; Wang, Xiang; Gerdes, Hans-Hermann

2012-01-01

365

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

PubMed

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

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

2014-10-01

366

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

NASA Astrophysics Data System (ADS)

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

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

2005-05-01

367

Spatio-temporal analysis of soil erosion risk and runoff using AnnAGNPS  

NASA Astrophysics Data System (ADS)

Soil erosion is one form of land degradation in Ethiopia deteriorating the fertility and productivity of the land. This fact indicates the need to delineate high erosion risk areas for appropriate soil and conservation measures. Land use/cover change is one of the important factors in soil erosion. This study attempts test and implement AnnAGNPS model to estimate the spatio-temporal patterns of soil erosion and runoff associated with land use changes in the past 50 years in the 9900 ha upstream part of the Koga catchment. High erosion risk areas will then be delineated for simulation of the appropriate soil and water conservation measures that would reduce the soil loss. The study is based on two years high temporal resolution data on discharge, sediment, and rain fall accompanied by historical land use/cover data generated from satellite imagery. In addition, it uses several documented physical parameters of the study area. The Koga catchment is one of the agriculture dominated typical catchments in the North Western Ethiopian highlands with high population density that lead to increased pressure on natural resources.

Yeshaneh, Eleni; Wagner, Wolfgang; Blöschl, Günter

2014-05-01

368

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

NASA Astrophysics Data System (ADS)

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

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

2007-03-01

369

Spatio-temporal variation and statistical characteristic of extreme dry spell in Yellow River Basin, China  

NASA Astrophysics Data System (ADS)

Drought is one of the most detrimental natural hazards in Yellow River Basin (YRB). In this research, spatio-temporal variation and statistical characteristic of drought in YRB is studied by using dry spell. Two extreme series, including annual maximum series (AMS) and partial duration series (PDS), are used and simulated with generalized extreme value (GEV), generalized Pareto (GP), and Pearson type III (PE3) distributions. The results show that the northern part is drier than the southern part of YRB. Besides, the maximum dry spell usually starts in October, November, and December. According to the trend analysis, mean maximum length of dry spell (MxDS) shows a negative trend in most stations. From the L-moments and Kolmogorov-Smirnov test method, it can be found that GEV model can better fit AMS while GP and PE3 can better fit PDS. Moreover, the quantiles from optimal model of AMS and PDS depict a similar distribution with values increases from south to north. The spatial distribution of scale and location parameters of GEV model for AMS shows a south-to-north gradient, while the distribution of shape parameter is a little irregularity. Furthermore, based on the linear correlation analysis, there is an evident linear relation between location and scale parameters with mean and standard variation of MxDS, respectively.

She, Dunxian; Xia, Jun; Song, Jiyun; Du, Hong; Chen, Junxu; Wan, Long

2013-04-01

370

Spatio-temporal variability of satellite-derived aerosol optical thickness over Northeast Asia in 2004  

NASA Astrophysics Data System (ADS)

In this study a modified Bremen aerosol retrieval (BAER) method was used to retrieve aerosol optical thickness (AOT) over both land and ocean using moderate resolution imaging spectro-radiometer (MODIS) data over Northeast Asia for a full year during 2004. Retrieved MODIS AOT data were in good agreement with data obtained from a ground-based AERONET sunphotometer ( r=0.90, linear slope=0.89). Seasonal variation analysis of AOT revealed maximum values in summer (˜0.41) and minimum values in winter (˜0.25). The contribution of each aerosol type to total AOT was estimated for each pixel. A spectral shape fitting procedure was used to select the optimum aerosol model for AOT retrieval among six aerosol types: urban, rural, maritime, tropospheric, Asian dust, and biomass burning. The spatio-temporal distribution of average AOT was analyzed for the following five sectors in Northeast Asia: (I) East China, (II) Yellow Sea, (III) Korea, (IV) East Sea, and (V) South Sea plus a part of Japan. Maximum AOT values of 0.75±0.18 were measured over sector (I) in summer, while minimum values of 0.10±0.02 were recorded over sector (IV) in winter. AOT estimates over sector (I) were much higher than those of other sectors due to an increased contribution to the total AOT by fine urban aerosol, which contributed up to 56.5% of the total AOT.

Lee, Kwon Ho; Kim, Young Joon; von Hoyningen-Huene, Wolfgang; Burrow, John P.

371

The influence of spatio-temporal resource fluctuations on insular rat population dynamics  

PubMed Central

Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture–recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control.

Russell, James C.; Ruffino, Lise

2012-01-01

372

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

NASA Astrophysics Data System (ADS)

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

Lee, Chieh-Han; Yu, Hwa-Lung

2014-05-01

373

Spatio-Temporal Complexity analysis of the Sea Surface Temperature in the Philippines  

NASA Astrophysics Data System (ADS)

A spatio-temporal complexity (STC) measure which has been previously used to analyze data from terrestrial ecosystems is employed to analyse 21 years of remotely sensed sea-surface temperature (SST) data from the Philippines. STC on the Philippine wide SST showed the monsoonal variability of the Philippine waters. STC is correlated with the SST mean (R2 ? 0.7), and inversely correlated with the SST standard deviation (R2 ? 0.9). Both STC and SST are highest during the middle of the year, which coincides with the Southwest Monsoon, but with the STC values being higher towards the end of the monsoon until the start of the inter-monsoon. In order to determine if STC has the potential to define limits of bio-regions, the spatial domain was subsequently divided into six thermal regions computed via clustering of temperature means. STC and EOF of the STC values were computed for each thermal region. Our STC analysis of the SST data, and comparisons with SST values suggest that the STC measure may be useful for characterising environmental heterogeneity over space and time for many long-term remotely sensed data.

Botin, Z. T.; David, L. T.; Del Rosario, R. C. H.; Parrott, L.

2010-11-01

374

Spatio-temporal requirements for transposable element piRNA-mediated silencing during Drosophila oogenesis  

PubMed Central

During Drosophila oogenesis, transposable element (TE) repression involves the Piwi-interacting RNA (piRNA) pathway which ensures genome integrity for the next generation. We developed a transgenic model to study repression of the Idefix retrotransposon in the germline. Using a candidate gene KD-approach, we identified differences in the spatio-temporal requirements of the piRNA pathway components for piRNA-mediated silencing. Some of them (Aub, Vasa, Spn-E) are necessary in very early stages of oogenesis within the germarium and appear to be less important for efficient TE silencing thereafter. Others (Piwi, Ago3, Mael) are required at all stages of oogenesis. Moreover, during early oogenesis, in the dividing cysts within the germarium, Idefix anti-sense transgenes escape host control, and this is associated with very low piwi expression. Silencing of P-element-based transgenes is also strongly weakened in these cysts. This region, termed the ‘Piwiless pocket’ or Pilp, may ensure that new TE insertions occur and are transmitted to the next generation, thereby contributing to genome dynamics. In contrast, piRNA-mediated silencing is strong in germline stem cells in which TE mobilization is tightly repressed ensuring the continued production of viable germline cysts.

Dufourt, Jeremy; Dennis, Cynthia; Boivin, Antoine; Gueguen, Nathalie; Theron, Emmanuelle; Goriaux, Coline; Pouchin, Pierre; Ronsseray, Stephane; Brasset, Emilie; Vaury, Chantal

2014-01-01

375

Spatio-temporal dynamics of the magnetosphere: Mutual information function analysis  

NASA Astrophysics Data System (ADS)

The magnetospheric response to strong driving by the solar wind is highly structured, and spatially resolved data are essential for the understanding of the spatio-temporal dynamics. The global and local features of the magnetosphere are studied using nonlinear dynamical techniques of phase space reconstruction. A database of the solar wind data from satellites and ground-based magnetometer stations is used to study the magnetospheric response to solar wind variables using mutual information functions. A key feature of the mutual information function is its ability to bring out the linear as well as nonlinear correlations and such functions are needed to study the inherently nonlinear dynamics of the magnetosphere. The spreads in the average mutual information functions computed for the different stations show strong correlations with the solar wind convective electric field and the sudden changes in the dynamic pressure. The time evolution of mutual information shows a westward expansion of the disturbed region in the night side magnetosphere, starting from the near midnight sectors. The mutual information functions are used to quantify the transfer of information among the different locations.

Sharma, Surja; Chen, Jian; Veeramani, Thangamani

2007-11-01

376

A stereoscopic video conversion scheme based on spatio-temporal analysis of MPEG videos  

NASA Astrophysics Data System (ADS)

In this article, an automatic stereoscopic video conversion scheme which accepts MPEG-encoded videos as input is proposed. Our scheme is depth-based, relying on spatio-temporal analysis of the decoded video data to yield depth perception cues, such as temporal motion and spatial contrast, which reflect the relative depths between the foreground and the background areas. Our scheme is shot-adaptive, demanding that shot change detection and shot classification be performed for tuning of algorithm or parameters that are used for depth cue combination. The above-mentioned depth estimation is initially block-based, followed by a locally adaptive joint trilateral upsampling algorithm to reduce the computing load significantly. A recursive temporal filter is used to reduce the possible depth fluctuations (and also artifacts in the synthesized images) resulting from wrong depth estimations. The traditional Depth-Image-Based-Rendering algorithm is used to synthesize the left- and right-view frames for 3D display. Subjective tests show that videos converted by our scheme provide comparable perceived depth and visual quality with those converted from the depth data calculated by stereo vision techniques. Also, our scheme is shown to outperform the well-known TriDef software in terms of human's perceived 3D depth. Based on the implementation by using "OpenMP" parallel programming model, our scheme is capable of executing in real-time on a multi-core CPU platform.

Lin, Guo-Shiang; Huang, Hsiang-Yun; Chen, Wei-Chih; Yeh, Cheng-Ying; Liu, Kai-Che; Lie, Wen-Nung

2012-12-01

377

Spatio-Temporal Analysis of Photospheric Turbulent Velocity Fields Using the Proper Orthogonal Decomposition  

NASA Astrophysics Data System (ADS)

The spatio-temporal dynamics of the solar photosphere are studied by performing a proper orthogonal decomposition (POD) of line-of-sight velocity fields computed from high-resolution data coming from the SOHO/MDI instrument. Using this technique, we are able to identify and characterize the different dynamical regimes acting in the system. All of the POD modes are characterized by two well-separated peaks in the frequency spectra. In particular, low-frequency oscillations, with frequencies in the range 20 130 ?Hz, dominate the most energetic POD modes (excluding solar rotation) and are characterized by spatial patterns with typical scales of about 3 Mm. Patterns with larger typical scales, of about 10 Mm, are dominated by p-mode oscillations at frequencies of about 3000 ?Hz. The p-mode properties found by POD are in agreement with those obtained with the classical Fourier analysis. The spatial properties of high-energy POD modes suggest the presence of a strong coupling between low-frequency modes and turbulent convection.

Vecchio, A.; Carbone, V.; Lepreti, F.; Primavera, L.; Sorriso-Valvo, L.; Straus, T.; Veltri, P.

2008-09-01

378

Spatio-Temporal Correlation Tensors Reveal Functional Structure in Human Brain  

PubMed Central

Resting state functional magnetic resonance imaging (fMRI) has been commonly used to measure functional connectivity between cortical regions, while diffusion tensor imaging (DTI) can be used to characterize structural connectivity of white matter tracts. In principle combining resting state fMRI and DTI data could allow characterization of structure-function relations of distributed neural networks. However, due to differences in the biophysical origins of their signals and in the tissues to which they apply, there has been no direct integration of these techniques to date. We demonstrate that MRI signal variations and power spectra in a resting state are largely comparable between gray matter and white matter, that there are temporal correlations of fMRI signals that persist over long distances within distinct white matter structures, and that neighboring intervoxel correlations of low frequency resting state signals showed distinct anisotropy in many regions. These observations suggest that MRI signal variations from within white matter in a resting state may convey similar information as their corresponding fluctuations of MRI signals in gray matter. We thus derive a local spatio-temporal correlation tensor which captures directional variations of resting-state correlations and which reveals distinct structures in both white and gray matter. This novel concept is illustrated with in vivo experiments in a resting state, which demonstrate the potential of the technique for mapping the functional structure of neural networks and for direct integration of structure-function relations in the human brain.

Ding, Zhaohua; Newton, Allen T.; Xu, Ran; Anderson, Adam W.; Morgan, Victoria L.; Gore, John C.

2013-01-01

379

Influence of density dependence on predator-prey seabird interactions at large spatio-temporal scales  

PubMed Central

Theoretical investigations of competitive dynamics have noted that numbers of predator and prey influence each other. However, few empirical studies have demonstrated how a life-history trait of the prey (such as fecundity) can be affected simultaneously by its own density and the density of predators. For instance, density dependence can reduce fecundity with increasing number of prey, while inverse density dependence or Allee effects may occur especially when the prey is a social organism. Here we analysed an intraguild predator–prey system of two seabird species at a large spatio-temporal scale. As expected, we found that fecundity of prey was negatively affected by predator density. Nevertheless, fecundity of prey also increased nonlinearly with its own density and strikingly with the prey–predator ratio. Small groups of prey were probably not able to defend their nests especially against large number of predators. At the highest prey densities (i.e. when anti-predator strategies should be most efficient), prey fecundity also lowered, suggesting the appearance of density dependence mediated by food competition. Allee effects and density dependence occurred across a broad range of population sizes of both the prey and the predator at several local populations facing different ecological environments.

Oro, Daniel; Martinez-Abrain, Alejandro; Paracuellos, Mariano; Nevado, Juan Carlos; Genovart, Meritxell

2005-01-01

380

Window of audio-visual simultaneity is unaffected by spatio-temporal visual clutter  

PubMed Central

In the present study we investigate the rules governing the perception of audiovisual synchrony within spatio-temporally cluttered visual environments. Participants viewed a ring of 19 discs modulating in luminance while hearing an amplitude modulating tone. Each disc modulated with a unique temporal phase (40?ms intervals), with only one synchronized to the tone. Participants searched for the synchronised disc whose spatial location varied randomly across trials. Square-wave modulation facilitated search: the synchronized disc was frequently chosen, with tight response distributions centred near zero-phase lag. In the sinusoidal condition responses were equally distributed over the 19 discs regardless of phase. To investigate whether subjective synchrony in the square-wave condition was limited by spatial or temporal factors we repeated the experiment with either reduced spatial density (9 discs) or temporal density (80?ms phase intervals). Reduced temporal density greatly facilitated synchrony perception but left the synchrony bandwidth unchanged, while no influence of spatial density was found. We conclude that audio-visual synchrony is not strongly constrained by the spatial or temporal density of the visual display, but by a temporal window within which audio-visual events are perceived as synchronous, with a full bandwidth of ~185?ms.

Van der Burg, Erik; Cass, John; Alais, David

2014-01-01

381

Spatio-temporal control of laser beams with thin film shapers  

NASA Astrophysics Data System (ADS)

Recent progress in laser beam shaping and characterization with novel-type thin-film microoptics is presented. These novel microoptical devices offer several distinctive advantages, such as a short optical path, small angles, low roughness or multilayer design. These features allow shaping of laser beams at extreme parameters with respect to spectrum, angular distribution, intensity, or pulse duration. Particular emphasis is laid on (i) hybrid components for high-power diode laser collimation, (ii) spatio-temporal shaping of localized few-cycle wavepackets, and (iii) microoptics for the vacuum ultraviolet. For the fabrication of thin-film structures, vapor deposition with shading masks was used. To improve the efficiency of diode laser collimation, spatially variable AR coatings and integrated arrays of cylindrical microlenses were developed. Arrays of Bessel-like beams were generated from sub-10-fs Ti:sapphire laser pulses by refractive and reflective microaxicons. We further demonstrated the use of microaxicon arrays for spatially resolved autocorrelation of ultrashort pulses. Deposition and etching transfer of flat VUV-structures was studied. Finally, the generation of single-maximum nondiffracting beams by self-apodizing system design is discussed.

Grunwald, Ruediger; Neumann, Uwe J.; Griebner, Uwe; Kebbel, Volker; Kuehn, Hans-Joachim

2004-06-01

382

Spatio-temporal variation of the diterpene steviol in Stevia rebaudiana grown under different photoperiods.  

PubMed

As part of an ongoing study on the effects of photoperiodism on the metabolism of steviol glycosides (SVglys) in Stevia rebaudiana, the spatio-temporal variations of free steviol (SV) have now been evaluated. For its quantitation, an internal standard method was used, based upon a specific fluorometric detection of SV as its methoxycoumarinyl derivative. The level of free SV in leaves did not exceed 30 ?g/g dry wt and was at least 1000-fold smaller than that of its glycosidic conjugates. In other organs, free SV was mainly measured in stem tissue and apices, with relatively large amounts measured in the latter. Similarly to SVglys, the content of free SV was influenced by photoperiod and genotype. In plants grown under long-days (LD) of 16 h, more spatial variations were seen compared to those under short-days (SD) of 8h. In the former, upper leaves contained almost four times more free SV compared to lower ones near the end of vegetative growth. In addition, the correlation between SV and its glycosidic conjugates was more linear under SD. Despite the variability of SV levels, a decrease was noted in all conditions after flower opening, which can be related a decreased transcription of the biosynthetic genes involved. PMID:23402803

Ceunen, Stijn; Geuns, Jan M C

2013-05-01

383

Turing instabilities and spatio-temporal chaos in ratio-dependent Holling-Tanner model.  

PubMed

In this paper we consider a modified spatiotemporal ecological system originating from the temporal Holling-Tanner model, by incorporating diffusion terms. The original ODE system is studied for the stability of coexisting homogeneous steady-states. The modified PDE system is investigated in detail with both numerical and analytical approaches. Both the Turing and non-Turing patterns are examined for some fixed parametric values and some interesting results have been obtained for the prey and predator populations. Numerical simulation shows that either prey or predator population do not converge to any stationary state at any future time when parameter values are taken in the Turing-Hopf domain. Prey and predator populations exhibit spatiotemporal chaos resulting from temporal oscillation of both the population and spatial instability. With help of numerical simulations we have shown that Turing-Hopf bifurcation leads to onset of spatio-temporal chaos when predator's diffusivity is much higher compared to prey population. Our investigation reveals the fact that Hopf-bifurcation is essential for the onset of spatiotemporal chaos. PMID:22207074

Banerjee, Malay; Banerjee, Santo

2012-03-01

384

Spatio-Temporal Data Comparisons for Global Highly Pathogenic Avian Influenza (HPAI) H5N1 Outbreaks  

PubMed Central

Highly pathogenic avian influenza subtype H5N1 is a zoonotic disease and control of the disease is one of the highest priority in global health. Disease surveillance systems are valuable data sources for various researches and management projects, but the data quality has not been paid much attention in previous studies. Based on data from two commonly used databases (Office International des Epizooties (OIE) and Food and Agriculture Organization of the United Nations (FAO)) of global HPAI H5N1 outbreaks during the period of 2003–2009, we examined and compared their patterns of temporal, spatial and spatio-temporal distributions for the first time. OIE and FAO data showed similar trends in temporal and spatial distributions if they were considered separately. However, more advanced approaches detected a significant difference in joint spatio-temporal distribution. Because of incompleteness for both OIE and FAO data, an integrated dataset would provide a more complete picture of global HPAI H5N1 outbreaks. We also displayed a mismatching profile of global HPAI H5N1 outbreaks and found that the degree of mismatching was related to the epidemic severity. The ideas and approaches used here to assess spatio-temporal data on the same disease from different sources are useful for other similar studies.

Chen, Dongmei; Chen, Yue; Wang, Lei; Zhao, Fei; Yao, Baodong

2010-01-01

385

Adaptive Spatio-Temporal Filtering for Movement Related Potentials in EEG-Based Brain-Computer Interfaces.  

PubMed

Movement related potentials (MRPs) are used as features in many brain-computer interfaces (BCIs) based on electroencephalogram (EEG). MRP feature extraction is challenging since EEG is noisy and varies between subjects. Previous studies used spatial and spatio-temporal filtering methods to deal with these problems. However, they did not optimize temporal information or may have been susceptible to overfitting when training data are limited and the feature space is of high dimension. Furthermore, most of these studies manually select data windows and low-pass frequencies. We propose an adaptive spatio-temporal (AST) filtering method to model MRPs more accurately in lower dimensional space. AST automatically optimizes all parameters by employing a Gaussian kernel to construct a low-pass time-frequency filter and a linear ridge regression (LRR) algorithm to compute a spatial filter. Optimal parameters are simultaneously sought by minimizing leave-one-out cross-validation error through gradient descent. Using four BCI datasets from 12 individuals, we compare the performances of AST filter to two popular methods: the discriminant spatial pattern filter and regularized spatio-temporal filter. The results demonstrate that our AST filter can make more accurate predictions and is computationally feasible. PMID:24723632

Lu, Jun; Xie, Kan; McFarland, Dennis J

2014-07-01

386

Scaling Issues and Spatio-Temporal Variability in Ecohydrological Modeling on Mountain Topography: Methods and Future of the VELMA Model  

NASA Astrophysics Data System (ADS)

The interactions between vegetation and hydrology in mountainous terrain are difficult to represent in mathematical models. There are at least three primary reasons for this difficulty. First, expanding plot-scale measurements to the watershed scale requires finding the balance between computational intensity and physical significance. Second, parameters that affect soil, plant and hydrologic processes are distributed heterogeneously across mountain landscapes, and these patterns and processes may be spatially connected. Third, temporal variation in water availability (particularly in seasonal rainfall climates) may involve a “topographical memory” that may be expressed as “lags” between biological and hydrological processes. A unique opportunity for examining the implications of scaling and spatio-temporal variability on ecohydrological models exists at the H.J. Andrews Experimental Forest (HJA) in Blue River, Oregon. HJA is a National Science Foundation Long Term Ecological Research (LTER) site, and has been monitoring climate, stream, and vegetation characteristics of small watersheds for more than 50 years. A recent LIDAR (Light Detection and Ranging) reconnaissance has produced watershed scale estimations of vegetation and soil surface parameters at a very high spatial resolution, allowing spatially-explicit expansion of long-term data. An ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA) developed by the Stieglitz lab at Georgia Tech in collaboration with EPA has also been calibrated specifically for watershed topographies in HJA. VELMA is a coupled ecohydrological model that simulates the cycling and transport of water and nutrients in three dimensions by specific parameterization of hydrological and biogeochemical functions. It contains submodels for plant, soil, and water processes including surface and sub-surface flow on a daily time step. We are using the VELMA model to explore three sequential and fundamental questions in ecohydrological modeling in mountainous terrain. 1) How does the topographical structure of mountains (elevation, slope, and aspect) impact hydrological parameters such as temperature, rainfall, soil depth, canopy structure, and airflow? 2) To what degree are the model results from high-resolution, spatially-explicit parameterization different from results based on broadly distributed means, and when different, on what scale(s) are the discrepancies most pronounced? 3) Is there an optimal scale for the process-based ecohydrological modeling, and if so, what are the computational limits at this scale? This poster will present our overall experimental plan and initial findings. Experimentation on and establishment of a standard procedure for spatial and temporal partitioning in ecohydrological models is a fundamental step from which advancement towards more comprehensive, dynamic models can be developed.

Peterson, K.; Bond, B. J.; McKane, R.; Abdelnour, A. G.; Stieglitz, M.

2010-12-01

387

Monitoring Spatio-temporal Dielectric Permittivity Variation in the Shallow Subsurface through Bayesian Inversion of GPR Data  

NASA Astrophysics Data System (ADS)

A minimum-relative-entropy (MRE) based Bayesian inversion framework is applied to monitor spatio-temporal distribution of dielectric permittivity using tomographic radar first arrival time data from a synt