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Sample records for spatio-temporal blind source

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

    PubMed Central

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

    2009-01-01

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

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

    PubMed

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

    2015-08-01

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

  3. Spatio-temporal source modeling of evoked potentials to acoustic and cochlear implant stimulation.

    PubMed

    Ponton, C W; Don, M; Waring, M D; Eggermont, J J; Masuda, A

    1993-01-01

    Spatio-temporal source modeling (STSM) of event-related potentials was used to estimate the loci and characteristics of cortical activity evoked by acoustic stimulation in normal hearing subjects and by electrical stimulation in cochlear implant (CI) subjects. In both groups of subjects, source solutions obtained for the N1/P2 complex were located in the superior half of the temporal lobe in the head model. Results indicate that it may be possible to determine whether stimulation of different implant channels activates different regions of cochleotopically organized auditory cortex. Auditory system activation can be assessed further by examining the characteristics of the source wave forms. For example, subjects whose cochlear implants provided auditory sensations and normal hearing subjects had similar source activity. In contrast, a subject in whom implant activation evoked eyelid movements exhibited different source wave forms. STSM analysis may provide an electrophysiological technique for guiding rehabilitation programs based on the capabilities of the individual implant user and for disentangling the complex response patterns to electrical stimulation of the brain. PMID:7694834

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  7. STRAPS: A Fully Data-Driven Spatio-Temporally Regularized Algorithm for M/EEG Patch Source Imaging.

    PubMed

    Liu, Ke; Yu, Zhu Liang; Wu, Wei; Gu, Zhenghui; Li, Yuanqing

    2015-06-01

    For M/EEG-based distributed source imaging, it has been established that the L2-norm-based methods are effective in imaging spatially extended sources, whereas the L1-norm-based methods are more suited for estimating focal and sparse sources. However, when the spatial extents of the sources are unknown a priori, the rationale for using either type of methods is not adequately supported. Bayesian inference by exploiting the spatio-temporal information of the patch sources holds great promise as a tool for adaptive source imaging, but both computational and methodological limitations remain to be overcome. In this paper, based on state-space modeling of the M/EEG data, we propose a fully data-driven and scalable algorithm, termed STRAPS, for M/EEG patch source imaging on high-resolution cortices. Unlike the existing algorithms, the recursive penalized least squares (RPLS) procedure is employed to efficiently estimate the source activities as opposed to the computationally demanding Kalman filtering/smoothing. Furthermore, the coefficients of the multivariate autoregressive (MVAR) model characterizing the spatial-temporal dynamics of the patch sources are estimated in a principled manner via empirical Bayes. Extensive numerical experiments demonstrate STRAPS's excellent performance in the estimation of locations, spatial extents and amplitudes of the patch sources with varying spatial extents. PMID:25903226

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  9. [Spatio-temporal characteristics and source identification of water pollutants in Wenruitang River watershed].

    PubMed

    Ma, Xiao-xue; Wang, La-chun; Liao, Ling-ling

    2015-01-01

    Identifying the temp-spatial distribution and sources of water pollutants is of great significance for efficient water quality management pollution control in Wenruitang River watershed, China. A total of twelve water quality parameters, including temperature, pH, dissolved oxygen (DO), total nitrogen (TN), ammonia nitrogen (NH4+ -N), electrical conductivity (EC), turbidity (Turb), nitrite-N (NO2-), nitrate-N(NO3-), phosphate-P(PO4(3-), total organic carbon (TOC) and silicate (SiO3(2-)), were analyzed from September, 2008 to October, 2009. Geographic information system(GIS) and principal component analysis(PCA) were used to determine the spatial distribution and to apportion the sources of pollutants. The results demonstrated that TN, NH4+ -N, PO4(3-) were the main pollutants during flow period, wet period, dry period, respectively, which was mainly caused by urban point sources and agricultural and rural non-point sources. In spatial terms, the order of pollution was tertiary river > secondary river > primary river, while the water quality was worse in city zones than in the suburb and wetland zone regardless of the river classification. In temporal terms, the order of pollution was dry period > wet period > flow period. Population density, land use type and water transfer affected the water quality in Wenruitang River. PMID:25898648

  10. Atmospheric particulate mercury in the megacity Beijing: Spatio-temporal variations and source apportionment

    NASA Astrophysics Data System (ADS)

    Schleicher, N. J.; Schäfer, J.; Blanc, G.; Chen, Y.; Chai, F.; Cen, K.; Norra, S.

    2015-05-01

    Particulate mercury (HgP) concentrations in weekly aerosol samples (PM2.5 and TSP) from Beijing, China, were measured for a complete year. In addition, spatial differences were measured for a shorter time period at four different sites and potential source materials were analyzed. Average HgP concentrations in PM2.5 samples were 0.26 ng/m3 for day-time PM2.5, 0.28 ng/m3 for night-time PM2.5, and 0.57 ng/m3 for TSP samples, respectively. Coal combustion was identified as the major source of HgP in Beijing. Other sources included industrial activities as well as red color on historical buildings as a minor contribution. Spatial differences were pronounced with highest concentrations in the inner city (inside the 3rd ring road). The results further showed a strong seasonality with highest concentrations in winter and lowest in summer due to local meteorological conditions (precipitation in summer and stagnant conditions and low mixing layer height in winter) as well as seasonal sources, such as coal combustion for heating purposes. Day-night differences also showed a seasonal pattern with higher night-time concentrations during summer and higher day-time concentrations during winter. Compared to other cities worldwide, the HgP concentrations in Beijing were alarmingly high, suggesting that airborne particulate Hg should be the focus of future monitoring activities and mitigation measures.

  11. The role of heat source for spatio-temporal variations of mantle plumes

    NASA Astrophysics Data System (ADS)

    Kumagai, I.; Yamagishi, Y.; Davaille, A.

    2014-12-01

    Hot mantle plumes ascending from the core-mantle boundary experience a filtering effect by the endothermic phase change at the 660-km discontinuity. Fluid dynamics predicts that some hot mantle plumes stagnate at the phase boundary and locally heat the bottom of the upper mantle. This generates the secondary plumes in the upper mantle originating hotspots volcanic activities on the Earth's surface. Recently, seismic tomographic images around the upper-lower mantle boundary showed that the horizontal scale of the low velocity regions, which corresponds to that of the thermally buoyant heat sources, is the order of 100-1000 km. Although most of the fluid dynamic theories on the thermal plumes have been developed using an assumption that the heat source effect is negligible, the behaviors of the starting plumes in the upper mantle should depend on the size of heat source, which is generated by the hotter plume from the CMB. In order to understand the effects of heater size on the starting plume generation, we have experimentally investigated the behaviors of thermally buoyant plumes using a localized heat source (circular plate heater). The combination of quantitative visualization techniques of temperature (Thermochromic Liquid Crystals) and velocity (Particle Image Velocimetry) fields reveals the transient nature of the plume evolution: a variety of the spatio-tempotal distribution of plumes. Simple scaling laws for their ascent velocity and spacing of the plumes are experimentally determined. We also estimate the onset time of the secondary plumes in the upper mantle which depends on the local characteristics of the thermal boundary layer developing at the upper-lower mantle boundary.

  12. Total Nitrogen Sources of the Three Gorges Reservoir--A Spatio-Temporal Approach.

    PubMed

    Ren, Chunping; Wang, Lijing; Zheng, Binghui; Holbach, Andreas

    2015-01-01

    Understanding the spatial and temporal variation of nutrient concentrations, loads, and their distribution from upstream tributaries is important for the management of large lakes and reservoirs. The Three Gorges Dam was built on the Yangtze River in China, the world's third longest river, and impounded the famous Three Gorges Reservoir (TGR). In this study, we analyzed total nitrogen (TN) concentrations and inflow data from 2003 till 2010 for the main upstream tributaries of the TGR that contribute about 82% of the TGR's total inflow. We used time series analysis for seasonal decomposition of TN concentrations and used non-parametric statistical tests (Kruskal-Walli H, Mann-Whitney U) as well as base flow segmentation to analyze significant spatial and temporal patterns of TN pollution input into the TGR. Our results show that TN concentrations had significant spatial heterogeneity across the study area (Tuo River> Yangtze River> Wu River> Min River> Jialing River>Jinsha River). Furthermore, we derived apparent seasonal changes in three out of five upstream tributaries of the TGR rivers (Kruskal-Walli H ρ = 0.009, 0.030 and 0.029 for Tuo River, Jinsha River and Min River in sequence). TN pollution from non-point sources in the upstream tributaries accounted for 68.9% of the total TN input into the TGR. Non-point source pollution of TN revealed increasing trends for 4 out of five upstream tributaries of the TGR. Land use/cover and soil type were identified as the dominant driving factors for the spatial distribution of TN. Intensifying agriculture and increasing urbanization in the upstream catchments of the TGR were the main driving factors for non-point source pollution of TN increase from 2003 till 2010. Land use and land cover management as well as chemical fertilizer use restriction were needed to overcome the threats of increasing TN pollution. PMID:26510158

  13. Total Nitrogen Sources of the Three Gorges Reservoir — A Spatio-Temporal Approach

    PubMed Central

    Ren, Chunping; Wang, Lijing; Zheng, Binghui; Holbach, Andreas

    2015-01-01

    Understanding the spatial and temporal variation of nutrient concentrations, loads, and their distribution from upstream tributaries is important for the management of large lakes and reservoirs. The Three Gorges Dam was built on the Yangtze River in China, the world’s third longest river, and impounded the famous Three Gorges Reservoir (TGR). In this study, we analyzed total nitrogen (TN) concentrations and inflow data from 2003 till 2010 for the main upstream tributaries of the TGR that contribute about 82% of the TGR’s total inflow. We used time series analysis for seasonal decomposition of TN concentrations and used non-parametric statistical tests (Kruskal-Walli H, Mann-Whitney U) as well as base flow segmentation to analyze significant spatial and temporal patterns of TN pollution input into the TGR. Our results show that TN concentrations had significant spatial heterogeneity across the study area (Tuo River> Yangtze River> Wu River> Min River> Jialing River>Jinsha River). Furthermore, we derived apparent seasonal changes in three out of five upstream tributaries of the TGR rivers (Kruskal-Walli H ρ = 0.009, 0.030 and 0.029 for Tuo River, Jinsha River and Min River in sequence). TN pollution from non-point sources in the upstream tributaries accounted for 68.9% of the total TN input into the TGR. Non-point source pollution of TN revealed increasing trends for 4 out of five upstream tributaries of the TGR. Land use/cover and soil type were identified as the dominant driving factors for the spatial distribution of TN. Intensifying agriculture and increasing urbanization in the upstream catchments of the TGR were the main driving factors for non-point source pollution of TN increase from 2003 till 2010. Land use and land cover management as well as chemical fertilizer use restriction were needed to overcome the threats of increasing TN pollution. PMID:26510158

  14. An Open Source Geovisual Analytics Toolbox for Multivariate Spatio-Temporal Data in Environmental Change Modelling

    NASA Astrophysics Data System (ADS)

    Bernasocchi, M.; Coltekin, A.; Gruber, S.

    2012-07-01

    In environmental change studies, often multiple variables are measured or modelled, and temporal information is essential for the task. These multivariate geographic time-series datasets are often big and difficult to analyse. While many established methods such as PCP (parallel coordinate plots), STC (space-time cubes), scatter-plots and multiple (linked) visualisations help provide more information, we observe that most of the common geovisual analytics suits do not include three-dimensional (3D) visualisations. However, in many environmental studies, we hypothesize that the addition of 3D terrain visualisations along with appropriate data plots and two-dimensional views can help improve the analysts' ability to interpret the spatial relevance better. To test our ideas, we conceptualize, develop, implement and evaluate a geovisual analytics toolbox in a user-centred manner. The conceptualization of the tool is based on concrete user needs that have been identified and collected during informal brainstorming sessions and in a structured focus group session prior to the development. The design process, therefore, is based on a combination of user-centred design with a requirement analysis and agile development. Based on the findings from this phase, the toolbox was designed to have a modular structure and was built on open source geographic information systems (GIS) program Quantum GIS (QGIS), thus benefiting from existing GIS functionality. The modules include a globe view for 3D terrain visualisation (OSGEarth), a scattergram, a time vs. value plot, and a 3D helix visualisation as well as the possibility to view the raw data. The visualisation frame allows real-time linking of these representations. After the design and development stage, a case study was created featuring data from Zermatt valley and the toolbox was evaluated based on expert interviews. Analysts performed multiple spatial and temporal tasks with the case study using the toolbox. The expert

  15. Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

    NASA Astrophysics Data System (ADS)

    Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

    Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river

  16. The choice of the source space and the Laplacian matrix in LORETA and the spatio-temporal Kalman filter EEG inverse methods.

    PubMed

    Habboush, Nawar; Hamid, Laith; Japaridze, Natia; Wiegand, Gert; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Siniatchkin, Michael

    2015-08-01

    The discretization of the brain and the definition of the Laplacian matrix influence the results of methods based on spatial and spatio-temporal smoothness, since the Laplacian operator is used to define the smoothness based on the neighborhood of each grid point. In this paper, the results of low resolution electromagnetic tomography (LORETA) and the spatiotemporal Kalman filter (STKF) are computed using, first, a greymatter source space with the standard definition of the Laplacian matrix and, second, using a whole-brain source space and a modified definition of the Laplacian matrix. Electroencephalographic (EEG) source imaging results of five inter-ictal spikes from a pre-surgical patient with epilepsy are used to validate the two aforementioned approaches. The results using the whole-brain source space and the modified definition of the Laplacian matrix were concentrated in a single source activation, stable, and concordant with the location of the focal cortical dysplasia (FCD) in the patient's brain compared with the results which use a grey-matter grid and the classical definition of the Laplacian matrix. This proof-of-concept study demonstrates a substantial improvement of source localization with both LORETA and STKF and constitutes a basis for further research in a large population of patients with epilepsy. PMID:26736860

  17. Modeling spatio-temporal field evolution

    NASA Astrophysics Data System (ADS)

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

    2009-06-01

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

  18. Database Organisation in a Web-Enabled Free and Open-Source Software (foss) Environment for Spatio-Temporal Landslide Modelling

    NASA Astrophysics Data System (ADS)

    Das, I.; Oberai, K.; Sarathi Roy, P.

    2012-07-01

    Landslides exhibit themselves in different mass movement processes and are considered among the most complex natural hazards occurring on the earth surface. Making landslide database available online via WWW (World Wide Web) promotes the spreading and reaching out of the landslide information to all the stakeholders. The aim of this research is to present a comprehensive database for generating landslide hazard scenario with the help of available historic records of landslides and geo-environmental factors and make them available over the Web using geospatial Free & Open Source Software (FOSS). FOSS reduces the cost of the project drastically as proprietary software's are very costly. Landslide data generated for the period 1982 to 2009 were compiled along the national highway road corridor in Indian Himalayas. All the geo-environmental datasets along with the landslide susceptibility map were served through WEBGIS client interface. Open source University of Minnesota (UMN) mapserver was used as GIS server software for developing web enabled landslide geospatial database. PHP/Mapscript server-side application serve as a front-end application and PostgreSQL with PostGIS extension serve as a backend application for the web enabled landslide spatio-temporal databases. This dynamic virtual visualization process through a web platform brings an insight into the understanding of the landslides and the resulting damage closer to the affected people and user community. The landslide susceptibility dataset is also made available as an Open Geospatial Consortium (OGC) Web Feature Service (WFS) which can be accessed through any OGC compliant open source or proprietary GIS Software.

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2014-09-01

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

  1. Source identification, spatio-temporal distribution and ecological risk of persistent organic pollutants in sediments from the upper Danube catchment.

    PubMed

    Kukučka, Petr; Audy, Ondřej; Kohoutek, Jiří; Holt, Eva; Kalábová, Tereza; Holoubek, Ivan; Klánová, Jana

    2015-11-01

    Riverine sediments, collected on a monthly basis during a period of one year, from five sites in a mixed land use region of the Czech Republic were analysed for chlorinated and brominated persistent organic pollutants (POPs). The region is located in the upper catchment of the Danube River. The POPs concentrations were as follows: 11-930 pg g(-1) polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDDs/Fs), 170-980 pg g(-1) dioxin-like polychlorinated biphenyls (dl-PCBs), 34-13,700 pg g(-1) polychlorinated naphthalenes (PCNs), 5.7-29,200 pg g(-1) polybrominated diphenylethers (PBDEs) and 0.21-351 ng g(-1) hexabromocyclododecanes (HBCDs). Concentrations expressed as toxic equivalents (TEQs), for PCDD/F+dl-PCB+PCN (TEQPCDD/F+dl-PCB+PCN) ranged from 0.37 to 19 pg g(-1). The results revealed a clear spatial separation between sites based on concentration and congener profile. There were also some obvious temporal patterns of selected POPs, which were related to river flow (seasonality) and organic carbon (TOC) of the sediment. Potential sources of POPs include local municipalities (flame retardants), some diffuse sources (PCNs and PCDDs/Fs) and potential point sources (PBDEs). Risk assessment based on risk quotients (RQ) revealed limited to medium ecological risk from PBDEs. TEQPCDD/F+dl-PCB+PCN were low relative to other European rivers, hence the risk to aquatic organisms was considered to be low. PCNs contributed significantly to overall TEQ in several cases. PMID:26291759

  2. Spatio-temporal distribution, source, and genotoxic potential of polycyclic aromatic hydrocarbons in estuarine and riverine sediments from southern India.

    PubMed

    Goswami, Prasun; Ohura, Takeshi; Guruge, Keerthi S; Yoshioka, Miyako; Yamanaka, Noriko; Akiba, Masato; Munuswamy, Natesan

    2016-08-01

    In order to categorize the distribution, source, and effects of polycyclic aromatic hydrocarbons (PAHs) in aquatic systems of southern India, chemical and toxicological analyses were performed on surface and core sediments, collected from Adyar river, Cooum river, Ennore estuary, and Pulicat lake near Chennai city. The total PAH concentration in surface sediment ranged from 13 to 31,425ng/g with a mean value of 4320ng/g; the concentration was markedly higher in Cooum river compared to that at other sites. The historical PAH dissemination in core samples in the Cooum river, Ennore estuary, and Pulicat lake ranged from 30 to 31,425ng/g, from 8.6 to 910ng/g, and from 62 to 546ng/g, respectively. Surface sediments were predominantly contaminated with low molecular weight (LMW) PAHs. Historical profiles suggest that PAH contamination in the area is now greater than it had been in the past. PAH accumulation in Pulicat lake was distinct from that at other locations where high molecular weight (HMW) PAHs were predominant. DNA damage in HepG2 cells treated with sediment extracts from different locations showed a good correlation with their respective total PAH levels. Statistical analysis revealed that 3-ring and 4-ring PAHs may synergistically contribute to the genotoxic potency compared to others in sediments. The study also showed that a majority of PAHs in the study area indicated a petrogenic origin. Based on the enrichment and toxicological assessment of PAHs in sediments, Cooum river was shown to suffer the highest biological impairment among the studied water bodies. PMID:27092974

  3. The Voronoi spatio-temporal data structure

    NASA Astrophysics Data System (ADS)

    Mioc, Darka

    2002-04-01

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

    Cheng, Tao; Wicks, Thomas

    2014-01-01

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

  7. Spatio-temporal EEG source localization using a three-dimensional subspace FINE approach in a realistic geometry inhomogeneous head model.

    PubMed

    Ding, Lei; He, Bin

    2006-09-01

    The subspace source localization approach, i.e., first principle vectors (FINE), is able to enhance the spatial resolvability and localization accuracy for closely-spaced neural sources from EEG and MEG measurements. Computer simulations were conducted to evaluate the performance of the FINE algorithm in an inhomogeneous realistic geometry head model under a variety of conditions. The source localization abilities of FINE were examined at different cortical regions and at different depths. The present computer simulation results indicate that FINE has enhanced source localization capability, as compared with MUSIC and RAP-MUSIC, when sources are closely spaced, highly noise-contaminated, or inter-correlated. The source localization accuracy of FINE is better, for closely-spaced sources, than MUSIC at various noise levels, i.e., signal-to-noise ratio (SNR) from 6 dB to 16 dB, and RAP-MUSIC at relatively low noise levels, i.e., 6 dB to 12 dB. The FINE approach has been further applied to localize brain sources of motor potentials, obtained during the finger tapping tasks in a human subject. The experimental results suggest that the detailed neural activity distribution could be revealed by FINE. The present study suggests that FINE provides enhanced performance in localizing multiple closely spaced, and inter-correlated sources under low SNR, and may become an important alternative to brain source localization from EEG or MEG. PMID:16941829

  8. Spatio-temporal modeling of the invasive potential of wild boar--a conflict-prone species-using multi-source citizen science data.

    PubMed

    Jordt, Astrid Moltke; Lange, Martin; Kramer-Schadt, Stephanie; Nielsen, Lisbeth Harm; Nielsen, Søren Saxmose; Thulke, Hans-Hermann; Vejre, Henrik; Alban, Lis

    2016-02-01

    Denmark was considered not to have an established population of free-ranging wild boar. Today, sporadic observations of wild boar challenge that view. Due to its reservoir role for economic devastating swine diseases, wild boar represents a potential threat for Denmark's position as a large pig- and pork-exporting country. This study assessed the prospects of wild boar invasion in Denmark. Multi-source citizen science data of wild boar observations were integrated into a multi-modelling approach linking habitat suitability models with agent-based, spatially-explicit simulations. We tested whether the currently observed presence of wild boar is due to natural immigration across the Danish-German border, or whether it is more likely that wild boar escaped fenced premises. Five observational data sources served as evaluation data: (1) questionnaires sent to all 1625 registered owners of Danish farm land, located in the 60 parishes closest to the border, (2) an online questionnaire, (3) a mobile web-based GPS application, (4) reports in the media or by governmental agencies, and (5) geo-referenced locations of fenced wild boar populations. Data covering 2008-2013 included 195 observations of wild boar, including 16 observations of breeding sows. The data from the Danish Nature Agency and the mailed questionnaires were consistent regarding the location of wild boar observations, while data from the Danish Veterinary and Food Administration, the media and the electronic questionnaires documented individual scattered observations in the rest of Jutland. Most observations were made in the region bordering Germany. It is uncertain whether the relatively few observations represent an established population. Model outcomes suggested that the origin of wild boar in about half of the area with sporadic observations of wild boar could be attributed to spatial expansions from a local Danish population near the border and consisting of wild boar originally of German origin

  9. [PUF passive air sampling of polycyclic aromatic hydrocarbons in atmosphere of the Yangtze River Delta, China: spatio-temporal distribution and potential sources].

    PubMed

    Zhang, Li-fei; Yang, Wen-long; Dong, Liang; Shi, Shuang-xin; Zhou, Li; Zhang, Xiu-lan; Li, Ling-ling; Niu, Shan; Huang, Ye-ru

    2013-09-01

    Atmosphere is regarded to be an important media in the environmental pollution research area. Passive air sampling was one of the effective complementary sampling techniques for the active high volume air sampler in recent decades. A regional scale investigation on the atmospheric polycyclic aromatic hydrocarbons (PAHs) was conducted in the Yangtze River Delta (YRD). Polyurethane foam based passive air samplers were used to collect the atmospheric PAHs from 31 sampling sites in this area. PAHs concentrations ranged from 10.1 ng x m(-1) to 367 ng x m(-3) in this study. The annual average concentration of benzo [a] pyrene (BaP) reached 2.25 ng x m(-3), which was two times higher exceeding the national standard, GB 3095-2012. The atmospheric PAHs during four seasons decreased in the following order: autumn > winter > spring > summer. Larger BaP excessive areas were found in autumn and winter than other seasons. Moreover, an obvious emission of BaP was confirmed during the winter time. Traffic related petroleum combustion, coal and biomass burning, and coke oven were identified as potential sources of atmospheric PAHs, contributing 38.1%, 42.4%, and 19.5%, respectively. PMID:24288973

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

    PubMed

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

    2016-06-01

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

  11. Spatio-temporal distribution of phytoplankton in the Danjiangkou Reservoir, a water source area for the Southto-North Water Diversion Project (Middle Route), China

    NASA Astrophysics Data System (ADS)

    Yin, Dacong; Zheng, Lingling; Song, Lirong

    2011-05-01

    One of the water source areas of the South-to-North Water Diversion Project is the Danjiangkou Reservoir (DJKR). To understand seasonal variation in phytoplankton composition, abundance and distribution in the DJKR area before water diversion, as well as to estimate potential risks of water quality after water diversion, we conducted an investigation on phytoplankton in the DJKR from August 2008 to May 2009. The investigation included 10 sampling sites, each with four depths of 0.5, 5, 10, and 20 m. In this study, 117 taxa belonging to 76 genera were identified, consisting of diatoms (39 taxa), green algae (47 taxa), blue-green algae (19 taxa), and others (12 taxa). Annual average phytoplankton abundance was 2.01 × 106 ind./L, and the highest value was 14.72 × 106 ind/L (at site 3 in August 2008). Phytoplankton abundance in front of the Danjiangkou Dam (DJKD) was higher than that of the Danjiang Reservoir Basin. Phytoplankton distribution showed a vertical declining trend from 0.5 m to 20 m at most sites in August 2008 (especially at sites of 1, 2, 4 and 10), but no distinct pattern in other sampling months. In December 2008 and March 2009, Stephanodiscus sp. was the most abundant species, amounting to 55.23% and 72.34%, respectively. We propose that high abundance of Stephanodiscus sp. may have contributed greatly to the frequent occurrence of Stephanodiscus sp. blooms in middle-low reaches of the Hanjiang River during the early spring of 2009. In comparison with previous studies conducted from 1992 to 2006, annual average phytoplankton density, green algae and blue-green algae species, as well as major nutrient concentrations increased, while phytoplankton diversity indices declined. This indicates a gradual decline in water quality. More research should be conducted and countermeasures taken to prevent further deterioration of water quality in the DJKR.

  12. Spatio-temporal variability in Ebro river basin (NE Spain): Global SST as potential source of predictability on decadal time scales

    NASA Astrophysics Data System (ADS)

    Gámiz-Fortis, S. R.; Hidalgo-Muñoz, J. M.; Argüeso, D.; Esteban-Parra, M. J.; Castro-Díez, Y.

    2011-11-01

    SummaryThis paper investigates the spatial and temporal variability of streamflow in the Ebro river basin and its potential predictability. Principal Component Analysis applied to monthly streamflow series from 83 gauging stations distributed through the basin, reveals three homogeneous regions: Basque-Cantabrian, Pyrenees and Southern Mediterranean. Attending to this classification the main characteristic time scales of the maximum monthly streamflows are studied by Singular Spectral Analysis (SSA). Decadal variations in streamflow make particularly large contributions to year-to-year streamflow variance in stations placed in the Basque-Cantabrian and Southern Mediterranean regions, while for the Pyrenees flows the interannual contribution is more important. The predictability of the Ebro flow anomalies has been investigated using a combined methodology: at decadal time scales SST anomalies from several regions provide a significant source of predictability for the Ebro flow, while at interannual time scales autoregressive-moving-average modelling, applied to the time series previously filtered by SSA, is able to provide potential skill in forecasting. For gauging stations associated to the Basque-Cantabrian region significant correlations between the maximum monthly streamflow anomalies and a tripole-like pattern in the North Atlantic SSTs during the previous spring are found. This association is found maximum and stable for the tropical part of the pattern (approximately 0-20°N). For the gauging stations placed to the southeast of basin some influence from the Pacific Decadal Oscillation (PDO) is found. This method allows evaluating, independently, the decadal and interannual predictability of the streamflow series. In addition, the combination of both modelling techniques gives as result a methodology that has the capacity to provide basin-specific hydroclimatic predictions which vary (for the 1990-2003 validation period) between 62% for the Basque

  13. Spatio-temporal properties of letter crowding

    PubMed Central

    Chung, Susana T. L.

    2016-01-01

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

  14. Spatio-temporal properties of letter crowding.

    PubMed

    Chung, Susana T L

    2016-04-01

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

  15. Spatio-Temporal Clustering of Monitoring Network

    NASA Astrophysics Data System (ADS)

    Hussain, I.; Pilz, J.

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-10-01

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

  18. Spatio-temporal activity of lightnings over Greece

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  20. Spatio-temporal correlations in Coulomb clusters

    NASA Astrophysics Data System (ADS)

    Ghosal, Amit; Ash, Biswarup; Chakrabarti, Jaydeb

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

  1. Spatio-temporal registration of multiple trajectories.

    PubMed

    Padoy, Nicolas; Hager, Gregory D

    2011-01-01

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

  2. 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)...

  3. Parallel indexing technique for spatio-temporal data

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  4. Spatio-temporal change modeling with array data

    NASA Astrophysics Data System (ADS)

    Lu, Meng; Pebesma, Edzer

    2015-04-01

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

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

    PubMed Central

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Morita, Satoru

    2016-02-01

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

  7. Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats.

    PubMed

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-09-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004-2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004-2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

  8. Spatio-Temporal Patterns of Schistosomiasis Japonica in Lake and Marshland Areas in China: The Effect of Snail Habitats

    PubMed Central

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-01-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004–2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004–2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

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

    PubMed Central

    Musolesi, Mirco

    2016-01-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks. PMID:27429776

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

    PubMed

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks. PMID:27429776

  11. Reaction diffusion equation with spatio-temporal delay

    NASA Astrophysics Data System (ADS)

    Zhao, Zhihong; Rong, Erhua

    2014-07-01

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

  12. Time reversal and the spatio-temporal matched filter

    SciTech Connect

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

    2004-03-08

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

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

    PubMed Central

    Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

    2011-01-01

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

  14. Spatio-temporal analysis of environmental radiation in Korea

    SciTech Connect

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

    2007-07-01

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

  15. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovič, Dušan; Stopar, Bojan

    2011-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Sun, Shiyan; Zhang, Hong; Yuan, Ding

    2015-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  18. Cubic map algebra functions for spatio-temporal analysis

    USGS Publications Warehouse

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

    2005-01-01

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

  19. Finding Spatio-Temporal Patterns in Large Sensor Datasets

    ERIC Educational Resources Information Center

    McGuire, Michael Patrick

    2010-01-01

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

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

    PubMed

    Heaton, Matthew J; Gelfand, Alan E

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  2. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    NASA Astrophysics Data System (ADS)

    Schöll, Eckehard

    2005-08-01

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

  3. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    NASA Astrophysics Data System (ADS)

    Schöll, Eckehard

    2001-02-01

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

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

    DOE PAGESBeta

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

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

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

    PubMed Central

    Cooper, Gregory F

    2010-01-01

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

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed Central

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

    2011-01-01

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

  9. Inverse hydrological modelling of spatio-temporal rainfall patterns

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

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

  10. Spatio-temporal optical random number generator.

    PubMed

    Stipčević, M; Bowers, J E

    2015-05-01

    We present a first random number generator (RNG) which simultaneously uses independent spatial and temporal quantum randomness contained in an optical system. Availability of the two independent sources of entropy makes the RNG resilient to hardware failure and signal injection attacks. We show that the deviation from randomness of the generated numbers can be estimated quickly from simple measurements thus eliminating the need for usual time-consuming statistical testing of the output data. As a confirmation it is demonstrated that generated numbers pass NIST Statistical test suite. PMID:25969254

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

    PubMed

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

    2016-04-13

    In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. PMID:26953173

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

    PubMed Central

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

    2016-01-01

    In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal–spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. PMID:26953173

  13. Working with Spatio-Temporal Data Type

    NASA Astrophysics Data System (ADS)

    Raza, A.

    2012-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  15. Visual tracking with spatio-temporal Dempster-Shafer information fusion.

    PubMed

    Li, Xi; Dick, Anthony; Shen, Chunhua; Zhang, Zhongfei; van den Hengel, Anton; Wang, Hanzi

    2013-08-01

    A key problem in visual tracking is how to effectively combine spatio-temporal visual information from throughout a video to accurately estimate the state of an object. We address this problem by incorporating Dempster-Shafer (DS) information fusion into the tracking approach. To implement this fusion task, the entire image sequence is partitioned into spatially and temporally adjacent subsequences. A support vector machine (SVM) classifier is trained for object/nonobject classification on each of these subsequences, the outputs of which act as separate data sources. To combine the discriminative information from these classifiers, we further present a spatio-temporal weighted DS (STWDS) scheme. In addition, temporally adjacent sources are likely to share discriminative information on object/nonobject classification. To use such information, an adaptive SVM learning scheme is designed to transfer discriminative information across sources. Finally, the corresponding DS belief function of the STWDS scheme is embedded into a Bayesian tracking model. Experimental results on challenging videos demonstrate the effectiveness and robustness of the proposed tracking approach. PMID:23529089

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

    PubMed

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

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    SciTech Connect

    Platt, N.; Hammel, S.M.

    1996-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Jeong, Hawoong

    2005-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Sampson, K. M.; Wilhelmi, O.

    2009-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Mukai, Ryan; Lee, Dennis; Vilnrotter, Victor

    2010-01-01

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

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

    SciTech Connect

    Sen, Satyabrata

    2013-01-01

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

  5. Modelling spatio-temporal patterns of long-distance Culicoides dispersal into northern Australia.

    PubMed

    Eagles, D; Walker, P J; Zalucki, M P; Durr, P A

    2013-07-01

    Novel arboviruses, including new serotypes of bluetongue virus, are isolated intermittently from cattle and insects in northern Australia. These viruses are thought to be introduced via windborne dispersal of Culicoides from neighbouring land masses to the north. We used the HYSPLIT particle dispersal model to simulate the spatio-temporal patterns of Culicoides dispersal into northern Australia from nine putative source sites across Indonesia, Timor-Leste and Papua New Guinea. Simulated dispersal was found to be possible from each site, with the islands of Timor and Sumba highlighted as the likely principal sources and February the predominant month of dispersal. The results of this study define the likely spatial extent of the source and arrival regions, the relative frequency of dispersal from the putative sources and the temporal nature of seasonal winds from source sites into arrival regions. Importantly, the methodology and results may be applicable to other insect and pathogen incursions into northern Australia. PMID:23642857

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  7. Mining fuzzy association rules in spatio-temporal databases

    NASA Astrophysics Data System (ADS)

    Shu, Hong; Dong, Lin; Zhu, Xinyan

    2008-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

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

    SciTech Connect

    Wikle, C.K.

    1996-12-31

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

  10. The spatio-temporal spectrum of turbulent flows.

    PubMed

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

    2015-12-01

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

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

    SciTech Connect

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

    1990-01-01

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

  12. Spatio-temporal Granger causality: a new framework

    PubMed Central

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

    2015-01-01

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

  13. Multiscale recurrence analysis of spatio-temporal data

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

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

    2013-10-01

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

  15. Stochastic spatio-temporal modelling with PCRaster Python

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  16. Spatio-Temporal Data Comparisons for Global Highly Pathogenic Avian Influenza (HPAI) H5N1 Outbreaks

    PubMed Central

    Chen, Dongmei; Chen, Yue; Wang, Lei; Zhao, Fei; Yao, Baodong

    2010-01-01

    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. PMID:21187964

  17. Spatio-temporal distribution of VOC emissions in urban area based on receptor modeling

    NASA Astrophysics Data System (ADS)

    Stojić, A.; Stanišić Stojić, S.; Mijić, Z.; Šoštarić, A.; Rajšić, S.

    2015-04-01

    In the present study, the concentrations of VOC were measured using Proton Transfer Reaction Mass Spectrometer, together with NOx, NO2, NO, SO2, CO, and PM10 during winter 2014 in Belgrade, Serbia. For the purpose of source apportionment, receptor models Positive Matrix Factorization and Unmix were applied to the obtained dataset, both resolving six profiles. The reliable identification of pollutant sources, description of their characteristics, and estimation of their spatio-temporal distribution are presented through comprehensive analysis and comparison of receptor model solutions, with respect to meteorological data, planetary boundary layer height, and regional and long-range transport. For emissions from petrochemical industry and oil refinery a significant contribution of transport is observed, and hybrid receptor models were applied for identification of potential non-local source regions.

  18. Geostatistical Analysis of Spatio-Temporal Forest Fire Data

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    PubMed

    Nakagawa, T; Ohashi, A

    1980-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  1. Target tracking based on spatio-temporal fractal error

    NASA Astrophysics Data System (ADS)

    Allen, Brian S.

    2007-04-01

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

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

    SciTech Connect

    He, Shoujie; Jing, Ha

    2014-01-15

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

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

    PubMed

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

    2014-07-16

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

  4. Spatio-temporal population estimates for risk management

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    He, Shoujie; Jing, Ha

    2014-01-01

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

  6. Spatio-Temporal Structure of Hooded Gull Flocks

    PubMed Central

    Yomosa, Makoto; Mizuguchi, Tsuyoshi; Hayakawa, Yoshinori

    2013-01-01

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

  7. High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  8. SPATIO-TEMPORAL COMPLEXITY OF THE AORTIC SINUS VORTEX

    PubMed Central

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-01-01

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

  9. Spatio-temporal clustering of wildfires in Portugal

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    PubMed Central

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

    2015-01-01

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

  11. Hirarchical Bayesian Spatio-Temporal Interpolation including Covariates

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  12. Spatio-temporal variability of shallow groundwater quality in a typical agricultural catchment in subtropical central China

    NASA Astrophysics Data System (ADS)

    Liu, X.

    2015-12-01

    Excessive agriculture-sourced N leaching into shallow groundwater has deteriorated the domestic water quality in rural China. To effectively prevent the above environmental contamination issue, it is an essential prerequisite of exploring the spatio-temporal variability (stV) of the groundwater quality. In this study, a large observation program was deployed to observe ammonium-N (NH4N), nitrate-N (NO3N) and total N (TN) concentrations in 194 groundwater observation wells (1.5 m deep from soil surface) from April 2010 to November 2012 in the Jinjing river catchment in Hunan Province of China. A logit function was applied to transform NH4N, NO3N and TN data for normality; the resultant variables were thus named as NH4Nt, NO3Nt and TNt, respectively. A spatio-temporal semivariogram model in a sum-metric form was used to quantify the stV of NH4Nt, NO3Nt and TNt. The results indicated that the 33-month means ± standard deviations of the NH4N, NO3N and TN concentrations were 0.75±0.10, 1.60±0.19 and 2.99±0.29 mg N L-1, respectively. NH4Nt and NO3Nt exhibited a strong spatio-temporal dependence, while TNt only presented a strong temporal structure. Spatio-temporal ordinary kriging (stOK) was applied to predict the spatio-temporal distributions of NH4N, NO3N and TN over the catchment. The cross-validation results indicated that the stOK predictions for NH4N (r=0.48, RMSE=1.11 mg N L-1), NO3N (r=0.46, RMSE=1.21 mg N L-1) outperformed that for TN (r=0.29, RMSE=2.11 mg N L-1). Referenced to the Chinese Environmental Quality Standards for Groundwater (GB/T 14848-93), the proportions of areas contaminated by NH4N, NO3N and TN in the catchment over a 33-month period were 20.5%, 1.46%, and 5.07%, respectively. Our findings suggested that the Jinjing groundwater was mainly polluted by NH4N, which is probably attributed to the intensive rice agriculture featured with high urea fertilizer applications in the catchment.

  13. Spatio-Temporal Analyses of CH4 and SO2 over Pakistan

    NASA Astrophysics Data System (ADS)

    Mahmood, Irfan; Imran Shahzad, Muhammad; Farooq Iqbal, Muhammad

    2016-07-01

    SO2 and associated compounds are one of main atmospheric pollutant. Moreover, methane - a potent greenhouse gas can also deteriorate the air quality of the region under certain chemical and meteorological conditions. Role of such gases in regional air quality of Pakistan have not been significantly studied. This study involves the analyses of CH4 and SO2 in terms of spatio-temporal distribution over Pakistan from the period 2004 - 2014 using space borne sensors namely Ozone Monitoring Instrument (OMI) and Advanced Infrared Sounder Instrument (AIRS) respectively. Results show an increase in SO2 concentration attributed to trans-boundary sources. Monthly Methane total column results show an increase in atmospheric concentration of methane for the period 2004-2014. Results of the study are complimented by calculating the back trajectories to identify the transport paths. The study significantly describes the regional description and convection phenomenon for SO2 and CH4.

  14. Neural field simulator: two-dimensional spatio-temporal dynamics involving finite transmission speed

    PubMed Central

    Nichols, Eric J.; Hutt, Axel

    2015-01-01

    Neural Field models (NFM) play an important role in the understanding of neural population dynamics on a mesoscopic spatial and temporal scale. Their numerical simulation is an essential element in the analysis of their spatio-temporal dynamics. The simulation tool described in this work considers scalar spatially homogeneous neural fields taking into account a finite axonal transmission speed and synaptic temporal derivatives of first and second order. A text-based interface offers complete control of field parameters and several approaches are used to accelerate simulations. A graphical output utilizes video hardware acceleration to display running output with reduced computational hindrance compared to simulators that are exclusively software-based. Diverse applications of the tool demonstrate breather oscillations, static and dynamic Turing patterns and activity spreading with finite propagation speed. The simulator is open source to allow tailoring of code and this is presented with an extension use case. PMID:26539105

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-04-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  19. Spatio-temporal isotopic signatures (δ13 C and δ15 N) reveal that two sympatric West African mullet species do not feed on the same basal production sources.

    PubMed

    Le Loc'h, F; Durand, J-D; Diop, K; Panfili, J

    2015-04-01

    Potential trophic competition between two sympatric mullet species, Mugil cephalus and Mugil curema, was explored in the hypersaline estuary of the Saloum Delta (Senegal) using δ(13) C and δ(15) N composition of muscle tissues. Between species, δ(15) N compositions were similar, suggesting a similar trophic level, while the difference in δ(13) C compositions indicated that these species did not feed from exactly the same basal production sources or at least not in the same proportions. This result provides the first evidence of isotopic niche segregation between two limno-benthophageous species belonging to the geographically widespread, and often locally abundant, Mugilidae family. PMID:25846862

  20. Spatio-temporal pollution features in Seoul, Korea using magnetic measurements of roadside dusts

    NASA Astrophysics Data System (ADS)

    Doh, S.; Kim, W.; Lee, J.; Park, Y.

    2006-12-01

    Seoul is generally influenced by spatial distribution of anthropogenic sources, topography and atmospheric conditions (e.g., prevailing wind direction), and clearly demonstrates that monthly magnetic mapping could be highly informative on the investigation of spatio-temporal pollution features in urban areas.

  1. Spatio-temporal filtering techniques for the detection of disaster-related communication.

    PubMed

    Fitzhugh, Sean M; Ben Gibson, C; Spiro, Emma S; Butts, Carter T

    2016-09-01

    Individuals predominantly exchange information with one another through informal, interpersonal channels. During disasters and other disrupted settings, information spread through informal channels regularly outpaces official information provided by public officials and the press. Social scientists have long examined this kind of informal communication in the rumoring literature, but studying rumoring in disrupted settings has posed numerous methodological challenges. Measuring features of informal communication-timing, content, location-with any degree of precision has historically been extremely challenging in small studies and infeasible at large scales. We address this challenge by using online, informal communication from a popular microblogging website and for which we have precise spatial and temporal metadata. While the online environment provides a new means for observing rumoring, the abundance of data poses challenges for parsing hazard-related rumoring from countless other topics in numerous streams of communication. Rumoring about disaster events is typically temporally and spatially constrained to places where that event is salient. Accordingly, we use spatio and temporal subsampling to increase the resolution of our detection techniques. By filtering out data from known sources of error (per rumor theories), we greatly enhance the signal of disaster-related rumoring activity. We use these spatio-temporal filtering techniques to detect rumoring during a variety of disaster events, from high-casualty events in major population centers to minimally destructive events in remote areas. We consistently find three phases of response: anticipatory excitation where warnings and alerts are issued ahead of an event, primary excitation in and around the impacted area, and secondary excitation which frequently brings a convergence of attention from distant locales onto locations impacted by the event. Our results demonstrate the promise of spatio-temporal

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

    PubMed

    Tarasov, Nikita; Sugavanam, Srikanth; Churkin, Dmitry

    2015-09-21

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

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

    PubMed

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

    2016-05-01

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

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

    SciTech Connect

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

    1989-01-01

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

  5. Spatio-temporal self-organization in mudstones.

    SciTech Connect

    Dewers, Thomas A.

    2010-12-01

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

  6. Research of spatio-temporal analysis of agricultural pest

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Dewers, T. A.

    2010-12-01

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

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

    PubMed Central

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

    2015-01-01

    Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations. PMID:26442094

  9. Spatio-Temporal Multiscale Denoising of Fluoroscopic Sequence.

    PubMed

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

    2016-06-01

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

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

    PubMed

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

    2014-01-01

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

  11. Spatio-temporal patterns in inclined layer convection

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  12. Efficient Segmentation of Spatio-Temporal Data from Simulations

    SciTech Connect

    Fodor, I K; Kamath, C

    2003-01-15

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

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

    PubMed

    Zhou, Feng; Torre, Fernando De la

    2016-08-01

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

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

    USGS Publications Warehouse

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

    2015-01-01

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

  15. Spatio-temporal distribution of human lifespan in China

    PubMed Central

    Wang, Shaobin; Luo, Kunli; Liu, Yonglin

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed

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

    2016-07-27

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

  18. Spatio-Temporal Measurements of Short Wind Water Waves

    NASA Astrophysics Data System (ADS)

    Rocholz, Roland; Jähne, Bernd

    2010-05-01

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

  19. Spatio-temporal coupling of EEG signals in epilepsy

    NASA Astrophysics Data System (ADS)

    Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

    2011-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-08-01

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

  1. Spatio-Temporal Dynamics of Hypoxia during Radiotherapy.

    PubMed

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

    2015-01-01

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

  2. Spatio-temporal microseismicity clustering in the Cretan region

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Heyman, Joris; Ancey, Christophe

    2014-05-01

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

  4. Spatio-Temporal Dynamics of Hypoxia during Radiotherapy

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  6. Spatio-Temporal Oscillations in Predator-Prey Systems

    NASA Astrophysics Data System (ADS)

    Tomé, T.; de Carvalho, K. Cristina

    2005-10-01

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

  7. Spatio-temporal representativeness of aerosol remote sensing observations

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  8. A Spatio-Temporal Framework for Estimating Trial-to-Trial Amplitude Variation in Event-Related MEG/EEG

    PubMed Central

    Limpiti, Tulaya; Van Veen, Barry D.; Attias, Hagai T.; Nagarajan, Srikantan S.

    2009-01-01

    A spatio-temporal framework for estimating trial-to-trial variability in evoked response data is presented. Spatial and temporal bases capture the aspects of the response that are consistent across trials, while the basis expansion coefficients represent the variable components of the response. We focus on the simplest case of constant spatio-temporal response shape and varying amplitude across trials. Two different constraints on the amplitude evolution are employed to effectively integrate the individual responses and improve robustness at low SNR. The linear dynamical system response (LDSR) constraint estimates the current trial amplitude as an unknown constant scaling of the estimate in the previous trial plus zero-mean Gaussian noise with unknown variance. The independent response (IR) constraint estimates response amplitudes across trials as independent Gaussian random variables having unknown mean and variance. We develop a generalized expectation-maximization algorithm to obtain the maximum likelihood estimates of the signal waveform, noise covariance matrix, and unknown constraint parameters. Maximum likelihood source localization is achieved by scanning the likelihood over different sets of spatial bases. We demonstrate the variability estimation and source localization effectiveness of the proposed algorithms using both real and simulated evoked response data. PMID:19272883

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    SciTech Connect

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

    2010-11-15

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

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

    PubMed

    Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    de Lavenne, Alban; Cudennec, Christophe

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  14. A Spatio-Temporal Framework for MEG/EEG Evoked Response Amplitude and Latency Variability Estimation

    PubMed Central

    Limpiti, Tulaya; Van Veen, Barry D.; Wakai, Ronald T.

    2009-01-01

    This paper presents a spatio-temporal framework for estimating single-trial response latencies and amplitudes from evoked response MEG/EEG data. Spatial and temporal bases are employed to capture the aspects of the evoked response that are consistent across trials. Trial amplitudes are assumed independent but have the same underlying normal distribution with unknown mean and variance. The trial latency is assumed to be deterministic but unknown. We assume the noise is spatially correlated with unknown covariance matrix. We introduce a generalized expectation-maximization algorithm called TriViAL (Trial Variability in Amplitude and Latency) which computes the maximum likelihood (ML) estimates of the amplitudes, latencies, basis coefficients, and noise covariance matrix. The proposed approach also performs ML source localization by scanning the TriViAL algorithm over spatial bases corresponding to different locations on the cortical surface. Source locations are identified as the locations corresponding to large likelihood values. The effectiveness of the TriViAL algorithm is demonstrated using simulated data and human evoked response experiments. The localization performance is validated using tactile stimulation of the finger. The efficacy of the algorithm in estimating latency variability is shown using the known dependence of the M100 auditory response latency to stimulus tone frequency. We also demonstrate that estimation of response amplitude is improved when latency is included in the signal model. PMID:19789097

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed

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

    2009-06-22

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

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

    PubMed

    Jousimo, Jussi; Ovaskainen, Otso

    2016-01-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  3. Spatio-temporal analysis of potential aquifer recharge: Application to the Basin of Mexico

    NASA Astrophysics Data System (ADS)

    Carrera-Hernández, J. J.; Gaskin, S. J.

    2008-05-01

    SummaryRegional estimates of aquifer recharge are needed in data-scarce regions such as the Basin of Mexico, where nearly 20 million people are located and where the Basin's aquifer system represents the main water source. In order to develop the spatio-temporal estimates of aquifer recharge and to analyze to what extent urban growth has affected aquifer recharge, this work presents a daily soil water balance which uses different vegetation and soil types as well as the effect of topography on climatological variables and evapotranspiration. The soil water balance was applied on a daily time step in the Basin of Mexico for the period 1975-1986, obtaining an annually-lumped potential recharge flow of 10.9-23.8 m 3/s (35.9-78.1 mm) in the entire Basin, while the monthly values for the year with the largest lumped recharge value (1981 = 78.1 mm) range from 1 m 3/s (0.3 mm) in December to 87.9 m 3/s (23.7 mm) in June. As aquifer recharge in the Basin mainly occurs by subsurface flow from its enclosing mountains as Mountain Block Recharge, urban growth has had a minimal impact on aquifer recharge, although it has diminished recharge in the alluvial plain.

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

    PubMed

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

    2009-02-15

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

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

    NASA Astrophysics Data System (ADS)

    Wang, Hao; Liu, Yaolin

    2007-06-01

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

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

    PubMed Central

    Fritz, Rafael Dominik; Pertz, Olivier

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

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

    SciTech Connect

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

    2009-05-01

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

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

    PubMed

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

    2016-04-01

    Ongoing biodiversity decline impairs ecosystem processes, including pollination. Flower visitation, an important indicator of pollination services, is influenced by plant species richness. However, the spatio-temporal responses of different pollinator groups to plant species richness have not yet been analyzed experimentally. Here, we used an experimental plant species richness gradient to analyze plant-pollinator interactions with an unprecedented spatio-temporal resolution. We observed four pollinator functional groups (honeybees, bumblebees, solitary bees, and hoverflies) in experimental plots at three different vegetation strata between sunrise and sunset. Visits were modified by plant species richness interacting with time and space. Furthermore, the complementarity of pollinator functional groups in space and time was stronger in species-rich mixtures. We conclude that high plant diversity should ensure stable pollination services, mediated via spatio-temporal niche complementarity in flower visitation. PMID:27069585

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

    NASA Astrophysics Data System (ADS)

    Wolff, Markus; Asche, Hartmut

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

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

    NASA Astrophysics Data System (ADS)

    Yokota, Masae; Yokota, Yasunari

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Kurtosis Approach Nonlinear Blind Source Separation

    NASA Technical Reports Server (NTRS)

    Duong, Vu A.; Stubbemd, Allen R.

    2005-01-01

    In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation Keywords: Independent Component Analysis, Kurtosis, Higher order statistics.

  14. Kurtosis Approach for Nonlinear Blind Source Separation

    NASA Technical Reports Server (NTRS)

    Duong, Vu A.; Stubbemd, Allen R.

    2005-01-01

    In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    . 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. 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. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

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

    PubMed Central

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

    2007-01-01

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

  17. Transform domain steganography with blind source separation

    NASA Astrophysics Data System (ADS)

    Jouny, Ismail

    2015-05-01

    This paper applies blind source separation or independent component analysis for images that may contain mixtures of text, audio, or other images for steganography purposes. The paper focuses on separating mixtures in the transform domain such as Fourier domain or the Wavelet domain. The study addresses the effectiveness of steganography when using linear mixtures of multimedia components and the ability of standard blind sources separation techniques to discern hidden multimedia messages. Mixing in the space, frequency, and wavelet (scale) domains is compared. Effectiveness is measured using mean square error rate between original and recovered images.

  18. Spatio-temporal precipitation error propagation in runoff modelling: a case study in central Sweden

    NASA Astrophysics Data System (ADS)

    Olsson, J.

    2006-07-01

    The propagation of spatio-temporal errors in precipitation estimates to runoff errors in the output from the conceptual hydrological HBV model was investigated. The study region was the Gimån catchment in central Sweden, and the period year 2002. Five precipitation sources were considered: NWP model (H22), weather radar (RAD), precipitation gauges (PTH), and two versions of a mesoscale analysis system (M11, M22). To define the baseline estimates of precipitation and runoff, used to define seasonal precipitation and runoff biases, the mesoscale climate analysis M11 was used. The main precipitation biases were a systematic overestimation of precipitation by H22, in particular during winter and early spring, and a pronounced local overestimation by RAD during autumn, in the western part of the catchment. These overestimations in some cases exceeded 50% in terms of seasonal subcatchment relative accumulated volume bias, but generally the bias was within ±20%. The precipitation data from the different sources were used to drive the HBV model, set up and calibrated for two stations in Gimån, both for continuous simulation during 2002 and for forecasting of the spring flood peak. In summer, autumn and winter all sources agreed well. In spring H22 overestimated the accumulated runoff volume by ~50% and peak discharge by almost 100%, owing to both overestimated snow depth and precipitation during the spring flood. PTH overestimated spring runoff volumes by ~15% owing to overestimated winter precipitation. The results demonstrate how biases in precipitation estimates may exhibit a substantial space-time variability, and may further become either magnified or reduced when applied for hydrological purposes, depending on both temporal and spatial variations in the catchment. Thus, the uncertainty in precipitation estimates should preferably be specified as a function of both time and space.

  19. Spatio-temporal radiation biology with conventionally or laser-accelerated particles for ELIMED

    SciTech Connect

    Ristić-Fira, A.; Bulat, T.; Keta, O.; Petrović, I.; Romano, F.; Cirrone, P.; Cuttone, G.

    2013-07-26

    The aim of this study is to investigate the behavior of radio-resistant human malignant cells, thus enabling better understanding of radiobiological effects of ions in such a case. Radiation sources such as accelerated continuous ion beams and laser technology-based ultra short radiation sources with energy of around 10 MeV will be used. The HTB140 melanoma cells are chosen since it has been shown that they represent the limit case of cellular radio-resistance among the studied tumor cell lines. These cells are particularly interesting as they provide data on the very edge of inactivation capacity of each beam line that is tested. After exposing the cell monolayers to continuous radiations of low (γ-rays) and high (protons) linear energy transfer, the kinetics of disappearance of the phosphorylated histone H2AX (γ-H2AX) foci per cell will be determined. The same procedure will be performed with the pulsed high dose rate protons. Detection and quantification of γ-H2AX foci will be performed by immunohistochemical 3D time-dependent imaging analyses using laser scanning confocal microscopy. Immunoblotting will enable the follow-up of the relation between γ-H2AX and cell cycle arrest via the p53/p21 pathway. In such a way the spatio-temporal changes on sub-cellular level will be visualized, quantified and compared. These results will show whether there is a difference in the effects on cells between continuous and pulsed irradiation mode. Therefore, they will contribute to the data base that might promote pulsed sources for medical treatments of malignant growths.

  20. Spatio-temporal radiation biology with conventionally or laser-accelerated particles for ELIMED

    NASA Astrophysics Data System (ADS)

    Ristić-Fira, A.; Bulat, T.; Keta, O.; Romano, F.; Cirrone, P.; Cuttone, G.; Petrović, I.

    2013-07-01

    The aim of this study is to investigate the behavior of radio-resistant human malignant cells, thus enabling better understanding of radiobiological effects of ions in such a case. Radiation sources such as accelerated continuous ion beams and laser technology-based ultra short radiation sources with energy of around 10 MeV will be used. The HTB140 melanoma cells are chosen since it has been shown that they represent the limit case of cellular radio-resistance among the studied tumor cell lines. These cells are particularly interesting as they provide data on the very edge of inactivation capacity of each beam line that is tested. After exposing the cell monolayers to continuous radiations of low (γ-rays) and high (protons) linear energy transfer, the kinetics of disappearance of the phosphorylated histone H2AX (γ-H2AX) foci per cell will be determined. The same procedure will be performed with the pulsed high dose rate protons. Detection and quantification of γ-H2AX foci will be performed by immunohistochemical 3D time-dependent imaging analyses using laser scanning confocal microscopy. Immunoblotting will enable the follow-up of the relation between γ-H2AX and cell cycle arrest via the p53/p21 pathway. In such a way the spatio-temporal changes on sub-cellular level will be visualized, quantified and compared. These results will show whether there is a difference in the effects on cells between continuous and pulsed irradiation mode. Therefore, they will contribute to the data base that might promote pulsed sources for medical treatments of malignant growths.

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    ERIC Educational Resources Information Center

    Chartrel, Estelle; Vinter, Annie

    2008-01-01

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

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

    PubMed

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    PubMed

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

    2016-07-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Zaal, Peter; Sweet, Barbara

    2010-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

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

    2016-07-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

    2014-05-01

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

  14. Testing the accuracy ratio of the Spatio-Temporal Epidemiological Modeler (STEM) through Ebola haemorrhagic fever outbreaks.

    PubMed

    Baldassi, F; D'Amico, F; Carestia, M; Cenciarelli, O; Mancinelli, S; Gilardi, F; Malizia, A; DI Giovanni, D; Soave, P M; Bellecci, C; Gaudio, P; Palombi, L

    2016-05-01

    Mathematical modelling is an important tool for understanding the dynamics of the spread of infectious diseases, which could be the result of a natural outbreak or of the intentional release of pathogenic biological agents. Decision makers and policymakers responsible for strategies to contain disease, prevent epidemics and fight possible bioterrorism attacks, need accurate computational tools, based on mathematical modelling, for preventing or even managing these complex situations. In this article, we tested the validity, and demonstrate the reliability, of an open-source software, the Spatio-Temporal Epidemiological Modeler (STEM), designed to help scientists and public health officials to evaluate and create models of emerging infectious diseases, analysing three real cases of Ebola haemorrhagic fever (EHF) outbreaks: Uganda (2000), Gabon (2001) and Guinea (2014). We discuss the cases analysed through the simulation results obtained with STEM in order to demonstrate the capability of this software in helping decision makers plan interventions in case of biological emergencies. PMID:27029910

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

    NASA Astrophysics Data System (ADS)

    Masse, A.; Christophe, S.

    2015-08-01

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

  16. Spatio-temporal changes in biomass carbon sinks in China's forests from 1977 to 2008.

    PubMed

    Guo, Zhaodi; Hu, Huifeng; Li, Pin; Li, Nuyun; Fang, Jingyun

    2013-07-01

    Forests play a leading role in regional and global carbon (C) cycles. Detailed assessment of the temporal and spatial changes in C sinks/sources of China's forests is critical to the estimation of the national C budget and can help to constitute sustainable forest management policies for climate change. In this study, we explored the spatio-temporal changes in forest biomass C stocks in China between 1977 and 2008, using six periods of the national forest inventory data. According to the definition of the forest inventory, China's forest was categorized into three groups: forest stand, economic forest, and bamboo forest. We estimated forest biomass C stocks for each inventory period by using continuous biomass expansion factor (BEF) method for forest stands, and the mean biomass density method for economic and bamboo forests. As a result, China's forests have accumulated biomass C (i.e., biomass C sink) of 1896 Tg (1 Tg=10(12) g) during the study period, with 1710, 108 and 78 Tg C in forest stands, and economic and bamboo forests, respectively. Annual forest biomass C sink was 70.2 Tg C a(-1), offsetting 7.8% of the contemporary fossil CO2 emissions in the country. The results also showed that planted forests have functioned as a persistent C sink, sequestrating 818 Tg C and accounting for 47.8% of total C sink in forest stands, and that the old-, mid- and young-aged forests have sequestrated 930, 391 and 388 Tg C from 1977 to 2008. Our results suggest that China's forests have a big potential as biomass C sink in the future because of its large area of planted forests with young-aged growth and low C density. PMID:23722235

  17. Estimating the size of polyps during actual endoscopy procedures using a spatio-temporal characterization.

    PubMed

    Martínez, Fabio; Ruano, Josué; Gómez, Martín; Romero, Eduardo

    2015-07-01

    Colorectal cancer usually appears in polyps developed from the mucosa. Carcinoma is frequently found in those polyps larger than 10mm and therefore only this kind of polyps is sent for pathology examination. In consequence, accurate estimation of a polyp size determines the surveillance interval after polypectomy. The follow up consists in a periodic colonoscopy whose frequency depends on the estimation of the size polyp. Typically, this polyp measure is achieved by examining the lesion with a calibrated endoscopy tool. However, measurement is very challenging because it must be performed during a procedure subjected to a complex mix of noise sources, namely anatomical variability, drastic illumination changes and abrupt camera movements. This work introduces a semi-automatic method that estimates a polyp size by propagating an initial manual delineation in a single frame to the whole video sequence using a spatio-temporal characterization of the lesion, during a routine endoscopic examination. The proposed approach achieved a Dice Score of 0.7 in real endoscopy video-sequences, when comparing with an expert. In addition, the method obtained a root mean square error (RMSE) of 0.87mm in videos artificially captured in a cylindric structure with spheres of known size that simulated the polyps. Finally, in real endoscopy sequences, the diameter estimation was compared with measures obtained by a group of four experts with similar experience, obtaining a RMSE of 4.7mm for a set of polyps measuring from 5 to 20mm. An ANOVA test performed for the five groups of measurements (four experts and the method) showed no significant differences (p<0.01). PMID:25670148

  18. A spatio-temporally detailed and regular description of the external field over the last solar cycle using EOFs

    NASA Astrophysics Data System (ADS)

    Shore, Robert; Freeman, Mervyn; Wild, James; Dorrian, Gareth; Gjerloev, Jesper

    2016-04-01

    Using the Empirical Orthogonal Function (EOF) method, we demonstrate that an irregular network of ground-based vector magnetic data can provide a spatio-temporally detailed and regular description of the external magnetic field without a priori assumptions of the source current geometry. The EOF method analyses the spatio-temporal co-variance of the data to decompose it into dynamically distinct modes (each mode is a pair of spatial and temporal basis vectors). A small number of these modes can cumulatively represent most of the variance of the original data. After binning the observatory data we use the modes to provide a self-consistent infill mechanism for empty bins. Since the basis vectors are defined by the data, the infill solutions only converge upon reinforcement of the natural patterns present in the data, hence the completion of the data coverage is self-consistent. This is in contrast to other commonly-used decomposition methods such as Fourier and spherical harmonic expansions. We discuss the application of the iteratively-infilled EOF method to vector data from the SuperMAG archive spanning 1997 - 2008 (a full solar cycle). Using a comparison of the temporal behaviour of the modes alongside independent measures of solar-terrestrial coupling, we demonstrate that the leading three modes describe the well-known Disturbance-Polar currents types 2 and 1 (DP2, DP1) and the system of cusp currents (DPY). These three modes account for the majority of the variance of the data - other modes describe the spatial motions of these current systems. We demonstrate that the use of ground-based data provides an important complement to the coverage of polar data available from satellites, such as AMPERE. Lastly we discuss situations in which the EOF analysis will perform better or worse than other methods, and assess the types of signal that the analysis responds to most strongly.

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

    EPA Science Inventory

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

  20. Spatio-temporal variability in isotopic signatures of atmospheric NOx emissions from vehicles

    NASA Astrophysics Data System (ADS)

    Miller, D. J.; Wojtal, P.; O'Connor, M.; Clark, S.; Hastings, M. G.

    2015-12-01

    Atmospheric nitrogen oxides (NOx = NO + NO2) play key roles in atmospheric chemistry and radiative forcing. Their oxidation products, nitric acid or nitrate, have significant contributions to nitrogen (N) deposition, with implications for ecosystem health. On-road vehicle NOx sources currently dominate U.S. anthropogenic emission budgets, yet vehicle NOx emissions contributions to local and regional N deposition patterns are highly uncertain. NOx isotopic signatures offer a potentially valuable observational tool to trace source contributions to N deposition. We characterize the spatio-temporal variability of vehicle NOx emission isotopic signatures with a field and laboratory-verified technique for actively capturing NOx in solution to quantify the nitrogen isotopic composition (δ15N-NOx) to within ±1.5‰ (1σ) precision. We present a novel combination of on-road mobile and stationary urban δ15N-NOx measurements at minutes to hourly resolution along with NOx and CO2 concentration measurements. We evaluate spatial gradients of δ15N-NOx on U.S. Northeast and Midwest highways, including six urban metropolitan areas and rural interstate highways during summer and autumn. We also assess on-road diurnal δ15N-NOx variations over ~800 km driving distance in Providence, RI by targeting the upwind footprint of urban background measurements to distinguish background and source NOx. We observe on-road δ15N-NOx signatures range from -3 to -10‰ under different traffic conditions in the U.S. Northeast and Midwest. On-road δ15N-NOx daytime variations from -3 to -6‰ agree well with simultaneous urban background sampling in Providence, RI, suggesting that vehicles dominate NOx emissions in this region. We use these datasets to estimate the range of representative δ15N-NOx source signatures for U.S. vehicle fleet-integrated emission plumes. Our novel approach suggests that previously reported isotopic signatures for vehicle NOx are not necessarily representative. These

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Kennett, Malcolm; Fitzpatrick, Matthew

    2016-05-01

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

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

    USGS Publications Warehouse

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

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    PubMed Central

    Arab, Ali

    2015-01-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    SciTech Connect

    Kurt Derr; Milos Manic

    2008-09-01

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

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Greenewald, Kristjan H.; Hero, Alfred O.

    2014-06-01

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

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

    SciTech Connect

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Réfrégier, Philippe

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

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

    NASA Astrophysics Data System (ADS)

    Clairambault, Jean; Eliaš, Ján

    2016-06-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Smith, Tony E.; Wu, Peggy

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhou, Chengtao; Zhou, Fan; Chen, Yaowu

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Manga, Edna; Awang, Norhashidah

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhou, Qin; Zhu, Qiuping

    2015-03-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Ananthakrishna, G.; Sarmah, R.

    2013-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Alkan, M.; Polat, Z. A.

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    PubMed

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

    2016-09-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Mitchell, Richard

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Bhattacharjee, S.; Ghosh, S. K.

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2004-01-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    SciTech Connect

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

    2010-01-01

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

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

    PubMed

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

    2016-07-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed

    Widgren, Stefan; Frössling, Jenny

    2010-11-01

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

  10. Modelling natural grass production and its spatio-temporal variations in a semiarid Mediterranean watershed

    NASA Astrophysics Data System (ADS)

    Schnabel, Susanne; Lozano-Parra, Javier; Maneta-López, Marco

    2014-05-01

    Natural grasses are found in semiarid rangelands with disperse tree cover of part of the Iberian Peninsula and constitute a resource with high ecologic and economic value worth, being an important source of food for livestock, playing a significant role in the hydrologic cycle, controlling the soil thermal regime, and are a key factor in reducing soil erosion and degradation. However, increasing pressure on the resources, changes in land use as well as possible climate variations threaten the sustainability of natural grasses. Despite of their importance, the spatio-temporal variations of pasture production over whole watersheds are poorly known. In this sense, previous studies by other authors have indicated its dependence on a balance of positive and negative effects brought about by the main limiting factors: water, light, nutrients and space. Nevertheless, the specific weight of each factor is not clear because they are highly variable due to climate characteristics and the structure of these agroforestry systems. We have used a physical spatially-distributed ecohydrologic model to investigate the specific weight of factors that contribute to pasture production in a semiarid watershed of 99.5 ha in western Spain. This model couples a two layer (canopy and understory) vertical local closure energy balance scheme, a hydrologic model and a carbon uptake and vegetation growth component, and it was run using a synthetic daily climate dataset generated by a stochastic weather generator, which reproduced the range of climatic variations observed under mediterranean current climate. The modelling results reproduced satisfactorily the seasonality effects of climate as precipitation and temperatures, as well as annual and inter-annual variations of pasture production. Spatial variations of pasture production were largely controlled by topographic and tree effects, showing medium-low values depending of considered areas. These low values require introduction of feed to

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    PubMed

    Junge, Wolfgang

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

    2016-04-01

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

  14. An algebra for spatio-temporal information generation

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  16. Bayesian Blind Source Separation of Positive Non Stationary Sources

    NASA Astrophysics Data System (ADS)

    Ichir, Mahieddine M.; Mohammad-Djafari, Ali

    2004-11-01

    In this contribution, we address the problem of blind non negative source separation. This problem finds its application in many fields of data analysis. We propose herein a novel approach based on Gamma mixture probability priors: Gamma densities to constraint the unobserved sources to lie on the positive half plane; a mixture density with a first order Markov model on the associated hidden variables to account for eventual non stationarity on the sources. Posterior mean estimates are obtained via appropriate Monte Carlo Markov Chain sampling.

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

    DOE PAGESBeta

    Sen, Satyabrata

    2015-08-04

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. Spatio-temporal foraging patterns of a giant zooplanktivore, the leatherback turtle

    NASA Astrophysics Data System (ADS)

    Fossette, Sabrina; Hobson, Victoria J.; Girard, Charlotte; Calmettes, Beatriz; Gaspar, Philippe; Georges, Jean-Yves; Hays, Graeme C.

    2010-05-01

    Understanding food web functioning through the study of natural bio-indicators may constitute a valuable and original approach. In the context of jellyfish proliferation in many overexploited marine ecosystems studying the spatio-temporal foraging patterns of the giant "jellyvore" leatherback turtle turns out to be particularly relevant. Here we analyzed long-term tracking data to assess spatio-temporal foraging patterns in 21 leatherback turtles during their pluri-annual migration in the Northern Atlantic. Through an analytical approach based on the animal's own motion (independent of currents) and diving behavior distinct zones of high and low foraging success were identified. High foraging success occurred in a sub-equatorial zone spanning the width of the Atlantic and at high (>30°N) latitudes. Between these zones in the centre of North Atlantic gyre there was low foraging success. This "ocean desert" area was traversed at high speed by leatherbacks on their way to more productive areas at higher latitudes. Animals traveled slowly in high foraging success areas and dived shallower (17.2 ± 8.0 km day - 1 and 53.6 ± 33.1 m mean ± SD respectively) than in low foraging success areas (51.0 ± 13.1 km day - 1 and 81.8 ± 56.2 m mean ± SD respectively). These spatio-temporal foraging patterns seem to relatively closely match the main features of the integrated meso-zooplankton distribution in the North Atlantic. Our method of defining high foraging success areas is intuitive and relatively easy to implement but also takes into account the impact of oceanic currents on animal's behavior.

  1. A bio-inspired system for spatio-temporal recognition in static and video imagery

    NASA Astrophysics Data System (ADS)

    Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

    2007-04-01

    This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

  2. Spatio-temporal patterns of dengue in Malaysia: combining address and sub-district level.

    PubMed

    Ling, Cheong Y; Gruebner, Oliver; Krämer, Alexander; Lakes, Tobia

    2014-11-01

    Spatio-temporal patterns of dengue risk in Malaysia were studied both at the address and the sub-district level in the province of Selangor and the Federal Territory of Kuala Lumpur. We geocoded laboratory-confirmed dengue cases from the years 2008 to 2010 at the address level and further aggregated the cases in proportion to the population at risk at the sub-district level. Kulldorff's spatial scan statistic was applied for the investigation that identified changing spatial patterns of dengue cases at both levels. At the address level, spatio-temporal clusters of dengue cases were concentrated at the central and south-eastern part of the study area in the early part of the years studied. Analyses at the sub-district level revealed a consistent spatial clustering of a high number of cases proportional to the population at risk. Linking both levels assisted in the identification of differences and confirmed the presence of areas at high risk for dengue infection. Our results suggest that the observed dengue cases had both a spatial and a temporal epidemiological component, which needs to be acknowledged and addressed to develop efficient control measures, including spatially explicit vector control. Our findings highlight the importance of detailed geographical analysis of disease cases in heterogeneous environments with a focus on clustered populations at different spatial and temporal scales. We conclude that bringing together information on the spatio-temporal distribution of dengue cases with a deeper insight of linkages between dengue risk, climate factors and land use constitutes an important step towards the development of an effective risk management strategy. PMID:25545931

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

    NASA Astrophysics Data System (ADS)

    Poggio, Laura; Gimona, Alessandro; Brown, Iain

    2012-08-01

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

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

    SciTech Connect

    Sen, Satyabrata

    2015-08-04

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

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

    PubMed Central

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

    2011-01-01

    Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

  6. Blind source separation of convolutive mixtures

    NASA Astrophysics Data System (ADS)

    Makino, Shoji

    2006-04-01

    This paper introduces the blind source separation (BSS) of convolutive mixtures of acoustic signals, especially speech. A statistical and computational technique, called independent component analysis (ICA), is examined. By achieving nonlinear decorrelation, nonstationary decorrelation, or time-delayed decorrelation, we can find source signals only from observed mixed signals. Particular attention is paid to the physical interpretation of BSS from the acoustical signal processing point of view. Frequency-domain BSS is shown to be equivalent to two sets of frequency domain adaptive microphone arrays, i.e., adaptive beamformers (ABFs). Although BSS can reduce reverberant sounds to some extent in the same way as ABF, it mainly removes the sounds from the jammer direction. This is why BSS has difficulties with long reverberation in the real world. If sources are not "independent," the dependence results in bias noise when obtaining the correct separation filter coefficients. Therefore, the performance of BSS is limited by that of ABF. Although BSS is upper bounded by ABF, BSS has a strong advantage over ABF. BSS can be regarded as an intelligent version of ABF in the sense that it can adapt without any information on the array manifold or the target direction, and sources can be simultaneously active in BSS.

  7. Spatio-temporal Dynamics of Pond Use and Recruitment in Florida Gopher Frogs (Rana Capito aesopus)

    SciTech Connect

    Greenberg, C.H.

    2000-05-16

    We examined spatio-temporal dynamics of the Florida Gopher frog breeding and juvenile recruitment. Ponds were situated in a hardwood or pine-savanna matrix of upland forest. Movement was monitored from 1994-1999. Adult pond use was low but relatively constant. Juvenile recruitment was higher in the upland savanna matrix. Body size was negatively correlated with the number of juveniles exiting the pond in only one year suggesting intraspecific competition is one of many factors. Most immigration occurred in May through August and was unrelated to rainfall.

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

    PubMed

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

    2014-05-01

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

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

    PubMed Central

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

    2012-01-01

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

  10. Study of Spatio-Temporal Immunofluorescence on Bead Patterns in a Microfluidic Channel

    NASA Astrophysics Data System (ADS)

    Sivagnanam, Venkataragavalu; Yang, Hui; Gijs, Martin A. M.

    2010-12-01

    We performed a direct immunoassay inside a microfluidic channel on patterned streptavidin-coated beads, which captured fluorescently-labeled biotin target molecules from a continuous flow. We arranged the beads in a dot array at the bottom of the channel and demonstrated their position- and flow rate-dependent fluorescence. As the target analyte gets gradually depleted from the flow when passing downstream the channel, the highest fluorescence intensity was observed on the most upstream positioned dot patterns. We propose a simple analytical convection model to explain this spatio-temporal fluorescence.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  12. Spatio-temporal analysis of human electroencephalograms: Petit-mal epilepsy

    NASA Astrophysics Data System (ADS)

    Friedrich, R.; Uhl, C.

    An analysis of multigrid electroencephalograms (EEG) derived from two different persons suffering from petit-mal epilepsy is performed. Using a previously devised method for analyzing spatio-temporal patterns (Uhl, et al., Z. Phys. B 92 (1993) 211-219), we find a suitable mode decomposition of the EEG. Additionally, we are able to extract a three-dimensional dynamical system which describes the dynamics of the patterns as a kind of mode interaction. We show that the spike-wave behavior characteristic for petit-mal epilepsy arising in the dynamical system is related with Sil'nikov-type behavior of the mode dynamics.

  13. Spatio-temporal description of the cavitating flow behavior around NACA 2412 hydrofoil

    NASA Astrophysics Data System (ADS)

    Rudolf, P.; Štefan, D.; Sedlář, M.; Kozák, J.; Habán, V.; Huzlík, R.

    2015-12-01

    Spatio-temporal description of the cavitating flow around hydrofoil with 8 degrees incidence using proper orthogonal decomposition (POD) is presented. POD is a suitable tool, which provides information not only about the flow dynamics, but also about relevance of different flow structures. POD also enables to track energy transport within the domain and energy transfer among the eigenmodes of the flow field. Analysis documents change of the flow structure for decreasing cavitation number, which can be most likely attributed to sheet/cloud cavitation transition.

  14. A Fisher-gradient complexity in systems with spatio-temporal dynamics

    NASA Astrophysics Data System (ADS)

    Arbona, A.; Bona, C.; Massó, J.; Miñano, B.; Plastino, A.

    2016-04-01

    We define a benchmark for definitions of complexity in systems with spatio-temporal dynamics and employ it in the study of Collective Motion. We show that LMC's complexity displays interesting properties in such systems, while a statistical complexity model (SCM) based on autocorrelation reasonably meets our perception of complexity. However this SCM is not as general as desirable, as it does not merely depend on the system's Probability Distribution Function. Inspired by the notion of Fisher information, we develop a SCM candidate, which we call the Fisher-gradient complexity, which exhibits nice properties from the viewpoint of our benchmark.

  15. Detection of spatio-temporal gait parameters by using wearable motion sensors.

    PubMed

    Lee, Seon-Woo; Mase, Kenji; Kogure, Kiyoshi

    2005-01-01

    This paper presents a method to detect the spatio-temporal parameters of gait by using wearable motion sensors with a gyro, accelerometer, and magnetic sensor. The detected gait parameters are as follows: stance (ST), double support (DS), and gait cycle (GC) time as temporal parameters, and the stride length (SL) as spatial parameter. Four motion sensors are attached on both thighs and shanks of users, and the sensor data are collected in a portable PC. The temporal parameters are estimated by finding walking events, and then the stride length is calculated with two gait models. The estimated parameters are compared to those obtained from a motion capture system (VICON system). PMID:17281844

  16. Transient spatio-temporal dynamics of a diffusive plant-herbivore system with Neumann boundary conditions.

    PubMed

    Yu, Fang; Wang, Lin; Watmough, James

    2016-12-01

    In many existing predator-prey or plant-herbivore models, the numerical response is assumed to be proportional to the functional response. In this paper, without such an assumption, we consider a diffusive plant-herbivore system with Neumann boundary conditions. Besides stability of spatially homogeneous steady states, we also derive conditions for the occurrence of Hopf bifurcation and steady-state bifurcation and provide geometrical methods to locate the bifurcation values. We numerically explore the complex transient spatio-temporal behaviours induced by these bifurcations. A large variety of different types of transient behaviours including oscillations in one or both of space and time are observed. PMID:27572052

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

    USGS Publications Warehouse

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

    2010-01-01

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

  18. Amplitude equations for collective spatio-temporal dynamics in arrays of coupled systems

    SciTech Connect

    Yanchuk, S.; Wolfrum, M.; Perlikowski, P.; Stefański, A.; Kapitaniak, T.

    2015-03-15

    We study the coupling induced destabilization in an array of identical oscillators coupled in a ring structure where the number of oscillators in the ring is large. The coupling structure includes different types of interactions with several next neighbors. We derive an amplitude equation of Ginzburg-Landau type, which describes the destabilization of a uniform stationary state and close-by solutions in the limit of a large number of nodes. Studying numerically an example of unidirectionally coupled Duffing oscillators, we observe a coupling induced transition to collective spatio-temporal chaos, which can be understood using the derived amplitude equations.

  19. Sustained spatio-temporal chaotic flow at onset of electroconvection in nematic liquid crystals

    NASA Astrophysics Data System (ADS)

    Gleeson, J. T.

    1997-02-01

    In the presence of a strong magnetic field parallel to the applied electric field, electrohydrodynamic convection (EHC) in nematic liquid crystals is a pattern forming system with weakly broken rotational symmetry in the plane parallel to the magnetic field. In this system, the first instability observed is to a spatio-temporally chaotic state, in qualitative agreement with recent theoretical results. We report experimental results demonstrating sustained time dependence and spatial disorder immediately above the subcritical transition from the quiescent state in this system.

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

    PubMed

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

    2014-09-01

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

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

    PubMed

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

    2016-08-15

    This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. PMID:27100003

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

    NASA Astrophysics Data System (ADS)

    Luhtala, Hanna; Tolvanen, Harri

    2016-06-01

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

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

    PubMed Central

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

    2015-01-01

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

  4. Multiple dipole modeling and localization from spatio-temporal MEG data

    SciTech Connect

    Mosher, J.C. ); Lewis, P.S. ); Leahy, R. )

    1992-06-01

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

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

    SciTech Connect

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

    2014-12-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

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

    PubMed Central

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity. PMID:27297496

  8. Evaluation of spatio-temporal variability in Land Surface Temperature: A case study of Zonguldak, Turkey.

    PubMed

    Sekertekin, Aliihsan; Kutoglu, Senol Hakan; Kaya, Sinasi

    2016-01-01

    The aim of this study is to analyze spatio-temporal variability in Land Surface Temperature (LST) in and around the city of Zonguldak as a result of the growing urbanization and industrialization during the last decade. Three Landsat 5 data and one Landsat 8 data acquired on different dates were exploited in acquiring LST maps utilizing mono-window algorithm. The outcomes obtained from this study indicate that there exists a significant temperature rise in the region for the time period between 1986 and 2015. Some cross sections were selected in order to examine the relationship between the land use and LST changes in more detail. The mean LST difference between 1986 and 2015 in ERDEMIR iron and steel plant (6.8 °C), forestland (3 °C), city and town centers (4.2 °C), municipal rubbish tip (-3.9 °C), coal dump site (12.2 °C), and power plants' region (7 °C) were presented. In addition, the results indicated that the mean LST difference between forestland and city centers was approximately 5 °C, and the difference between forestland and industrial enterprises was almost 8 °C for all years. Spatio-temporal variability in LST in Zonguldak was examined in that study and due to the increase in LST, policy makers and urban planners should consider LST and urban heat island parameters for sustainable development. PMID:26666659

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  12. GeoMesa: a distributed architecture for spatio-temporal fusion

    NASA Astrophysics Data System (ADS)

    Hughes, James N.; Annex, Andrew; Eichelberger, Christopher N.; Fox, Anthony; Hulbert, Andrew; Ronquest, Michael

    2015-05-01

    Recent advances in distributed databases and computing have transformed the landscape of spatio-temporal machine learning. This paper presents GeoMesa, a distributed spatio-temporal database built on top of Hadoop and column-family databases such as Accumulo and HBase, that includes a suite of tools for indexing, managing and analyzing both vector and raster data. The indexing techniques use space filling curves to map multi-dimensional data to the single lexicographic list managed by the underlying distributed database. In contrast to traditional non-distributed RDBMS, GeoMesa is capable of scaling horizontally by adding more resources at runtime; the index rebalances across the additional resources. In the raster domain, GeoMesa leverages Accumulo's server-side iterators and aggregators to perform raster interpolation and associative map algebra operations in parallel at query time. The paper concludes with two geo-time data fusion examples: using GeoMesa to aggregate Twitter data by keywords; and georegistration to drape full-motion video (FMV) over terrain.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  14. Scaling and interleaving of subsystem Lyapunov exponents for spatio-temporal systems

    NASA Astrophysics Data System (ADS)

    Carretero-González, R.; Ørstavik, S.; Huke, J.; Broomhead, D. S.; Stark, J.

    1999-06-01

    The computation of the entire Lyapunov spectrum for extended dynamical systems is a very time consuming task. If the system is in a chaotic spatio-temporal regime it is possible to approximately reconstruct the Lyapunov spectrum from the spectrum of a subsystem by a suitable rescaling in a very cost effective way. We compute the Lyapunov spectrum for the subsystem by truncating the original Jacobian without modifying the original dynamics and thus taking into account only a portion of the information of the entire system. In doing so we notice that the Lyapunov spectra for consecutive subsystem sizes are interleaved and we discuss the possible ways in which this may arise. We also present a new rescaling method, which gives a significantly better fit to the original Lyapunov spectrum. We evaluate the performance of our rescaling method by comparing it to the conventional rescaling (dividing by the relative subsystem volume) for one- and two-dimensional lattices in spatio-temporal chaotic regimes. Finally, we use the new rescaling to approximate quantities derived from the Lyapunov spectrum (largest Lyapunov exponent, Lyapunov dimension, and Kolmogorov-Sinai entropy), finding better convergence as the subsystem size is increased than with conventional rescaling.

  15. Scaling and interleaving of subsystem Lyapunov exponents for spatio-temporal systems.

    PubMed

    Carretero-Gonzalez, R.; Orstavik, S.; Huke, J.; Broomhead, D. S.; Stark, J.

    1999-06-01

    The computation of the entire Lyapunov spectrum for extended dynamical systems is a very time consuming task. If the system is in a chaotic spatio-temporal regime it is possible to approximately reconstruct the Lyapunov spectrum from the spectrum of a subsystem by a suitable rescaling in a very cost effective way. We compute the Lyapunov spectrum for the subsystem by truncating the original Jacobian without modifying the original dynamics and thus taking into account only a portion of the information of the entire system. In doing so we notice that the Lyapunov spectra for consecutive subsystem sizes are interleaved and we discuss the possible ways in which this may arise. We also present a new rescaling method, which gives a significantly better fit to the original Lyapunov spectrum. We evaluate the performance of our rescaling method by comparing it to the conventional rescaling (dividing by the relative subsystem volume) for one- and two-dimensional lattices in spatio-temporal chaotic regimes. Finally, we use the new rescaling to approximate quantities derived from the Lyapunov spectrum (largest Lyapunov exponent, Lyapunov dimension, and Kolmogorov-Sinai entropy), finding better convergence as the subsystem size is increased than with conventional rescaling. (c) 1999 American Institute of Physics. PMID:12779843

  16. Rational spatio-temporal strategies for controlling a Chagas disease vector in urban environments

    PubMed Central

    Levy, Michael Z.; Malaga Chavez, Fernando S.; Cornejo del Carpio, Juan G.; Vilhena, Daril A.; McKenzie, F. Ellis; Plotkin, Joshua B.

    2010-01-01

    The rational design of interventions is critical to controlling communicable diseases, especially in urban environments. In the case of the Chagas disease vector Triatoma infestans, successful control is stymied by the return of the insect after the effectiveness of the insecticide wanes. Here, we adapt a genetic algorithm, originally developed for the travelling salesman problem, to improve the spatio-temporal design of insecticide campaigns against T. infestans, in a complex urban environment. We find a strategy that reduces the expected instances of vector return 34-fold compared with the current strategy of sequential insecticide application to spatially contiguous communities. The relative success of alternative control strategies depends upon the duration of the effectiveness of the insecticide, and it shows chaotic fluctuations in response to unforeseen delays in a control campaign. We use simplified models to analyse the outcomes of qualitatively different spatio-temporal strategies. Our results provide a detailed procedure to improve control efforts for an urban Chagas disease vector, as well as general guidelines for improving the design of interventions against other disease agents in complex environments. PMID:20061346

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity. PMID:27297496

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

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

    PubMed

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

    2014-08-01

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

  2. Spatio-Temporal Pattern Analysis for Regional Climate Change Using Mathematical Morphology

    NASA Astrophysics Data System (ADS)

    Das, M.; Ghosh, S. K.

    2015-07-01

    Of late, significant changes in climate with their grave consequences have posed great challenges on humankind. Thus, the detection and assessment of climatic changes on a regional scale is gaining importance, since it helps to adopt adequate mitigation and adaptation measures. In this paper, we have presented a novel approach for detecting spatio-temporal pattern of regional climate change by exploiting the theory of mathematical morphology. At first, the various climatic zones in the region have been identified by using multifractal cross-correlation analysis (MF-DXA) of different climate variables of interest. Then, the directional granulometry with four different structuring elements has been studied to detect the temporal changes in spatial distribution of the identified climatic zones in the region and further insights have been drawn with respect to morphological uncertainty index and Hurst exponent. The approach has been evaluated with the daily time series data of land surface temperature (LST) and precipitation rate, collected from Microsoft Research - Fetch Climate Explorer, to analyze the spatio-temporal climatic pattern-change in the Eastern and North-Eastern regions of India throughout four quarters of the 20th century.

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

    NASA Astrophysics Data System (ADS)

    Dasgupta, Udayan; Ali, Murtaza

    2011-03-01

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

  4. Stochastic Spatio-Temporal Dynamic Model for Gene/Protein Interaction Network in Early Drosophila Development

    PubMed Central

    Li, Cheng-Wei; Chen, Bor-Sen

    2009-01-01

    In order to investigate the possible mechanisms for eve stripe formation of Drosophila embryo, a spatio-temporal gene/protein interaction network model is proposed to mimic dynamic behaviors of protein synthesis, protein decay, mRNA decay, protein diffusion, transcription regulations and autoregulation to analyze the interplay of genes and proteins at different compartments in early embryogenesis. In this study, we use the maximum likelihood (ML) method to identify the stochastic 3-D Embryo Space-Time (3-DEST) dynamic model for gene/protein interaction network via 3-D mRNA and protein expression data and then use the Akaike Information Criterion (AIC) to prune the gene/protein interaction network. The identified gene/protein interaction network allows us not only to analyze the dynamic interplay of genes and proteins on the border of eve stripes but also to infer that eve stripes are established and maintained by network motifs built by the cooperation between transcription regulations and diffusion mechanisms in early embryogenesis. Literature reference with the wet experiments of gene mutations provides a clue for validating the identified network. The proposed spatio-temporal dynamic model can be extended to gene/protein network construction of different biological phenotypes, which depend on compartments, e.g. postnatal stem/progenitor cell differentiation. PMID:20054403

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

    PubMed Central

    Li, Yehua; Guan, Yongtao

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

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

  8. Context aware spatio-temporal cell tracking in densely packed multilayer tissues.

    PubMed

    Chakraborty, Anirban; Roy-Chowdhury, Amit K

    2015-01-01

    Modern live imaging technique enables us to observe the internal part of a tissue over time by generating serial optical images containing spatio-temporal slices of hundreds of tightly packed cells. Automated tracking of plant and animal cells from such time lapse live-imaging datasets of a developing multicellular tissue is required for quantitative, high throughput analysis of cell division, migration and cell growth. In this paper, we present a novel cell tracking method that exploits the tight spatial topology of neighboring cells in a multicellular field as contextual information and combines it with physical features of individual cells for generating reliable cell lineages. The 2D image slices of multicellular tissues are modeled as a conditional random field and pairwise cell to cell similarities are obtained by estimating marginal probability distributions through loopy belief propagation on this CRF. These similarity scores are further used in a spatio-temporal graph labeling problem to obtain the optimal and feasible set of correspondences between individual cell slices across the 4D image dataset. We present results on (3D+t) confocal image stacks of Arabidopsis shoot meristem and show that the method is capable of handling many visual analysis challenges associated with such cell tracking problems, viz. poor feature quality of individual cells, low SNR in parts of images, variable number of cells across slices and cell division detection. PMID:25461334

  9. Correlated Spatio-Temporal Fluctuations in Chromatin Compaction States Characterize Stem Cells

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  11. Spatio-temporal visualization of air-sea CO2 flux and carbon budget using volume rendering

    NASA Astrophysics Data System (ADS)

    Du, Zhenhong; Fang, Lei; Bai, Yan; Zhang, Feng; Liu, Renyi

    2015-04-01

    This paper presents a novel visualization method to show the spatio-temporal dynamics of carbon sinks and sources, and carbon fluxes in the ocean carbon cycle. The air-sea carbon budget and its process of accumulation are demonstrated in the spatial dimension, while the distribution pattern and variation of CO2 flux are expressed by color changes. In this way, we unite spatial and temporal characteristics of satellite data through visualization. A GPU-based direct volume rendering technique using half-angle slicing is adopted to dynamically visualize the released or absorbed CO2 gas with shadow effects. A data model is designed to generate four-dimensional (4D) data from satellite-derived air-sea CO2 flux products, and an out-of-core scheduling strategy is also proposed for on-the-fly rendering of time series of satellite data. The presented 4D visualization method is implemented on graphics cards with vertex, geometry and fragment shaders. It provides a visually realistic simulation and user interaction for real-time rendering. This approach has been integrated into the Information System of Ocean Satellite Monitoring for Air-sea CO2 Flux (IssCO2) for the research and assessment of air-sea CO2 flux in the China Seas.

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

    NASA Astrophysics Data System (ADS)

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

    2009-08-01

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

  13. User requirements for geo-collaborative work with spatio-temporal data in a web-based virtual globe environment.

    PubMed

    Yovcheva, Zornitza; van Elzakker, Corné P J M; Köbben, Barend

    2013-11-01

    Web-based tools developed in the last couple of years offer unique opportunities to effectively support scientists in their effort to collaborate. Communication among environmental researchers often involves not only work with geographical (spatial), but also with temporal data and information. Literature still provides limited documentation when it comes to user requirements for effective geo-collaborative work with spatio-temporal data. To start filling this gap, our study adopted a User-Centered Design approach and first explored the user requirements of environmental researchers working on distributed research projects for collaborative dissemination, exchange and work with spatio-temporal data. Our results show that system design will be mainly influenced by the nature and type of data users work with. From the end-users' perspective, optimal conversion of huge files of spatio-temporal data for further dissemination, accuracy of conversion, organization of content and security have a key role for effective geo-collaboration. PMID:23164199

  14. Spatio-temporal modeling and optimization of a deformable-grating compressor for short high-energy laser pulses.

    PubMed

    Qiao, J; Papa, J; Liu, X

    2015-10-01

    Monolithic large-scale diffraction gratings are desired to improve the performance of high-energy laser systems and scale them to higher energy, but the surface deformation of these diffraction gratings induce spatio-temporal coupling that is detrimental to the focusability and compressibility of the output pulse. A new deformable-grating-based pulse compressor architecture with optimized actuator positions has been designed to correct the spatial and temporal aberrations induced by grating wavefront errors. An integrated optical model has been built to analyze the effect of grating wavefront errors on the spatio-temporal performance of a compressor based on four deformable gratings. A 1.5-meter deformable grating has been optimized using an integrated finite-element-analysis and genetic-optimization model, leading to spatio-temporal performance similar to the baseline design with ideal gratings. PMID:26480107

  15. Spatio-Temporal Distribution Characteristics and Trajectory Similarity Analysis of Tuberculosis in Beijing, China.

    PubMed

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-03-01

    Tuberculosis (TB) is an infectious disease with one of the highest reported incidences in China. The detection of the spatio-temporal distribution characteristics of TB is indicative of its prevention and control conditions. Trajectory similarity analysis detects variations and loopholes in prevention and provides urban public health officials and related decision makers more information for the allocation of public health resources and the formulation of prioritized health-related policies. This study analysed the spatio-temporal distribution characteristics of TB from 2009 to 2014 by utilizing spatial statistics, spatial autocorrelation analysis, and space-time scan statistics. Spatial statistics measured the TB incidence rate (TB patients per 100,000 residents) at the district level to determine its spatio-temporal distribution and to identify characteristics of change. Spatial autocorrelation analysis was used to detect global and local spatial autocorrelations across the study area. Purely spatial, purely temporal and space-time scan statistics were used to identify purely spatial, purely temporal and spatio-temporal clusters of TB at the district level. The other objective of this study was to compare the trajectory similarities between the incidence rates of TB and new smear-positive (NSP) TB patients in the resident population (NSPRP)/new smear-positive TB patients in the TB patient population (NSPTBP)/retreated smear-positive (RSP) TB patients in the resident population (RSPRP)/retreated smear-positive TB patients in the TB patient population (RSPTBP) to detect variations and loopholes in TB prevention and control among the districts in Beijing. The incidence rates in Beijing exhibited a gradual decrease from 2009 to 2014. Although global spatial autocorrelation was not detected overall across all of the districts of Beijing, individual districts did show evidence of local spatial autocorrelation: Chaoyang and Daxing were Low-Low districts over the six

  16. Spatio-Temporal Distribution Characteristics and Trajectory Similarity Analysis of Tuberculosis in Beijing, China

    PubMed Central

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-01-01

    Tuberculosis (TB) is an infectious disease with one of the highest reported incidences in China. The detection of the spatio-temporal distribution characteristics of TB is indicative of its prevention and control conditions. Trajectory similarity analysis detects variations and loopholes in prevention and provides urban public health officials and related decision makers more information for the allocation of public health resources and the formulation of prioritized health-related policies. This study analysed the spatio-temporal distribution characteristics of TB from 2009 to 2014 by utilizing spatial statistics, spatial autocorrelation analysis, and space-time scan statistics. Spatial statistics measured the TB incidence rate (TB patients per 100,000 residents) at the district level to determine its spatio-temporal distribution and to identify characteristics of change. Spatial autocorrelation analysis was used to detect global and local spatial autocorrelations across the study area. Purely spatial, purely temporal and space-time scan statistics were used to identify purely spatial, purely temporal and spatio-temporal clusters of TB at the district level. The other objective of this study was to compare the trajectory similarities between the incidence rates of TB and new smear-positive (NSP) TB patients in the resident population (NSPRP)/new smear-positive TB patients in the TB patient population (NSPTBP)/retreated smear-positive (RSP) TB patients in the resident population (RSPRP)/retreated smear-positive TB patients in the TB patient population (RSPTBP) to detect variations and loopholes in TB prevention and control among the districts in Beijing. The incidence rates in Beijing exhibited a gradual decrease from 2009 to 2014. Although global spatial autocorrelation was not detected overall across all of the districts of Beijing, individual districts did show evidence of local spatial autocorrelation: Chaoyang and Daxing were Low-Low districts over the six

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

    PubMed Central

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

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

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

    SciTech Connect

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

    2014-09-08

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

  20. Blind Source Separation For Ion Mobility Spectra

    NASA Astrophysics Data System (ADS)

    Marco, S.; Pomareda, V.; Pardo, A.; Kessler, M.; Goebel, J.; Mueller, G.

    2009-05-01

    Miniaturization is a powerful trend for smart chemical instrumentation in a diversity of applications. It is know that miniaturization in IMS leads to a degradation of the system characteristics. For the present work, we are interested in signal processing solutions to mitigate limitations introduced by limited drift tube length that basically involve a loss of chemical selectivity. While blind source separation techniques (BSS) are popular in other domains, their application for smart chemical instrumentation is limited. However, in some conditions, basically linearity, BSS may fully recover the concentration time evolution and the pure spectra with few underlying hypothesis. This is extremely helpful in conditions where non-expected chemical interferents may appear, or unwanted perturbations may pollute the spectra. SIMPLISMA has been advocated by Harrington et al. in several papers. However, more modern methods of BSS for bilinear decomposition with the restriction of positiveness have appeared in the last decade. In order to explore and compare the performances of those methods a series of experiments were performed.

  1. Blind Source Separation For Ion Mobility Spectra

    SciTech Connect

    Marco, S.; Pomareda, V.

    2009-05-23

    Miniaturization is a powerful trend for smart chemical instrumentation in a diversity of applications. It is know that miniaturization in IMS leads to a degradation of the system characteristics. For the present work, we are interested in signal processing solutions to mitigate limitations introduced by limited drift tube length that basically involve a loss of chemical selectivity. While blind source separation techniques (BSS) are popular in other domains, their application for smart chemical instrumentation is limited. However, in some conditions, basically linearity, BSS may fully recover the concentration time evolution and the pure spectra with few underlying hypothesis. This is extremely helpful in conditions where non-expected chemical interferents may appear, or unwanted perturbations may pollute the spectra. SIMPLISMA has been advocated by Harrington et al. in several papers. However, more modern methods of BSS for bilinear decomposition with the restriction of positiveness have appeared in the last decade. In order to explore and compare the performances of those methods a series of experiments were performed.

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

    PubMed Central

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

    2009-01-01

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

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

    SciTech Connect

    Gaffney, S; Smyth, P

    2001-01-10

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Fu, D.; Chen, B.

    2012-04-01

    Remote sensing has great potential for estimating gross primary production (GPP) without resorting to interpolation of many surface observations. Meanwhile, it can be applied to analyzing the variation of GPP at different ecosystems across a wide range of spatial, temporal, and spectral resolutions. However, the availability of input data for remote-sensing-based GPP models is the bottleneck. The input data of remote-sensing-based greenness and radiation (GR) model is more independent on climate or ground-based observations, and the result is promising. Previous work using this modeling approach only used coarse spatial resolution data (e.g. MODerate resolution Imaging Spectroradiometer, MODIS), the estimated spatio-temporal distributions of GPP with higher resolution remains unclear. To overcome this limitation, a modified image fusion method was developed based on Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (mESTARFM), producing images with high spatial and temporal resolutions based on Landsat Thematic Mapper (TM) / Enhanced TM Plus (ETM+) (high spatial resolution, low temporal resolution) and MODIS (low spatial resolution, high temporal resolution). Meanwhile, the Simple Analytical Footprint model on Eulerian coordinates (SAFE) model to estimate the flux tower's footprint, which will be helpful for GR model's calibration, and improve the accuracy of GPP estimate. In the study, twelve flux sites belonging to Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) were selected, covering grassland, forest, and wetland biomes. The remote sensing dataset acquired in this study for each site include MODIS reflectance product (MOD09A1, 500 m), Landsat TM /ETM+ (30 m), MODIS BRDF/ Albedo model parameter product (MCD43A1, 500 m), MODIS BRDF/ Albedo quality product (MCD43A2, 500 m). The steps are as follows:: (i) Landsat TM /ETM+ and MODIS data were used as mESTARFM inputs to produce reflectance datasets with high spatio-temporal

  6. A Customized Light Sheet Microscope to Measure Spatio-Temporal Protein Dynamics in Small Model Organisms

    PubMed Central

    Rieckher, Matthias; Kourmoulakis, Georgios; Tavernarakis, Nektarios; Ripoll, Jorge; Zacharakis, Giannis

    2015-01-01

    We describe a customizable and cost-effective light sheet microscopy (LSM) platform for rapid three-dimensional imaging of protein dynamics in small model organisms. The system is designed for high acquisition speeds and enables extended time-lapse in vivo experiments when using fluorescently labeled specimens. We demonstrate the capability of the setup to monitor gene expression and protein localization during ageing and upon starvation stress in longitudinal studies in individual or small groups of adult Caenorhabditis elegans nematodes. The system is equipped to readily perform fluorescence recovery after photobleaching (FRAP), which allows monitoring protein recovery and distribution under low photobleaching conditions. Our imaging platform is designed to easily switch between light sheet microscopy and optical projection tomography (OPT) modalities. The setup permits monitoring of spatio-temporal expression and localization of ageing biomarkers of subcellular size and can be conveniently adapted to image a wide range of small model organisms and tissue samples. PMID:26000610

  7. Multivariate testing of spatio-temporal consistence of daily precipitation records

    NASA Astrophysics Data System (ADS)

    Mächel, H.; Kapala, A.

    2013-06-01

    The project KLIDADIGI of the German Meteorological Service (DWD) systematically rescues historical daily climate data of Germany by keying and imaging. Up to now, daily nearly gap-free precipitation time series at 118 locations for the period 1901-2000 are collected and extended by digitalization of hand-written protocols. To screen the spatio-temporal consistence of these raw data, we apply principal component analysis (PCA) in S (spatial) mode for daily precipitation records as well as for indices such as the number of rainy days above a certain threshold, intensity and absolute daily maximum in monthly, seasonal or annual resolution. Results of this screening test indicate that the PCA is a useful tool for detection of questionable stations and data preprocessing for further quality control and homogenization.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    SciTech Connect

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

    1995-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Baumann, Peter

    2014-05-01

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

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

    PubMed

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

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  13. Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders.

    PubMed

    Wang, Xin; Pinto-Duarte, António; Behrens, M Margarita; Zhou, Xianjin; Sejnowski, Terrence J

    2015-01-01

    Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies. PMID:26459883

  14. Effects of Spatio-Temporal Aliasing on Out-the-Window Visual Systems

    NASA Technical Reports Server (NTRS)

    Sweet, Barbara T.; Stone, Leland S.; Liston, Dorion B.; Hebert, Tim M.

    2014-01-01

    Designers of out-the-window visual systems face a challenge when attempting to simulate the outside world as viewed from a cockpit. Many methodologies have been developed and adopted to aid in the depiction of particular scene features, or levels of static image detail. However, because aircraft move, it is necessary to also consider the quality of the motion in the simulated visual scene. When motion is introduced in the simulated visual scene, perceptual artifacts can become apparent. A particular artifact related to image motion, spatiotemporal aliasing, will be addressed. The causes of spatio-temporal aliasing will be discussed, and current knowledge regarding the impact of these artifacts on both motion perception and simulator task performance will be reviewed. Methods of reducing the impact of this artifact are also addressed

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

    SciTech Connect

    Dimitrijevic, D. R.; Maluckov, A. A.

    2010-01-21

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

  16. Shot boundary detection and label propagation for spatio-temporal video segmentation

    NASA Astrophysics Data System (ADS)

    Piramanayagam, Sankaranaryanan; Saber, Eli; Cahill, Nathan D.; Messinger, David

    2015-02-01

    This paper proposes a two stage algorithm for streaming video segmentation. In the first stage, shot boundaries are detected within a window of frames by comparing dissimilarity between 2-D segmentations of each frame. In the second stage, the 2-D segments are propagated across the window of frames in both spatial and temporal direction. The window is moved across the video to find all shot transitions and obtain spatio-temporal segments simultaneously. As opposed to techniques that operate on entire video, the proposed approach consumes significantly less memory and enables segmentation of lengthy videos. We tested our segmentation based shot detection method on the TRECVID 2007 video dataset and compared it with block-based technique. Cut detection results on the TRECVID 2007 dataset indicate that our algorithm has comparable results to the best of the block-based methods. The streaming video segmentation routine also achieves promising results on a challenging video segmentation benchmark database.

  17. Holographic frequency resolved optical gating for spatio-temporal characterization of ultrashort optical pulse

    NASA Astrophysics Data System (ADS)

    Mehta, Nikhil; Yang, Chuan; Xu, Yong; Liu, Zhiwen

    2014-09-01

    We introduce a novel method for characterizing the spatio-temporal evolution of ultrashort optical field by recording the spectral hologram of frequency resolved optical gating (FROG) trace. We show that FROG holography enables the measurement of phase (up to an overall constant) and group delay of the pulse which cannot be measured by conventional FROG method. To illustrate our method, we perform numerical simulation to generate holographic collinear FROG (cFROG) trace of a chirped optical pulse and retrieve its complex profile at multiple locations as it propagates through a hypothetical dispersive medium. Further, we experimentally demonstrate our method by retrieving a 67 fs pulse at three axial locations in the vicinity of focus of an objective lens and compute its group delay.

  18. Spatio-temporal processing of massive glottic images from high-speed videoendoscopy

    NASA Astrophysics Data System (ADS)

    Yan, Yuling; Izdebski, Krzysztof; Marriott, Emma

    2011-03-01

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

  19. Transition to Spatio-Temporal Chaos with Increasing Length in the Reaction-Diffusion System

    NASA Astrophysics Data System (ADS)

    Trail, Collin; Tomlin, Brett; Olsen, Thomas; Wiener, Richard J.

    2003-11-01

    Calculations based up the Reaction-Diffusion model (H. Riecke and H.-G. Paap, Europhys. Lett. 14), 1235 (1991).have proven to be suggestive for a wide variety of pattern forming systems, including Taylor-Couette flow with hourglass geometry(Richard J. Wiener et al), Phys. Rev. E 55, 5489 (1997).. Seeking insight to guide experimental investigations, we extend these calculations. Previous calculations indicated that in smaller systems, only temporal chaos, located in a small region, would be observed, while in longer systems instabilities would form over a wide region. Our simulations explore this transition from purely temporal chaos to spatio-temporal chaos as the length of the system is increased.

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

    PubMed Central

    Díez-Ajenjo, Maria Amparo; Capilla, Pascual

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Jing, Ha; He, Shoujie

    2015-02-01

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

  2. Spatio-temporal imaging of light transport in scattering media using white light illumination (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Badon, Amaury; Li, Dayan; Lerosey, Geoffroy; Boccara, Claude; Fink, Mathias; Aubry, Alexandre

    2016-03-01

    We recently showed how the correlations of a broadband and incoherent wave-field can directly yield the time-dependent Green's functions between scatterers of a complex medium [Badon et al., Phys. Rev. Lett., 2015]. In this study, we apply this approach to the imaging of optical transport properties in complex media. A parallel measurement of millions of Green's functions at the surface of several strongly scattering samples (ZnO, TiO2, Teflon tape) is performed. A statistical analysis of this Green's matrix allows to investigate locally the spatio-temporal evolution of the diffusive halo within the scattering sample. An image of diffusion tensor is then obtained. It allows to map quantitatively the local concentration of scatterers and their anisotropy within the scattering medium. The next step of this work is to test this approach on biological tissues and illustrate how it can provide an elegant and powerful alternative to diffuse optical imaging techniques.

  3. Spatio-temporal modelling of foot-and-mouth disease outbreaks.

    PubMed

    Malesios, C; Demiris, N; Kostoulas, P; Dadousis, K; Koutroumanidis, T; Abas, Z

    2016-09-01

    We present and analyse data collected during a severe epidemic of foot-and-mouth disease (FMD) that occurred between July and September 2000 in a region of northeastern Greece with strategic importance since it represents the southeastern border of Europe and Asia. We implement generic Bayesian methodology, which offers flexibility in the ability to fit several realistically complex models that simultaneously capture the presence of 'excess' zeros, the spatio-temporal dependence of the cases, assesses the impact of environmental noise and controls for multicollinearity issues. Our findings suggest that the epidemic was mostly driven by the size and the animal type of each farm as well as the distance between farms while environmental and other endemic factors were not important during this outbreak. Analyses of this kind may prove useful to informing decisions related to optimal control measures for potential future FMD outbreaks as well as other acute epidemics such as FMD. PMID:27150839

  4. Satellite Remote Sensing For Spatio-Temporal Changes Analysis Of Urban Surface Biogeophysical Parameters

    NASA Astrophysics Data System (ADS)

    Zoran, Maria

    2010-01-01

    Based on satellite imagery data, this research developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying spatio-temporal changes between 1989-2008 in Bucharest metropolitan area, Romania, and for examining the environmental impact of such changes on urban biogeophysical parameters. The changes over the years of surface biophysical parameters are examined in association with landcover/landuse changes to illustrate how these parameters respond to rapid urban expansion in Bucharest and surrounding region. For detailed landuse classifications in a digital form these properties were analyzed in a statistical way .This study attempts to provide environmental awareness to urban planners in future urban development. The land cover information, properly classified, can provide a spatially and temporally explicit view of societal and environmental attributes and can be an important complement to in-situ measurements. Also, this information provides a perspective for understanding factors potentially mediating the interactions between urbanisation and variations of environmental quality.

  5. Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

    PubMed

    Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

    2016-05-15

    To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. PMID:26775938

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

    SciTech Connect

    Jing, Ha; He, Shoujie

    2015-02-15

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Koss, Jordan; Coppersmith, Susan

    2000-03-01

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

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

    PubMed Central

    OuYang, Chuanzi; Liang, Zhidan; Li, Lingjun

    2014-01-01

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

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

    PubMed Central

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

    2015-01-01

    Here we report an ABA triblock copolymer that can express microscopic autonomous formation and break-up of aggregates under constant condition to generate macroscopic viscoelastic self-oscillation of the solution. The ABA triblock copolymer is designed to have hydrophilic B segment and self-oscillating A segment at the both sides by RAFT copolymerization. In the A segment, a metal catalyst of chemical oscillatory reaction, i.e., the Belousov-Zhabotinsky (BZ) reaction, is introduced as a chemomechanical transducer to change the aggregation state of the polymer depending on the redox states. Time-resolved DLS measurements of the ABA triblock copolymer confirm the presence of a transitional network structure of micelle aggregations in the reduced state and a unimer structure in the oxidized state. This autonomous oscillation of a well-designed triblock copolymer enables dynamic biomimetic softmaterials with spatio-temporal structure. PMID:26511660

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

    NASA Astrophysics Data System (ADS)

    Ito, Kentaro; Sumpter, David; Nakagaki, Toshiyuki

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

  12. Emergence of spatio-temporal dynamics from exact coherent solutions in pipe flow

    NASA Astrophysics Data System (ADS)

    Ritter, Paul; Mellibovsky, Fernando; Avila, Marc

    2016-08-01

    Turbulent-laminar patterns are ubiquitous near transition in wall-bounded shear flows. Despite recent progress in describing their dynamics in analogy to non-equilibrium phase transitions, there is no theory explaining their emergence. Dynamical-system approaches suggest that invariant solutions to the Navier–Stokes equations, such as traveling waves and relative periodic orbits in pipe flow, act as building blocks of the disordered dynamics. While recent studies have shown how transient chaos arises from such solutions, the ensuing dynamics lacks the strong fluctuations in size, shape and speed of the turbulent spots observed in experiments. We here show that chaotic spots with distinct dynamical and kinematic properties merge in phase space and give rise to the enhanced spatio-temporal patterns observed in pipe flow. This paves the way for a dynamical-system foundation to the phenomenology of turbulent-laminar patterns in wall-bounded extended shear flows.

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

    NASA Astrophysics Data System (ADS)

    Vasquez, R.; Bravo, L.

    2013-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

  15. A flood risk curve development for inundation disaster considering spatio-temporal rainfall distribution

    NASA Astrophysics Data System (ADS)

    Tanaka, T.; Tachikawa, Y.; Yorozu, K.

    2015-06-01

    To manage flood disaster with an exceeding designed level, flood risk control based on appropriate risk assessment is essential. To make an integrated economic risk assessment by flood disaster, a flood risk curve, which is a relation between flood inundation damage and its exceedance probability, plays an important role. This research purposes a method to develop a flood risk curve by utilizing a probability distribution function of annual maximum rainfall through rainfall-runoff and inundation simulations so that risk assessment can consider climate and socio-economic changes. Among a variety of uncertainties, the method proposed in this study considered spatio-temporal rainfall distributions that have high uncertainty for damage estimation. The method was applied to the Yura-gawa river basin (1882 km2) in Japan; and the annual economic benefit of an existing dam in the basin was successfully quantified by comparing flood risk curves with/without the dam.

  16. Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders

    PubMed Central

    Wang, Xin; Pinto-Duarte, António; Margarita Behrens, M.; Zhou, Xianjin; Sejnowski, Terrence J.

    2015-01-01

    Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies. PMID:26459883

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

    PubMed Central

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

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  18. Spatio-temporal dynamcis of a cell signal cascade with negative feedback

    NASA Astrophysics Data System (ADS)

    Maya Bernal, Jose Luis; Ramirez-Santiago, Guillermo

    2014-03-01

    We studied the spatio-temporal dynamics of a system of reactio-diffusion equations that models a cell signal transduction pathway with six cycles and negative feedback. The basic cycle consists of the phosphorylation-dephosphorylation of two antagonic proteins. We found two regimes of saturation of the enzimatic reaction in the kinetic parameters space and determined the conditions for the signal propagation in the steady state. The trajectories for which transduction occurs are defined in terms of the ratio of the enzimatic activities. We found that in spite of the negative feedback the cell signal cascade behaves as an amplifier and produces phosphoprotein concentration gradients within the cell. This model behaves also as a noise filter and as a switch. Supported by DGAPA-UNAM Contract IN118410-3.

  19. Automatic right ventricle (RV) segmentation by propagating a basal spatio-temporal characterization

    NASA Astrophysics Data System (ADS)

    Atehortúa, Angélica; Zuluaga, María. A.; Martínez, Fabio; Romero, Eduardo

    2015-12-01

    An accurate right ventricular (RV) function quantification is important to support the evaluation, diagnosis and prognosis of several cardiac pathologies and to complement the left ventricular function assessment. However, expert RV delineation is a time consuming task with high inter-and-intra observer variability. In this paper we present an automatic segmentation method of the RV in MR-cardiac sequences. Unlike atlas or multi-atlas methods, this approach estimates the RV using exclusively information from the sequence itself. For so doing, a spatio-temporal analysis segments the heart at the basal slice, segmentation that is then propagated to the apex by using a non-rigid-registration strategy. The proposed approach achieves an average Dice Score of 0:79 evaluated with a set of 48 patients.

  20. MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering.

    PubMed

    von Landesberger, Tatiana; Brodkorb, Felix; Roskosch, Philipp; Andrienko, Natalia; Andrienko, Gennady; Kerren, Andreas

    2016-01-01

    Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods. PMID:26529684

  1. Assessment of soil organic carbon distribution in Europe scale by spatio-temporal data and geostatistics

    NASA Astrophysics Data System (ADS)

    Aksoy, Ece; Panagos, Panos; Montanarella, Luca

    2013-04-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted using combination of LUCAS soil samples with local soil data and ten spatio-temporal predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, average temperature and precipitation) with Regression-Kriging method in Europe scale. Significant correlation between the covariates and the organic carbon dependent variable was found.

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

    PubMed

    Starzyk, Janusz A; He, Haibo

    2009-05-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Sen, Satyabrata; Barhen, Jacob

    2015-05-01

    We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of- freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully-adaptive OFDM-STAP, we propose a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain, as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we propose to optimally design the transmit OFDM signals by maximizing the output signal- to-interference-plus-noise ratio (SINR) in order to improve the STAP-performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity- based technique and adaptive waveform design.

  5. Urban green spatio- temporal changes assessment through time-series satellite data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

    2015-10-01

    Understanding spatio-temporal changes of urban environments is essential for regional and local planning and environmental management. With the rapid changes of Bucharest city in Romania during past decades, green spaces have been fragmented and dispersed causing impairment and dysfunction of these urban elements. The main goal of this study is to address these tasks in synergy with in-situ data and new analytical methods. Spatio- temporal monitoring of urban vegetation land cover changes is important for policy decisions, regulatory actions and subsequent land use activities. This study explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Land Surface Temperature (LST) and evapotranspiration (ET) data to provide vegetation change detection information for metropolitan area of Bucharest. Training and validation are based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2002- 2014 was assessed to be of 87%, with a reasonable balance between change commission errors (20.24%), change omission errors (25.65%), and Kappa coefficient of 0.72. Annual change detection rates across the urban/periurban areas over the study period (2002-2014) were estimated at 0.79% per annum in the range of 0.46% (2002) to 0.77% (2014).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system. Extracted green space areas were further analyzed quantitatively in relation with air quality data and extreme climate events. The results have been analyzed in terms of environmental impacts and future climate trends.

  6. Spatio-Temporal Variability of Aquatic Vegetation in Taihu Lake over the Past 30 Years

    PubMed Central

    Zhao, Dehua; Lv, Meiting; Jiang, Hao; Cai, Ying; Xu, Delin; An, Shuqing

    2013-01-01

    It is often difficult to track the spatio-temporal variability of vegetation distribution in lakes because of the technological limitations associated with mapping using traditional field surveys as well as the lack of a unified field survey protocol. Using a series of Landsat remote sensing images (i.e. MSS, TM and ETM+), we mapped the composition and distribution area of emergent, floating-leaf and submerged macrophytes in Taihu Lake, China, at approximate five-year intervals over the past 30 years in order to quantify the spatio-temporal dynamics of the aquatic vegetation. Our results indicated that the total area of aquatic vegetation increased from 187.5 km2 in 1981 to 485.0 km2 in 2005 and then suddenly decreased to 341.3 km2 in 2010. Similarly, submerged vegetation increased from 127.0 km2 in 1981 to 366.5 km2 in 2005, and then decreased to 163.3 km2. Floating-leaf vegetation increased continuously through the study period in both area occupied (12.9 km2 in 1981 to 146.2 km2 in 2010) and percentage of the total vegetation (6.88% in 1981 to 42.8% in 2010). In terms of spatial distribution, the aquatic vegetation in Taihu Lake has spread gradually from the East Bay to the surrounding areas. The proportion of vegetation in the East Bay relative to that in the entire lake has decreased continuously from 62.3% in 1981, to 31.1% in 2005 and then to 21.8% in 2010. Our findings have suggested that drastic changes have taken place over the past 30 years in the spatial pattern of aquatic vegetation as well as both its relative composition and the amount of area it occupies. PMID:23823189

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

    PubMed

    Humble, James; Denham, Susan; Wennekers, Thomas

    2012-01-01

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

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

    PubMed

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

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Hassler, Sibylle; Weiler, Markus; Blume, Theresa

    2014-05-01

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

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-11-01

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

  12. Spatio-Temporal Canopy Complexity and Leaf Acclimation to Variable Canopy Microhabitats.

    NASA Astrophysics Data System (ADS)

    Fotis, A. T.

    2014-12-01

    The theory that forests become carbon (C) neutral with maturity has recently been challenged. While a growing body of evidence shows that net C accumulation continues in forests that are centuries old, the reasons remain poorly known. Increasing canopy structural complexity, quantified by high variability in leaf distribution, has been proposed as a mechanism for sustained rates of C assimilation in mature forests. The goal of our research was to expand on these findings and explore a new idea of spatio-temporal canopy structural complexity as a mechanism linking canopy structure to function (C assimilation).Our work takes place at the UMBS AmeriFlux core facility (US-UMB) in northern Michigan, USA. Canopy structure was quantified over 6 seasons with portable canopy LiDAR (PCL) and canopy spatial microhabitat variability was studied using hemispherical photographs from different heights within the canopy. We found a more even distribution of irradiance in more structurally complex canopies within a single year, and furthermore, that between-year variability of spatial leaf arrangement decreased with increasing canopy complexity. We suggest that in complex canopies less redistribution of leaf material over time may lead to more similar light microhabitats within and among years. Conversely, in less complex canopies this relationship can lead to a year-to-year time lag in morphological leaf acclimation since the effects of the previous-year's light environment are reflected in the morphological characteristics of current-year leaves.Our study harnesses unique spatio-temporal resolution measurements of canopy structure and microhabitat that can inform better management strategies seeking to maximize forest C uptake. Future research quantifying the relationship between canopy structure and light distribution will improve performance of ecosystem models that currently lack spatially explicit canopy structure information.

  13. Characterization and application of simultaneously spatio-temporally focused ultrafast laser pulses

    NASA Astrophysics Data System (ADS)

    Greco, Michael J.

    Chirped pulse amplication of ultrafast laser pulses has become an essential technology in the elds of micromachining, tissue ablation, and microscopy. With specically tailored pulses of light we have been able to begin investigation into lab-on-a-chip technology, which has the potential of revolutionizing the medical industry. Advances in microscopy have allowed sub diraction limited resolution to become a reality as well as lensless imaging of single molecules. An intimate knowledge of ultrafast optical pulses, the ability to manipulate an optical spectrum and generate an optical pulse of a specic temporal shape, allows us to continue pushing these elds forward as well as open new ones. This thesis investigates the spatio-temporal construction of pulses which are simultaneously spatio-temporally focused (SSTF) and about their current and future applications. By laterally chirping a compressed laser pulse we have conned the peak intensity to a shorter distance along the optical axis than can be achieved by conventional methods. This also brings about interesting changes to the structure of the pulse intensity such as pulse front tilt (PFT), an eect where the pulse energy is delayed across the focal spot at the focal plane by longer durations than the pulse itself. Though these pulses have found utility in microscopy and micromachining, in-situ methods for characterizing them spatially and temporally are not yet wide spread. I present here an in-situ characterization technique for both spatial and temporal diagnosis of SSTF pulses. By performing a knife-edge scan and collecting the light in a spectrometer, the relative spectral position as well as beam size can be deduced. Temporal characterization is done by dispersion scan, where a second harmonic crystal through the beam focus. Combining the unknown phase of the pulse with the known phase (a result of angular dispersion) allows the unknown phase to be extracted from the second harmonic spectra.

  14. Spatio-Temporal Variability of Aquatic Vegetation in Taihu Lake over the Past 30 Years.

    PubMed

    Zhao, Dehua; Lv, Meiting; Jiang, Hao; Cai, Ying; Xu, Delin; An, Shuqing

    2013-01-01

    It is often difficult to track the spatio-temporal variability of vegetation distribution in lakes because of the technological limitations associated with mapping using traditional field surveys as well as the lack of a unified field survey protocol. Using a series of Landsat remote sensing images (i.e. MSS, TM and ETM+), we mapped the composition and distribution area of emergent, floating-leaf and submerged macrophytes in Taihu Lake, China, at approximate five-year intervals over the past 30 years in order to quantify the spatio-temporal dynamics of the aquatic vegetation. Our results indicated that the total area of aquatic vegetation increased from 187.5 km(2) in 1981 to 485.0 km(2) in 2005 and then suddenly decreased to 341.3 km(2) in 2010. Similarly, submerged vegetation increased from 127.0 km(2) in 1981 to 366.5 km(2) in 2005, and then decreased to 163.3 km(2). Floating-leaf vegetation increased continuously through the study period in both area occupied (12.9 km(2) in 1981 to 146.2 km(2) in 2010) and percentage of the total vegetation (6.88% in 1981 to 42.8% in 2010). In terms of spatial distribution, the aquatic vegetation in Taihu Lake has spread gradually from the East Bay to the surrounding areas. The proportion of vegetation in the East Bay relative to that in the entire lake has decreased continuously from 62.3% in 1981, to 31.1% in 2005 and then to 21.8% in 2010. Our findings have suggested that drastic changes have taken place over the past 30 years in the spatial pattern of aquatic vegetation as well as both its relative composition and the amount of area it occupies. PMID:23823189

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

    PubMed

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

    2016-10-15

    Understanding of the distribution patterns of sediment erosion, concentration and transport in river basins is critically important as sediment plays a major role in river basin hydrophysical and ecological processes. In this study, we proposed an integrated framework for the assessment of sediment dynamics, including soil erosion (SE), suspended sediment load (SSL) and suspended sediment concentration (SSC), and applied this framework to the Mekong River Basin. The Revised Universal Soil Loss Equation (RUSLE) model was adopted with a geographic information system to assess SE and was coupled with a sediment accumulation and a routing scheme to simulate SSL. This framework also analyzed Landsat imagery captured between 1987 and 2000 together with ground observations to interpolate spatio-temporal patterns of SSC. The simulated SSL results from 1987 to 2000 showed the relative root mean square error of 41% and coefficient of determination (R(2)) of 0.89. The polynomial relationship of the near infrared exoatmospheric reflectance and the band 4 wavelength (760-900nm) to the observed SSC at 9 sites demonstrated the good agreement (overall relative RMSE=5.2%, R(2)=0.87). The result found that the severe SE occurs in the upper (China and Lao PDR) and lower (western part of Vietnam) regions. The SSC in the rainy season (June-November) showed increasing and decreasing trends longitudinally in the upper (China and Lao PDR) and lower regions (Cambodia), respectively, while the longitudinal profile of SSL showed a fluctuating trend along the river in the early rainy season. Overall, the results described the unique spatio-temporal patterns of SE, SSL and SSC in the Mekong River Basin. Thus, the proposed integrated framework is useful for elucidating complex process of sediment generation and transport in the land and river systems of large river basins. PMID:27338846

  16. Spatio-temporal analysis techniques for detailed investigations of space storm dynamics

    NASA Astrophysics Data System (ADS)

    Vassiliadis, D.; Daglis, I. A.; Klimas, A. J.; Clauer, C. R.

    2001-09-01

    We present several spatio-temporal analysis techniques, which integrate mid-latitude ground magnetogram data and are useful in identifying key features in the ring current response. In this way we can quantify a) the intensity and spatial extent of inner magnetosphere convection, b) the intensity of the geomagnetic response to interplanetary pressure pulses, c) the penetration of the substorm current wedge to lower latitudes and d) the effect of particle injections on the ring current. The first technique creates a spatio-temporal storm "portrait" based on the axial component of the ground magnetic field H(UT;LT) [Clauer and McPherron, 1974]. Displaying the field data in UT-LT coordinates allows comparison of the activity in the inner magnetosphere. In addition to visual identification of the above features, we introduce a second technique that uses principal component analysis (PCA) of the storm portrait. PCA peaks correspond, in order of decreasing eigenvalue, to symmetric ring current, asymmetric ring current and substorm current wedge, and injections into the ring current, typically during substorms. Identification of the major PCA peaks with large-scale current systems is confirmed by correlation with and timing relative to geomagnetic indices (Dst, AL, etc). The intensity and direction of ring current injections is estimated by a bandpass filter technique for individual magnetograms. Examples using the storms of June 4, 1991, and September 26, 1998, are given. In these cases the asymmetric ring current can have a geomagnetic effect as strong as the azimuthally symmetric part meaning the majority of plasma sheet particles convecting deep into the inner magnetosphere are quickly (~2-3 hours) lost at the dayside magnetopause. On the other hand, the estimate for particle injections compared to slow convection reaches up to 30% in terms of the average geomagnetic field amplitude. Thus, individual substorms can have a significant influence on the storm-time ring

  17. Spatio-Temporal Simulation of First Pass Drug Perfusion in the Liver

    PubMed Central

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

    2014-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  19. An Ethnographic Case Study of Spatio-Temporal Practices Circulating On- and Off-Line in a Distance Learning Class

    ERIC Educational Resources Information Center

    Kabat-Ryan, Katalin Judith

    2013-01-01

    This dissertation examines the spatio-temporal practices of a distance learning class in a graduate institution in the Northeast United States. Guided by a multispatial and temporal perspective, the case study builds on Hine's (2003) and Leander and McKim's (2003) connective ethnography of offline and online research sites, and frames the research…

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

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

    PubMed Central

    Farnsworth, Matthew L.; Ward, Michael P.

    2009-01-01

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

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

    SciTech Connect

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

    2010-01-01

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

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

    PubMed Central

    Marinkovic, Ksenija; Courtney, Maureen G.; Witzel, Thomas; Dale, Anders M.; Halgren, Eric

    2014-01-01

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

  4. The spatio-temporal domains of Frizzled6 action in planar polarity control of hair follicle orientation.

    PubMed

    Chang, Hao; Smallwood, Philip M; Williams, John; Nathans, Jeremy

    2016-01-01

    In mammals, hair follicles cover most of the body surface and exhibit precise and stereotyped orientations relative to the body axes. Follicle orientation is controlled by the planar cell polarity (PCP; or, more generally, tissue polarity) system, as determined by the follicle mis-orientation phenotypes observed in mice with PCP gene mutations. The present study uses conditional knockout alleles of the PCP genes Frizzled6 (Fz6), Vangl1, and Vangl2, together with a series of Cre drivers to interrogate the spatio-temporal domains of PCP gene action in the developing mouse epidermis required for follicle orientation. Fz6 is required starting between embryonic day (E)11.5 and E12.5. Eliminating Fz6 in either the anterior or the posterior halves of the embryo or in either the feet or the torso leads to follicle mis-orientation phenotypes that are limited to the territories associated with Fz6 loss, implying either that PCP signaling is required for communicating polarity information on a local but not a global scale, or that there are multiple independent sources of global polarity information. Eliminating Fz6 in most hair follicle cells or in the inter-follicular epidermis at E15.5 suggests that PCP signaling in developing follicles is not required to maintain their orientation. The asymmetric arrangement of Merkel cells around the base of each guard hair follicle dependents on Fz6 expression in the epidermis but not in differentiating Merkel cells. These experiments constrain current models of PCP signaling and the flow of polarity information in mammalian skin. PMID:26517967

  5. Correlation of Spatio-Temporal Contaminant Distribution, Land Use, and Hydrogeological Factors in the Karst Aquifers of Northern Puerto Rico

    NASA Astrophysics Data System (ADS)

    Torres Torres, N. I.; Padilla, I. Y.

    2015-12-01

    Karst aquifers are characterized by caves, springs, and sinkholes, and typified by interconnected fissures, fractures and conduits. These characteristics make these aquifers highly productive, and vulnerable to contamination. Previous studies in the northern karst aquifers of Puerto Rico have shown significant distribution of contaminants, including volatile organic compounds, phthalates and other contaminants of emerging concern, beyond demarked sources of contamination. This study develops spatial-temporal distributions of phthalate contaminants in the karst system of northern Puerto Rico and assesses statistical correlations between hydrogeologic factors and groundwater contamination with phthalates. Geographic Information Systems (GIS) tools and technologies, and statistical models are applied to attain these objectives. Results show that there is an extensive contamination with phthalates that varies with time. Contamination is present in the confined and shallow aquifers. Di-(2-ethylhexyl) phthalate (DEHP) is the most detected contaminant (20.6% of the sites). Diethyl phthalate and and dibutyl phthalate are also detected in 6.7% and 8.24% of the sites, respectively. Phthalates detected as mixtures components are significantly detected in areas of high urban and industrial development. They are also detected in areas within 5 miles of superfund sites and landfills. The results indicate that phthalate contamination is highly related to land use. Statistical models show that the hydraulic conductivity of the aquifers, sinkholes density, and time are significantly related to the presence of phthalates in groundwater. The extensive spatio-temporal contamination suggests that contaminants can persist in the environment for long periods of time, and that land use and hydrogeological factors are important factors contributing to the presence of emerging contaminants in karst systems.

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

    PubMed

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

    2016-06-01

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

  7. Characterizing and explaining spatio-temporal variation of water quality in a highly disturbed river by multi-statistical techniques.

    PubMed

    Liu, Jianfeng; Zhang, Xiang; Xia, Jun; Wu, Shaofei; She, Dunxian; Zou, Lei

    2016-01-01

    Assessing the spatio-temporal variations of surface water quality is important for water environment management. In this study, surface water samples are collected from 2008 to 2015 at 17 stations in the Ying River basin in China. The two pollutants i.e. chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) are analyzed to characterize the river water quality. Cluster analysis and the seasonal Kendall test are used to detect the seasonal and inter-annual variations in the dataset, while the Moran's index is utilized to understand the spatial autocorrelation of the variables. The influence of natural factors such as hydrological regime, water temperature and etc., and anthropogenic activities with respect to land use and pollutant load are considered as driving factors to understand the water quality evolution. The results of cluster analysis present three groups according to the similarity in seasonal pattern of water quality. The trend analysis indicates an improvement in water quality during the dry seasons at most of the stations. Further, the spatial autocorrelation of water quality shows great difference between the dry and wet seasons due to sluices and dams regulation and local nonpoint source pollution. The seasonal variation in water quality is found associated with the climatic factors (hydrological and biochemical processes) and flow regulation. The analysis of land use indicates a good explanation for spatial distribution and seasonality of COD at the sub-catchment scale. Our results suggest that an integrated water quality measures including city sewage treatment, agricultural diffuse pollution control as well as joint scientific operations of river projects is needed for an effective water quality management in the Ying River basin. PMID:27512630

  8. Spatio-temporal hazard estimation in the Auckland Volcanic Field, New Zealand, with a new event-order model

    NASA Astrophysics Data System (ADS)

    Bebbington, Mark S.; Cronin, Shane J.

    2011-01-01

    The Auckland Volcanic Field (AVF) with 49 eruptive centres in the last c. 250 ka presents many challenges to our understanding of distributed volcanic field construction and evolution. We re-examine the age constraints within the AVF and perform a correlation exercise matching the well-dated record of tephras from cores distributed throughout the field to the most likely source volcanoes, using thickness and location information and a simple attenuation model. Combining this augmented age information with known stratigraphic constraints, we produce a new age-order algorithm for the field, with errors incorporated using a Monte Carlo procedure. Analysis of the new age model discounts earlier appreciations of spatio-temporal clustering in the AVF. Instead the spatial and temporal aspects appear independent; hence the location of the last eruption provides no information about the next location. The temporal hazard intensity in the field has been highly variable, with over 63% of its centres formed in a high-intensity period between 40 and 20 ka. Another, smaller, high-intensity period may have occurred at the field onset, while the latest event, at 504 ± 5 years B.P., erupted 50% of the entire field's volume. This emphasises the lack of steady-state behaviour that characterises the AVF, which may also be the case in longer-lived fields with a lower dating resolution. Spatial hazard intensity in the AVF under the new age model shows a strong NE-SW structural control of volcanism that may reflect deep-seated crustal or subduction zone processes and matches the orientation of the Taupo Volcanic Zone to the south.

  9. Spatio-temporal characteristics of livestock and their effects on pollution in China based on geographic information system.

    PubMed

    Liu, Ruimin; Xu, Fei; Liu, Yongyan; Wang, Jiawei; Yu, Wenwen

    2016-07-01

    Livestock pollution, caused by rural household's scatter breeding mainly, is one of the major non-point sources. Different animal manures are abundant with different nutrients. Adopting the policies, management practices, and technologies related to livestock production based on livestock structure analysis can improve the efficiency on preventing pollution. Based on statistical data, the component structure of livestock was analyzed and corresponding effect on pollution was evaluated during the period of 1992-2012 in China. The results showed that the average annual growth rate (AAGR) of total China was 1.58 % during the 20 years. Larger amounts of livestock were concentrated in Southwest China and East China. In the view of component structure, each type of livestock had different distribution characteristics and constant increasing amounts were presented during the 20 years. Cattle took the largest proportion in almost every province, and the number of heads was over 40 % of all the livestock quantity for most provinces. Pollution of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) caused by livestock excretion in East and Southeast China was much more serious than that in other regions. However, the load of COD was far less than that of TN and TP. Cattle accounted most for the livestock pollution, and swine was the second one. The intensity characteristics of TN, TP, and COD were different from that of total pollution loads. The spatio-temporal characteristics of amounts and component structure of livestock were influenced by three kinds of factors (natural, economic, and social), such as climate, topography, modes of production, feed grain sector, related policies, and area of the study regions. Different livestock excrements had different impacts on environment. According to various livestock structures and economy conditions, different disposal methods should be adopted. PMID:27053044

  10. Spatio-temporal variability of airborne bacterial communities and their correlation with particulate matter chemical composition across two urban areas.

    PubMed

    Gandolfi, I; Bertolini, V; Bestetti, G; Ambrosini, R; Innocente, E; Rampazzo, G; Papacchini, M; Franzetti, A

    2015-06-01

    The study of spatio-temporal variability of airborne bacterial communities has recently gained importance due to the evidence that airborne bacteria are involved in atmospheric processes and can affect human health. In this work, we described the structure of airborne microbial communities in two urban areas (Milan and Venice, Northern Italy) through the sequencing, by the Illumina platform, of libraries containing the V5-V6 hypervariable regions of the 16S rRNA gene and estimated the abundance of airborne bacteria with quantitative PCR (qPCR). Airborne microbial communities were dominated by few taxa, particularly Burkholderiales and Actinomycetales, more abundant in colder seasons, and Chloroplasts, more abundant in warmer seasons. By partitioning the variation in bacterial community structure, we could assess that environmental and meteorological conditions, including variability between cities and seasons, were the major determinants of the observed variation in bacterial community structure, while chemical composition of atmospheric particulate matter (PM) had a minor contribution. Particularly, Ba, SO4 (2-) and Mg(2+) concentrations were significantly correlated with microbial community structure, but it was not possible to assess whether they simply co-varied with seasonal shifts of bacterial inputs to the atmosphere, or their variation favoured specific taxa. Both local sources of bacteria and atmospheric dispersal were involved in the assembling of airborne microbial communities, as suggested, to the one side by the large abundance of bacteria typical of lagoon environments (Rhodobacterales) observed in spring air samples from Venice and to the other by the significant effect of wind speed in shaping airborne bacterial communities at all sites. PMID:25592734

  11. [Spatio-temporal pattern of larvae and eggs of gastrointestinal nematodes in cattle pastures in Veracruz, Mexico].

    PubMed

    Flota-Bañuelos, Carolina; Martínez, Imelda; López-Collado, José; Vargas Mendoza, Mónica; González Hernández, Hector; Fajersson, Pernilla

    2013-12-01

    The spatial and temporal distribution of gastrointestinal nematodes of cattle has been little studied in Mexico. Previous studies have described periods of higher larval presence, vertical and horizontal migration in grasslands, and the frequency of adult nematodes; as well as the effect of pasture trichomes on the migration and survival of Haemonchus larvae. The aim of this study was to determine the time-space layout and spread of gastrointestinal nematode larvae on pasture, and to estimate the effect of ivermectin applied to cattle on the time-dependent abundance of their eggs in a ranch in Veracruz. To determine the spatio-temporal arrangement, monthly morning grass samples were obtained from 30 sampling points from July 2008 to June 2009. Third stage larvae (L3) from each point were counted, and aggregation patterns were estimated through variance/mean and negative binomial K indices. Additionally, the number of eggs per gram in cattle feces was determined, from samples with (CI) and without ivermectin (SI), using standard techniques. A total of 20 276 L(3) larvae were recovered in the pasture, of which an 80% corresponded to Haemonchus contortus. The highest nematode density with more than 5 000L(3)/kgDM was detected in October 2008, and the lowest in February and March 2009. The L3 showed an aggregated spatial pattern of varying intensity throughout the year. The number of eggs in the stool was not reduced with the ivermectin application to cattle, which suggested a failure of control. However, the highest parasite loads were observed from July to November 2008. We concluded that the application of ivermectin was not effective to control nematodes eggs, and that L3 populations fluctuated on pasture for ten months, providing an infection source to grazing animals afterwards. PMID:24432531

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

    NASA Astrophysics Data System (ADS)

    Chemin, Yann

    2013-04-01

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

  13. Assessing site-specific spatio-temporal variations in hydrogen and oxygen stable isotopes of human drinking water

    NASA Astrophysics Data System (ADS)

    Kennedy, C. D.; Bowen, G. J.; Ehleringer, J. R.

    2008-12-01

    Stable isotope ratios of hydrogen and oxygen (δ2H and δ18O) are environmental forensic tracers that can be used to constrain the origin and movement of animals, people, and products. The fundamental assumption underlying this method is that water resources at different geographic locations have distinct and characteristic isotopic signatures that are assimilated into organic tissues. Although much is known about regional-scale spatio-temporal variability in δ2H and δ18O of water, few studies have addressed the question of how distinct these geographic and seasonal patterns are for any given site. To address this question, a 2-year survey of δ2H and δ18O in tap water from across the contiguous U.S. and Canada was conducted. The data show that seasonal variability in δ2H and δ18O of tap water is generally low (<10 ‰ for δ2H), and those with the highest variability can be classified as: a) cities or towns in areas of high climate seasonality, or b) large cities in arid or seasonally arid regions which access and switch among multiple water sources throughout the year. The data suggest that inter-annual variation in tap water isotope ratios is typically low, with a median difference for month-month pairs during the 2 sampling years of 2.7 (δ2H). The results from this study confirm the existence of temporal variability in δ2H and δ18O of tap water, but suggest that this variability in human-managed systems is highly damped and may be amenable to classification, modeling, and prediction. In all, the data provide the foundation for incorporating temporal variation in predictive models of water and organic δ2H and δ18O, leading to more robust and statistically defensible tests of geographic origin.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  15. Interactions between Inhibitory Interneurons and Excitatory Associational Circuitry in Determining Spatio-Temporal Dynamics of Hippocampal Dentate Granule Cells: A Large-Scale Computational Study

    PubMed Central

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

    2015-01-01

    This paper reports on findings from a million-cell granule cell model of the rat dentate gyrus that was used to explore the contributions of local interneuronal and associational circuits to network-level activity. The model contains experimentally derived morphological parameters for granule cells, which each contain approximately 200 compartments, and biophysical parameters for granule cells, basket cells, and mossy cells that were based both on electrophysiological data and previously published models. Synaptic input to cells in the model consisted of glutamatergic AMPA-like EPSPs and GABAergic-like IPSPs from excitatory and inhibitory neurons, respectively. The main source of input to the model was from layer II entorhinal cortical neurons. Network connectivity was constrained by the topography of the system, and was derived from axonal transport studies, which provided details about the spatial spread of axonal terminal fields, as well as how subregions of the medial and lateral entorhinal cortices project to subregions of the dentate gyrus. Results of this study show that strong feedback inhibition from the basket cell population can cause high-frequency rhythmicity in granule cells, while the strength of feedforward inhibition serves to scale the total amount of granule cell activity. Results furthermore show that the topography of local interneuronal circuits can have just as strong an impact on the development of spatio-temporal clusters in the granule cell population as the perforant path topography does, both sharpening existing clusters and introducing new ones with a greater spatial extent. Finally, results show that the interactions between the inhibitory and associational loops can cause high frequency oscillations that are modulated by a low-frequency oscillatory signal. These results serve to further illustrate the importance of topographical constraints on a global signal processing feature of a neural network, while also illustrating how rich

  16. Optimizing Spatio-Temporal Sampling Designs of Synchronous, Static, or Clustered Measurements

    NASA Astrophysics Data System (ADS)

    Helle, Kristina; Pebesma, Edzer

    2010-05-01

    When sampling spatio-temporal random variables, the cost of a measurement may differ according to the setup of the whole sampling design: static measurements, i.e. repeated measurements at the same location, synchronous measurements or clustered measurements may be cheaper per measurement than completely individual sampling. Such "grouped" measurements may however not be as good as individually chosen ones because of redundancy. Often, the overall cost rather than the total number of measurements is fixed. A sampling design with grouped measurements may allow for a larger number of measurements thus outweighing the drawback of redundancy. The focus of this paper is to include the tradeoff between the number of measurements and the freedom of their location in sampling design optimisation. For simple cases, optimal sampling designs may be fully determined. To predict e.g. the mean over a spatio-temporal field having known covariance, the optimal sampling design often is a grid with density determined by the sampling costs [1, Ch. 15]. For arbitrary objective functions sampling designs can be optimised relocating single measurements, e.g. by Spatial Simulated Annealing [2]. However, this does not allow to take advantage of lower costs when using grouped measurements. We introduce a heuristic that optimises an arbitrary objective function of sampling designs, including static, synchronous, or clustered measurements, to obtain better results at a given sampling budget. Given the cost for a measurement, either within a group or individually, the algorithm first computes affordable sampling design configurations. The number of individual measurements as well as kind and number of grouped measurements are determined. Random locations and dates are assigned to the measurements. Spatial Simulated Annealing is used on each of these initial sampling designs (in parallel) to improve them. In grouped measurements either the whole group is moved or single measurements within the

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Bahr, Thomas

    2016-04-01

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

  20. Simulating Future Changes in Spatio-temporal Precipitation by Identifying and Characterizing Individual Rainstorm Events

    NASA Astrophysics Data System (ADS)

    Chang, W.; Stein, M.; Wang, J.; Kotamarthi, V. R.; Moyer, E. J.

    2015-12-01

    A growing body of literature suggests that human-induced climate change may cause significant changes in precipitation patterns, which could in turn influence future flood levels and frequencies and water supply and management practices. Although climate models produce full three-dimensional simulations of precipitation, analyses of model precipitation have focused either on time-averaged distributions or on individual timeseries with no spatial information. We describe here a new approach based on identifying and characterizing individual rainstorms in either data or model output. Our approach enables us to readily characterize important spatio-temporal aspects of rainstorms including initiation location, intensity (mean and patterns), spatial extent, duration, and trajectory. We apply this technique to high-resolution precipitation over the continental U.S. both from radar-based observations (NCEP Stage IV QPE product, 1-hourly, 4 km spatial resolution) and from model runs with dynamical downscaling (WRF regional climate model, 3-hourly, 12 km spatial resolution). In the model studies we investigate the changes in storm characteristics under a business-as-usual warming scenario to 2100 (RCP 8.5). We find that in these model runs, rainstorm intensity increases as expected with rising temperatures (approximately 7%/K, following increased atmospheric moisture content), while total precipitation increases by a lesser amount (3%/K), consistent with other studies. We identify for the first time the necessary compensating mechanism: in these model runs, individual precipitation events become smaller. Other aspects are approximately unchanged in the warmer climate. Because these spatio-temporal changes in rainfall patterns would impact regional hydrology, it is important that they be accurately incorporated into any impacts assessment. For this purpose we have developed a methodology for producing scenarios of future precipitation that combine observational data and

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

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

  4. Spatio-Temporal Analysis of Smear-Positive Tuberculosis in the Sidama Zone, Southern Ethiopia

    PubMed Central

    Dangisso, Mesay Hailu; Datiko, Daniel Gemechu; Lindtjørn, Bernt

    2015-01-01

    Background Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia. Methods A retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings. Results A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001), with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001), with 7,584 observed and 4,738 expected cases in 2003-2012. Conclusion The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control

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

    USGS Publications Warehouse

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Xu, Bing

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

  9. Physical and biogeochemical correlates of spatio-temporal variation in the δ13C of marine macroalgae

    NASA Astrophysics Data System (ADS)

    Mackey, Andrew P.; Hyndes, Glenn A.; Carvalho, Matheus C.; Eyre, Bradley D.

    2015-05-01

    Carbon isotope ratios (13C/12C) can be used to trace sources of production supporting food chains, as δ13C undergoes relatively small and predictable increases (∼0.5‰) through each trophic level. However, for this technique to be precise, variation in δ13C signatures of different sources of production (baseline sources) must be clearly defined and distinct from each other. Despite this, δ13C in the primary producers of marine systems are highly variable over space and time, due to the complexity of physical and biogeochemical processes that drive δ13C variation at the base of these foodwebs. We measured spatial and temporal variation in the δ13C of two species of macroalgae that are important dietary components of grazers over temperate reefs: the small kelp Ecklonia radiata, and the red alga Plocamium preissianum, and related any variation to a suite of physical and biogeochemical variables. Patterns in δ13C variation, over different spatial (10 s m to 100 km) and temporal scales (weeks to seasons), differed greatly between taxa, but these were partly explained by the δ13C of dissolved inorganic carbon (DIC) and light. However, while the δ13C in E. radiata was not related to water temperature, a highly significant proportion of the spatio-temporal variation in δ13C of P. preissianum was explained by temperature alone. Accordingly, we applied this relationship to project (across temperate Australasia) and forecast (in time, south-western Australia) patterns in P. preissianum δ13C. The mean projected δ13C for P. preissianum in the study region varied by only ∼1‰ over a 12-month period, compared to ∼3‰ over 2000 km. This illustrates the potential scale in the shift of δ13C in baseline food sources over broad scales, and its implications to food web studies. While we show that those relationships differ across taxonomic groups, we recommend developing models to explain variability in δ13C of other baseline sources to facilitate the

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

    PubMed

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Leppelt, Thomas; Gebbert, Sören

    2015-04-01

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

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

    PubMed Central

    D'Angelo, Egidio

    2008-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2015-01-01

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

  15. Spatio-temporal control of laser beams with thin film shapers

    NASA Astrophysics Data System (ADS)

    Grunwald, Ruediger; Neumann, Uwe J.; Griebner, Uwe; Kebbel, Volker; Kuehn, Hans-Joachim

    2004-06-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed

    Fofonov, Alexey; Molchanov, Vladimir; Linsen, Lars

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-05-01

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

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

    PubMed

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

    2014-10-01

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

  20. The spatio-temporal strain response of oedematous and nonoedematous tissue to sustained compression in vivo.

    PubMed

    Berry, Gearóid P; Bamber, Jeffrey C; Mortimer, Peter S; Bush, Nigel L; Miller, Naomi R; Barbone, Paul E

    2008-04-01

    Poroelastic theory predicts that compression-induced fluid flow through a medium reveals itself via the spatio-temporal behaviour of the strain field. Such strain behaviour has already been observed in simple poroelastic phantoms using generalised elastographic techniques (Berry et al. 2006a, 2006b). The aim of this current study was to investigate the extent to which these techniques could be applied in vivo to image and interpret the compression-induced time-dependent local strain response in soft tissue. Tissue on both arms of six patients presenting with unilateral lymphoedema was subjected to a sustained compression for up to 500 s, and the induced strain was imaged as a function of time. The strain was found to exhibit time-dependent spatially varying behaviour, which we interpret to be consistent with that of a heterogeneous poroelastic material. This occurred in both arms of all patients, although it was more easily seen in the ipsilateral (affected) arm than in the contralateral (apparently unaffected) arm in five out of the six patients. Further work would appear to be worthwhile to determine if poroelasticity imaging could be used in future both to diagnose lymphoedema and to explore the patho-physiology of the condition. PMID:18222033

  1. Spatio-temporal variance and meteorological drivers of the urban heat island in a European city

    NASA Astrophysics Data System (ADS)

    Arnds, Daniela; Böhner, Jürgen; Bechtel, Benjamin

    2015-12-01

    Urban areas are especially vulnerable to high temperatures, which will intensify in the future due to climate change. Therefore, both good knowledge about the local urban climate as well as simple and robust methods for its projection are needed. This study has analysed the spatio-temporal variance of the mean nocturnal urban heat island (UHI) of Hamburg, with observations from 40 stations from different suppliers. The UHI showed a radial gradient with about 2 K in the centre mostly corresponding to the urban densities. Temporarily, it has a strong seasonal cycle with the highest values between April and September and an inter-annual variability of approximately 0.5 K. Further, synoptic meteorological drivers of the UHI were analysed, which generally is most pronounced under calm and cloud-free conditions. Considered were meteorological parameters such as relative humidity, wind speed, cloud cover and objective weather types. For the stations with the highest UHI intensities, up to 68.7 % of the variance could be explained by seasonal empirical models and even up to 76.6 % by monthly models.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2013-03-01

    Meiofauna organisms that play an important role in the trophic ecology of soft bottom benthos, have short life cycles and they respond quickly to disturbance and pollution. The present study shows the spatio-temporal variation ofsubtidal meiofauna (metazoans passing a 500im sieve but retained on meshes of 40-63micro m) in four shallow subtidal stations. Samples were taken in the sandy beach of San Luis, in the Northeastern coast of Venezuela, from October 2005 until September 2006. For this, three replicate sediment core samples (4.91cm2), were collected monthly to a depth of 10cm into the sediment, and preserved in 6% formalin stained with rose Bengal. Specimens of 14 meiofaunal groups (Foraminifera excluded) were collected, being the nematodes, ostracods and harpacticoid copepods the most abundant. Monthly density was comprised between 64 and 503ind./10cm2, and mean density of stations between 173 and 449ind./10cm2. There is a trend of low densities from October to February (end of the rainy season until the middle of the dry season). The San Luis beach control of the meiofaunal community is shared by climatic conditions and by the biology of the species found. The meiofauna mean density in San Luis beach (263ind./10cm2) was low when compared to other studies in tropical areas. PMID:23894963

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

    SciTech Connect

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

    2015-04-22

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

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

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  8. Sedimentological constraints to the spatio-temporal evolution of the first Cenozoic Antarctic glaciation

    NASA Astrophysics Data System (ADS)

    Stocchi, P.; Galeotti, S.; De Boer, B.; Escutia, C.; DeConto, R.; Houben, A. J.; Passchier, S.; Vermeersen, B. L.; Van de Wal, R.; Brinkhuis, H.

    2012-12-01

    Glacial Isostatic Adjustement (GIA) modeling of solid Earth and gravitational perturbations induced by the Antarctic glaciation across the Eocene/Oligocene transition (EOT; ~34 Ma) predicts a relative sea level (rsl) rise over-ice proximal marine marginal settings. Accordingly, available sedimentary records from the Ross Sea (CIROS1, CRP-3), Prydz Bay (ODP 739, 1166) and Wilkes Land (IOPD U1356, U1360) provide evidence for progressively deeper depositional environments across the late Eocene towards the Oligocene isotope event-1 (Oi-1; 33.7 Ma, which marks a major glacial advancement episode. Since bathymetric changes at these near-field sites are controlled by GIA, the analysis and inter-site comparison of their sedimentary records provide insights into the spatio-temporal evolution of the nascent Antarctic Ice Sheet. In this work we simulate the inception of the Antarctic glaciation by means of a thermomechanical ice sheet-shelf model dynamically coupled to a sea level model based on the gravitationally self-consistent Sea Level Equation (SLE). We generate a set of ice-sheet and rsl scenarios according to (i) different values for the Earth rheological parameters, (ii) initial topographic/bathymetric conditions and (iii) precipitation/temperature patterns. By comparing the observations with the modeling solutions we find that the initial undeformed topography/bathymetry, and consequently its deformations driven by the GIA described by the SLE, are important conditions for a realistic development of the Antarctic ice-sheet.

  9. A stereoscopic video conversion scheme based on spatio-temporal analysis of MPEG videos

    NASA Astrophysics Data System (ADS)

    Lin, Guo-Shiang; Huang, Hsiang-Yun; Chen, Wei-Chih; Yeh, Cheng-Ying; Liu, Kai-Che; Lie, Wen-Nung

    2012-12-01

    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.

  10. Spatio-temporal regulations and functions of neuronal alternative RNA splicing in developing and adult brains.

    PubMed

    Iijima, Takatoshi; Hidaka, Chiharu; Iijima, Yoko

    2016-08-01

    Alternative pre-mRNA splicing is a fundamental mechanism that generates molecular diversity from a single gene. In the central nervous system (CNS), key neural developmental steps are thought to be controlled by alternative splicing decisions, including the molecular diversity underlying synaptic wiring, plasticity, and remodeling. Significant progress has been made in understanding the molecular mechanisms and functions of alternative pre-mRNA splicing in neurons through studies in invertebrate systems; however, recent studies have begun to uncover the potential role of neuronal alternative splicing in the mammalian CNS. This article provides an overview of recent findings regarding the regulation and function of neuronal alternative splicing. In particular, we focus on the spatio-temporal regulation of neurexin, a synaptic adhesion molecule, by neuronal cell type-specific factors and neuronal activity, which are thought to be especially important for characterizing neural development and function within the mammalian CNS. Notably, there is increasing evidence that implicates the dysregulation of neuronal splicing events in several neurological disorders. Therefore, understanding the detailed mechanisms of neuronal alternative splicing in the mammalian CNS may provide plausible treatment strategies for these diseases. PMID:26853282

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  12. Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor.

    PubMed

    Pearlman, P C; Tagare, H D; Lin, B A; Sinusas, A J; Duncan, J S

    2012-02-01

    This paper presents an algorithm for segmenting left ventricular endocardial boundaries from RF ultrasound. Our method incorporates a computationally efficient linear predictor that exploits short-term spatio-temporal coherence in the RF data. Segmentation is achieved jointly using an independent identically distributed (i.i.d.) spatial model for RF intensity and a multiframe conditional model that relates neighboring frames in the image sequence. Segmentation using the RF data overcomes challenges due to image inhomogeneities often amplified in B-mode segmentation and provides geometric constraints for RF phase-based speckle tracking. The incorporation of multiple frames in the conditional model significantly increases the robustness and accuracy of the algorithm. Results are generated using between 2 and 5 frames of RF data for each segmentation and are validated by comparison with manual tracings and automated B-mode boundary detection using standard (Chan and Vese-based) level sets on echocardiographic images from 27 3D sequences acquired from six canine studies. PMID:22078842

  13. Segmentation of 3D RF echocardiography using a multiframe spatio-temporal predictor.

    PubMed

    Pearlman, Paul C; Tagare, Hemant D; Lin, Ben A; Sinusas, Albert J; Duncan, James S

    2011-01-01

    We present an approach for segmenting left ventricular endocardial boundaries from RF ultrasound. Segmentation is achieved jointly using an independent identically distributed (i.i.d.) spatial model for RF intensity and a multiframe conditional model. The conditional model relates neighboring frames in the image sequence by means of a computationally efficient linear predictor that exploits spatio-temporal coherence in the data. Segmentation using the RF data overcomes problems due to image inhomogeneities often amplified in B-mode segmentation and provides geometric constraints for RF phase-based speckle tracking. The incorporation of multiple frames in the conditional model significantly increases the robustness and accuracy of the algorithm. Results are generated using between 2 and 5 frames of RF data for each segmentation and are validated by comparison with manual tracings and automated B-mode boundary detection using standard (Chan and Vese-based) level sets on echocardiographic images from 27 3D sequences acquired from 6 canine studies. PMID:21761644

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

    PubMed

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

    2013-01-01

    Hox genes encode transcription factors that function to pattern regional tissue identities along the anterior-posterior axis during animal embryonic development. Divergent nested Hox gene expression patterns within the posterior pharyngeal arches may play an important role in patterning morphological variation in the pharyngeal jaw apparatus (PJA) between evolutionarily divergent teleost fishes. Recent gene expression studies have shown the expression patterns from all Hox paralog group (PG) 2-6 genes in the posterior pharyngeal arches (PAs) for the Japanese medaka (Oryzias latipes) and from most genes of these PGs for the Nile tilapia (Oreochromis niloticus). While several orthologous Hox genes exhibit divergent spatial and temporal expression patterns between these two teleost species in the posterior PAs, several tilapia Hox gene expression patterns from PG3-6 must be documented for a full comparative study. Here we present the spatio-temporal expression patterns of hoxb3b, c3a, b4a, a5a, b5a, b5b, b6a and b6b in the neural tube and posterior PAs of the Nile tilapia. We show that several of these tilapia Hox genes exhibit divergent expression patterns in the posterior PAs from their medaka orthologs. We also compare these gene expression patterns to orthologs in other gnathostome vertebrates, including the dogfish shark. PMID:23376031

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  16. Global Spatio-temporal Patterns of Influenza in the Post-pandemic Era

    NASA Astrophysics Data System (ADS)

    He, Daihai; Lui, Roger; Wang, Lin; Tse, Chi Kong; Yang, Lin; Stone, Lewi

    2015-06-01

    We study the global spatio-temporal patterns of influenza dynamics. This is achieved by analysing and modelling weekly laboratory confirmed cases of influenza A and B from 138 countries between January 2006 and January 2015. The data were obtained from FluNet, the surveillance network compiled by the the World Health Organization. We report a pattern of skip-and-resurgence behavior between the years 2011 and 2013 for influenza H1N1pdm, the strain responsible for the 2009 pandemic, in Europe and Eastern Asia. In particular, the expected H1N1pdm epidemic outbreak in 2011/12 failed to occur (or “skipped”) in many countries across the globe, although an outbreak occurred in the following year. We also report a pattern of well-synchronized wave of H1N1pdm in early 2011 in the Northern Hemisphere countries, and a pattern of replacement of strain H1N1pre by H1N1pdm between the 2009 and 2012 influenza seasons. Using both a statistical and a mechanistic mathematical model, and through fitting the data of 108 countries, we discuss the mechanisms that are likely to generate these events taking into account the role of multi-strain dynamics. A basic understanding of these patterns has important public health implications and scientific significance.

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

    PubMed Central

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

    2014-01-01

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

  18. Spatio-temporal analysis of soil erosion risk and runoff using AnnAGNPS

    NASA Astrophysics Data System (ADS)

    Yeshaneh, Eleni; Wagner, Wolfgang; Blöschl, Günter

    2014-05-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  2. Recent homogeneity analysis and long-term spatio-temporal rainfall trends in Nigeria

    NASA Astrophysics Data System (ADS)

    Akinsanola, A. A.; Ogunjobi, K. O.

    2015-12-01

    Accurately predicting precipitation trends is vital in the economic development of a country. Ground observed data from the Nigeria Meteorological Agency (NIMET) was analyzed to study the long-term spatio-temporal trends of rainfall on annual and seasonal scales for 23 stations in Nigeria during a 40-year period spanning from 1974 to 2013. After testing the presence of autocorrelation, Mann-Kendall (modified Mann-Kendall) test was applied to non-autocorrelated (autocorrelated) series to detect the trends in rainfall data. Theil and Sen's slope estimator test was used to find the magnitude of change over a time period. Pettitt's test, Standard Normal Homogeneity Test, and Buishand's test were further used to test the homogeneity of the rainfall series. The results show an increasing trend in annual rainfall; however, only nine stations have a significant increase during the period of study. On the seasonal time scale, a significant increasing trend was observed in the pre- and post-monsoon seasons, while only nine stations show a significant increasing trend in monsoon rainfall and a significant decreasing trend in the winter rainfall over the last 40 years. During the study period, 15.4 and 13.90 % increase were estimated for annual and monsoonal rainfall, respectively. Furthermore, seven stations exhibit changes in mean rainfall while majority of the stations considered (Eighteen stations) exhibit homogeneous trends in annual and seasonal rainfall over the country. The performance of the different tests used in this study was consistent at the verified significance level.

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

    NASA Astrophysics Data System (ADS)

    Ahluwalia-Khalilova, D. V.

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

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

    NASA Astrophysics Data System (ADS)

    Naish, S.; Tong, S.

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Ring, A.; Lampkin, D. J.

    2014-12-01

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

  6. Understanding the spatio-temporal variability of phytoplankton biomass distribution in a microtidal Mediterranean estuary

    NASA Astrophysics Data System (ADS)

    Artigas, M. L.; Llebot, C.; Ross, O. N.; Neszi, N. Z.; Rodellas, V.; Garcia-Orellana, J.; Masqué, P.; Piera, J.; Estrada, M.; Berdalet, E.

    2014-03-01

    Understanding the spatio-temporal variability of phytoplankton in aquaculture zones is necessary for the prevention and/or prediction of harmful algal bloom events. Synoptic cruises, time series analyses of physical and biological parameters, and 3D modeling were combined to investigate the variability of phytoplankton biomass in Alfacs Bay at basin scale. This microtidal estuary located in the NW Mediterranean is an important area of shellfish and finfish exploitation, which is regularly affected by toxic outbreaks. Observations showed the existence of a preferential phytoplankton accumulation area on the NE interior of the bay. This pattern can be observed throughout the year, and we show that it is directly linked to the physical forcing in the bay, in particular, the interplay between freshwater input and wind-induced turbulence. Both drivers affect the strength of the estuarine circulation, explaining nearly 75% of the variability in phytoplankton biomass. More cells are retained when stratification is weakened and the estuarine circulation reduced, while flushing rates are higher during times of increased stratification and stronger estuarine flow. This has been confirmed by using a 3D hydrodynamic model with Eulerian tracers. Nutrients, while important to support phytoplankton populations, have been found to play only a secondary role in explaining this variability at basin scale.

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

    NASA Astrophysics Data System (ADS)

    Lee, Chieh-Han; Yu, Hwa-Lung

    2014-05-01

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

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

    PubMed

    Grunwald, R; Elsaesser, T; Bock, M

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Cybulski, Paweł

    2014-12-01

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

  10. Global Spatio-temporal Patterns of Influenza in the Post-pandemic Era

    PubMed Central

    He, Daihai; Lui, Roger; Wang, Lin; Tse, Chi Kong; Yang, Lin; Stone, Lewi

    2015-01-01

    We study the global spatio-temporal patterns of influenza dynamics. This is achieved by analysing and modelling weekly laboratory confirmed cases of influenza A and B from 138 countries between January 2006 and January 2015. The data were obtained from FluNet, the surveillance network compiled by the the World Health Organization. We report a pattern of skip-and-resurgence behavior between the years 2011 and 2013 for influenza H1N1pdm, the strain responsible for the 2009 pandemic, in Europe and Eastern Asia. In particular, the expected H1N1pdm epidemic outbreak in 2011/12 failed to occur (or “skipped”) in many countries across the globe, although an outbreak occurred in the following year. We also report a pattern of well-synchronized wave of H1N1pdm in early 2011 in the Northern Hemisphere countries, and a pattern of replacement of strain H1N1pre by H1N1pdm between the 2009 and 2012 influenza seasons. Using both a statistical and a mechanistic mathematical model, and through fitting the data of 108 countries, we discuss the mechanisms that are likely to generate these events taking into account the role of multi-strain dynamics. A basic understanding of these patterns has important public health implications and scientific significance. PMID:26046930

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

    SciTech Connect

    Riecke, H.

    1994-05-01

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

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

    PubMed Central

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

    2015-01-01

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

  13. Spatio-temporal analysis of tamoxifen-induced bystander effects in breast cancer cells using microfluidics.

    PubMed

    Rios-Mondragon, Ivan; Wang, Xiang; Gerdes, Hans-Hermann

    2012-06-01

    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. PMID:23750189

  14. Spatio-temporal analysis of Rayleigh-B{acute e}nard convection

    SciTech Connect

    Lainscsek, C.S.; Schuerrer, F.

    1996-06-01

    The analysis of Rayleigh-B{acute e}nard convection in a thin layer of an incompressible fluid caused by heating from below, is based on the Navier-Stokes equations. In planar geometry the Navier-Stokes equations in Bousinesq-approximation reduce to two nonlinear coupled partial differential equations for the velocity flux function {xi} and the temperature deviation {theta}. These equations are analyzed in form of spatial Fourier modes with time-dependent amplitudes. Only modes corresponding to free-free boundary conditions were selected. In this way, a set of ten coupled nonlinear ordinary differential equations for the mode amplitudes was obtained. These equations were solved numerically for different Rayleigh numbers. The temporal information in the ten dimensional phase space of the mode amplitudes is analyzed with respect to the dimension of the attractor. In addition, a time series of flow patterns in real space is constructed. For this spatio-temporal patterns the empirical orthonormal functions are determined and used to find the temporal evolution from the projection onto the basic vectors. Finally the result of different types of analysis were compared. This should lead to a better understanding how to analyze real systems in terms of observational data, e.g., thermal convection on the surface of the sun. {copyright} {ital 1996 American Institute of Physics.}

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  17. Coexistence of productive and non-productive populations by fluctuation-driven spatio-temporal patterns.

    PubMed

    Behar, Hilla; Brenner, Naama; Louzoun, Yoram

    2014-09-01

    Cooperative interactions, their stability and evolution, provide an interesting context in which to study the interface between cellular and population levels of organization. Here we study a public goods model relevant to microorganism populations actively extracting a growth resource from their environment. Cells can display one of two phenotypes - a productive phenotype that extracts the resources at a cost, and a non-productive phenotype that only consumes the same resource. Both proliferate and are free to move by diffusion; growth rate and diffusion coefficient depend only weakly phenotype. We analyze the continuous differential equation model as well as simulate stochastically the full dynamics. We find that the two sub-populations, which cannot coexist in a well-mixed environment, develop spatio-temporal patterns that enable long-term coexistence in the shared environment. These patterns are purely fluctuation-driven, as the corresponding continuous spatial system does not display Turing instability. The average stability of coexistence patterns derives from a dynamic mechanism in which the producing sub-population equilibrates with the environmental resource and holds it close to an extinction transition of the other sub-population, causing it to constantly hover around this transition. Thus the ecological interactions support a mechanism reminiscent of self-organized criticality; power-law distributions and long-range correlations are found. The results are discussed in the context of general pattern formation and critical behavior in ecology as well as in an experimental context. PMID:25058368

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Ping, Bo; Su, Fenzhen; Meng, Yunshan

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Memiş, Abbas; Albayrak, Songül

    2013-12-01

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

  1. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

    PubMed

    Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

    2016-01-01

    Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned. PMID:25700480

  2. Unveiling TRPV1 Spatio-Temporal Organization in Live Cell Membranes

    PubMed Central

    Storti, Barbara; Di Rienzo, Carmine; Cardarelli, Francesco; Bizzarri, Ranieri; Beltram, Fabio

    2015-01-01

    Transient Receptor Potential Vanilloid 1 (TRPV1) is a non-selective cation channel that integrates several stimuli into nociception and neurogenic inflammation. Here we investigated the subtle TRPV1 interplay with candidate membrane partners in live cells by a combination of spatio-temporal fluctuation techniques and fluorescence resonance energy transfer (FRET) imaging. We show that TRPV1 is split into three populations with fairly different molecular properties: one binding to caveolin-1 and confined into caveolar structures, one actively guided by microtubules through selective binding, and one which diffuses freely and is not directly implicated in regulating receptor functionality. The emergence of caveolin-1 as a new interactor of TRPV1 evokes caveolar endocytosis as the main desensitization pathway of TRPV1 receptor, while microtubule binding agrees with previous data suggesting the receptor stabilization in functional form by these cytoskeletal components. Our results shed light on the hitherto unknown relationships between spatial organization and TRPV1 function in live-cell membranes. PMID:25764349

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

    PubMed

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

    2015-01-01

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

  4. Robust spatio-temporal registration of 4D cardiac ultrasound sequences

    NASA Astrophysics Data System (ADS)

    Bersvendsen, Jørn; Toews, Matthew; Danudibroto, Adriyana; Wells, William M.; Urheim, Stig; Estépar, Raúl San José; Samset, Eigil

    2016-04-01

    Registration of multiple 3D ultrasound sectors in order to provide an extended field of view is important for the appreciation of larger anatomical structures at high spatial and temporal resolution. In this paper, we present a method for fully automatic spatio-temporal registration between two partially overlapping 3D ultrasound sequences. The temporal alignment is solved by aligning the normalized cross correlation-over-time curves of the sequences. For the spatial alignment, corresponding 3D Scale Invariant Feature Transform (SIFT) features are extracted from all frames of both sequences independently of the temporal alignment. A rigid transform is then calculated by least squares minimization in combination with random sample consensus. The method is applied to 16 echocardiographic sequences of the left and right ventricles and evaluated against manually annotated temporal events and spatial anatomical landmarks. The mean distances between manually identified landmarks in the left and right ventricles after automatic registration were (mean+/-SD) 4.3+/-1.2 mm compared to a reference error of 2.8 +/- 0.6 mm with manual registration. For the temporal alignment, the absolute errors in valvular event times were 14.4 +/- 11.6 ms for Aortic Valve (AV) opening, 18.6 +/- 16.0 ms for AV closing, and 34.6 +/- 26.4 ms for mitral valve opening, compared to a mean inter-frame time of 29 ms.

  5. Spatio-Temporal Plasticity in Chromatin Organization in Mouse Cell Differentiation and during Drosophila Embryogenesis

    PubMed Central

    Bhattacharya, Dipanjan; Talwar, Shefali; Mazumder, Aprotim; Shivashankar, G.V.

    2009-01-01

    Cellular differentiation and developmental programs require changing patterns of gene expression. Recent experiments have revealed that chromatin organization is highly dynamic within living cells, suggesting possible mechanisms to alter gene expression programs, yet the physical basis of this organization is unclear. In this article, we contrast the differences in the dynamic organization of nuclear architecture between undifferentiated mouse embryonic stem cells and terminally differentiated primary mouse embryonic fibroblasts. Live-cell confocal tracking of nuclear lamina evidences highly flexible nuclear architecture within embryonic stem cells as compared to primary mouse embryonic fibroblasts. These cells also exhibit significant changes in histone and heterochromatin binding proteins correlated with their distinct epigenetic signatures as quantified by immunofluorescence analysis. Further, we follow histone dynamics during the development of the Drosophila melanogaster embryo, which gives an insight into spatio-temporal evolution of chromatin plasticity in an organismal context. Core histone dynamics visualized by fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, and fluorescence anisotropy within the developing embryo, revealed an intriguing transition from plastic to frozen chromatin assembly synchronous with cellular differentiation. In the embryo, core histone proteins are highly mobile before cellularization, actively exchanging with the pool in the yolk. This hyperdynamic mobility decreases as cellularization and differentiation programs set in. These findings reveal a direct correlation between the dynamic transitions in chromatin assembly with the onset of cellular differentiation and developmental programs. PMID:19413989

  6. Spatio-temporal variation of the diterpene steviol in Stevia rebaudiana grown under different photoperiods.

    PubMed

    Ceunen, Stijn; Geuns, Jan M C

    2013-05-01

    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 μg/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

  7. Evaluating Projected Changes in Mean Processes, Extreme Events, and their Spatio-Temporal Dependence Structures

    NASA Astrophysics Data System (ADS)

    Ganguly, A. R.; Steinhaeuser, K.; Kodra, E. A.; Kao, S.

    2010-12-01

    Observational datasets - both raw measurements and derived data products such as reanalysis data - are used to evaluate climate simulations run in forecast and hindcast modes. Bias and uncertainty in mean processes is quantified using statistical comparisons between observations and model-generated outputs. Weather and hydrological extremes under climate change are characterized using both event definitions and extreme value theory (EVT), and their aggregate statistics (intensity, duration and frequency) are likewise compared. The geographic variability and topographical biases are examined at continental to regional scales, and dependence structures (both spatio-temporal autocorrelation and long-range dependence) are assessed using statistical and nonlinear dynamical methods. These tools were developed primarily using the CMIP3/IPCC-AR4 archived model outputs, and are being additional tested with simulations from regional climate models which dynamically downscale the AR4 archives. This combination of traditional and novel tools is thus geared towards evaluation of multiple climate models which may handle processes or generate outputs at different spatial and temporal scales. The tools are expected to be immediately applicable to the CMIP5 data when it becomes available. The anticipated space-time resolutions will pose algorithmic challenges and computational demands, which will be addressed using analytic solutions and implementations thereof on high-performance scientific computing platforms.

  8. Insight into others’ minds: spatio-temporal representations by intrinsic frame of reference

    PubMed Central

    Sun, Yanlong; Wang, Hongbin

    2014-01-01

    Recent research has seen a growing interest in connections between domains of spatial and social cognition. Much evidence indicates that processes of representing space in distinct frames of reference (FOR) contribute to basic spatial abilities as well as sophisticated social abilities such as tracking other’s intention and belief. Argument remains, however, that belief reasoning in social domain requires an innately dedicated system and cannot be reduced to low-level encoding of spatial relationships. Here we offer an integrated account advocating the critical roles of spatial representations in intrinsic frame of reference. By re-examining the results from a spatial task (Tamborello etal., 2012) and a false-belief task (Onishi and Baillargeon, 2005), we argue that spatial and social abilities share a common origin at the level of spatio-temporal association and predictive learning, where multiple FOR-based representations provide the basic building blocks for efficient and flexible partitioning of the environmental statistics. We also discuss neuroscience evidence supporting these mechanisms. We conclude that FOR-based representations may bridge the conceptual as well as the implementation gaps between the burgeoning fields of social and spatial cognition. PMID:24592226

  9. Spatio-Temporal dependence effects of the 17 March 2015 space weather event

    NASA Astrophysics Data System (ADS)

    Bagiya, Mala; Sunda, Surendra; Sunil, A. S.

    2016-07-01

    The super storm of 17 March 2015 has been the largest space weather event of solar cycle 24 till date. The main phase for this storm occurred in two steps. The present study describes the response of global low latitude ionosphere to this event. Total Electron Content (TEC) observations from low latitude International GNSS Services (IGS) stations and one of our own equatorial GNSS station at Tirunelveli are used to derive the temporal ionospheric variability over a large spatial scale during this storm. Intense equatorial ionisation anomaly (EIA) developed over the longitudes where first step of the main phase coincided with local noon time. Equatorial Spread-F (ESF) irregularities occurred quiet strongly in the dusk sector that coincided in time with the initiation of second step of the main phase. The combined effects of overshielding electric field and the disturbance dynamo electric field reduced TEC during first step of the main phase. The storm effects observed to be mostly absent in the post-midnight to early morning sector. The presented spatio-temporal variabilities of low latitude ionosphere during the 17 March 2015 storm are discussed in view of the local time dependence of storm time electrodynamical coupling between high and low latitudes.

  10. A Four Dimensional Spatio-Temporal Analysis of an Agricultural Dataset

    PubMed Central

    Donald, Margaret R.; Mengersen, Kerrie L.; Young, Rick R.

    2015-01-01

    While a variety of statistical models now exist for the spatio-temporal analysis of two-dimensional (surface) data collected over time, there are few published examples of analogous models for the spatial analysis of data taken over four dimensions: latitude, longitude, height or depth, and time. When taking account of the autocorrelation of data within and between dimensions, the notion of closeness often differs for each of the dimensions. Here, we consider a number of approaches to the analysis of such a dataset, which arises from an agricultural experiment exploring the impact of different cropping systems on soil moisture. The proposed models vary in their representation of the spatial correlation in the data, the assumed temporal pattern and choice of conditional autoregressive (CAR) and other priors. In terms of the substantive question, we find that response cropping is generally more effective than long fallow cropping in reducing soil moisture at the depths considered (100 cm to 220 cm). Thus, if we wish to reduce the possibility of deep drainage and increased groundwater salinity, the recommended cropping system is response cropping. PMID:26513746

  11. An inducible, modular system for spatio-temporal control of gene expression in stomatal guard cells.

    PubMed

    Xiong, Tou Cheu; Hann, Cliona M; Chambers, John P; Surget, Marie; Ng, Carl K-Y

    2009-01-01

    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. PMID:19700494

  12. Fish in a ring: spatio-temporal pattern formation in one-dimensional animal groups

    PubMed Central

    Abaid, Nicole; Porfiri, Maurizio

    2010-01-01

    In this work, we study the collective behaviour of fish shoals in annular domains. Shoal mates are modelled as self-propelled particles moving on a discrete lattice. Collective decision-making is determined by information exchange among neighbours. Neighbourhoods are specified using the perceptual limit and numerosity of fish. Fish self-propulsion and obedience to group decisions are described through random variables. Spatio-temporal schooling patterns are measured using coarse observables adapted from the literature on coupled oscillator networks and features of the time-varying network describing the fish-to-fish information exchange. Experiments on zebrafish schooling in an annular tank are used to validate the model. Effects of group size and obedience parameter on coarse observables and network features are explored to understand the implications of perceptual numerosity and spatial density on fish schooling. The proposed model is also compared with a more traditional metric model, in which the numerosity constraint is released and fish interactions depend only on physical configurations. Comparison shows that the topological regime on which the proposed model is constructed allows for interpreting characteristic behaviours observed in the experimental study that are not captured by the metric model. PMID:20413559

  13. Circles on pommel horse with a suspended aid: spatio-temporal characteristics.

    PubMed

    Fujihara, Toshiyuki; Gervais, Pierre

    2012-01-01

    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 suspended aid on a pommel horse under which two force plates were set. Three-dimensional coordinates were acquired using 13 Qualisys motion tracking cameras operating at 100 Hz. The results showed that circles with the aid were characterised by a smaller body flexion angle, a greater shoulder angle, a greater ankle circle diameter, earlier hand releases, and a longer total duration. In contrast, the body lateral flexion angle, the arm-leaning angle, and the shoulder circle diameter remained relatively similar to circles without the aid. It was confirmed that circles with the aid actually appeared to be more desirable in terms of the movement amplitude. In this sense, a suspended aid could function as spotting, which is often used for a progression to learn gymnastics skills and to let gymnasts experience a desired movement pattern. PMID:22313144

  14. Spatio-temporal dynamics of alpine snow algae measured with multi-year imaging spectrometer data

    NASA Astrophysics Data System (ADS)

    Painter, T.; Thomas, W. H.; Duval, B.

    2003-04-01

    The spatio-temporal dynamics of alpine snow algae have not been documented at the basin scale. This study focuses on the interannual variability of the concentration of alga chlamydomonas nivalis as mapped with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) over the Sierra Nevada, California, USA in the springs of 2000, 2001, and 2002. AVIRIS was flown at high spatial resolution (1.5 m) and medium spatial resolution (8 m) on board the NOAA Twin Otter and the NASA ER-2. AVIRIS data were atmospherically-corrected to apparent surface reflectance using a non-linear least squares vapor-fitting algorithm coupled with the atmospheric transmission MODTRAN4. We calculated algal concentration using a model that relates concentration to the continuum-normalized integral of the coupled chlorophyll-a, b absorption features with peak at 680 nm wavelength in the snow spectral reflectance signatures (Painter et al., 2001, Applied and Environmental Microbiology). The AVIRIS data were georeferenced to a digital elevation model of the Tioga Pass, CA region generated in the NASA Shuttle Radar Topography Mission. Interannual variability in basin-wide concentration and pixel-by-pixel concentration trajectories were evaluated.

  15. Large-Scale Spatio-Temporal Patterns of Mediterranean Cephalopod Diversity

    PubMed Central

    Keller, Stefanie; Bartolino, Valerio; Hidalgo, Manuel; Bitetto, Isabella; Casciaro, Loredana; Cuccu, Danila; Esteban, Antonio; Garcia, Cristina; Garofalo, Germana; Josephides, Marios; Jadaud, Angelique; Lefkaditou, Evgenia; Maiorano, Porzia; Manfredi, Chiara; Marceta, Bojan; Massutí, Enric; Micallef, Reno; Peristeraki, Panagiota; Relini, Giulio; Sartor, Paolo; Spedicato, Maria Teresa; Tserpes, George; Quetglas, Antoni

    2016-01-01

    Species diversity is widely recognized as an important trait of ecosystems’ functioning and resilience. Understanding the causes of diversity patterns and their interaction with the environmental conditions is essential in order to effectively assess and preserve existing diversity. While diversity patterns of most recurrent groups such as fish are commonly studied, other important taxa such as cephalopods have received less attention. In this work we present spatio-temporal trends of cephalopod diversity across the entire Mediterranean Sea during the last 19 years, analysing data from the annual bottom trawl survey MEDITS conducted by 5 different Mediterranean countries using standardized gears and sampling protocols. The influence of local and regional environmental variability in different Mediterranean regions is analysed applying generalized additive models, using species richness and the Shannon Wiener index as diversity descriptors. While the western basin showed a high diversity, our analyses do not support a steady eastward decrease of diversity as proposed in some previous studies. Instead, high Shannon diversity was also found in the Adriatic and Aegean Seas, and high species richness in the eastern Ionian Sea. Overall diversity did not show any consistent trend over the last two decades. Except in the Adriatic Sea, diversity showed a hump-shaped trend with depth in all regions, being highest between 200–400 m depth. Our results indicate that high Chlorophyll a concentrations and warmer temperatures seem to enhance species diversity, and the influence of these parameters is stronger for richness than for Shannon diversity. PMID:26760965

  16. Unification of Bell, Leggett-Garg and Kochen-Specker inequalities: Hybrid spatio-temporal inequalities

    NASA Astrophysics Data System (ADS)

    Das, Siddhartha; Aravinda, S.; Srikanth, R.; Home, Dipankar

    2013-12-01

    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.

  17. Spatio-temporal properties and evolution of the 2013 Aigion earthquake swarm (Corinth Gulf, Greece)

    NASA Astrophysics Data System (ADS)

    Mesimeri, M.; Karakostas, V.; Papadimitriou, E.; Schaff, D.; Tsaklidis, G.

    2016-04-01

    The 2013 Aigion earthquake swarm that took place in the west part of Corinth Gulf is investigated for revealing faulting and seismicity properties of the activated area. The activity started on May 21 and was appreciably intense in the next 3 months. The recordings of the Hellenic Unified Seismological Network (HUSN), which is adequately dense around the affected area, were used to accurately locate 1501 events. The double difference ( hypoDD) technique was employed for the manually picked P and S phases along with differential times derived from waveform cross-correlation for improving location accuracy. The activated area with dimensions 6 × 2 km is located approximately 5 km SE of Aigion. Focal mechanisms of 77 events with M ≥ 2.0 were determined from P wave first motions and used for the geometry identification of the ruptured segments. Spatio-temporal distribution of earthquakes revealed an eastward and westward hypocentral migration from the starting point suggesting the division of the seismic swarm into four major clusters. The hypocentral migration was corroborated by the Coulomb stress change calculation, indicating that four fault segments involved in the rupture process successively failed by stress change encouragement. Examination of fluid flow brought out that it cannot be unambiguously considered as the driving mechanism for the successive failures.

  18. Taming of Modulation Instability by Spatio-Temporal Modulation of the Potential

    PubMed Central

    Kumar, S.; Herrero, R.; Botey, M.; Staliunas, K.

    2015-01-01

    Spontaneous pattern formation in a variety of spatially extended nonlinear systems always occurs through a modulation instability, sometimes called Turing instability: the homogeneous state of the system becomes unstable with respect to growing modulation modes. Therefore, the manipulation of the modulation instability is of primary importance in controlling and manipulating the character of spatial patterns initiated by that instability. We show that a spatio-temporal periodic modulation of the potential of spatially extended systems results in a modification of its pattern forming instability. Depending on the modulation character the instability can be partially suppressed, can change its spectrum (for instance the long wave instability can transform into short wave instability), can split into two, or can be completely eliminated. The latter result is of special practical interest, as it can be used to stabilize the intrinsically unstable system. The result bears general character, as it is shown here on a universal model of the Complex Ginzburg-Landau equation in one and two spatial dimensions (and time). The physical mechanism of the instability suppression can be applied to a variety of intrinsically unstable dissipative systems, like self-focusing lasers, reaction-diffusion systems, as well as in unstable conservative systems, like attractive Bose Einstein condensates. PMID:26286250

  19. An integrated framework for spatio-temporal registration of intravascular ultrasound pullbacks

    NASA Astrophysics Data System (ADS)

    Zhang, Ling; Wahle, Andreas; Chen, Zhi; Downe, Richard; Lopez, John; Kovarnik, Tomas; Sonka, Milan

    2015-03-01

    Spatio-temporal registration of baseline and follow-up intravascular ultrasound (IVUS) pullbacks is of paramount importance in studying the progression/regression of coronary artery disease. Automating these two tasks has the potential to increase productivity when studying large patient populations. Current automated methods are often designed for only one of the two tasks - spatial or temporal. In this paper, we propose an integrated framework which combines the two tasks and employs side-branches to constrain the IVUS pullback registration tasks. For temporal registration, canonical time warping technique optimizes extracted features and weighs cumulative distances. For spatial registration, the search range of cross-correlation based method is constrained by utilizing the angular differences between side-branches. Pilot validation is currently available for ten pairs of IVUS pullback sub-sequences. Results show average spatial and temporal registration errors of 0.49 mm +/- 0.51 mm and 5.56° +/- 3.35°, respectively, a notable improvement over our previous approach (p < 0.001) in temporal registration. Our method has the potential to improve spatial and temporal correspondence in studies of atherosclerotic vascular disease development using IVUS.

  20. Spatio-temporal covariation of urban particle number concentration and ambient noise

    NASA Astrophysics Data System (ADS)

    Weber, Stephan

    Mobile measurements of ambient noise and particle number concentrations were carried out within an urban residential area in Essen, Germany, during summer 2008. A busy major road with a traffic intensity of about 44,000 vehicles per day was situated within the study area. The spatio-temporal distribution of noise and particles was closely coupled to road traffic on the major road. Total particle number concentrations in proximity to the main road were on average between 25,000 cm -3 and 35,000 cm -3 while sound levels reached 70-78 dB(A). These estimates were more than double-fold (factor 2.4) in comparison to the urban residential background. At a 50 m distance off the road particle number concentrations were decaying to about 50% of the initial value. The measurements were characterised by close spatial correlation between total particle number concentration and ambient noise with correlation coefficients of up to r = 0.74. However, during one measurement day coupling between both quantities was weak due to higher turbulent mixing within the canopy layer and a change in ambient wind directions. Enhanced dilution of particle emission from road traffic by turbulent mixing and 'decoupling' from the influence of road traffic are believed to be responsible.

  1. Spreading speeds and uniqueness of traveling waves for a reaction diffusion equation with spatio-temporal delays

    NASA Astrophysics Data System (ADS)

    Xu, Zhaoquan; Xiao, Dongmei

    2016-01-01

    A class of reaction diffusion equation with spatio-temporal delays is systematically investigated. When the reaction function of this equation is nonlinear without monotonicity, it is shown that there exists a spreading speed c* > 0 for this equation such that c* is linearly determinate and coincides with the minimal wave speed of traveling waves, and that this equation admits a unique traveling wave (up to translation) with speed c >c* and no traveling wave with c

  2. Bayesian spatio-temporal modelling of national milk-recording data of seasonal-calving New Zealand dairy herds.

    PubMed

    Clements, A C A; Pfeiffer, D U; Hayes, D

    2005-10-12

    A spatio-temporal analysis was undertaken with the aim of identifying the dynamics of herd mean individual cow SCCs (MICSCC) in seasonally calving New Zealand dairy herds. Two datasets were extracted from the Livestock Improvement Corporation's extensive national dairy recording database: (1) milk-recording data aggregated at the herd-level and (2) sales questionnaire data containing information on the size, location and infrastructure of each farm. A Bayesian spatio-temporal modelling approach was applied to the analysis. The data were aggregated by 10 km(2) grid cells and linear regression models were developed with spatially structured and unstructured random effects, a linear temporal trend random effect and spatial-temporal interactions for log-transformed median MISCC (ln(median MISCC)). Significant associations were found between ln(median MISCC) and milk yield, milk fat, milk protein, farm area and number of cups in the dairy. This led us to suggest that SCCs should be adjusted for volume and constituents prior to determining a threshold MISCC for identification of subclinical mastitis (SCM) problem herds. Part, or all, of the temporal trend in MISCC in the spatio-temporal model was accounted for by inclusion of yield and milk constituents as independent variables. This supports the hypothesis of a dilution effect with potential consequences for misdiagnosis of SCM, particularly in late lactation. Unmeasured covariates were similarly likely to be spatially structured and unstructured. PMID:16107283

  3. An agent-based model driven by tropical rainfall to understand the spatio-temporal heterogeneity of a chikungunya outbreak.

    PubMed

    Dommar, Carlos J; Lowe, Rachel; Robinson, Marguerite; Rodó, Xavier

    2014-01-01

    Vector-borne diseases, such as dengue, malaria and chikungunya, are increasing across their traditional ranges and continuing to infiltrate new, previously unaffected, regions. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. We develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure vs. precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission. PMID:23958228

  4. Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

    PubMed Central

    Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

    2015-01-01

    It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources. PMID:26492263

  5. Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+.

    PubMed

    Karakaya, Nusret; Evrendilek, Fatih

    2011-10-01

    The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO₃-N), silicate (SiO₄), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO₂-N (P = 0.008) to 0.79 for S (depth) (P < 0.001). Parsimonious MLR models built in this study appear to be promising for monitoring and predicting spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay. PMID:21181257

  6. Mapping Spatio-Temporal Diffusion inside the Human Brain Using a Numerical Solution of the Diffusion Equation

    PubMed Central

    Zhan, Wang; Jiang, Li; Loew, Murray; Yang, Yihong

    2008-01-01

    Diffusion is an important mechanism for molecular transport in living biological tissues. Diffusion magnetic resonance imaging (dMRI) provides a unique probe to examine microscopic structures of the tissues in vivo, but current dMRI techniques usually ignore the spatio-temporal evolution process of the diffusive medium. In the present study, we demonstrate the feasibility to reveal the spatio-temporal diffusion process inside the human brain based on a numerical solution of the diffusion equation. Normal human subjects were scanned with a diffusion tensor imaging (DTI) technique on a 3-Tesla MRI scanner, and the diffusion tensor in each voxel was calculated from the DTI data. The diffusion equation, a partial-derivative description of Fick’s Law for the diffusion process, was discretized into equivalent algebraic equations. A finite-difference method was employed to obtain the numerical solution of the diffusion equation with a Crank-Nicholson iteration scheme to enhance the numerical stability. By specifying boundary and initial conditions, the spatio-temporal evolution of the diffusion process inside the brain can be virtually reconstructed. Our results exhibit similar medium profiles and diffusion coefficients as those of light fluorescence dextrans measured in integrative optical imaging experiments. The proposed method highlights the feasibility to non-invasively estimate the macroscopic diffusive transport time for a molecule in a given region of the brain. PMID:18440744

  7. Spatio-temporal dynamics of kind versus hostile intentions in the human brain: An electrical neuroimaging study.

    PubMed

    Wang, Yiwen; Huang, Liang; Zhang, Wei; Zhang, Zhen; Cacioppo, Stephanie

    2015-01-01

    . The present study provides preliminary evidence of the spatio-temporal dynamics sustaining the dissociation between the understandings of different types of social intentions. PMID:25517193

  8. Correlation analysis of spatio-temporal images for estimating two-dimensional flow velocity field in a rotating flow condition

    NASA Astrophysics Data System (ADS)

    Yu, Kwonkyu; Kim, Seojun; Kim, Dongsu

    2015-10-01

    Flow velocity estimation in actual rivers using image processing technique has been highlighted for hydrometric communities in the last decades, and this technique is called Large Scale Particle Image Velocimetry (LSPIV). Although LSPIV has been successfully tested in many flow conditions, it has addressed several limitations estimating mean flow field because of difficult flow conditions such as rotating, lack of light and seeds, and noisy flow conditions. Recently, an alternative technique named STIV to use spatio-temporal images based on successively recorded images has been introduced to overcome the limitations of LSPIV. The STIV was successfully applied to obtain one-dimensional flow component in the river for estimating streamflow discharge, where the main flow direction is known. Using the 5th order of central difference scheme, the STIV directly calculated the mean angle of slopes which appeared as strips in the spatio-temporal images and has been proved to be more reliable and efficient for the discharge estimation as compared with the conventional LSPIV. However, yet it has not been sufficiently qualified to derive two-dimensional flow field in the complex flow, such as rotating or locally unsteady flow conditions. We deemed that it was because the strips in the given spatio-temporal images from not properly oriented for main flow direction are not narrow enough or clearly visible, thus the direct estimating strip slope could give erroneous results. Thereby, the STIV has been mainly applied for obtaining one-dimensional flow component. In this regard, we proposed an alternative algorithm to estimate the mean slope angle for enhancing the capability of the STIV, which used correlation coefficient between odd and even image splits from the given spatio-temporal image. This method was named CASTI (Correlation Analysis of Spatio-Temporal Image). This paper described the step-by-step procedure of the CASTI and validated its capability for estimating two

  9. A single glance at natural face images generate larger and qualitatively different category-selective spatio-temporal signatures than other ecologically-relevant categories in the human brain.

    PubMed

    Jacques, Corentin; Retter, Talia L; Rossion, Bruno

    2016-08-15

    Although humans discriminate natural images of faces from other categories at a single glance, clarifying the neural specificity and spatio-temporal dynamics of this process without low-level visual confounds remains a challenge. We recorded high-density scalp electroencephalogram while presenting natural images of various objects at a fast periodic rate (5.88images/s). In different stimulation sequences, numerous variable exemplars of three categories associated with cortical specialization in neuroimaging - faces, body parts, or houses - appeared every five images (5.88Hz/5=1.18Hz). In these fast periodic visual stimulation (FPVS) sequences, common low- and high-level visual processes between these categories and other objects are captured at the 5.88Hz frequency, while high-level category-selective responses are objectively quantified at the 1.18Hz frequency and harmonics. Category-selective responses differed quantitatively and qualitatively between faces, body parts and houses. First, they were much larger (2-4 times) for faces over the whole scalp. Second, specific and reliable scalp topographical maps of category-selective responses pointed to distinct principle neural sources for faces (ventral occipito-temporal), body parts (lateral occipito-temporal) and houses (dorso-medial occipital). Category-selective EEG responses were found at multiple time-windows from 110 to 600ms post-stimulus onset. Faces elicited the most complex spatio-temporal profile with up to four selective responses, although body parts and houses also elicited selective responses more complex than previously described. These observations indicate that a single glance at natural face images inserted in a rapid stream of natural objects generates a quantitatively and qualitatively unique category-selective spatio-temporal signature in occipito-temporal cortical areas of the human brain. PMID:27138205

  10. Spatio-temporal surface-subsurface water exchanges: from the local to the watershed scale

    NASA Astrophysics Data System (ADS)

    Rivière, Agnès; Flipo, Nicolas; Mouhri, Amer; Ansart, Patrick; Baudin, Aurélien; Berrhouma, Asma; Bodet, Ludovic; Cocher, Emmanuel; Cucchi, Karina; Durand, Véronique; Flageul, Sébastien; de Fouquet, Chantal; Goblet, Patrick; Hovhannissian, Gaghik; Jost, Anne; Pasquet, Sylvain; Rejiba, Fayçal; Rubin, Yoram; Tallec, Gaëlle; Mouchel, Jean-Marie

    2016-04-01

    Understanding the temporal and spatial variations of the surface-subsurface water exchanges is a prerequisite to achieve sustainable water use in basin. The concept of nested stream-aquifer interfaces (Flipo et al., 2014) is used to simulate the variation of the spatio-temporal surface-subsurface exchanges at the watershed scale from LOcal MOnitoring Stations (LOMOSs) measurements of the stream-aquifer exchanges. This method is applied along the stream network of the Avenelles basin. The Avenelles basin (46 km2) is located 70 km east from Paris. The basin is composed of a multi-layer aquifer system which consists of two limestone aquifers: the Brie aquifer (Oligocene) and the Champigny aquifer (Eocene) separated by a clayey aquitard. The meandering river is shallow, connected with the Brie aquifer in its upstream part and the Champigny aquifer in its downstream part. A high-frequency hydrologic monitoring network was deployed on the basin from 1960. The network measures water levels and water temperatures in the aquifers, and in-stream discharge rates. Five LOMOSs have been operating since 2012 along the stream-network (two upstream, two intermediate, and one downstream site) to monitor spatio-temporal stream-aquifer exchanges over years. LOMOSs are composed of one or two shallow piezometers to monitor the temperature and the hydraulic head variations in the aquifers, two hyporheic zone (HZ) temperature profiles located close to each river bank and one water level and temperature monitoring system in the river. A local 2D thermo-hydro model is used to determine hydrogeological and thermal properties of the aquifer and the HZ by inversion and to quantify the stream-aquifer exchanges at the local scale. We performed a pseudo 3D hydro(geo)logical simulation, over 23 years, at the Avenelles basin scale by the used of CAWAQS modelling platform. The CAWAQS platform is composed of four spatially distributed modules (Surface, Sub-surface, River and Groundwater

  11. Spatio-temporal variability of aerosols in the tropics relationship with atmospheric and oceanic environments

    NASA Astrophysics Data System (ADS)

    Zuluaga-Arias, Manuel D.

    2011-12-01

    Earth's radiation budget is directly