Science.gov

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. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.; Rmy, 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 data. We also present a time-invariant GIA field and an elastic vertical motion field for the bedrock. All fields are solved for simultaneously alongside posterior errors that are consistent with the full suite of observations and priors. The framework we have developed can incorporate other data, such as shallow/deep ice core records of accumulation, coffee-can point measurements of mass balance, and snow radar data. The framework can also be applied to other ice masses and components of the climate system that suffer similar source separation issues: for example, solving the sea level budget.

  7. [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

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

    NASA Astrophysics Data System (ADS)

    Schleicher, N. J.; Schfer, 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.

  9. 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

  10. 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 ? = 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

  11. A Validation Framework for Non-Point Source Simulation Models: Application to the Southern California Central Valley with Spatio-Temporally Heterogenous Source Rates

    NASA Astrophysics Data System (ADS)

    Kourakos, G.; Harter, T.

    2013-12-01

    Non-point source pollution on groundwater of agricultural regions is an alarming issue of global importance. The very large response times of contaminants which may vary from decades to centuries, require mitigation measures to be based on reliable modeling. Here we present a novel computational framework to assess and evaluate the dynamic, spatio-temporally distributed linkages between non-point sources above a groundwater basin and groundwater discharges to wells, streams, or other compliance discharge surfaces (CDSs) within a groundwater basin. The modeling framework allows for efficient evaluation of NPS pollution scenarios and of their short- and long-term effects on pollutant exceedance probabilities in CDSs. We apply the model to simulate 100 years of nitrate pollution at high resolution in a 2 million hectare semi-arid, irrigated agricultural region with a large diversity of crops, but also natural lands and urban areas, and highly heterogeneous, temporally variable loading landscape in the Southern California Central Valley. Results show that the timing of nitrate breakthrough in wells is significantly controlled by aquifer recharge and pumping rates in NPS areas and by the effective porosity of the aquifer system. MLast the model predictions are compared against a highly heterogeneous, spatio-temporally varying in space and time database of historic nitrate records and an attempt is made to compute the spatial distribution of nitrate half-life due to denitrification.

  12. 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 interviews were helpful to gain initial insight into the usability of the tools and to highlight further improvements and challenges; revealing certain usability issues and indicating that analysts consider the linked views to be potentially very beneficial and they appreciate seeing the data in its spatial context.

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

    PubMed

    Lindstrm, 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

  14. 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

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

    PubMed

    Kuku?ka, Petr; Audy, Ond?ej; Kohoutek, Ji?; Holt, Eva; Kalbov, Tereza; Holoubek, Ivan; Klnov, 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

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

    PubMed

    Legorburu, Irati; Rodrguez, Jos Germn; Borja, Angel; Menchaca, Iratxe; Solaun, Oihana; Valencia, Victoriano; Galparsoro, Ibon; Larreta, Joana

    2013-01-15

    According to Water Framework Directive requirements, Member States must identify and analyze effects derived from human pressures in aquatic systems. As different kind of pressures can impact water bodies at different scales, analyses of spatio-temporal evolution of water bodies becomes essential in order to understand ecosystem responses. In this investigation, an analysis of spatio-temporal evolution of sedimentary metal pollution (Cd, Cr, Cu, Hg, Ni, Pb, Zn) in 12 Basque estuaries (Bay of Biscay) is presented. Data collected in extensive sampling surveys is the basis for the GIS-based statistical approach used. The implementation of pollution abatement measures is reflected in a long-term decontamination process, mostly evident in estuaries with highest historical sediment pollution levels. Spatial evolution is determined by either naturally occurring or human driven processes. Such spatial processes are more obviously being reflected in estuaries with lower historical sediment pollution levels. PMID:23218773

  17. Dynamic proximity of spatio-temporal sequences.

    PubMed

    Horn, David; Dror, Gideon; Quenet, Brigitte

    2004-09-01

    Recurrent networks can generate spatio-temporal neural sequences of very large cycles, having an apparent random behavior. Nonetheless a proximity measure between these sequences may be defined through comparison of the synaptic weight matrices that generate them. Following the dynamic neural filter (DNF) formalism we demonstrate this concept by comparing teacher and student recurrent networks of binary neurons. We show that large sequences, providing a training set well exceeding the Cover limit, allow for good determination of the synaptic matrices. Alternatively, assuming the matrices to be known, very fast determination of the biases can be achieved. Thus, a spatio-temporal sequence may be regarded as spatio-temporal encoding of the bias vector. We introduce a linear support vector machine (SVM) variant of the DNF in order to specify an optimal weight matrix. This approach allows us to deal with noise. Spatio-temporal sequences generated by different DNFs with the same number of neurons may be compared by calculating correlations of the synaptic matrices of the reconstructed DNFs. Other types of spatio-temporal sequences need the introduction of hidden neurons, and/or the use of a kernel variant of the SVM approach. The latter is being defined as a recurrent support vector network (RSVN). PMID:15484877

  18. 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

  19. 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

  20. Spatio-temporal EEG Source Localization Using a Three-dimensional Subspace FINE Approach in a Realistic Geometry Inhomogeneous Head Model

    PubMed Central

    Ding, Lei; He, Bin

    2007-01-01

    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. 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 signal-to-noise ratio, and may become an important alternative to brain source localization from EEG or MEG. PMID:16941829

  1. Spatio-temporal isotopic signatures (?13 C and ?15 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 ?(13) C and ?(15) N composition of muscle tissues. Between species, ?(15) N compositions were similar, suggesting a similar trophic level, while the difference in ?(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

  2. 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. However, the other half, located distant to the border, were likely a result of animals escaping fenced premises inside the country. The approach serves as a template to assess the status of an invading species and improve the knowledge base for risk assessment and management decision. PMID:26775815

  3. 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.

  4. 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-Cantabrian region, 76% for the Southern Mediterranean and 81% for the Pyrenees. In summary, this work shows the existence of a valuable decadal and interannual predictability of the Ebro streamflow, a result which may be useful to water resources management.

  5. 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 existed. Soltani and Modarres (2006) classified the sites by using only average rainfall of sites, they did not consider time replications and spatial coordinates. Kerby et.al (2007) purposed spatial clustering method based on likelihood. They took account of the geographic locations through the variance covariance matrix. Their purposed method works like hierarchical clustering methods. Moreovere, it is inappropiriate for time replication data and could not perform well for large number of sites. Tuia.et.al (2008) used scan statistics for identifying spatio-temporal clusters for fire sequences in the Tuscany region in Italy. The scan statistics clustering method was developed by Kulldorff et al. (1997) to detect spatio-temporal clusters in epidemiology and assessing their significance. The purposed scan statistics method is used only for univariate discrete stochastic random variables. In this paper we make use of a very simple approach for spatio-temporal clustering which can create separable and homogeneous clusters. Most of the clustering methods are based on Euclidean distances. It is well known that geographic coordinates are spherical coordinates and estimating Euclidean distances from spherical coordinates is inappropriate. As a transformation from geographic coordinates to rectangular (D-plane) coordinates we use the Lambert projection method. The partition around medoids clustering method is incorporated on the data including D-plane coordinates. Ordinary kriging is taken as validity measure for the precipitation data. The kriging results for clusters are more accurate and have less variation compared to complete monitoring network precipitation data. References Casto.V.E and Murray.A.T (1997). Spatial Clustering with Data Mining with Genetic Algorithms. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8573 Kaufman.L and Rousseeuw.P.J (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley series of Probability and Mathematical Statistics, New York. Kulldorf.M (1997). A spatial scan statistic. Commun. Stat.-Theor. Math. 26(6), 1481-1496 Kerby. A , Marx. D, Samal. A and Adamchuck. V. (2007). Spatial Clustering Using the Likelihood Function. Seventh IEEE International Conference on Data Mining - Workshops Steinhaus.H (1956). Sur la division des corp materiels en parties. Bull. Acad. Polon. Sci., C1. III vol IV:801- 804 Snyder, J. P. (1987). Map Projection: A Working Manual. U. S. Geological Survey Professional Paper 1395. Washington, DC: U. S. Government Printing Office, pp. 104-110 Sap.M.N and Awan. A.M (2005). Finding Spatio-Temporal Patterns in Climate Data Using Clustering. Proceedings of the International Conference on Cyberworlds (CW'05) Soltani.S and Modarres.R (2006). Classification of Spatio -Temporal Pattern of Rainfall in Iran: Using Hierarchical and Divisive Cluster Analysis. Journal of Spatial Hydrology Vol.6, No.2 Tuia.D, Ratle.F, Lasaponara.R, Telesca.L and Kanevski.M (2008). Scan Statistics Analysis for Forest Fire Clusters. Commun. in Nonlinear science and numerical simulation 13,1689-1694.

  6. Spatio-temporal autocorrelation measures for nonstationary series: A new temporally detrended spatio-temporal Moran's index

    NASA Astrophysics Data System (ADS)

    Shen, Chenhua; Li, Chaoling; Si, Yali

    2016-01-01

    In order to measure the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series, the new temporally detrended global and local spatio-temporal Moran's indexes (TDGSTI and TDLSTI) are proposed. The implementation of the new Moran's indexes is illustrated through artificial and real examples. Analyses of the influencing factors on TDGSTI are performed. A statistical test of TDGSTI is taken. The Moran's scatter plot, which discloses the spatio-temporal cluster pattern's characteristics and pattern's change, is extended. TDGSTI is found to reveal the autocorrelation level of spatio-temporal objects. For a positive TDGSTI, the higher the TDGSTI, the higher the autocorrelation level, and vice versa. TDGSTI is closely related to time-scale s, time-lag h and spatio-temporal weight matrix. For s ? h, TDGSTI is significant, while for s ? h and s < h, TDGSTI is insignificant. TDGSTI has clear potential to test the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series in other research fields.

  7. 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.

  8. 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.

  9. Multiscale blind source separation

    NASA Astrophysics Data System (ADS)

    Kisilev, Pavel; Zibulevsky, Michael; Zeevi, Yehoshua Y.; Pearlmutter, Barak A.

    2001-03-01

    The concern of the blind source separation problem is to extract the underlying source signals from a set of their linear mixtures, where the mixing matrix is unknown. It was discovered recently, that use of sparsity of source representation in some signal dictionary dramatically improves the quality of separation. In this work we use the property of multiscale transforms, such as wavelet or wavelet packets, to decompose signals into sets of local features with various degrees of sparsity. We use this intrinsic property for selecting the best (most sparse) subsets of features for further separation. Experiments with simulated signals, musical sounds and images demonstrate significant improvement of separation quality.

  10. 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.

  11. 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)...

  12. Blind source separation: new tools for extraction of source signals and denoising

    NASA Astrophysics Data System (ADS)

    Cichocki, Andrzej S.

    2005-03-01

    Blind source separation (BSS) and related methods such as independent component analysis (ICA) and their extensions or sparse component analysis (SCA) refers to wide class of problems in signal and image processing, when one needs to extract the underlying sources from a set of mixture. The goal of BSS can be considered as estimation of true physical sources and parameters of a mixing system, while objective of generalized component analysis (GCA) is finding a new reduced or hierarchical and structured representation for the observed (sensor) multidimensional data that can be interpreted as physically meaningful coding or blind signal decompositions. These methods are generally based on a wide class of unsupervised learning algorithms and they found potential applications in many areas from engineering to neuroscience. The recent trends in blind source separation and generalized component analysis is to consider problems in the framework of matrix factorization or more general signals decomposition with probabilistic generative and tree structured graphical models and exploit some priori knowledge about true nature and structure of latent (hidden) components or sources such as spatio-temporal decorrelation, statistical independence, sparsity, nonnegativity, smoothness or lowest possible complexity. The key issue is to find a such transformation or coding which has true physical meaning and interpretation. In this paper we discuss some promising approaches and algorithms for BSS/GCA, especially for ICA and SCA in order to analyze, enhance, perform feature extraction, removing artifacts and denoising of multi-modal, multi-sensory data.

  13. A Distributed Spatio-Temporal EEG/MEG Inverse Solver

    PubMed Central

    Hmlinen, Matti S.; Golland, Polina

    2009-01-01

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

  14. A distributed spatio-temporal EEG/MEG inverse solver

    PubMed Central

    Ou, Wanmei; Hmlinen, Matti S.; Golland, Polina

    2009-01-01

    We propose a novel ?1?2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard ?1-norm inverse solvers, this sparse distributed inverse solver integrates the ?1-norm spatial model with a temporal model of the source signals in order to avoid unstable activation patterns and spiky reconstructed signals often produced by the currently used sparse solvers. The joint spatio-temporal model leads to a cost function with an ?1?2-norm regularizer whose minimization can be reduced to a convex second-order cone programming (SOCP) problem and efficiently solved using the interior-point method. The efficient computation of the SOCP problem allows us to implement permutation tests for estimating statistical significance of the inverse solution. Validation with simulated and human MEG data shows that the proposed solver yields source time course estimates qualitatively similar to those obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. Furthermore, the ?1?2-norm solver achieves fewer false positives and a better representation of the source locations than the conventional ?2 minimum-norm estimates. PMID:18979728

  15. 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 for forest disturbance detection. The study expects results that improve over a pure time series analysis approach, and that is practically applicable to massive complex spatio-temporal data.

  16. Atrial activity estimation from atrial fibrillation ECGs by blind source extraction based on a conditional maximum likelihood approach.

    PubMed

    Phlypo, Ronald; Zarzoso, Vicente; Lemahieu, Ignace

    2010-05-01

    This work presents a spatial filtering method for the estimation of atrial fibrillation activity in the cutaneous electrocardiogram. A linear extraction filter is obtained by maximising the extractor output power on the significant spectral support of the signal of interest. An iterative procedure based on a quasi-maximum likelihood estimator is proposed to jointly estimate the significant spectral support and the extraction filter. Compared with a previously proposed spatio-temporal blind source separation method, our approach yields an improved atrial activity signal estimate as quantified by a higher spectral concentration of the extractor output. The proposed methodology can readily be adapted to signal extraction problems in other application domains. PMID:20127523

  17. 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.

  18. 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 20042011 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 20042008; 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

  19. Spatio-temporal chaos in a chemotaxis model

    NASA Astrophysics Data System (ADS)

    Painter, Kevin J.; Hillen, Thomas

    2011-02-01

    In this paper we explore the dynamics of a one-dimensional Keller-Segel type model for chemotaxis incorporating a logistic cell growth term. We demonstrate the capacity of the model to self-organise into multiple cellular aggregations which, according to position in parameter space, either form a stationary pattern or undergo a sustained spatio-temporal sequence of merging (two aggregations coalesce) and emerging (a new aggregation appears). This spatio-temporal patterning can be further subdivided into either a time-periodic or time-irregular fashion. Numerical explorations into the latter indicate a positive Lyapunov exponent (sensitive dependence to initial conditions) together with a rich bifurcation structure. In particular, we find stationary patterns that bifurcate onto a path of periodic patterns which, prior to the onset of spatio-temporal irregularity, undergo a “periodic-doubling” sequence. Based on these results and comparisons with other systems, we argue that the spatio-temporal irregularity observed here describes a form of spatio-temporal chaos. We discuss briefly our results in the context of previous applications of chemotaxis models, including tumour invasion, embryonic development and ecology.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  2. Transient dynamics and rhythm coordination of inferior olive spatio-temporal patterns.

    PubMed

    Latorre, Roberto; Aguirre, Carlos; Rabinovich, Mikhail I; Varona, Pablo

    2013-01-01

    The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO is frequently proposed as the generator of timing signals to the cerebellum. Electrophysiological and imaging recordings show that the IO network generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. Our modeling reproduces and helps to understand important phenomena observed in IO in vitro and in vivo experiments, and draws new predictions regarding the computational properties of this network and the associated cerebellar circuits. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop (IL). The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of the IO neurons that nevertheless remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts. These results can be generalized beyond IO studies, as the control of wave pattern propagation is a highly relevant problem in the context of normal and pathological states in neural systems (e.g., related to tremor, migraine, epilepsy) where the study of the modulation of activity sinks and sources can have a potential large impact. PMID:24046731

  3. 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…

  4. 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.

  5. 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.

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

    PubMed Central

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

    2013-01-01

    Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC). Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value) color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms. PMID:23482090

  7. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovi?, Duan; 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.

  8. 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.

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

    PubMed

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

    2013-01-01

    Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC). Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value) color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms. PMID:23482090

  10. 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

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

    PubMed

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

    2014-06-01

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

  12. 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.

  13. Spatio-Temporal Statistical Models with Application to Atmospheric Processes.

    NASA Astrophysics Data System (ADS)

    Wikle, Christopher Kim

    This dissertation is concerned with spatio-temporal processes in the atmospheric sciences. In the first chapter, a comprehensive overview of spatio-temporal methods from the atmospheric science literature is presented. Focus is on Empirical Orthogonal Function (EOF), Principal Interaction Pattern (PIP), Principal Oscillation Pattern (POP), and spatio-temporal Canonical Correlation Analysis (CCA) methods. Previously unexamined issues related to measurement error, continuous space, and Bayesian ideas are considered. In the second chapter, harmonic analysis is used to make diagnostic inference about the spatial variation of the semiannual oscillation (SAO) in the Northern Hemisphere (NH) 500-hPa height field. The SAO is explained by the spatial and temporal asymmetries in the annual variation of stationary eddies. The SAO in the NH extratropics is a result of east-west land-sea contrasts, analogous to the well-known Southern Hemisphere (SH) SAO, which is explained by north-south land-sea contrasts. The third chapter examines the seasonal variability of mixed Rossby-gravity waves (MRGWs) in the lower stratosphere over the tropical western Pacific. Thirty-one years of lower stratospheric wind observations from four tropical Pacific stations are examined with seasonally varying cross -spectral analysis, which suggests significant twice-yearly peaks in the v-wind power and the mean squared coherence between the u- and v-winds, with peaks occurring in the winter-early spring and in summer-early fall. Horizontal momentum flux convergence is found with these waves, with the sign of the convergence opposite during the two seasonal maxima. Cyclic spectral analyses show that the frequency of the maximum v-wind power in the MRGW frequency band shifts seasonally. In the fourth chapter, a spatio-temporal statistical model is proposed that assumes a first-order Markov dynamic process combined with a spatially descriptive colored noise process. With a measurement error equation, a spatio-temporal Kalman filter gives predictions in time and at any spatial location. The model prediction equation includes a simple kriging analog as a special case. The model predicts well with simulated spatio-temporal data, and is superior to simple kriging applied independently at each time. Predictions of precipitation over the data-sparse South China Sea captures the dynamic variation of the spatial precipitation.

  14. 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

  15. 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.

  16. Motion analysis and segmentation through spatio-temporal slices processing.

    PubMed

    Ngo, Chong-Wah; Pong, Ting-Chuen; Zhang, Hong-Jiang

    2003-01-01

    This paper presents new approaches in characterizing and segmenting the content of video. These approaches are developed based upon the pattern analysis of spatio-temporal slices. While traditional approaches to motion sequence analysis tend to formulate computational methodologies on two or three adjacent frames, spatio-temporal slices provide rich visual patterns along a larger temporal scale. We first describe a motion computation method based on a structure tensor formulation. This method encodes visual patterns of spatio-temporal slices in a tensor histogram, on one hand, characterizing the temporal changes of motion over time, on the other hand, describing the motion trajectories of different moving objects. By analyzing the tensor histogram of an image sequence, we can temporally segment the sequence into several motion coherent subunits, in addition, spatially segment the sequence into various motion layers. The temporal segmentation of image sequences expeditiously facilitates the motion annotation and content representation of a video, while the spatial decomposition of image sequences leads to a prominent way of reconstructing background panoramic images and computing foreground objects. PMID:18237913

  17. Spatio-temporal Outlier Detection in Precipitation Data

    NASA Astrophysics Data System (ADS)

    Wu, Elizabeth; Liu, Wei; Chawla, Sanjay

    The detection of outliers from spatio-temporal data is an important task due to the increasing amount of spatio-temporal data available and the need to understand and interpret it. Due to the limitations of current data mining techniques, new techniques to handle this data need to be developed. We propose a spatio-temporal outlier detection algorithm called Outstretch, which discovers the outlier movement patterns of the top-k spatial outliers over several time periods. The top-k spatial outliers are found using the Exact-Grid Top- k and Approx-Grid Top- k algorithms, which are an extension of algorithms developed by Agarwal et al. [1]. Since they use the Kulldorff spatial scan statistic, they are capable of discovering all outliers, unaffected by neighbouring regions that may contain missing values. After generating the outlier sequences, we show one way they can be interpreted, by comparing them to the phases of the El Niño Southern Oscilliation (ENSO) weather phenomenon to provide a meaningful analysis of the results.

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

    PubMed

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

    2010-06-01

    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; Chils 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 summary of the analysis. Supplemental material, including color versions of Figures 4, 5, 6, 7, and 8, and MCMC diagnostic plots, are available online. PMID:21113385

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

    PubMed Central

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

    2011-01-01

    Multichannel electroencephalography (EEG) offers a non-invasive tool to explore spatio-temporal dynamics of brain activity. With EEG recordings consisting of multiple trials, traditional signal processing approaches that ignore inter-trial variability in the data may fail to accurately estimate the underlying spatio-temporal brain patterns. Moreover, precise characterization of such inter-trial variability per se can be of high scientific value in establishing the relationship between brain activity and behavior. In this paper, a statistical modeling framework is introduced for learning spatiotemporal decomposition of multiple-trial EEG data recorded under two contrasting experimental conditions. By modeling the variance of source signals as random variables varying across trials, the proposed two-stage hierarchical Bayesian model is able to capture inter-trial amplitude variability in the data in a sparse way where a parsimonious representation of the data can be obtained. A variational Bayesian (VB) algorithm is developed for statistical inference of the hierarchical model. The efficacy of the proposed modeling framework is validated with the analysis of both synthetic and real EEG data. In the simulation study we show that even at low signal-to-noise ratios our approach is able to recover with high precision the underlying spatiotemporal patterns and the evolution of source amplitude across trials; on two brain-computer interface (BCI) data sets we show that our VB algorithm can extract physiologically meaningful spatio-temporal patterns and make more accurate predictions than other two widely used algorithms: the common spatial patterns (CSP) algorithm and the Infomax algorithm for independent component analysis (ICA). The results demonstrate that our statistical modeling framework can serve as a powerful tool for extracting brain patterns, characterizing trial-to-trial brain dynamics, and decoding brain states by exploiting useful structures in the data. PMID:21420499

  20. Spatio-temporal optical random number generator.

    PubMed

    Stip?evi?, 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

  1. 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

  2. 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.

  3. 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

  4. Spatio-temporal Dynamics of Audiovisual Speech Processing

    PubMed Central

    Bernstein, Lynne E.; Auer, Edward T.; Wagner, Michael; Ponton, Curtis W.

    2007-01-01

    The cortical processing of auditory-alone, visual-alone, and audiovisual speech information is temporally and spatially distributed, and functional magnetic resonance imaging (fMRI) cannot adequately resolve its temporal dynamics. In order to investigate a hypothesized spatio-temporal organization for audiovisual speech processing circuits, event-related potentials (ERPs) were recorded using electroencephalography (EEG). Stimuli were congruent audiovisual /b?/, incongruent auditory /b?/ synchronized with visual /g?/, auditory-only /b?/, and visual-only /b?/ and /g?/. Current density reconstructions (CDRs) of the ERP data were computed across the latency interval of 50-250 milliseconds. The CDRs demonstrated complex spatio-temporal activation patterns that differed across stimulus conditions. The hypothesized circuit that was investigated here comprised initial integration of audiovisual speech by the middle superior temporal sulcus (STS), followed by recruitment of the intraparietal sulcus (IPS), followed by activation of Broca's area (Miller and d'Esposito, 2005). The importance of spatio-temporally sensitive measures in evaluating processing pathways was demonstrated. Results showed, strikingly, early (< 100 msec) and simultaneous activations in areas of the supramarginal and angular gyrus (SMG/AG), the IPS, the inferior frontal gyrus, and the dorsolateral prefrontal cortex. Also, emergent left hemisphere SMG/AG activation, not predicted based on the unisensory stimulus conditions was observed at approximately 160 to 220 msec. The STS was neither the earliest nor most prominent activation site, although it is frequently considered the sine qua non of audiovisual speech integration. As discussed here, the relatively late activity of the SMG/AG solely under audiovisual conditions is a possible candidate audiovisual speech integration response. PMID:17920933

  5. Forecasting the Spatio-Temporal Dynamics of the Magnetosphere

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  6. A navigating system for ventilation network spatio-temporal control

    SciTech Connect

    Tominaga, Yuusaku

    1999-07-01

    This paper presents a navigation system for spatio-temporal control of mine ventilation network to help keep miners safe in mine emergency situations such as mine fire, spontaneous combustion, and gas emission. The system is composed of sensors, computer simulation and binary controllers. The ventilation sensors are placed in specific branches of the ventilation network to monitor ventilation parameters such as air velocity. The Horonai coal mine, Hokkaido, Japan is used as an example to illustrate the applicability of the navigation system as on and in providing a safe evacuation route and to estimate the time interval to achieve steady airflow on and in determining distribution in the network.

  7. Robust Sparse Blind Source Separation

    NASA Astrophysics Data System (ADS)

    Chenot, Cecile; Bobin, Jerome; Rapin, Jeremy

    2015-11-01

    Blind Source Separation is a widely used technique to analyze multichannel data. In many real-world applications, its results can be significantly hampered by the presence of unknown outliers. In this paper, a novel algorithm coined rGMCA (robust Generalized Morphological Component Analysis) is introduced to retrieve sparse sources in the presence of outliers. It explicitly estimates the sources, the mixing matrix, and the outliers. It also takes advantage of the estimation of the outliers to further implement a weighting scheme, which provides a highly robust separation procedure. Numerical experiments demonstrate the efficiency of rGMCA to estimate the mixing matrix in comparison with standard BSS techniques.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  9. 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.

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

    PubMed Central

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

    2014-01-01

    A common method to explore the somatosensory function of the brain is to relate skin stimuli to neurophysiological recordings. However, interaction with the skin involves complex mechanical effects. Variability in mechanically induced spike responses is likely to be due in part to mechanical variability of the transformation of stimuli into spiking patterns in the primary sensors located in the skin. This source of variability greatly hampers detailed investigations of the response of the brain to different types of mechanical stimuli. A novel stimulation technique designed to minimize the uncertainty in the strain distributions induced in the skin was applied to evoke responses in single neurons in the cat. We show that exposure to specific spatio-temporal stimuli induced highly reproducible spike responses in the cells of the cuneate nucleus, which represents the first stage of integration of peripheral inputs to the brain. Using precisely controlled spatio-temporal stimuli, we also show that cuneate neurons, as a whole, were selectively sensitive to the spatial and to the temporal aspects of the stimuli. We conclude that the present skin stimulation technique based on localized differential tractions greatly reduces response variability that is exogenous to the information processing of the brain and hence paves the way for substantially more detailed investigations of the brain's somatosensory system. PMID:24451390

  11. 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.

  12. Spatio-temporal Variability of Nitrate Across Scales in Texas Aquifers

    NASA Astrophysics Data System (ADS)

    Dwivedi, D.; Mohanty, B. P.

    2010-12-01

    Nitrate (NO3-) is considered the most prevalent contaminant in groundwater (GW). NO3- in GW shows significant spatio-temporal variability which comes from interaction among multiple geophysical factors such as source availability (land use), thickness and composition of the vadose zone, types of aquifers (confined or unconfined), aquifer heterogeneity (geological and alluvial), and precipitation characteristics etc. The present work seeks to describe the spatio-temporal variability of NO3- at multiple scales in two different hydrogeologic settings the Trinity and Ogallala Aquifers in Texas at three spatial scales, fine (25 km.25 km.), intermediate (50 km.50 km.), and coarse (100 km.100 km.) grids. An entropy-based approach was used to analyze spatial-temporal variability of NO3- within the aquifers. The Hurst exponent was used to evaluate the long-term persistence and trend in the variability of NO3-. The results demonstrate that the spatial variability of NO3- is controlled by the effect of soil type, irrigation-pumping, and local flow at the small scale and by the complex interactions between rivers and aquifers along with land use at the intermediate scale, and by lithology and geology at the coarse scale. The trends of variability of NO3- show long term persistence at the intermediate and coarse scales.

  13. Multiscale recurrence analysis of spatio-temporal data.

    PubMed

    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. PMID:26723150

  14. 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.

  15. 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.

  16. Spatio-temporal habitat heterogeneity across an Alpine stream system

    NASA Astrophysics Data System (ADS)

    Dickson, N.; Brown, L. E.; Carrivick, J. L.; Fureder, L.

    2009-04-01

    Alpine stream systems provide unique habitats for riverine biota as a result of their dynamic flow, water temperature and suspended sediment regimes. Understanding how these spatio-temporal physicochemical variations influence macroinvertebrate communities could provide insights into how alpine lotic ecosystems are likely to respond to climate change or other more direct human influences (abstraction/regulation). However, detailed year-round data sets are rare for alpine stream systems, yet such knowledge is clearly a prerequisite to obtaining a holistic understanding of how these ecosystems function. This paper reports findings from year-round data collection at the Odenwinkelkees Glacier braidplain, Austrian Alps. Repeat aerial photography showed that the extent of flowing channels varied both diurnally and seasonally primarily as a consequence of meltwater pulses. Analysis of physicochemical data revealed high heterogeneity of flow regimes, water temperature and turbidity both spatially (reach to basin-scale) and temporally. For example the average discharge and turbidity were lower for predominantly groundwater-fed sites compared with meltwater-fed channels but water temperature was higher. This heterogeneity appears to play a key ‘filtering' role underpinning spatio-temporal patterns of benthic macroinvertebrates.

  17. Spatio-temporal prediction and inference by V1 neurons.

    PubMed

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

    2007-08-01

    In normal vision, visual scenes are predictable, as they are both spatially and temporally redundant. Evidence suggests that the visual system may use the spatio-temporal regularities of the external world, available in the retinal signal, to extract information from the visual environment and better reconstruct current and future stimuli. We studied this by recording neuronal responses of primary visual cortex (area V1) in anaesthetized and paralysed macaques during the presentation of dynamic sequences of bars, in which spatio-temporal regularities and local information were independently manipulated. Most V1 neurons were significantly modulated by events prior to and distant from stimulation of their classical receptive fields (CRFs); many were more strongly tuned to prior and distant events than they were to CRFs bars; and several showed tuning to prior information without any CRF stimulation. Hence, V1 neurons do not simply analyse local contours, but impute local features to the visual world, on the basis of prior knowledge of a visual world in which useful information can be distributed widely in space and time. PMID:17714195

  18. 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.

  19. 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

  20. Combinatorial binding predicts spatio-temporal cis-regulatory activity.

    PubMed

    Zinzen, Robert P; Girardot, Charles; Gagneur, Julien; Braun, Martina; Furlong, Eileen E M

    2009-11-01

    Development requires the establishment of precise patterns of gene expression, which are primarily controlled by transcription factors binding to cis-regulatory modules. Although transcription factor occupancy can now be identified at genome-wide scales, decoding this regulatory landscape remains a daunting challenge. Here we used a novel approach to predict spatio-temporal cis-regulatory activity based only on in vivo transcription factor binding and enhancer activity data. We generated a high-resolution atlas of cis-regulatory modules describing their temporal and combinatorial occupancy during Drosophila mesoderm development. The binding profiles of cis-regulatory modules with characterized expression were used to train support vector machines to predict five spatio-temporal expression patterns. In vivo transgenic reporter assays demonstrate the high accuracy of these predictions and reveal an unanticipated plasticity in transcription factor binding leading to similar expression. This data-driven approach does not require previous knowledge of transcription factor sequence affinity, function or expression, making it widely applicable. PMID:19890324

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

    PubMed

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

    2013-11-01

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

  2. Spatio-temporal brain activation profiles associated with line bisection judgments and double simultaneous visual stimulation.

    PubMed

    Billingsley, R L; Simos, P G; Sarkari, S; Fletcher, J M; Papanicolaou, A C

    2004-06-01

    We used magnetic source imaging (MSI) to investigate the spatio-temporal patterns of brain activity associated with line bisection judgments and double simultaneous visual stimulation in 14 healthy adults. Consistent with lesion and hemodynamic neuroimaging studies, we found the greatest number of activity sources in right inferior parietal cortex. These sources were most prominent, on average, between 200 and 300 ms after the onset of single (left, right, or center) target stimuli. A greater number of significant activity sources were found in right inferior parietal, occipital, and prefrontal cortices during bilateral compared with unilateral stimulus presentation. Based on these observations, we suggest that a more parsimonious physiological explanation of visual extinction than the hemispheric rivalry account may be the additional neuronal excitation required in right occipital and parietal cortices for accurate bilateral visual perception. PMID:15135973

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Distributed spatio-temporal outlier detection in sensor networks

    NASA Astrophysics Data System (ADS)

    Jun, Minwook C.; Jeong, H.; Kuo, C.-C. J.

    2005-06-01

    A spatio-temporal filtering method is proposed to detect outliers in wireless sensor networks in this work. Outliers are assumed to be uncorrelated in time and space, and modeled as an alpha-stable distribution. The proposed algorithm consists of collaborative time-series estimation, variogram application, and principle component analysis (PCA). It is realized on self-organized clusters that can manage the data locally. Conceptually, each node detects any temporally abnormal data and transmits the rectified data to a local cluster-head, which detects any survived spatial outliers and determines the faulty sensors accordingly. As a result, faulty sensors do not burden the sink to achieve the following two goals simultaneously, i.e., enhancing the data quality and reducing the communication cost in wireless sensor networks. It is demonstrated that the maximum outlier detection rate is around 94% when the noise level is alpha=0.9.

  5. Spatio-temporal distribution of malaria in Yunnan Province, China.

    PubMed

    Hui, Feng-Ming; Xu, Bing; Chen, Zhang-Wei; Cheng, Xiao; Liang, Lu; Huang, Hua-Bing; Fang, Li-Qun; Yang, Hong; Zhou, Hong-Ning; Yang, Heng-Lin; Zhou, Xiao-Nong; Cao, Wu-Chun; Gong, Peng

    2009-09-01

    The spatio-temporal distribution pattern of malaria in Yunnan Province, China was studied using a geographic information system technique. Both descriptive and temporal scan statistics revealed seasonal fluctuation in malaria incidences in Yunnan Province with only one peak during 1995-2000, and two apparent peaks from 2001 to 2005. Spatial autocorrelation analysis indicated that malaria incidence was not randomly distributed in the province. Further analysis using spatial scan statistics discovered that the high risk areas were mainly clustered at the bordering areas with Myanmar and Laos, and in Yuanjiang River Basin. There were obvious associations between Plasmodium vivax and Plasmodoium falciparum malaria incidences and climatic factors with a clear 1-month lagged effect, especially in cluster areas. All these could provide information on where and when malaria prevention and control measures would be applied. These findings imply that countermeasures should target high risk areas at suitable times, when climatic factors facilitate the transmission of malaria. PMID:19706922

  6. 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.

  7. Spatio-temporal environmental data tide corrections for reconnaissance operations

    NASA Astrophysics Data System (ADS)

    Barbu, Costin; Avera, Will; Harris, Mike; Malpass, Kevyn

    2005-06-01

    Dynamic, accurate near-real time environmental data is critical to the success of the mine countermeasures operations. Bathymetric data acquired from the AQS-20 mine hunting sensor should be adjusted for local tide variations related to the specific geographic area and time interval. This problem can be overcome by a spatio-temporal estimate of tide corrections provided for the area and time of interest by the Naval Research Laboratory tide prediction code PCTides. For each geographic position of the AQS-20 sonar, a tide height relative to mean sea level is computed by interpolating the tidal information from the K - nearest neighbored stations for the corresponding time. The value is used to correct the measured depth generated by the AQS-20 sonar in that location to mean sea level for fusion with other bathymetric data products. It is argued that this paper provides a useful tool to the MCM decision factors during Mine Warfare operations.

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

  9. 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 neighbors position in terms of coordinates based on each individuals 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

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

    PubMed

    Mosquera-Fernndez, M; Rodrguez-Lpez, 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

  11. 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.

  12. 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??s 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}?{sub u} ? B{sup 3}?{sub g} transition for nitrogen. In addition, the capacitances in parallel connected with the discharge cell have important influence on the pulsing frequency.

  13. 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), 501-510, 1997. [3] N.D. Le, and J.V. Zidek, Statistical analysis of environmental space-time processes, Springer Verlag, (2006), PP. 272-294

  14. 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.

  15. SPATIO-TEMPORAL COMPLEXITY OF THE AORTIC SINUS VORTEX

    PubMed Central

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-01-01

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

  16. 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-sensitive vector-borne diseases. PMID:26154506

  17. Modeling directional spatio-temporal processes in island biogeography.

    PubMed

    Carvalho, Jos C; Cardoso, Pedro; Rigal, Franois; Triantis, Kostas A; Borges, Paulo A V

    2015-10-01

    A key challenge in island biogeography is to quantity the role of dispersal in shaping biodiversity patterns among the islands of a given archipelago. Here, we propose such a framework. Dispersal within oceanic archipelagos may be conceptualized as a spatio-temporal process dependent on: (1) the spatial distribution of islands, because the probability of successful dispersal is inversely related to the spatial distance between islands and (2) the chronological sequence of island formation that determines the directional asymmetry of dispersal (hypothesized to be predominantly from older to younger islands). From these premises, directional network models may be constructed, representing putative connections among islands. These models may be translated to eigenfunctions in order to be incorporated into statistical analysis. The framework was tested with 12 datasets from the Hawaii, Azores, and Canaries. The explanatory power of directional network models for explaining species composition patterns, assessed by the Jaccard dissimilarity index, was compared with simpler time-isolation models. The amount of variation explained by the network models ranged from 5.5% (for Coleoptera in Hawaii) to 60.2% (for Pteridophytes in Canary Islands). In relation to the four studied taxa, the variation explained by network models was higher for Pteridophytes in the three archipelagos. By the contrary, small fractions of explained variation were observed for Coleoptera (5.5%) and Araneae (8.6%) in Hawaii. Time-isolation models were, in general, not statistical significant and explained less variation than the equivalent directional network models for all the datasets. Directional network models provide a way for evaluating the spatio-temporal signature of species dispersal. The method allows building scenarios against which hypotheses about dispersal within archipelagos may be tested. The new framework may help to uncover the pathways via which species have colonized the islands of a given archipelago and to understand the origins of insular biodiversity. PMID:26668731

  18. 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

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

    NASA Astrophysics Data System (ADS)

    Thiel, Martin; Hinojosa, Ivn 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.

  20. 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

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

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  4. 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.

  5. 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

  6. Spatio-temporal distribution of human lifespan in China

    NASA Astrophysics Data System (ADS)

    Wang, Shaobin; Luo, Kunli; Liu, Yonglin

    2015-09-01

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

  7. Spatio-temporal distribution of human lifespan in China.

    PubMed

    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

  8. Spatio-temporal expression of chromogranin A during zebrafish embryogenesis.

    PubMed

    Xie, Jing; Wang, Wei-Qing; Liu, Ting-Xi; Deng, Min; Ning, Guang

    2008-09-01

    Chromogranin A (CHGA), a protein participating in the biogenesis of dense core secretory granules in various neuroendocrine tissues, plays a critical role in the release of hormones/peptides and the pathogenesis of pheochromocytoma. However, little is known about the developmental origin of CHGA-expressing cells during embryogenesis. Here, we report the structural characterization and spatio-temporal expression pattern of zebrafish (Danio rerio) ortholog of mammalian CHGA. The earliest expression of chga transcripts was observed at 16 h post fertilization in the developing cranial ganglia as six distinct cellular masses arranged bilaterally as strings of beads in the dorsal root ganglia (DRG) precursors along the dorsal trunk. With development advancing, the chga transcripts were expressed abundantly in diencephalon, mesencephalon, and rhombencephalon as well as in the DRG. Interestingly, double in situ hybridization assay of chga with genes expressed in pronephros (Wilms' tumor suppressor 1, wt1), adrenal cortex (side-chain cleavage enzyme, scc), and sympathoadrenal neuron/chromaffin cell (dopamine-beta-hydroxylase, dbh), respectively, showed that the chga-expressing cells are spatially separated from wt1-, scc-, and dbh-positive cell populations during early embryonic development. The pronephros region does not express chga even up to 7 days post fertilization, while chga positive-staining cells bind in the brain and DRG, indicating that chga may play an important role in nervous system development during the early embryonic stages. PMID:18586978

  9. 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

  10. Stability and dynamics of spatio-temporal structures

    SciTech Connect

    Riecke, H.

    1993-03-01

    The main goal of the project supported in this grant is to contribute to the understanding of localized spatial and spatio-temporal structures far from thermodynamic equilibrium. Here we report on our progress in the study of two classes of systems. (1) We have started to investigate localized wave-pulses in binary-mixture convection. This work is based on our recently derived extension of the conventionally used complex Ginzburg-Landau equations. We are considering three regimes: Dispersion-less supercritical waves; strongly dispersive subcritical waves; and localized waves as bound states of fronts between dispersionless subcritical waves and the motionless conductive state. (2) We have completed our investigation of steady domain structures in which domains of structures with different wave numbers alternate, separated by domain walls. In particular, we have studied their regimes of existence and stability within the framework of a Ginzburg-Landau equation and have compared it to previous results. Those were based on a long-wavelength approximation, which misses certain aspects which turn out to be important for the stability of the domain structures in realistic situations. In addition, we give a description of our work on resonantly forced waves in two-dimensional anisotropic systems.

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

    SciTech Connect

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

    1989-01-01

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

  12. Spatio-temporal data fusion for remote sensing applications

    NASA Astrophysics Data System (ADS)

    Nguyen, H. M.; Katzfuss, M.; Cressie, N.; Braverman, A. J.

    2011-12-01

    No single remote-sensing instrument currently provides measurements of the CO2 concentration near the surface, but inferences can be made by considering a weighted difference of total column CO2 concentration observed by the Greenhouse gases Observing Satellite (GOSAT) with mid-tropospheric CO2 concentration observed by the Atmospheric Infrared Sounder (AIRS). However, data from these two instruments have different resolutions and measurement-error characteristics. Furthermore, while daily data are sparse relative to the entire globe, the spatio-temporal domains are large and the AIRS dataset is massive. We describe a spatial-temporal data fusion methodology based on the Kalman filter and smoother that can combine complementary datasets to optimally estimate lower atmospheric CO2 concentration, properly handle spatial and temporal dependence, and estimate CO2 concentration in the data gaps. We show that predictions from our methodology match up well with validation data from NOAA. Our method is designed for massive remote sensing datasets and accounts for differences in instrument footprints and measurement-error characteristics.

  13. An object-relational spatio-temporal geoscience data model

    NASA Astrophysics Data System (ADS)

    Le, Hai Ha; Gabriel, Paul; Gietzel, Jan; Schaeben, Helmut

    2013-08-01

    A model for spatially and temporally indexed multi-dimensional geoscience data has been developed by first embedding a combinatorial topological model in terms of G-Maps in the domain RmTime(m?N), and then converting it into an object-relational model which can easily be implemented in an object-relational database system. Geoscience objects referring to space and time often have complex geometries which are usually partitioned into simpler cells and have geometrical, topological, geological, geophysical, geochemical and other relevant properties assigned to their cells. These objects may exist in a Euclidean space Rm of arbitrary dimension m depending on which properties are chosen as "coordinates", where usually m=3 and refers to three spatial dimensions, and evolve in one dimensional valid time (Time). The valid time is independent of geometry, topology and properties but not vice versa, i.e., the geometry of an object, for example, and all its properties are modeled as functions of the valid time. Then the objects are assumed to be sampled at arbitrary but fixed instances of time, and their evolution between these instances is modeled by appropriate interpolation. The structure of the data model is well adapted to the interpolation required to represent the objects in between the instances of their observation. The data model provides the basis prerequisite of our envisioned spatio-temporal geoscience information system.

  14. Spatio-Temporal Analysis of Early Brain Development.

    PubMed

    Sadeghi, Neda; Prastawa, Marcel; Gilmore, John H; Lin, Weili; Gerig, Guido

    2010-01-01

    Analysis of human brain development is a crucial step for improved understanding of neurodevelopmental disorders. We focus on normal brain development as is observed in the multimodal longitudinal MRI/DTI data of neonates to two years of age. We present a spatio-temporal analysis framework using Gompertz function as a population growth model with three different spatial localization strategies: voxel-based, data driven clustering and atlas driven regional analysis. Growth models from multimodal imaging channels collected at each voxel form feature vectors which are clustered using the Dirichlet Process Mixture Models (DPMM). Clustering thus combines growth information from different modalities to subdivide the image into voxel groups with similar properties. The processing generates spatial maps that highlight the dynamic progression of white matter development. These maps show progression of white matter maturation where primarily, central regions mature earlier compared to the periphery, but where more subtle regional differences in growth can be observed. Atlas based analysis allows a quantitative analysis of a specific anatomical region, whereas data driven clustering identifies regions of similar growth patterns. The combination of these two allows us to investigate growth patterns within an anatomical region. Specifically, analysis of anterior and posterior limb of internal capsule show that there are different growth trajectories within these anatomies, and that it may be useful to divide certain anatomies into subregions with distinctive growth patterns. PMID:25328368

  15. 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

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

    NASA Astrophysics Data System (ADS)

    Bhringer, Klaus; Hess, Ortwin

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

  17. Association rule mining based on spatio-temporal processes of spatial distribution patterns

    NASA Astrophysics Data System (ADS)

    Zhang, Xuewu; Su, Fenzhen; Shi, Yishao; He, Yawen

    2008-12-01

    Spatial distribution pattern is an arrangement of two or more spatial objects according to some spatial relations, such as spatial direction, topological and distance relations. In the real world, spatial objects and spatial distribution pattern all vary continuously along the time-line. Traditional spatial and non-spatial data dissevers this continuous spatio-temporal process. Under analyzing relations among spatial object, its attributes and spatial distribution pattern, we brought metaspatio- temporal process, spatio-temporal process and spatial distribution pattern spatio-temporal process. Rainfall in Eastern China has a typical spatial distribution pattern, being composed of the northern rain area and the southern rain area. Through constructing spatio-temporal process transactions, the association rules can be extracted from spatiotemporal process data set by the Apriori algorithm. The result of the spaio-temporal process association rule mining is consistent with the analysis of the theory. Finally, it is concluded that the spatio-temporal process can describe change of a spatial object in a defined time range, and change trend of one entity can be forecasted through varying trend of others based on the valuable spatio-temporal process association rules.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  19. Spatio-Temporal 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

  20. Spatio-temporal drought forecasting within Bayesian networks

    NASA Astrophysics Data System (ADS)

    Madadgar, Shahrbanou; Moradkhani, Hamid

    2014-05-01

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

  1. Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters

    PubMed Central

    Suk, Heung-Il; Fazli, Siamac; Mehnert, Jan; Mller, Klaus-Robert; Lee, Seong-Whan

    2014-01-01

    Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI) has become increasingly popular. In this work, we discuss a novel, fully Bayesianand thereby probabilisticframework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO) and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythmsa phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject prototypes (like ? - or ? -rhythm type subjects) or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session. PMID:24551050

  2. 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.

  3. Spatio-temporal coupling of EEG signals in epilepsy

    NASA Astrophysics Data System (ADS)

    Senger, Vanessa; Mller, 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.

  4. 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 Lbrea 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, verify that distances between the deforestation warning and the roads explain part of the significant clustering.

  5. 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

  6. The spatio-temporal signatures of category-selective responses to natural images as evidenced with fast periodic visual stimulation.

    PubMed

    Jacques, Corentin; Retter, Talia; Rossion, Bruno

    2015-01-01

    Humans are extremely rapid at categorizing visual inputs, an ability which relies on occipito-temporal brain processes. Functional neuroimaging studies have identified the spatial organization of neural responses in these regions to ecologically-relevant categories such as faces, bodyparts or houses. However, much less is known about the spatio-temporal dynamics of these category-selective responses at the system level of organization. Here we investigate this issue by recording scalp electroencephalogram (EEG) during fast periodic visual stimulation (FPVS) with natural images (Rossion et al., 2015). Eleven subjects viewed 60 seconds sequences of natural images of various object categories displayed at a base frequency of 6 Hz (6 images/second), in which images of either faces, bodyparts or houses appeared every 5 images (oddball frequency =6Hz/5 =1.2Hz). Category-selective oddball responses manifest at the 1.2Hz oddball frequency and harmonics (2.4Hz, 3.6Hz, etc.). While significant oddball responses were observed for all categories over occipito-temporal regions, responses were much stronger for faces than for limbs and houses. Further, scalp topography pattern analyses point to distinct neural sources across category-selective responses, with responses to faces, bodyparts and houses respectively maximal at ventral occipito-temporal, lateral occipito-temporal, and dorso-medial occipital channels. Time-domain analyses indicate that EEG responses are dissociable across categories at multiple spatio-temporal windows from around 110ms to 500ms post-stimulus onset, with faces eliciting up to five distinct selective responses. These observations go well beyond traditional face-selective EEG responses as identified using transient stimulus presentation (i.e., N170) by indicating that multiple ecologically-relevant categories generate unique spatio-temporal signatures over posterior scalp regions. Finally, these findings highlight the power of the FPVS approach to reveal the spatio-temporal signatures of high-level visual processing at the system level. Rossion, B., et al. (2015). Fast periodic presentation of natural images reveals a robust face-selective electrophysiological response in the human brain. Journal of Vision. Meeting abstract presented at VSS 2015. PMID:26326380

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

    NASA Astrophysics Data System (ADS)

    de Lavenne, Alban; Cudennec, Christophe

    2013-04-01

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

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

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

    PubMed Central

    Caucci, Luca; Barrett, Harrison H.; Rodrguez, 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

  10. 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

  11. 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.

  12. 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.

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

    PubMed

    Qi, Feifei; Li, Yuanqing; Wu, Wei

    2015-12-01

    Learning optimal spatio-temporal filters is a key to feature extraction for single-trial electroencephalogram (EEG) classification. The challenges are controlling the complexity of the learning algorithm so as to alleviate the curse of dimensionality and attaining computational efficiency to facilitate online applications, e.g., brain-computer interfaces (BCIs). To tackle these barriers, this paper presents a novel algorithm, termed regularized spatio-temporal filtering and classification (RSTFC), for single-trial EEG classification. RSTFC consists of two modules. In the feature extraction module, an l2 -regularized algorithm is developed for supervised spatio-temporal filtering of the EEG signals. Unlike the existing supervised spatio-temporal filter optimization algorithms, the developed algorithm can simultaneously optimize spatial and high-order temporal filters in an eigenvalue decomposition framework and thus be implemented highly efficiently. In the classification module, a convex optimization algorithm for sparse Fisher linear discriminant analysis is proposed for simultaneous feature selection and classification of the typically high-dimensional spatio-temporally filtered signals. The effectiveness of RSTFC is demonstrated by comparing it with several state-of-the-arts methods on three brain-computer interface (BCI) competition data sets collected from 17 subjects. Results indicate that RSTFC yields significantly higher classification accuracies than the competing methods. This paper also discusses the advantage of optimizing channel-specific temporal filters over optimizing a temporal filter common to all channels. PMID:25730834

  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. 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.

  16. In-situ image data capturing and spatio-temporal data management in the context of a multi-hazard risk assessment

    NASA Astrophysics Data System (ADS)

    Wieland, Marc; Pittore, Massimiliano

    2014-05-01

    Monitoring of the spatio-temporal variability of exposure and vulnerability indicators for risk assessments is dependent not only on the amount and quality of the data upon which the assessment is made, but also on the tools and methodologies employed to capture, store, manage and analyse the information. Spatio-temporal changes need to be properly integrated into a sound, comprehensive conceptual and methodological framework, which is able to deal with multi-dimensional data coming from different sources, at varying scales and changing over time. Commonly used approaches to capture data about an exposed building stock with respect to its physical characteristics and vulnerability usually entail a detailed (inside and outside) screening of buildings by structural engineers. These approaches are often not suitable for the rapidly changing spatio-temporal conditions in many present-day cities, and moreover do not often scale well with end-user's limited resource allocation. Also purely satellite-based approaches, which are used as time- and cost-effective alternative, show limitations in that they are only capable of providing information about vulnerability-related characteristics that can be assessed from the top view. This work, therefore, introduces a methodological and technical framework to combine remote sensing with in-situ image data capturing to overcome the limitations of previous approaches. A novel mobile mapping system and Remote Rapid Visual Screening (RRVS) technique based on omnidirectional imaging is presented. A key objective of this work is, moreover, to present a prototype spatio-temporal database system that functions as basis for the storage and management of data from different sources, at varying scales and changing over time. Examples from our study sites in Central Asia and Germany will be presented to highlight the application of the proposed approach.

  17. 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.

  18. An accessible method for implementing hierarchical models with spatio-temporal abundance data.

    PubMed

    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

  19. Spatio-temporal dynamics of nutrients in the upper Han River basin, China.

    PubMed

    Li, Siyue; Liu, Wenzhi; Gu, Sheng; Cheng, Xiaoli; Xu, Zhifang; Zhang, Quanfa

    2009-03-15

    The upper Han River basin with an area of approximately 95,000 km(2), is the water source area of the Middle Route of China's South to North Water Transfer Project. Thus, water quality in the basin's river network is of great importance. Nutrients including dissolved inorganic nitrogen (DIN), NO(3)(-)-N, NH(4)(+)-N, and dissolved phosphorus (DP) were analyzed in 41 sites during the period of 2005-2006. Cluster analysis (CA), analysis of variance (ANOVA) and general linear models (GLM) were performed to explore their spatio-temporal variations in the basin. The results revealed that the DIN, NO(3)(-)-N and NH(4)(+)-N increased over the 2 year study period, and their concentrations in the wet season was higher than those in the dry season. The seasonal variation in nitrogen was strongly associated with seasonal pattern of precipitation and there was a negative relationship between DP concentration and river flow. Cluster analysis indicated high nutrient contents in the urban and agricultural production areas. The research will help articulate water resource management strategy for the interbasin water transfer project. PMID:18675508

  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. The early spatio-temporal correlates and task independence of cerebral voice processing studied with MEG.

    PubMed

    Capilla, Almudena; Belin, Pascal; Gross, Joachim

    2013-06-01

    Functional magnetic resonance imaging studies have repeatedly provided evidence for temporal voice areas (TVAs) with particular sensitivity to human voices along bilateral mid/anterior superior temporal sulci and superior temporal gyri (STS/STG). In contrast, electrophysiological studies of the spatio-temporal correlates of cerebral voice processing have yielded contradictory results, finding the earliest correlates either at ?300-400 ms, or earlier at ?200 ms ("fronto-temporal positivity to voice", FTPV). These contradictory results are likely the consequence of different stimulus sets and attentional demands. Here, we recorded magnetoencephalography activity while participants listened to diverse types of vocal and non-vocal sounds and performed different tasks varying in attentional demands. Our results confirm the existence of an early voice-preferential magnetic response (FTPVm, the magnetic counterpart of the FTPV) peaking at about 220 ms and distinguishing between vocal and non-vocal sounds as early as 150 ms after stimulus onset. The sources underlying the FTPVm were localized along bilateral mid-STS/STG, largely overlapping with the TVAs. The FTPVm was consistently observed across different stimulus subcategories, including speech and non-speech vocal sounds, and across different tasks. These results demonstrate the early, largely automatic recruitment of focal, voice-selective cerebral mechanisms with a time-course comparable to that of face processing. PMID:22610392

  2. Low-complexity algorithms for spatio-temporal directional spectrum sensing with applications in cognitive radio

    NASA Astrophysics Data System (ADS)

    Madanayake, Arjuna; Wijenayake, Chamith; Potluri, Uma; Abeysekara, Judith; Mugler, Dale

    2013-05-01

    A suit of low complexity signal processing algorithms are identified for the directional spectrum sensing and two-dimensional (2-D) spatio-temporal white space detection in cognitive radio systems. The concept of spectral white spaces in 2-D spatio-temporal frequency space is reviewed based on the specific spectral properties of 2-D spatio-temporal array signals. The proposed system contains an array processing stage, magnitude-fast-Fourier-transform (FFT) stage followed by an energy detection stage. The use of 2-D infinite impulse response (IIR) filters having beam-shaped passbands in the 2-D frequency space is identi_ed as a low complexity solution for the array processing stage for the directional enhancement of radio signals. A low complexity algorithm that delivers the magnitude FFT is described for the 16-point case and computational complexity is expressed in closed-form.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  5. Spatio-temporal light springs: extended encoding of orbital angular momentum in ultrashort pulses.

    PubMed

    Pariente, G; Qur, F

    2015-05-01

    We introduce a new class of spatio-temporally coupled ultrashort laser beams, which are obtained by superimposing Laguerre-Gauss beams whose azimuthal mode index is correlated to their frequency. These beams are characterized by helical structures for their phase and intensity profiles, which both encode the orbital angular momentum carried by the light. They can easily be engineered in the optical range, and are naturally produced at shorter wavelengths when attosecond pulses are generated by intense femtosecond Laguerre-Gauss laser beams. These spatio-temporal "light springs" will allow for the transfer of the orbital angular momentum to matter by stimulated Raman scattering. PMID:25927778

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. 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.

  8. 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.

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

    SciTech Connect

    Risti?-Fira, A.; Bulat, T.; Keta, O.; Petrovi?, 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 (?-rays) and high (protons) linear energy transfer, the kinetics of disappearance of the phosphorylated histone H2AX (?-H2AX) foci per cell will be determined. The same procedure will be performed with the pulsed high dose rate protons. Detection and quantification of ?-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 ?-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.

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2002-02-01

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

  13. 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...

  14. 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.

  15. On fitting spatio-temporal disease mapping models using approximate Bayesian inference.

    PubMed

    Ugarte, Mara Dolores; Adin, Aritz; Goicoa, Tomas; Militino, Ana Fernandez

    2014-12-01

    Spatio-temporal disease mapping comprises a wide range of models used to describe the distribution of a disease in space and its evolution in time. These models have been commonly formulated within a hierarchical Bayesian framework with two main approaches: an empirical Bayes (EB) and a fully Bayes (FB) approach. The EB approach provides point estimates of the parameters relying on the well-known penalized quasi-likelihood (PQL) technique. The FB approach provides the posterior distribution of the target parameters. These marginal distributions are not usually available in closed form and common estimation procedures are based on Markov chain Monte Carlo (MCMC) methods. However, the spatio-temporal models used in disease mapping are often very complex and MCMC methods may lead to large Monte Carlo errors and a huge computation time if the dimension of the data at hand is large. To circumvent these potential inconveniences, a new technique called integrated nested Laplace approximations (INLA), based on nested Laplace approximations, has been proposed for Bayesian inference in latent Gaussian models. In this paper, we show how to fit different spatio-temporal models for disease mapping with INLA using the Leroux CAR prior for the spatial component, and we compare it with PQL via a simulation study. The spatio-temporal distribution of male brain cancer mortality in Spain during the period 1986-2010 is also analysed. PMID:24713158

  16. An integrated environment for spatio-temporal analysis, simulation, and representation for public health research

    NASA Astrophysics Data System (ADS)

    Hu, Haitang; Bao, Shuming; Xu, Bing; Liang, Song

    2006-10-01

    Geographic space, as the arena within which all of the natural and social processes occur, and time, have become key research components of social science for the past two decades. However, most GIS software packages lack the predictive and analytic capabilities for complex problems, such as spatial statistical methods and spatial modeling. Meanwhile, the spatio-temporally explicit representation of complex, heterogeneous and dynamic geographic data sets is a particularly challenging issue. Many efforts have been made in developing tools for effective representation of health data, spatio-temporal analysis of the data, and the dynamic process simulation of disease transmission. To meet this demand, we attempted to develop a tool for integrating spatio-temporal analysis, simulation and representation of health data and processes. In this paper, we will introduce some methods for spatial temporal data analysis and their applications in public health. We'll describe the conceptual model of spatial temporal process simulation and the process-oriented spatio-temporal data model adopted in the tool we developed. After that, we'll present the framework of our integrated research toolkit, and demonstrate how to conduct analysis, modeling, and simulation with this software. Finally, we will discuss some issues for future studies.

  17. Design and implementation of spatio-temporal database of water and soil loss

    NASA Astrophysics Data System (ADS)

    Lu, XinHai; Bian, Fulin; Tan, Xiaojun

    2008-12-01

    This paper analyzed the features and limitations of several typical spatio-temporal data models. "spatio-temporal cube": the main disadvantage is that the target change will produce great data redundancy when under non-consecutive circumstances. "Snapshots": it repeatedly saves graphics and attribute of no changes which resulted in waste of storage spaces, and it is impossible to reflect space objects under the same domain and the relationship between the attributes. "Base State with Amendments": merely modify changing object, but it's not suitable for continuous variation space object. "space-frame composite": currently, the model is lacking of sound framework structure and application model. "Object-oriented spatio-temporal model": The modeling concept, theoretical foundation and technical realization has not yet reached a consensus, it's not mature enough. In allusion to the features of the spatial database of water and soil loss, this essay expounded the characteristics of spatiotemporal databases. Spatial features in many practical circumstances ( such as thematic maps in soil and water conservation projects and space elements of soil erosion distribution map) have spatial data features, and also change with time, consequently, required us to establish spatio-temporal database, STDB, which can capture time data and space data at the same time. This analysis based on "ArcSDE versioning mechanisms" temporal and spatial database implement technologies, discussed the construction methods, process and data features of the database, and introduced the implementation of historical data rebuilding and version merging.

  18. Evaluating the impact of spatio-temporal scale on CPUE standardization

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

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

    PubMed Central

    Sa?lam, Blent; Bilgili, Ertu?rul; Durmaz, Bahar Din; Kad?o?ullar?, Ali ?hsan; Kk, mer

    2008-01-01

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

  20. 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

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

    PubMed

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

    2015-08-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  4. 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

  5. Analysis of air quality trace gas spatio-temporal variability over the USA using the WRF-chem regional model

    NASA Astrophysics Data System (ADS)

    Boynard, A.; Edwards, D. P.; Pfister, G.

    2010-12-01

    Ozone and carbon monoxide play key roles in the photo-chemical processes occurring in the atmosphere, with strong consequences for tropospheric chemistry, air quality and climate. Both molecules are highly variable, particularly in the troposphere, and need to be accurately monitored in order to provide a better insight into, for example, pollution episode development and pollution transport on regional to global scales. In this work, we analyse ozone and carbon monoxide concentrations simulated by the WRF chem regional model over the USA in order to characterize their geographical and temporal variations at the surface, in the lowermost troposphere and in the free troposphere along with their spatio-temporal correlations. In addition to model sensitivity studies, carbon monoxide tracers for different emission sources are used to differentiate the variability due to dynamics, photochemistry and emissions. We also present comparisons with surface measurements available from several ground-based stations over the USA.

  6. 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.

  7. Exploring spatio-temporal patterns of mortality using mixed effects models.

    PubMed

    Pickle, L W

    A linear mixed effects (LME) model previously used for a spatial analysis of mortality data for a single time period is extended to include time trends and spatio-temporal interactions. This model includes functions of age and time period that can account for increasing and decreasing death rates over time and age, and a change-point of rates at a predetermined age. A geographic hierarchy is included that provides both regional and small area age-specific rate estimates, stabilizing rates based on small numbers of deaths by sharing information within a region. The proposed log-linear analysis of rates allows the use of commercially available software for parameter estimation, and provides an estimator of overdispersion directly as the residual variance. Because of concerns about the accuracy of small area rate estimates when there are many instances of no observed deaths, we consider potential sources of error, focusing particularly on the similarity of likelihood inferences using the LME model for rates as compared to an exact Poisson-normal mixed effects model for counts. The proposed LME model is applied to breast cancer deaths which occurred among white women during 1979-1996. For this example, application of diagnostics for multiparameter likelihood comparisons suggests a restriction of age to a minimum of either 25 or 35, depending on whether small area rate estimates are required. Investigation into a convergence problem led to the discovery that the changes in breast cancer geographic patterns over time are related more to urbanization than to region, as previously thought. Published in 2000 by John Wiley & Sons, Ltd. PMID:10960851

  8. 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

  9. 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

  10. Blind source extraction using generalized autocorrelations.

    PubMed

    Shi, Zhenwei; Zhang, Changshui

    2007-09-01

    This letter addresses blind (semiblind) source extraction (BSE) problem when a desired source signal has temporal structures, such as linear or nonlinear autocorrelations. Using the temporal characteristics of sources, we develop objective functions based on the generalized autocorrelations of primary sources. Maximizing the objective functions, we propose simple fixed-point source extraction algorithms. We give the stability analysis and prove convergence properties of the algorithms as the generalized autocorrelation function is linear or nonlinear. Especially, as the generalized autocorrelation function is linear, the algorithm has interesting character of "one-iteration" convergence under some conditions. Computer simulations and real-data application experiments show that the algorithms are appealing BSE methods for temporal signals of interest by capturing the linear or nonlinear autocorrelations of the desired sources. PMID:18220199

  11. Spatio-temporal epidemiology of Campylobacter jejuni enteritis, in an area of Northwest England, 2000-2002.

    PubMed

    Gabriel, E; Wilson, D J; Leatherbarrow, A J H; Cheesbrough, J; Gee, S; Bolton, E; Fox, A; Fearnhead, P; Hart, C A; Diggle, P J

    2010-10-01

    A total of 969 isolates of Campylobacter jejuni originating in the Preston, Lancashire postcode district over a 3-year period were characterized using multi-locus sequence typing. Recently developed statistical methods and a genetic model were used to investigate temporal, spatial, spatio-temporal and genetic variation in human C. jejuni infections. The analysis of the data showed statistically significant seasonal variation, spatial clustering, small-scale spatio-temporal clustering and spatio-temporal interaction in the overall pattern of incidence, and spatial segregation in cases classified according to their most likely species-of-origin. PMID:20202286

  12. 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...

  13. Blind source separation by sparse decomposition

    NASA Astrophysics Data System (ADS)

    Zibulevsky, Michael; Pearlmutter, Barak A.

    2000-04-01

    The blind source separation problem is to extract the underlying source signals from a set of their linear mixtures, where the mixing matrix is unknown. This situation is common, eg in acoustics, radio, and medical signal processing. We exploit the property of the sources to have a sparse representation in a corresponding signal dictionary. Such a dictionary may consist of wavelets, wavelet packets, etc., or be obtained by learning from a given family of signals. Starting from the maximum a posteriori framework, which is applicable to the case of more sources than mixtures, we derive a few other categories of objective functions, which provide faster and more robust computations, when there are an equal number of sources and mixtures. Our experiments with artificial signals and with musical sounds demonstrate significantly better separation than other known techniques.

  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. 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 ? 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.

  17. 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.

  18. Reconstruction of dynamic PET data using spatio-temporal wavelet l(1) regularization.

    PubMed

    Verhaeghe, Jeroen; Van De Ville, Dimitri; Khalidov, Ildar; Unser, Michael; D'Asseler, Yves; Lemahieu, Ignace

    2007-01-01

    Tomographic reconstruction from PET data is an ill-posed problem that requires regularization. Recently, Daubechies et al. [1] proposed an l (1) regularization of the wavelet coefficients that can be optimized using iterative thresholding schemes. In this paper, we extend this approach for the reconstruction of dynamic (spatio-temporal) PET data. Instead of using classical wavelets in the temporal dimension, we introduce exponential-spline wavelets that are specially tailored to model time activity curves (TACs) in PET. We show the usefulness of spatio-temporal regularization and the superior performance of E-spline wavelets over conventional Battle-Lemari wavelets for a 1-D TAC fitting experiment and a tomographic reconstruction experiment. PMID:18003524

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

    NASA Astrophysics Data System (ADS)

    Rfrgier, 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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; Palu, Milan; Kurths, Jrgen

    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

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

    PubMed Central

    Mocenni, Chiara; Facchini, Angelo; Vicino, Antonio

    2010-01-01

    Complex spatio-temporal systems may exhibit irregular behaviors when driven far from equilibrium. Reaction-diffusion systems often lead to the formation of patterns and spatio-temporal chaos. When a limited number of observations is available, the reconstruction and identification of complex dynamical regimes become challenging problems. A method based on spatial recurrence properties is proposed to deal with this problem: generalized recurrence plots and generalized recurrence quantification analysis are exploited to show that detection of structural changes in spatially distributed systems can be performed by setting up appropriate diagrams accounting for different spatial recurrences. The method has been tested on two prototypical systems forming complex patterns: the complex GinzburgLandau equation and the Schnakenberg system. This work allowed us to identify changes in the stability of spiral wave solutions in the former system and to analyze the Turing bifurcations in the latter. PMID:20404202

  6. Chromatin Structure Exhibits Spatio-Temporal Heterogeneity within the Cell Nucleus

    PubMed Central

    Banerjee, Bidisha; Bhattacharya, Dipanjan; Shivashankar, G.V.

    2006-01-01

    Local chromatin compaction undergoes dynamic perturbations to regulate genetic processes. To address this, the direct measurement of the fluidity of chromatin structure is carried out in single live cells using steady-state anisotropy imaging and polarization modulation microscopy. Fluorescently tagged core and linker histones are used to probe different structural aspects of chromatin compaction. A graded spatial heterogeneity in compaction is observed for the chromatin besides the distinct positional ordering of core and linker histones. These spatio-temporal features are maintained by active processes and perturbed during death. With cell cycle, the distribution in compaction heterogeneity continually changes maximizing during M-G1 transition where it displays bimodal behavior. Such measurements of spatio-temporal chromatin fluidity could have broader implications in understanding chromatin remodeling within living cells. PMID:16815897

  7. A spatio-temporal absorbing state model for disease and syndromic surveillance.

    PubMed

    Heaton, Matthew J; Banks, David L; Zou, Jian; Karr, Alan F; Datta, Gauri; Lynch, James; Vera, Francisco

    2012-08-30

    Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data. PMID:22388709

  8. Multi-antenna spectrum sensing by exploiting spatio-temporal correlation

    NASA Astrophysics Data System (ADS)

    Ali, Sadiq; Ramrez, David; Jansson, Magnus; Seco-Granados, Gonzalo; Lpez-Salcedo, Jos A.

    2014-12-01

    In this paper, we propose a novel mechanism for spectrum sensing that leads us to exploit the spatio-temporal correlation present in the received signal at a multi-antenna receiver. For the proposed mechanism, we formulate the spectrum sensing scheme by adopting the generalized likelihood ratio test (GLRT). However, the GLRT degenerates in the case of limited sample support. To circumvent this problem, several extensions are proposed that bring robustness to the GLRT in the case of high dimensionality and small sample size. In order to achieve these sample-efficient detection schemes, we modify the GLRT-based detector by exploiting the covariance structure and factoring the large spatio-temporal covariance matrix into spatial and temporal covariance matrices. The performance of the proposed detectors is evaluated by means of numerical simulations, showing important advantages over existing detectors.

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

    NASA Astrophysics Data System (ADS)

    Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko

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

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

    Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.

  13. 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

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Snchez-Garduo, Faustino; Brea-Medina, Vctor 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.

  16. 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

  17. Spatio-temporal modelling of disease incidence with missing covariate values.

    PubMed

    Holland, R C; Jones, G; Benschop, J

    2015-06-01

    The search for an association between disease incidence and possible risk factors using surveillance data needs to account for possible spatial and temporal correlations in underlying risk. This can be especially difficult if there are missing values for some important covariates. We present a case study to show how this problem can be overcome in a Bayesian analysis framework by adding to the usual spatio-temporal model a component for modelling the missing data. PMID:25338646

  18. 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.

  19. 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

  20. Spatio-temporal variation in Helicoverpa egg parasitism by Trichogramma in a tropical Bt-transgenic cotton landscape

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Understanding the spatio-temporal dynamics of insects in agroecosystems is crucial when developing effective management strategies that emphasise biological control of pests. Wild populations of Trichogramma Westwood egg parasitoids are utilised for biological suppression of the potentially resistan...

  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. 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.

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

    NASA Astrophysics Data System (ADS)

    Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

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

  4. Reconstruction of the spatio-temporal dynamics of a human magnetoencephalogram

    NASA Astrophysics Data System (ADS)

    Jirsa, V. K.; Friedrich, R.; Haken, H.

    We reconstruct the entire experimentally observed spatio-temporal signal of a human magnetoencephalogram (MEG) observed in a sensori-motor-coordination experiment by Kelso et al. In this experiment, when an acoustic stimulus frequency is changed systematically, a spontaneous transition in coordination occurs at a critical frequency in both the motor behavior and brain signals. Here we present a stepwise approach for the reconstruction of the spatio-temporal signal: First, we identify the order parameters and recall a theoretical model by the present authors and Kelso which reproduces the temporal dynamics of the order parameters. Second, we use the variational method by Uhl et al. in order to determine the spatial modes of the order parameters. Third, we present a variational method for the reconstruction of the remaining spatio-temporal signal and determine the spatial modes and temporal dynamics of the enslaved variables and possible order parameter modifications. The obtained set of spatial modes proves to be a fixed spatial base system of the observed temporal dynamics in the brain.

  5. 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

  6. Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship

    NASA Astrophysics Data System (ADS)

    Chu, Hone-Jay; Huang, Bo; Lin, Chuan-Yao

    2015-02-01

    This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six clusters) in the PM data collected between 2005 and 2009 in Taiwan are identified and the industrial and urban areas of Taiwan (southwestern, west central, northwestern, and northern Taiwan) are found to have high PM concentrations. The PM10-PM2.5 relationship is then modeled with global ordinary least squares regression, geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR). The GTWR and GWR produce consistent results; however, GTWR provides more detailed information of spatio-temporal variations of the PM10-PM2.5 relationship. The results also show that GTWR provides a relatively high goodness of fit and sufficient space-time explanatory power. In particular, the PM2.5 or PM10 varies with time and space, depending on weather conditions and the spatial distribution of land use and emission patterns in local areas. Such information can be used to determine patterns of spatio-temporal heterogeneity in PM that will allow the control of pollutants and the reduction of public exposure.

  7. Nonparametric Evaluation of Dynamic Disease Risk: A Spatio-Temporal Kernel Approach

    PubMed Central

    Chen, Dongmei; Racine, Jeffrey S.; Ong, SengHuat; Chen, Yue; Zhao, Genming; Jiang, Qingwu

    2011-01-01

    Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the average spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled spatio-temporal kernel density estimation (stKDE) that employs hybrid kernel (i.e., weight) functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also borrows information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based) kernel density estimation (trKDE) which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method. PMID:21423612

  8. 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.

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  11. 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.

  12. A New Method for Blind Source Extraction

    NASA Astrophysics Data System (ADS)

    Yoshihara, Tsubasa; Matsuoka, Kiyotoshi

    Blind source separation (BSS) is a method for recovering a set of statistically independent signals from the observation of their mixtures without any prior knowledge about the mixing process. If, as a special case, only one source component is to be extracted, it is called blind source extraction (BSE). Since BSE involves a smaller number of parameters to be estimated than BSS, it requires less computation time. In this paper we propose a new algorithm for BSE of the convolutive mixture. The algorithm determines the extractor by evaluating independence between a target signal and other signals. It has some good properties. First, since it is formulated in the time domain, we do not need to worry about the so-called permutation problem. Second, by applying a particular constraint on the extractor the signal quality at the sensors is preserved through the extraction process. A couple of experiments are shown in which the proposed algorithm is applied to the mixture of five voice signals.

  13. 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

  14. 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

  15. 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 local scale. In general, this project could be used as a template for dust-transport modelling which couples spatial data focused on the construction of digital terrain models and thematic mapping with data generated by numerical simulations based on Reynolds averaged Navier-Stokes equations.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  17. 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 livestock. Valley bottoms, areas with low slopes, and spaces with low tree density are characterized by higher pasture production. Temporal variations of pasture production largely depended on the availability of soil moisture, which in turn depended on the temporal distribution of rainfall. This ecohydrologic model constitutes a valuable tool to investigate water and energy fluxes, as well as vegetation dynamics in semiarid rangelands, as was proved by a quantitative assessment of the quality of the simulations. The range of applications and possibilities contained in the model opens a wide field for future research.

  18. 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 sensitivity analysis is to shed light on the particular abilities of the model in assessing the likelihood of avalanche releases under evolving meteorological/snowpack conditions. Both spatial resolution (the abilities to produce reliable forecasts for individual avalanche paths) and temporal behaviour of the model are explored in details. Based on the sensitivity analysis, the uncertainty estimation for the provided forecasts is discussed. Particularly, the ensembles of prediction models are run and analysed in order to estimate the variability of the provided forecast and assess the uncertainty coming from the variety of sources: imprecise input data, uncertainty in weather forecast, sub-optimal parameters of the prediction model and variability in the choice of the training dataset.

  19. 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 -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

  20. A physiologically plausible spatio-temporal model for EEG signals recorded with intracerebral electrodes in human partial epilepsy.

    PubMed

    Cosandier-Riml, Delphine; Badier, Jean-Michel; Chauvel, Patrick; Wendling, Fabrice

    2007-03-01

    Stereoelectroencephalography (depth-EEG signals) is a presurgical investigation technique of drug-resistant partial epilepsy, in which multiple sensor intracerebral electrodes are used to directly record brain electrical activity. In order to interpret depth-EEG signals, we developed an extended source model which connects two levels of representation: (1) a distributed current dipole model which describes the spatial distribution of neuronal sources; (2) a model of coupled neuronal populations which describes their temporal dynamics. From this extended source model, depth-EEG signals were simulated from the forward solution at each electrode sensor located inside the brain. Results showed that realistic transient epileptiform activities (spikes) are obtained under specific conditions in the model in terms of degree of coupling between neuronal populations and spatial extent of the source. In particular, the cortical area involved in the generation of epileptic spikes was estimated to vary from 18 to 25 cm2, for brain conductivity values ranging from 30 to 35 x 10(-5) S/mm, for high coupling degree between neuronal populations and for a volume conductor model that accounts for the three main tissues of the head (brain, skull, and scalp). This study provides insight into the relationship between spatio-temporal properties of cortical neuronal sources and depth-EEG signals. PMID:17355049

  1. Spatio-temporal variability of global soil moisture products

    NASA Astrophysics Data System (ADS)

    Rtzer, K.; Montzka, C.; Vereecken, H.

    2015-03-01

    Being an important variable for various applications, for example hydrological and weather prediction models or data assimilation, a large range of global soil moisture products from different sources, such as modeling or active and passive microwave remote sensing, are available. The diverse measurement and estimation methods can lead to differences in the characteristics of the products. This study investigates the spatial and temporal behavior of three different products: (i) the Soil Moisture and Ocean Salinity (SMOS) Level 2 product, retrieved with a physically based approach from passive microwave remote sensing brightness temperatures, (ii) the MetOp-A Advanced Scatterometer (ASCAT) product retrieved with a change detection method from radar remote sensing backscattering coefficients, and (iii) the ERA Interim product from a weather forecast model reanalysis. Results show overall similar patterns of spatial soil moisture, but high deviations in absolute values. A ranking of mean relative differences demonstrates that ASCAT and ERA Interim products show most similar spatial soil moisture patterns, while ERA and SMOS products show least similarities. For selected regions in different climate classes, time series of the ASCAT product generally show higher variability of soil moisture than SMOS, and especially than ERA products. The relationship of spatial mean and variance is, especially during wet periods, influenced by sensor and retrieval characteristics in the SMOS product, while it is determined to a larger degree by the precipitation patterns of the respective regions in the ASCAT and ERA products. The decomposition of spatial variance into temporal variant and invariant components exhibits high dependence on the retrieval methods of the respective products. The change detection retrieval method causes higher influence of temporal variant factors (e.g. precipitation, evaporation) on the ASCAT product, while SMOS and ERA products are stronger determined by temporal invariant factors (e.g. topography, soil characteristics). The investigation of the effect of changing scales on spatial variance in three different areas indicates that the variance does not vary with increasing support scale. Increasing extent scales from 250 to 3000 km raise spatial variance of all products and all study areas according to a power law, which is varying seasonally. ERA shows a consistent scaling behavior with a constant power scale factor and similar intercepts across all study regions. In general, the investigated products show overall different spatial and temporal statistics which are induced by their different estimation methods and which are important to be aware of for the selection of a product for application and for their up- or downscaling.

  2. 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 variation in the horizontal polarization of surface waves along the direction of this pair of stations. It depends on the relative azimuth angle between the pair of stations and the direction of anisotropy, on the amplitude of anisotropy and the frequency band of the signal. Therefore, it is now possible to explain the large, rapid and very localized variations of surface waves horizontal polarization observed by Durand et al. (2011) during the Parkfield earthquake of 2004. Furthermore, some preliminary results about the investigation of seismic anisotropy change caused by the June 13, 2008 Iwate-Miyagi Nairiku earthquake (Mw = 6.9) will be presented.

  3. Spatio-temporal mapping cortical neuroplasticity in carpal tunnel syndrome

    PubMed Central

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

    2012-01-01

    Neuroimaging data demonstrate that carpal tunnel syndrome, a peripheral neuropathy, is accompanied by maladaptive central neuroplasticity. To further investigate this phenomenon, we collected magnetoencephalography data from 12 patients with carpal tunnel syndrome and 12 healthy control subjects undergoing somatosensory stimulation of the median nerve-innervated Digits 2 and 3, as well as Digit 5, which is innervated by the ulnar nerve. Nerve conduction velocity and psychophysical data were acquired to determine whether standard clinical measures correlated with brain response. In subjects with carpal tunnel syndrome, but not healthy controls, sensory nerve conduction velocity for Digits 2 and 3 was slower than Digit 5. However, somatosensory M20 latencies for Digits 2 and 3 were significantly longer than those of Digit 5. The extent of the M20 delay for median nerve-innervated Digit 2 was positively correlated with decreasing nerve conduction velocity and increasing pain severity. Thus, slower peripheral nerve conduction in carpal tunnel syndrome corresponds to greater delays in the first somatosensory cortical response. Furthermore, spectral analysis demonstrated weaker post-stimulus beta event-related desynchronization and earlier and shorter event-related synchronization in subjects with carpal tunnel syndrome. The extent of the decreased event-related desynchronization for median nerve-innervated digits was positively correlated with paraesthesia severity. We propose that ongoing paraesthesias in median nerve-innervated digits render their corresponding sensorimotor cortical areas ‘busy’, thus reducing their capacity to process external stimulation. Finally, subjects with carpal tunnel syndrome demonstrated a smaller cortical source separation for Digits 2 and 3 compared with healthy controls. This supports our hypothesis that ongoing paraesthesias promote blurring of median nerve-innervated digit representations through Hebbian plasticity mechanisms. In summary, this study reveals significant correlation between the clinical severity of carpal tunnel syndrome and the latency of the early M20, as well as the strength of long latency beta oscillations. These temporal magnetoencephalography measures are novel markers of neuroplasticity in carpal tunnel syndrome and could be used to study central changes that may occur following clinical intervention. PMID:23043143

  4. 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.

  5. 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.

  6. 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 (?2?=?7587, df?=?7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2012-12-01

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

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

    PubMed Central

    Wang, Grace I.

    2012-01-01

    The spatio-temporal pattern of auditory nerve (AN) activity, representing the relative timing of spikes across the tonotopic axis, contains cues to perceptual features of sounds such as pitch, loudness, timbre, and spatial location. These spatio-temporal cues may be extracted by neurons in the cochlear nucleus (CN) that are sensitive to relative timing of inputs from AN fibers innervating different cochlear regions. One possible mechanism for this extraction is cross-frequency coincidence detection (CD), in which a central neuron converts the degree of coincidence across the tonotopic axis into a rate code by preferentially firing when its AN inputs discharge in synchrony. We used Huffman stimuli (Carney LH. J Neurophysiol 64: 437456, 1990), which have a flat power spectrum but differ in their phase spectra, to systematically manipulate relative timing of spikes across tonotopically neighboring AN fibers without changing overall firing rates. We compared responses of CN units to Huffman stimuli with responses of model CD cells operating on spatio-temporal patterns of AN activity derived from measured responses of AN fibers with the principle of cochlear scaling invariance. We used the maximum likelihood method to determine the CD model cell parameters most likely to produce the measured CN unit responses, and thereby could distinguish units behaving like cross-frequency CD cells from those consistent with same-frequency CD (in which all inputs would originate from the same tonotopic location). We find that certain CN unit types, especially those associated with globular bushy cells, have responses consistent with cross-frequency CD cells. A possible functional role of a cross-frequency CD mechanism in these CN units is to increase the dynamic range of binaural neurons that process cues for sound localization. PMID:22972956

  10. 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

  11. 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

  12. 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.

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

    NASA Astrophysics Data System (ADS)

    Kitsunezaki, S.

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

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

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

    USGS Publications Warehouse

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

    2005-01-01

    1. Drought is a natural disturbance that can cause widespread mortality of aquatic organisms in wetlands. We hypothesized that seasonal drying of marsh surfaces (i.e. hydrological disturbance) shapes spatio-temporal patterns of fish populations. 2. We tested whether population dynamics of fishes were synchronized by hydrological disturbance (Moran effect) or distance separating study sites (dispersal). Spatio-temporal patterns were examined in local populations of five abundant species at 17 sites (sampled five times per year from 1996 to 2001) in a large oligotrophic wetland. 3. Fish densities differed significantly across spatio-temporal scales for all species. For all species except eastern mosquitofish (Gambusia holbrooki), a significant portion of spatio-temporal variation in density was attributed to drying events (used as a covariate). 4. We observed three patterns of response to hydrological disturbance. Densities of bluefin killifish (Lucania goodei), least killifish (Heterandria formosa), and golden top-minnow (Fundulus chrysotus) were usually lowest after a dry down and recovered slowly. Eastern mosquitofish showed no distinct response to marsh drying (i.e. they recovered quickly). Flagfish (Jordanella floridae) density was often highest after a dry down and then declined. Population growth after a dry down was often asymptotic for bluefin killifish and golden topminnow, with greatest asymptotic density and longest time to recovery at sites that dried infrequently. 5. Fish population dynamics were synchronized by hydrological disturbance (independent of distance) and distance separating study sites (independent of hydrological disturbance). Our ability to separate the relative importance of the Moran effect from dispersal was strengthened by a weak association between hydrological synchrony and distance among study sites. Dispersal was the primary mechanism for synchronous population dynamics of flagfish, whereas hydrological disturbance was the primary mechanism for synchronous population dynamics of the other species examined. 6. Species varied in the relative role of the Moran effect and dispersal in homogenizing their population dynamics, probably as a function of life history and ability to exploit dry-season refugia. ?? 2005 British Ecological Society.

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

    PubMed Central

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

    2014-01-01

    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 (1,1). In addition, the combined analysis of the prediction of IHD hospital admissions and the general hospital distributions shows that Pingshan and Longgang might experience the most serious burden of IHD hospital services in the near future, although Futian would still have the greatest number and the highest incidence rate of hospital admissions for IHD. PMID:24806191

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

    NASA Astrophysics Data System (ADS)

    Rudolf, P.; tefan, D.; Sedl?, M.; Kozk, J.; Habn, V.; Huzlk, 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.

  18. Spatio-temporal dynamics in vertical cavity surface emitting lasers excited by fast electrical pulses

    NASA Astrophysics Data System (ADS)

    Giudici, M.; Tredicce, J. R.; Vaschenko, G.; Rocca, J. J.; Menoni, C. S.

    1998-12-01

    We have measured the time average spatial intensity distribution and the spatio-temporal evolution of the spectrally resolved radiation emitted from broad-area vertical cavity surface emitting lasers (VCSEL) when pumped by a fast current pulse. We show that an intrinsic symmetry break exists due to geometrical asymmetry of the device structure and that the frequency separation between different modes allows the evaluation of the asymmetry factor. The space-time behavior shows the appearance of higher-order modes coexisting or alternating in time. The dynamical behavior shows a chirping in frequency.

  19. 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.

  20. Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

    PubMed Central

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

    2014-01-01

    Objective This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR?=?11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR?=?3.64) and not having access to a safe water source (OR?=?2.04) as the main causes of Shigella in Jiangsu Province. Conclusion Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. PMID:24416167

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

    NASA Astrophysics Data System (ADS)

    Marwan, Norbert; Kurths, Jrgen

    2015-09-01

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

  2. Spatio-temporal variations in soil hydrology of a typical semiarid sand-meadow-desert landscape

    NASA Astrophysics Data System (ADS)

    Duan, L.; Liu, T.; Wang, X.; Wang, G.; Ma, L.; Luo, Y.

    2011-02-01

    A good understanding of the interrelations between land cover alteration and changes in hydrologic conditions (e.g., soil moisture) as well as soil physicochemical properties (e.g., fine particles and nutrients) is crucial for maintaining the fragile hydrologic and environmental conditions of semiarid land, such as the Horqin Sandy Land in China, but is lacking in existing literature. The objectives of this study were to examine: (1) spatio-temporal variations of soil moisture and physicochemical properties in semiarid land; and (2) how those variations are influenced by land cover alteration. Using the data collected in a 9.71 km2 well-instrumented area of the Horqin Sandy Land, this study examined by visual examination and statistical analyses the spatio-temporal variations of soil moisture and physicochemical properties. The results indicated that for the study area, the soil moisture and physicochemical properties were dependent on local topography, soil texture, vegetation density, and human activity. Long-term reclamation for agriculture was found to reduce soil moisture by over 23% and significantly (p-value < 0.05) lower the contents of soil organic matter, fine particles, and nutrients.

  3. 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.

  4. 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

  5. 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.

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

    PubMed

    Estallo, E L; Carbajo, A E; Grech, M G; Fras-Cspedes, M; Lpez, L; Lanfri, M A; Luduea-Almeida, F F; Almirn, 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, Crdoba 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

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

    PubMed

    Guizard, Nicolas; Fonov, Vladimir S; Garca-Lorenzo, Daniel; Nakamura, Kunio; Aubert-Broche, Brengre; 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

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

    NASA Astrophysics Data System (ADS)

    Dasgupta, Udayan; Ali, Murtaza

    2011-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  10. 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 (6.8C), forestland (3C), city and town centers (4.2C), municipal rubbish tip (-3.9C), coal dump site (12.2C), and power plants' region (7C) were presented. In addition, the results indicated that the mean LST difference between forestland and city centers was approximately 5C, and the difference between forestland and industrial enterprises was almost 8C 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

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

    PubMed

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

    2013-02-01

    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

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

    PubMed Central

    Talwar, Shefali; Kumar, Abhishek; Rao, Madan; Menon, GautamI.; 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

  13. Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

    PubMed Central

    Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

    2014-01-01

    The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

  14. 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.

  15. Spatio-temporal dynamics in collective frog choruses examined by mathematical modeling and field observations.

    PubMed

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

    2014-01-01

    This paper reports theoretical and experimental studies on spatio-temporal dynamics in the choruses of male Japanese tree frogs. First, we theoretically model their calling times and positions as a system of coupled mobile oscillators. Numerical simulation of the model as well as calculation of the order parameters show that the spatio-temporal dynamics exhibits bistability between two-cluster antisynchronization and wavy antisynchronization, by assuming that the frogs are attracted to the edge of a simple circular breeding site. Second, we change the shape of the breeding site from the circle to rectangles including a straight line, and evaluate the stability of two-cluster and wavy antisynchronization. Numerical simulation shows that two-cluster antisynchronization is more frequently observed than wavy antisynchronization. Finally, we recorded frog choruses at an actual paddy field using our sound-imaging method. Analysis of the video demonstrated a consistent result with the aforementioned simulation: namely, two-cluster antisynchronization was more frequently realized. PMID:24463569

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

    PubMed Central

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

    2010-01-01

    Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems-level insight into the underlying processes is very limited. Using heart morphogenesis as general model for dissecting the functional architecture of organ development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages of a developing organ identifying several novel signaling modules. Our results show that organ development relies on surprisingly few, extensively recycled, protein modules that integrate into complex higher-order networks. This design allows the formation of a complicated organ using simple building blocks, and suggests how mutations in the same genes can lead to diverse phenotypes. We observe a striking temporal correlation between organ complexity and the number of discrete functional modules coordinating morphogenesis. Our analysis elucidates the organization and composition of spatio-temporal protein networks that drive the formation of organs, which in the future may lay the foundation of novel approaches in treatments, diagnostics, and regenerative medicine. PMID:20571530

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

    PubMed

    Li, Yehua; Guan, Yongtao

    2014-08-01

    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

  18. 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

  19. An exact stochastic hybrid model of excitable membranes including spatio-temporal evolution.

    PubMed

    Buckwar, Evelyn; Riedler, Martin G

    2011-12-01

    In this paper, we present a mathematical description for excitable biological membranes, in particular neuronal membranes. We aim to model the (spatio-) temporal dynamics, e.g., the travelling of an action potential along the axon, subject to noise, such as ion channel noise. Using the framework of Piecewise Deterministic Processes (PDPs) we provide an exact mathematical description-in contrast to pseudo-exact algorithms considered in the literature-of the stochastic process one obtains coupling a continuous time Markov chain model with a deterministic dynamic model of a macroscopic variable, that is coupling Markovian channel dynamics to the time-evolution of the transmembrane potential. We extend the existing framework of PDPs in finite dimensional state space to include infinite-dimensional evolution equations and thus obtain a stochastic hybrid model suitable for modelling spatio-temporal dynamics. We derive analytic results for the infinite-dimensional process, such as existence, the strong Markov property and its extended generator. Further, we exemplify modelling of spatially extended excitable membranes with PDPs by a stochastic hybrid version of the Hodgkin-Huxley model of the squid giant axon. Finally, we discuss the advantages of the PDP formulation in view of analytical and numerical investigations as well as the application of PDPs to structurally more complex models of excitable membranes. PMID:21243359

  20. 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.

  1. 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

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

    PubMed Central

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

    2007-01-01

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

  3. 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.

  4. 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.

  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. 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.

  7. 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.

  8. 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.

  9. Enhancing the emergence rate of coherent wavefronts from ocean ambient noise correlations using spatio-temporal filters.

    PubMed

    Leroy, Charlotte; Lani, Shane; Sabra, Karim G; Hodgkiss, William S; Kuperman, W A; Roux, Philippe

    2012-08-01

    Extracting coherent wavefronts between passive receivers using cross-correlations of ambient noise (CAN) provides a means for monitoring the seismoacoustic environment without using active sources. However, using cross-correlations between single receivers can require a long recording time in order to extract stable coherent arrivals from CAN. This becomes an issue if the propagation medium fluctuates significantly during the recording period. To address this issue, this article presents a general spatio-temporal filtering procedure to enhance the emergence rate for coherent wavefronts extracted from time-averaged ambient noise correlations between two spatially separated arrays. The robustness of this array-based CAN technique is investigated using ambient shipping noise recorded over 24 h in the frequency band [250-850 Hz] on two vertical line arrays deployed 143 m apart in shallow water (depth 20 m). Experimental results confirm that the array-based CAN technique can significantly reduce the recording duration (e.g., from 22 h to 30 min) required for extracting coherent wavefronts of sufficient amplitude (e.g., 20 dB over residual temporal fluctations) when compared to conventional CAN implementations between single pairs of hydrophones. These improvements of the CAN technique could benefit the development of noise-based ocean monitoring applications such as passive acoustic tomography. PMID:22894211

  10. Application of a simple multiplicative spatio-temporal stream water quality model to the river Conwy, North Wales.

    PubMed

    Cooper, D M; Evans, C D; Norris, D; Thacker, S; Pereira, M Glria

    2014-07-01

    We use a simple multiplicative spatio-temporal model to describe variability in a sequence of water quality monitoring data from headwater streams in the Conwy catchment, North Wales. The spatial component of the model treats concentrations as due to simple mixing of a small number of distinct source types, each associated with particular upstream catchment characteristics. The temporal component allows concentration variability due to seasonal or hydrological change. We apply the model using three candidate catchment characteristic classifications to generate mixing concentrations, and a seasonal component to describe temporal variability, and test a range of sub-models. We identify a cross-classification of soil and land cover as providing the best spatial indicator of water quality of the classifications considered. The spatial model based on a selected grouped cross-classification was shown to account for between 35% and 90% of the spatial variability and the seasonal model accounted for between 45% and 100% of the temporal variability in the data. Analysis of residuals showed an inverse relationship between DOC and sulphate and between hydrogen ion concentration and calcium and magnesium. We also found residual correlations between sites which are strongly related to landscape class. These are attributed to landscape class by time interactions which are not accounted for in the simple multiplicative model. PMID:24509947

  11. 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.

  12. 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

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

    PubMed

    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-year period. The purely spatial scan statistics analysis showed significant spatial clusters of high and low incidence rates; the purely temporal scan statistics showed the temporal cluster with a three-year period from 2009 to 2011 characterized by a high incidence rate; and the space-time scan statistics analysis showed significant spatio-temporal clusters. The distribution of the mean centres (MCs) showed that the general distributions of the NSPRP MCs and NSPTBP MCs were to the east of the incidence rate MCs. Conversely, the general distributions of the RSPRP MCs and the RSPTBP MCs were to the south of the incidence rate MCs. Based on the combined analysis of MC distribution characteristics and trajectory similarities, the NSP trajectory was most similar to the incidence rate trajectory. Thus, more attention should be focused on the discovery of NSP patients in the western part of Beijing, whereas the northern part of Beijing needs intensive treatment for RSP patients. PMID:26959048

  14. 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.

  15. 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 (?PSII) in response to ant-derived formic acid during its capture and digestion. PMID:20523127

  16. Spatio-temporal clustering of cholera: The impact of flood control in Matlab, Bangladesh, 19832003

    PubMed Central

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

    2009-01-01

    Introducing flood control to an area of endemic waterborne diseases could have significant impacts on spatio-temporal occurrence of cholera. Using 21-years of data from Bangladesh, we conducted cluster analysis to explore changes in spatial and temporal distribution of cholera incidence since construction of flood control structures. Striking changes in temporal cluster patterns emerged, including a shift from dry season to rainy season clusters following flood protection and delayed clustering inside the protected areas. Spatial differences in pre-flood protection and post-protection cholera clusters are weaker. Changes in spatio-temporal cholera clustering, associated with implementation of flood protection strategies, could affect local cholera prevention efforts. PMID:19217821

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

    SciTech Connect

    Hilbert, V.; Rdel, C.; Zastrau, U.; Brenner, G.; Dsterer, S.; Dziarzhytski, S.; Harmand, M.; Przystawik, A.; Redlin, H.; Toleikis, S.; Dppner, T.; Ma, T.; Fletcher, L.; Frster, 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 (598) 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.

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

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

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

    PubMed Central

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

    2009-01-01

    Background Transmission mechanisms of black-band disease (BBD) in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease. Methodology/Principal Findings 3,175 susceptible and infected corals were mapped over an area of 1010 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 2006December 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 infected corals surviving a disease season appear to play a major role in the re-introduction of the disease to the coral community in the following season. PMID:19337384

  1. Spatio-temporal Averaging of Removal Rate constants in River Networks: Is there an Emergent Pattern?

    NASA Astrophysics Data System (ADS)

    Basu, N. B.; Rao, P. C.; Zanardo, S.; Donner, S. D.; Ye, S.; Sivapalan, M.

    2009-12-01

    Scaling of nutrient loads across river networks is a function of complex interactions between hydrologic and biogeochemical processes that modulate the contaminant input signals from the hillslope via aggregation and attenuation in a converging network. We examined the inter-annual variability in stream nutrient delivery ratio (NDR) as moderated by the coupling between hydrologic and biogeochemical processes across the climate-landscape continuum. Experimental and modeling studies at the reach scale suggest an inverse dependence of the biogeochemical cycling rate constant (k; T-1) on the stream stage (h, L). This inverse function was implemented in the THMB large-scale hydrology and biogeochemistry model to describe nutrient processing at the reach scale, and simulate nitrogen export across Mississippi Basin. The spatio-temporally averaged reaction rate (kavg) constant from THMB exhibited similar inverse dependence on the stage at the outlet of large basins (~50,000 km2). Such emergent k-h dependence is hypothesized to be indicative of fractal scaling behavior of in-stream biogeochemical processing. Two parsimonious models were developed to scale up from the reach-scale to watershed scale, and explore the spatio-temporal averaging within the network under diverse climate forcing conditions. The first model was derived from THREW, and was enhanced by adding a two-compartment biogeochemical reaction module. The second model used the inverse k-h dependence at the daily time scale, without invoking the two-compartment model, similar to that used in the basin-scale model. Preliminary analyses indicated that temporal averaging decreased the exponent of the k-h relationship at smaller spatial scales (e.g., first- or second- order watersheds); however, the relationship converged towards the reach-scale dependence function at larger scales. The average k value at the smaller scales, and the trajectory of convergence, is a function of climatic (e.g., rainfall frequency,depth) and geomorphic (e.g., network structure, channel dimensions) controls. The reach-scale k-h relationship thus acts as an attractor for the entire system, such that at larger spatial scales an effective k, derived solely from the mean stage at the watershed outlet, is adequate to describe nutrient processing within the entire network. Implications of this unique spatio-temporal averaging behavior on the development of predictive models that describe nutrient loads in catchments across scales are discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

    Here we report an ABA triblock copolymer that can express microscopic autonomous formation and break-up of aggregates under constant condition to generate macroscopic viscoelastic self-oscillation of the solution. The ABA triblock copolymer is designed to have hydrophilic B segment and self-oscillating A segment at the both sides by RAFT copolymerization. In the A segment, a metal catalyst of chemical oscillatory reaction, i.e., the Belousov-Zhabotinsky (BZ) reaction, is introduced as a chemomechanical transducer to change the aggregation state of the polymer depending on the redox states. Time-resolved DLS measurements of the ABA triblock copolymer confirm the presence of a transitional network structure of micelle aggregations in the reduced state and a unimer structure in the oxidized state. This autonomous oscillation of a well-designed triblock copolymer enables dynamic biomimetic softmaterials with spatio-temporal structure.

  3. 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.

  4. 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.

  5. 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.

  6. 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

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

    PubMed

    Rieckher, Matthias; Kyparissidis-Kokkinidis, Ilias; Zacharopoulos, Athanasios; 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

  8. 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.

  9. 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

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

    PubMed

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

    2014-09-01

    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. PMID:25020092

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

    Luo, Jing; Cui, Weihong

    2007-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  16. 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.

  17. Transition to Spatio-Temporal Chaos with Increasing Length in the Reaction-Diffusion System

    NASA Astrophysics Data System (ADS)

    Trail, Collin; Tomlin, Brett; Olsen, Thomas; Wiener, Richard J.

    2003-11-01

    Calculations based up the Reaction-Diffusion model (H. Riecke and H.-G. Paap, Europhys. Lett. 14), 1235 (1991).have proven to be suggestive for a wide variety of pattern forming systems, including Taylor-Couette flow with hourglass geometry(Richard J. Wiener et al), Phys. Rev. E 55, 5489 (1997).. Seeking insight to guide experimental investigations, we extend these calculations. Previous calculations indicated that in smaller systems, only temporal chaos, located in a small region, would be observed, while in longer systems instabilities would form over a wide region. Our simulations explore this transition from purely temporal chaos to spatio-temporal chaos as the length of the system is increased.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  19. Writer Identification Using Super Paramagnetic Clustering and Spatio Temporal Neural Network

    NASA Astrophysics Data System (ADS)

    Taghavi Sangdehi, Seyyed Ataollah; Faez, Karim

    This paper discusses use of Super Paramagnetic Clustering (SPC) and Spatio Temporal Artificial Neuron in on-line writer identification, on Farsi handwriting. In online cases, speed and automation are advantages of one method on others, therefore we used unsupervised and relatively quick clustering method, which in comparison with conventional approaches, give us better result. Moreover, regardless of various parameters that available from acquisition systems, we only consider to displacement of pen tip at determined direction that lead to quick system due to its quick preprocessing and clustering. Also we use a threshold that remove displacement between disconnected point of a word that lead to a better classification result on on-line Farsi writers.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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

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

    NASA Astrophysics Data System (ADS)

    Thober, S.; Samaniego, L. E.

    2012-12-01

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

  7. Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders

    PubMed Central

    Wang, Xin; Pinto-Duarte, Antnio; 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

    Understanding the L ? H and H ? L transitions is crucial to successful ITER operation. In this paper we present novel theoretical and modelling study results on the spatio-temporal dynamics of the transition. We place a special emphasis on the role of zonal flows and the micro ? macro connection between dynamics and the power threshold (PT) dependences. The model studied evolves five coupled fields in time and one space dimension, in simplified geometry. The content of this paper is (a) the model fundamentals and the space-time evolution during the L ? I ? H transition, (b) the physics origin of the well-known ?B-drift asymmetry in PT, (c) the role of heat avalanches in the intrinsic variability of the L ? H transition, (d) the dynamics of the H ? L back transition and the physics of hysteresis, (e) conclusion and discussion, with a special emphasis on the implications of transition dynamics for the L ? H power threshold scalings.

  10. 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

  11. Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders.

    PubMed

    Wang, Xin; Pinto-Duarte, Antnio; 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

  12. 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.

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

    PubMed Central

    Jacquez, Geoffrey M.

    2010-01-01

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

  14. 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

  15. Spatio-temporal EEG power spectral patterns during a short daytime nap.

    PubMed

    Luo, Z; Honda, K; Inou, S

    2001-06-01

    This is an approach to investigate topographic changes in electroencephalographic (EEG) spectral power during pre- and post-nap wakefulness as well as stages 1 (S1) and 2 (S2) NREM sleep in 12 subjects. Delta- and theta-band power significantly increased in the frontal and central regions during S1 and S2 with an increase in inter- and intra-hemispheric correlations. Beta-band power significantly increased in the frontal, central and parietal regions during S2 with an increase in interhemispheric correlation. In contrast, alpha-band power significantly decreased in the parietal-occipital regions during S1 and S2 with a decrease in interhemispheric correlation. Thus, daytime nap modulated spatio-temporal patterns of EEG power spectral patterns in wide scalp regions. PMID:11422838

  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. Spatio-Temporal Parameters of Endosomal Signaling in Cancer: Implications for New Treatment Options.

    PubMed

    Stasyk, Taras; Huber, Lukas A

    2016-04-01

    The endo/lysosomal system in cells provides membranous platforms to assemble specific signaling complexes and to terminate signal transduction, thus, is essential for physiological signaling. Endocytic organelles can significantly extend signaling of activated cell surface receptors, and may additionally provide distinct locations for the generation of specific signaling outputs. Failures of regulation at different levels of endocytosis, recycling, degradation as well as aberrations in specific endo/lysosomal signaling pathways, such as mTORC1, might lead to different diseases including cancer. Therefore, a better understanding of spatio-temporal compartmentalization of sub-cellular signaling might provide an opportunity to interfere with aberrant signal transduction in pathological processes by novel combinatorial therapeutic approaches. J. Cell. Biochem. 117: 836-843, 2016. © 2015 The Authors. Journal of Cellular Biochemistry Published by Wiley Periodicals Inc. PMID:26506511

  18. Measures of spatio-temporal accuracy for time series land cover data

    NASA Astrophysics Data System (ADS)

    Tsutsumida, Narumasa; Comber, Alexis J.

    2015-09-01

    Remote sensing is a useful tool for monitoring changes in land cover over time. The accuracy of such time-series analyses has hitherto only been assessed using confusion matrices. The matrix allows global measures of user, producer and overall accuracies to be generated, but lacks consideration of any spatial aspects of accuracy. It is well known that land cover errors are typically spatially auto-correlated and can have a distinct spatial distribution. As yet little work has considered the temporal dimension and investigated the persistence or errors in both geographic and temporal dimensions. Spatio-temporal errors can have a profound impact on both change detection and on environmental monitoring and modelling activities using land cover data. This study investigated methods for describing the spatio-temporal characteristics of classification accuracy. Annual thematic maps were created using a random forest classification of MODIS data over the Jakarta metropolitan areas for the period of 2001-2013. A logistic geographically weighted model was used to estimate annual spatial measures of user, producer and overall accuracies. A principal component analysis was then used to extract summaries of the multi-temporal accuracy. The results showed how the spatial distribution of user and producer accuracy varied over space and time, and overall spatial variance was confirmed by the principal component analysis. The results indicated that areas of homogeneous land cover were mapped with relatively high accuracy and low variability, and areas of mixed land cover with the opposite characteristics. A multi-temporal spatial approach to accuracy is shown to provide more informative measures of accuracy, allowing map producers and users to evaluate time series thematic maps more comprehensively than a standard confusion matrix approach. The need to identify suitable properties for a temporal kernel are discussed.

  19. 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 liver in the future. PMID:24625393

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

    PubMed

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

    2015-11-01

    Emerging pathogens constitute a severe threat for human health and biodiversity. Determining the status (native or non-native) of emerging pathogens, and tracing back their spatio-temporal dynamics, is crucial to understand the eco-evolutionary factors promoting their emergence, to control their spread and mitigate their impacts. However, tracing back the spatio-temporal dynamics of emerging wildlife pathogens is challenging because (i) they are often neglected until they become sufficiently abundant and pose socio-economical concerns and (ii) their geographical range is often little known. Here, we combined classical population genetics tools and approximate Bayesian computation (i.e. ABC) to retrace the dynamics of Tracheliastes polycolpus, a poorly documented pathogenic ectoparasite emerging in Western Europe that threatens several freshwater fish species. Our results strongly suggest that populations of T. polycolpus in France emerged from individuals originating from a unique genetic pool that were most likely introduced in the 1920s in central France. From this initial population, three waves of colonization occurred into peripheral watersheds within the next two decades. We further demonstrated that populations remained at low densities, and hence undetectable, during 10 years before a major demographic expansion occurred, and before its official detection in France. These findings corroborate and expand the few historical records available for this emerging pathogen. More generally, our study demonstrates how ABC can be used to determine the status, reconstruct the colonization history and infer key evolutionary parameters of emerging wildlife pathogens with low data availability, and for which samples from the putative native area are inaccessible. PMID:26416083

  1. 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

  2. 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.

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

    PubMed Central

    Nicolas, Delphine; Rochette, Sbastien; 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

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

    NASA Astrophysics Data System (ADS)

    Schulte, M.; Schumann, A. H.

    2015-06-01

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

  5. Spatio-temporal dynamics of the magnetosphere during intense geospace storms

    NASA Astrophysics Data System (ADS)

    Chen, J.; Sharma, A.

    2006-05-01

    During geomagnetically active periods the magnetosphere exhibits global, regional and local features. The global features are in general captured by the geomagnetic indices and the regional and local features are measured by spacecraft-based imagers and ground-based instruments. The global features of the magnetosphere have been studied extensively using nonlinear dynamical techniques, such as phase space reconstruction from observational data. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere using phase space reconstruction techniques. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the ground-based magnetic field variations as the magnetospheric response. The magnetic field perturbation at 57 ground stations during year 2002 and the corresponding solar wind data are compiled for this study. The ground magnetometer data are from the three chains of stations: CANOPUS (13), IMAGE (26) and WDC (18). This new data set, with 1-minute resolution, is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This linear and nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. From the point of view of space weather the predictions of the spatial structure are crucial, as it is important to identify the regions of strong disturbances during intense geospace storms

  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. 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.

  8. 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

  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. 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 more sophisticated hydrological studies in the future.

  11. 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.

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

    PubMed Central

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

    2014-01-01

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

  13. 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.

  14. Spatio-temporal trend analysis of air temperature in Europe and Western Asia using data-coupled clustering

    NASA Astrophysics Data System (ADS)

    Chidean, Mihaela I.; Muñoz-Bulnes, Jesús; Ramiro-Bargueño, Julio; Caamaño, Antonio J.; Salcedo-Sanz, Sancho

    2015-06-01

    Over the last decades, different machine learning techniques have been used to detect climate change patterns, mostly using data from measuring stations located in different parts of the world. Some previous studies focus on temperature as primary variable of study, though there have been other works focused on precipitation or even wind speed as objective variable. In this paper, we use the self-organized Second Order Data Coupled Clustering (SODCC) algorithm to carry out a spatio-temporal analysis of temperature patterns in Europe. By applying the SODCC we identify three different regimes of spatio-temporal correlations based on their geographical extent: small, medium, and large-scale regimes. Based on these regimes, it is possible to detect a change in the spatio-temporal trend of air temperature, reflecting a shift in the extent of the correlations in stations in the Iberian Peninsula and Southern France. We also identify an oscillating spatio-temporal trend in the Western Asia region and a stable medium-scale regime affecting the British Isles. These results are found to be consistent with previous studies in climate change. The patterns obtained with the SODCC algorithm may represent a signal of climate change to be taken into account, and so the SODCC could be used as detection method.

  15. Bifurcation analysis and transient spatio-temporal dynamics for a diffusive plant-herbivore system with Dirichlet boundary conditions.

    PubMed

    Wang, Lin; Watmough, James; Yu, Fang

    2015-08-01

    In this paper, we study a diffusive plant-herbivore system with homogeneous and nonhomogeneous Dirichlet boundary conditions. Stability of spatially homogeneous steady states is established. We also derive conditions ensuring the occurrence of Hopf bifurcation and steady state bifurcation. Interesting transient spatio-temporal behaviors including oscillations in one or both of space and time are observed through numerical simulations. PMID:25974343

  16. In-situ, high spatio-temporal resolution measurements of CO2 flux and isotopic composition on Mammoth Mountain, CA

    NASA Astrophysics Data System (ADS)

    Lewicki, J. L.; Hilley, G. E.; Marino, B.; Bergfeld, D.; Fischer, M. L.; Hancyk, J.; Xu, L.

    2010-12-01

    Measurement of CO2 emissions from volcano flanks and in ground waters has become an integral part of many monitoring programs, as spatial and temporal variations in these emissions may be indicative of volcanic unrest. The source and magnitude of CO2 emissions have been intensely studied at Mammoth Mountain, a dacitic volcano located on the rim of Long Valley caldera, California. These observations, combined with multiple geophysical data sets, suggest that unrest at Mammoth Mountain is driven by periodic release of CO2-rich magmatic fluid derived from basaltic dikes and sills at mid-crustal depths. While measurements of CO2 flux and determination of CO2 sources at volcanoes can place important constraints on gas transport and its relationship to volcanic activity, the spatio-temporal resolution of these measurements has been limited by the time and cost associated with making point CO2 flux measurements using the accumulation chamber (AC) method and sample collection and analysis of isotopic (14C-CO2 and 13C-CO2) compositions. We present a novel instrument platform for real-time monitoring of spatio-temporal distribution, emission rate and source of CO2 in volcanic systems. Time and space averaged CO2 fluxes are measured every half hour by the eddy covariance (EC) method. Least-squares inversions of EC data and modeled footprint functions provide estimates of CO2 emission rate and surface flux spatial distribution. AC measurements of soil CO2 flux yield detailed maps of flux spatial distribution and comparative emission rate estimates. A new field-portable isotopic analyzer provides, for the first time, in-situ, high frequency measurements of 14C and 13C compositions of CO2 in the atmosphere, soil gas, and dissolved in ground water. We tested the CO2 flux-monitoring component of this platform at the Horseshoe Lake tree kill area on Mammoth Mountain from 8 September to 24 October 2006. EC CO2 fluxes ranged from 218 to 3500 g m-2d-1. Maps of surface CO2 flux were simulated based on AC measurements made repeatedly on a grid over a ten-day period; large meteorologically driven variations in surface flux distributions and emission rates (16 to 52 t d-1) were observed. Using footprint modeling, we compared EC to AC measurements of CO2 flux. Half-hour EC CO2 fluxes were moderately correlated (R2 = 0.42) with AC fluxes, whereas average-daily EC and AC fluxes were well correlated (R2 = 0.70). The integrated CO2 flux and isotopic monitoring platform will be deployed and tested in Fall 2010 at Mammoth Mountain. EC and AC measurements of CO2 fluxes will be made at the Horseshoe Lake tree kill area and modeled CO2 surface flux distributions and emission rates will be compared. Measurements of 14C and 13C compositions of atmospheric, soil, and ground water CO2 will provide real-time determination of CO2 source.

  17. 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:25426044

  18. [Spatio-temporal pattern of larvae and eggs of gastrointestinal nematodes in cattle pastures in Veracruz, Mexico].

    PubMed

    Flota-Bauelos, Carolina; Martnez, Imelda; Lpez-Collado, Jos; Vargas Mendoza, Mnica; Gonzlez Hernndez, 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

  19. 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

  20. 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 (?2H and ?18O) 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 ?2H and ?18O 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 ?2H and ?18O in tap water from across the contiguous U.S. and Canada was conducted. The data show that seasonal variability in ?2H and ?18O of tap water is generally low (<10 for ?2H), 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 (?2H). The results from this study confirm the existence of temporal variability in ?2H and ?18O 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 ?2H and ?18O, leading to more robust and statistically defensible tests of geographic origin.

  1. Correlating analysis on spatio-temporal variation of LUCC and water resources based on remote sensing data

    NASA Astrophysics Data System (ADS)

    Lin, Yi; Liu, Bing; Lu, Yuan; Xie, Feng

    2014-05-01

    Accurate classification for land use/cover with remote sensing image is the premise of monitoring land use/cover change, as well as temporal and spatial change analysis, which can distinguish the number, location and type of changed land during monitoring years. This paper presents a decision tree classification method based on expert knowledge for temporal and spatial variation analysis of land use/cover, which takes advantage of new water index (NWI), normalization construction index (NDBI) and transformational vegetation index (TNDVI). It takes Qingpu District in Shanghai for example. Effective classification and information extraction are realized by using multi-temporal Landsat5 TM images from the year 1987 to 2007. It combines available ancillary geographical data, field survey data and statistical yearbook data to verify the analysis results, and then analyzes profoundly area variation trend of each classification and relative proportion during these years. Meanwhile, multi-temporal change monitoring results are used for the temporal and spatial variation analysis of water resources information, combining with existing relevant data of water quality. On the basis of buffer analysis for water quality and land use/cover in city-level water quality monitoring stations of Qingpu District, a correlation coefficient matrix has been calculated to analyze the relevance between land resources changes and water resources. In conclusion, the scale of urban area and water area are the primary driving force factors of LUCC, which also have an effect on water resource change of Qingpu District. This research represents the application of image recognition technology in the spatio-temporal changes of environment monitoring, and how to carry on deep analysis combined with various non-spatial data. It also provides objective reference about how to protect and improve water quality by controlling land use allocation in water source protection zones.

  2. 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

  3. 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

  4. 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 spatio-temporal and oscillatory dynamics can evolve from a relatively small number of interacting local circuits. PMID:26635545

  5. 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 into concentric ring-shaped areas. Such an approach allows us to specify the maximum size of the network, where the evident uniform spatial response can be still noticed. In terms of reliable CMEs extraction, the local networks have to be up to 500-600 kilometres extent depending on its character (location). In this study we examined three approaches of spatio-temporal filtering based on stacking procedure. First was based on non-weighted (Wdowinski et. al., 1997) and second on weighted average formula, where the weights are formed by the RMS of individual station position in the corresponding epoch (Nikolaidis, 2002). The third stacking approach, proposed here, was previously unused. It combines the weighted stacking together with the distance between the station and network barycentre into one approach. The analysis allowed to determine the optimal size of local GNSS network and to select the appropriate stacking method for obtaining the most stable solutions for e.g. geodynamical studies. The values of L1 and L2 norms, RMS values of time series (describing stability of the time series) and Pearson correlation coefficients were calculated for the North, East and Up components from more than 200 permanent stations twice: before performing the filtration and after weighted stacking approach. We showed the improvement in the quality of time series analysis using MLE (Maximum Likelihood Estimation) to estimate noise parameters. We demonstrated that the relative RMS improvement of 10, 20 and 30% reduces the noise amplitudes of about 20, 35 and 45%, respectively, what causes the velocity uncertainty to be reduced of 0.3 mm/yr (for the assumption of 7-years of data and flicker noise). The relative decrement of spectral index kappa is 25, 35 and 45%, what means lower velocity uncertainty of even 0.2 mm/yr (when assuming 7 years of data and noise amplitude of 15 mm/yr^-kappa/4) . These results refer to the growing demands on the stability of the series due to their use to realize the kinematic reference frames and for geodynamical studies.

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

    PubMed

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

    1996-11-01

    This paper is an attempt to understand how knowledge and events are represented and processed in the brain. An important point is the question of what carries information in the brain - the mean firing rate or the timing of spikes? The idea we want to pursue is that, contrary to the traditional view, the brain might use higher order statistics, which means in essence that timing of spikes plays a critical role in encoding, representing, and processing knowledge and events in the brain.A recently revealed salient nature of cortical pyramidal cells, i.e., the high variability of inter-spike intervals suggests that a cortical neuron may function effectively as a coincidence detector. At the same time, non-classical experimental phenomena of task-related, short time-scaled dynamical modulations of temporal correlations between neurons suggest a non-classical view on the dynamics working in the brain. In response to contexts or external events, a group of neurons, a dynamical cell assembly, spontaneously organizes, linked temporarily by coincident timing of incident spikes, showing correlated firing with each other. This is an emergent property of neuronal populations in the cortex.We make a theoretical exploration on issues as (1) the description of such emergent dynamics of dynamical cell assemblies based on the working hypothesis that a cortica neuron functions effectively as a coincidence detector, and (2) the principle of spatio-temporal coding based on the hypothetical emergent dynamics. Note that the conventional rate coding hypothesis does not give satisfactory answers to fundamental questions on the representation and processing of knowledge or events in the brain, e.g., the questions of cross-modular integration of information or the binding problem, and representation of hierarchical knowledge etc.The first goal is to give a non-encyclopedic review on (1) the temporal structure of spike sequences, focusing on the question of the basic code in the brain; (2) the paradigms on representation of knowledge and events proposed from a theoretical or experimental basis. The classical paradigms of Hebb and Barlow with their experimental and theoretical critiques, and more recently proposed experiment-based paradigms are reviewed. Also a review is given on (3) the experimentally observed spatio-temporal structure of spike dynamics.The second goal is to give a description of the dynamical cell assembly - the central concept in this paper. Aside from the question of physiological basis, we make a theoretical study, under a working hypothesis that a cortical neuron functions effectively as a coincidence detector, on the emergent dynamics of cell assemblies, and also examine how the observed experimental data could be explained within this theoretical setting.We also try to give the principle of spatio-temporal coding based on the dynamical cell assembly framework. A key concept is the internal mechanism of "dialogue" among neuronal pools in the brain. This provides a dynamical foundation of bi-directional interactions for the linkage of distant modules to create integrated information. We present a simple model in order to illustrate the working principle of coincidence detector systems. Relations with other temporal coding paradigms are also discussed. Copyright 1996 Elsevier Science Ltd. PMID:12662537

  7. 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 group, e.g. static measurements may be moved to another location or the sampling times may be rearranged. After several optimisation steps, the objective functions of the sampling designs are compared. Only for the best ones optimisation is pursued. After several iterations the sampling designs are selected again. Thus more and more of the low performing sampling designs are deleted and computational effort is concentrated on the most promising candidates. The use case is optimisation of a monitoring sampling design for a river. We use a flow model to simulate the spread of a pollutant that enters the system at different locations with known, location-dependent probabilities and at random times. The objective function to be minimised is the amount of pollution that is not detected. Keywords: spatio-temporal sampling design, static sample, synchronous sample, spatial simulated annealing, cost function References [1] Jaap de Gruijter, Dick Brus, Marc Bierkens, and Martin Knotters. Sampling for Natural Ressource Monitoring. Springer, 2006. [2] J. W. van Groenigen. Spatial simulated annealing for optimizing sampling, In: GeoENV I Geostatistics for environmental applications, pages 351 - 361, 1997.

  8. A spatio-temporal Fourier-transform approach to acousto-optic interaction of light beams with cw and pulsed ultrasonic waves

    NASA Astrophysics Data System (ADS)

    Tarn, Chen-Wen; Banerjee, Partha P.

    1991-10-01

    We use a spatio-temporal Fourier-transform approach and a perturbation technique to analyze acousto-optic interaction between an input optical beam of arbitrary profile and pulsed ultrasound. We write the sound field as a superposition of a time- harmonic constant-amplitude wave and a modulated pulse. While the scattering of the input light beam by the former component can be effectively handled using a spatial Fourier-transform technique, the additional contribution can be analyzed using a spatio- temporal Fourier-transform approach. Numerical results, calculated using the equivalent spatial and spatio-temporal transfer functions, are shown for the case of Bragg diffraction.

  9. Intercomparing hillslope hydrological dynamics: Spatio-temporal variability and vegetation cover effects

    NASA Astrophysics Data System (ADS)

    Bachmair, S.; Weiler, M.; Troch, P. A.

    2012-05-01

    Generalizable process knowledge on hillslope hydrological dynamics is still very poor, yet indispensable for numerous theoretical and practical applications. To gain insight into the organization of hillslope hydrological dynamics we intercompared 90 observations of shallow water table dynamics at three neighboring large-scale (33 75 m) hillslopes with similar slope, aspect, curvature, geologic, and pedologic properties but differences in vegetation cover (grassland, coniferous forest, and mixed forest) over a time period of 9 months. High-resolution measurements of water table fluctuations, rainfall, and discharge in the creek at the foot of all hillslopes allowed a good system characterization. The aim of this study was to explore the spatio-temporal variability of water table fluctuations within and between hillslopes, the effect of event and antecedent characteristics on the observed dynamics, and how the hillslope subsurface flow (SSF) response is reflected in the runoff response. To intercompare the SSF behavior we conducted an event-based analysis of the percentage of well activation, several metrics characterizing the shape and timing of the water table response curves, rainfall characteristics, antecedent wetness conditions, and several runoff response metrics. The analysis reveals that there are distinct differences in SSF response between the grassland hillslope and the forested hillslopes, with a lower frequency of well activation and absolute water table rise at the grassland hillslope. Second, spatial patterns of water table dynamics differ between wet fall/winter/spring (predominantly saturation of the lower part of the hillslope, weaker water table response, and slower response times) and dry summer conditions (whole-hillslope activation but higher spatial variability, generally stronger water table dynamics, and quicker response times). The observed seasonally changing water table dynamics suggest the development of a preferential flow network during high-intensity rainstorms under dry summer conditions. Third, catchment runoff is strongly driven by hillslope dynamics, yet contrasting hydrographs during events with similar hillslope dynamics indicate the influence of additional processes. Overall, the observed high spatio-temporal variability of seemingly homogeneous hillslopes calls for rethinking of current monitoring strategies and developing and testing new conceptual models of hillslope hydrologic processes.

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

    NASA Astrophysics Data System (ADS)

    Biswas, Asim

    2014-05-01

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

  11. 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 yields several consistent relationships that persist across a variety of settlement types and physical environments. We use the multiple threshold method of Small et al (2011) to represent a continuum of settlement density by segmenting both night light brightness and multi-season land cover characteristics. Rank-size distributions of spatially contiguous segments quantify scaling and connectivity of land cover. Spatial and temporal evolution of rank-size distributions is consistent with power laws as suggested by Zipf's Law for city size based on population. However, unlike Zipf's Law, the observed distributions persist to global scales in which the larger agglomerations are much larger than individual cities. The scaling relations observed extend from the scale of cities and smaller settlements up to vast spatial networks of interconnected settlements.

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

    PubMed

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

    2012-05-01

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

  13. 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 11 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 implemented. The results from this study exhibit the observable changes in the rainfall extreme events that occurred over India in past century. The country experienced large spatial heterogeneity of all the four rainfall variables, even in the meteorologically homogeneous regions. The correlation analyses show that the maximum grids are having positive correlation, however for the duration-frequency, a significant correlation is observed in few grids, with most of the grids showing no correlation. The spatial variation of RL shows spatial heterogeneity and trend analyses exhibit lack of uniformity throughout India. The change in RL shows significant positive change in mainly during past 50 years. The possible reason could be urbanization and change in climate variables. Hence for further investigation, this analysis will be associated with the temperature extremes data throughout India.

  14. 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 Krmn 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 Krmn vortices in the flow field. Also, a local advection velocity of dominant eddies is inferred using lagged cross-correlations of scalar concentration time series at different spatial locations. The computed probability density function of this advection velocity agrees well with the laser Doppler anemometry measurements for the same rod canopy.

  15. 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 strategies for the geographic areas characterized by the highest CNRs. Further studies are required to understand the factors associated with clustering based on individual level locations and investigation of cases. PMID:26030162

  16. 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 number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.

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

    NASA Astrophysics Data System (ADS)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Srer, S.; Akyrek, Z.; Arda ?orman, A.; ?orman, A. ?.; nal ?orman, A.

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Cooper, Michael; Rees, Gareth; Bartsch, Annett

    2014-05-01

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

  20. 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 interpretation of variation in δ13C of consumers in food webs, particularly where data for baselines are absent over broad scales.

  1. The influence of the inhomogeneous gain profile on the spatio-temporal dynamics of broad-area class B lasers

    NASA Astrophysics Data System (ADS)

    Cabrera-Granado, E.; Odn Soler Rus, M.; Guerra, J. M.

    2010-03-01

    A study on the spatio-temporal dynamics of broad-area Nd:YAG (yttrium aluminium garnet), Nd-doped phosphate glass and Nd-doped silicate glass lasers is presented to show the influence of the inhomogeneous gain profile and cross-relaxation phenomena on the spatio-temporal dynamics of the system. The suppression of the order-disorder transition shown in Cabrera et al (2006 Opt. Lett. 31 1067) for homogeneously broadened class B lasers is found for both glass lasers, independently of the strength of the cross-relaxation mechanisms. The results obtained indicate that a higher degree of inhomogeneous broadening leads to suppression of the filamentation in the transverse intensity pattern.

  2. 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 operations can be assigned to space time datasets or to the results of operations between space time datasets. The temporal vector algebra adds spatial overlay and buffer operations that can be performed on temporal related vector map layers that are registered in space time vector datasets. Whereas the temporal raster and 3D raster algebra uses a subset of the arithmetic operators and spatial functions from the raster algebra in GRASS GIS. It provides in addition spatio-temporal neighborhood operators and spatio-temporal functions. All operations between multiple space time datasets can be combined in nested expressions and are preprocessed by meta data topology analysis before the relevant expressions are computed with parallel processing. [1] Tomlin, C. Dana., 1990. Geographic Information Systems and Cartographic Modeling. Englewood Cliffs, NJ: Prentice-Hall. [2] Gebbert, S., Pebesma, E., 2014. A temporal GIS for field based environmental modeling. Environ. Model. Softw. 53, 1-12.

  3. 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

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

    NASA Astrophysics Data System (ADS)

    Nasser, Hassan; Marre, Olivier; Cessac, Bruno

    2013-03-01

    Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles.

  5. Spatio-temporal templates of transient attention revealed by classification images.

    PubMed

    Megna, Nicola; Rocchi, Francesca; Baldassi, Stefano

    2012-02-01

    Visual attention is captured by transient signals in the periphery of the visual field, allowing enhanced perceptual representations in spatial tasks. However, it has been reported that the same cues impair performance in temporal tasks (e.g., Yeshurun, 2004; Yeshurun & Levy, 2003). This findings suggest that transient attention enhances the activity of slow, high-resolution channels, like parvocellular neurons, and/or shuts off faster channels better sensitive to low spatial frequencies, such as the ones of the magnocellular system. To test this idea, we have measured the spatio-temporal perceptive fields for transiently cued signals at various eccentricities using the classification images (CI) technique. At near eccentricities transient attention caused the perceptual templates to be sharper in space and characterized by much stronger high spatial frequency components. At the same time, they show a consistently larger temporal integration window. These effects of attention on perceptual filters are strongly reduced at far eccentricities and disappear when using longer target-cue lags. These data provide evidence in support of the parvocellular model of transient, exogenous attention, showing that in the presence of a well timed spatial cue observers rely on noisy evidence lasting longer and with finer spatial configurations. PMID:22186227

  6. A Spatio-Temporal Approach To Evolution Of Spatial Homogeneity Of Monsoon Extremes Over India

    NASA Astrophysics Data System (ADS)

    Ghosh, S.; Banerjee, B.; Sandeep, S.; Ravindran, A. M.

    2014-12-01

    There is a growing literature on climate change w.r.t. severe changes in extreme events related to the Monsoon rainfall over India. Evidence of increasing spatial variability of extreme rainfall triggers several aspects such as: how are the spatially homogeneous regions or clusters changing w.r.t. extreme rainfall over time? Is there detectable evidences of changes in cluster behavior? Can we arrive at a forecast? Purpose of this study is twofold: firstly, we introduce a novel discrete-time finite state-space hidden Markov models with non-constant transition matrix depending on a set of exogenous covariates including cluster level temporal information. We present a space-time varying dynamic with conditionally independent Generalized Extreme value (GEV) distribution as modeling extremes. Secondly, we introduce a model based spatio-temporal clustering algorithm based on the latter model. We illustrate this technique based on Monsoon rainfall data and show that the cluster characteristics are significantly changing along with the number of clusters. We also obtain one step ahead future patterns of the clusters.

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

    PubMed

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

    2007-06-01

    This paper presents various spatio-temporal feature-extraction techniques with applications to online and offline recognitions of isolated Arabic Sign Language gestures. The temporal features of a video-based gesture are extracted through forward, backward, and bidirectional predictions. The prediction errors are thresholded and accumulated into one image that represents the motion of the sequence. The motion representation is then followed by spatial-domain feature extractions. As such, the temporal dependencies are eliminated and the whole video sequence is represented by a few coefficients. The linear separability of the extracted features is assessed, and its suitability for both parametric and nonparametric classification techniques is elaborated upon. The proposed feature-extraction scheme was complemented by simple classification techniques, namely, K nearest neighbor (KNN) and Bayesian, i.e., likelihood ratio, classifiers. Experimental results showed classification performance ranging from 97% to 100% recognition rates. To validate our proposed technique, we have conducted a series of experiments using the classical way of classifying data with temporal dependencies, namely, hidden Markov models (HMMs). Experimental results revealed that the proposed feature-extraction scheme combined with simple KNN or Bayesian classification yields comparable results to the classical HMM-based scheme. Moreover, since the proposed scheme compresses the motion information of an image sequence into a single image, it allows for using simple classification techniques where the temporal dimension is eliminated. This is actually advantageous for both computational and storage requirements of the classifier. PMID:17550118

  8. 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.; Masqu, 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.

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  12. Spatio-Temporal Variability of Saturated Crevasses Along the Margins of Jakobshavn ISBR

    NASA Astrophysics Data System (ADS)

    Ring, A.; Lampkin, D. J.

    2014-12-01

    Jakobshavn Isbr 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.

  13. 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

  14. PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

    NASA Astrophysics Data System (ADS)

    Holden, P. B.; Edwards, N. R.; Garthwaite, P. H.; Fraedrich, K.; Lunkeit, F.; Kirk, E.; Labriet, M.; Kanudia, A.; Babonneau, F.

    2013-06-01

    Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5 resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

  15. 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.

  16. Drivers and Spatio-Temporal Extent of Hyporheic Patch Variation: Implications for Sampling

    PubMed Central

    Braun, Alexander; Auerswald, Karl; Geist, Juergen

    2012-01-01

    The hyporheic zone in stream ecosystems is a heterogeneous key habitat for species across many taxa. Consequently, it attracts high attention among freshwater scientists, but generally applicable guidelines on sampling strategies are lacking. Thus, the objective of this study was to develop and validate such sampling guidelines. Applying geostatistical analysis, we quantified the spatio-temporal variability of parameters, which characterize the physico-chemical substratum conditions in the hyporheic zone. We investigated eight stream reaches in six small streams that are typical for the majority of temperate areas. Data was collected on two occasions in six stream reaches (development data), and once in two additional reaches, after one year (validation data). In this study, the term spatial variability refers to patch contrast (patch to patch variance) and patch size (spatial extent of a patch). Patch contrast of hyporheic parameters (specific conductance, pH and dissolved oxygen) increased with macrophyte cover (r2 = 0.95, p<0.001), while patch size of hyporheic parameters decreased from 6 to 2 m with increasing sinuosity of the stream course (r2 = 0.91, p<0.001), irrespective of the time of year. Since the spatial variability of hyporheic parameters varied between stream reaches, our results suggest that sampling design should be adapted to suit specific stream reaches. The distance between sampling sites should be inversely related to the sinuosity, while the number of samples should be related to macrophyte cover. PMID:22860053

  17. 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

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

    PubMed

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

    2015-07-01

    We studied the temporal and spatial patterns of leptospirosis, its association with flooding and animal census data in Thailand. Flood data from 2010 to 2012 were extracted from spatial information taken from satellite images. The incidence rate ratio (IRR) was used to determine the relationship between spatio-temporal flooding patterns and the number of human leptospirosis cases. In addition, the area of flood coverage, duration of waterlogging, time lags between flood events, and a number of potential animal reservoirs were considered in a sub-analysis. There was no significant temporal trend of leptospirosis over the study period. Statistical analysis showed an inconsistent relationship between IRR and flooding across years and regions. Spatially, leptospirosis occurred repeatedly and predominantly in northeastern Thailand. Our findings suggest that flooding is less influential in leptospirosis transmission than previously assumed. High incidence of the disease in the northeastern region is explained by the fact that agriculture and animal farming are important economic activities in this area. The periodic rise and fall of reported leptospirosis cases over time might be explained by seasonal exposure from rice farming activities performed during the rainy season when flood events often occur. We conclude that leptospirosis remains an occupational disease in Thailand. PMID:25778527

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

    Spatio-temporal image correlation spectroscopy (STICS) is a powerful technique for assessing the nature of particle motion in complex systems although it has been rarely used to investigate the intracellular dynamics of nanocarriers so far. Here we introduce a method for characterizing the mode of motion of nanocarriers and for quantifying their transport parameters on different length scales from single-cell to subcellular level. Using this strategy we were able to study the mechanisms responsible for the intracellular transport of DOTAP-DOPC/DNA (DOTAP: 1,2-dioleoyl-3-trimethylammonium-propane; DOPC: dioleoylphosphocholine) and DC-Chol-DOPE/DNA (DC-Chol: 3?-[N-(N,N-dimethylaminoethane)-carbamoyl] cholesterol; DOPE: dioleoylphosphatidylethanolamine) lipoplexes in CHO-K1 (CHO: Chinese hamster ovary) live cells. Measurement of both diffusion coefficients and velocity vectors (magnitude and direction) averaged over regions of the cell revealed the presence of distinct modes of motion. Lipoplexes diffused slowly on the cell surface (diffusion coefficient: D ? 0.003 ?m2 s-1). In the cytosol, the lipoplexes motion was characterized by active transport with average velocity v ? 0.03 ?m2 s-1 and random motion. The method permitted us to generate an intracellular transport map showing several regions of concerted motion of lipoplexes.

  20. 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.

  1. 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

  2. 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

  3. Object-based rate allocation with spatio-temporal trade-offs

    NASA Astrophysics Data System (ADS)

    Lee, Jeong-Woo; Vetro, Anthony; Wang, Yao; Ho, Yo-Sung

    2002-01-01

    This paper describes a bit allocation algorithm that can achieve a constant bit rate when coding multiple video objects (MVOs), while improving the rate-distortion (R-D) performance over the reference method for MPEG-4 object-based rate control. In object-based coding, bit allocation is performed at the object level and temporal rates of different objects may vary. The proposed algorithm in this paper deals with these two issues. We pay particular attention to maintenance of buffer occupancy levels and propose a new method for spatio-temporal trades-offs for object-based coding. In order to improve the coding efficiency, we also consider several new R-D coding modes. These modes are available at the encoder to determine the best R-D performance under different coding conditions and are chosen automatically. Simulation results demonstrate moderate improvements at low and high bit rates. One important key aspect of the proposed algorithm is that the actual coded bits in the proposed algorithm are similar to the target bits over a wide range of bit rates. Consequently, the proposed algorithm has not experienced the buffer overflow/underflow over the entire range of bit rates.

  4. Spatio-temporal contextual approaches to mapping land cover change based on remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Jingxiong; Zhang, Jinping; Tang, Yunwei; You, Jiong

    2009-10-01

    This paper explores data-driven methods for quantifying and incorporating spatio-temporal contextual information in the mapping of land cover change. In remote sensing, area classes of land cover are typically mapped via statistical manipulation of feature-space measurement, e.g., reflectance data, and other ancillary data. Contextual information has been known to have the potential of increasing the accuracy of land cover classification and change detection, on the ground that land cover often exhibits spatial and temporal correlations and, as such, should be properly accommodated. In Bayesian methods, a priori probabilities of class occurrences can be considered as contextual information, which are combined with class-conditional probability densities to arrive at discriminant decisions with minimized misclassification. These prior probabilities may be made to vary locally to honor variability in the strengths of spatial dependence in class occurrences. For deriving local prior joint probabilities in land cover co-occurrences over time, a modified Expectation and Maximization (EM) algorithm was developed, in which a local window size can be adjusted in the light of spatial dependences inferred from class probability densities computed from spectral data. Empirical studies were performed using bi-temporal Landsat TM image subsets in Wuhan, which confirmed the comparative benefits of incorporating localized prior probabilities in land cover change detection.

  5. 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

  6. 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

  7. 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 others 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

  8. Stability and dynamics of spatio-temporal structures. Progress report, September 15, 1992--September 15, 1993

    SciTech Connect

    Riecke, H.

    1993-03-01

    The main goal of the project supported in this grant is to contribute to the understanding of localized spatial and spatio-temporal structures far from thermodynamic equilibrium. Here we report on our progress in the study of two classes of systems. (1) We have started to investigate localized wave-pulses in binary-mixture convection. This work is based on our recently derived extension of the conventionally used complex Ginzburg-Landau equations. We are considering three regimes: Dispersion-less supercritical waves; strongly dispersive subcritical waves; and localized waves as bound states of fronts between dispersionless subcritical waves and the motionless conductive state. (2) We have completed our investigation of steady domain structures in which domains of structures with different wave numbers alternate, separated by domain walls. In particular, we have studied their regimes of existence and stability within the framework of a Ginzburg-Landau equation and have compared it to previous results. Those were based on a long-wavelength approximation, which misses certain aspects which turn out to be important for the stability of the domain structures in realistic situations. In addition, we give a description of our work on resonantly forced waves in two-dimensional anisotropic systems.

  9. 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

  10. Northern gannets anticipate the spatio-temporal occurrence of their prey.

    PubMed

    Pettex, E; Bonadonna, F; Enstipp, M R; Siorat, F; Grmillet, D

    2010-07-15

    Seabirds, as other marine top predators, are often assumed to forage in an unpredictable environment. We challenge this concept and test the hypothesis that breeding Northern gannets (Morus bassanus) anticipate the spatio-temporal occurrence of their prey in the English Channel. We analyzed 23 foraging tracks of Northern gannets breeding on Rouzic Island (Brittany) that were recorded using GPS loggers during 2 consecutive years. All birds commuted between the breeding colony and foraging areas located at a mean distance of 85 km and 72 km (in 2005 and 2006, respectively) from the colony. Mean linearity indices of the outbound and inbound trips were between 0.83 and 0.87, approaching a beeline path to and from the foraging area. Additional parameters (flight speed, and number and duration of stopovers at sea) for the outbound and inbound trip were not statistically different, indicating that birds are capable of locating these feeding areas in the absence of visual clues, and to pin-point their breeding site when returning from the sea. Our bearing choice analysis also revealed that gannets anticipate the general direction of their foraging area during the first 30 min and the first 10 km of the trip. These results strongly suggest that birds anticipate prey location, rather than head into a random direction until encountering a profitable area. Further investigations are necessary to identify the mechanisms involved in seabird resource localization, such as sensorial abilities, memory effects, public information or a combination of these factors. PMID:20581265

  11. 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

  12. 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

  13. 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.

  14. Spatio-temporal variance and meteorological drivers of the urban heat island in a European city

    NASA Astrophysics Data System (ADS)

    Arnds, Daniela; Bhner, Jrgen; 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.

  15. 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

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

    PubMed Central

    Schneider, Johannes; Klein, Teresa; Mielich-Sss, Benjamin; Koch, Gudrun; Franke, Christian; Kuipers, Oscar P.; Kovcs, kos 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

  17. Hierarchical Bayesian Spatio Temporal Model Comparison on the Earth Trapped Particle Forecast

    NASA Astrophysics Data System (ADS)

    Suparta, Wayan; Gusrizal

    2014-10-01

    We compared two hierarchical Bayesian spatio temporal (HBST) results, Gaussian process (GP) and autoregressive (AR) models, on the Earth trapped particle forecast. Two models were employed on the South Atlantic Anomaly (SAA) region. Electron of >30 keV (mep0e1) from National Oceanic and Atmospheric Administration (NOAA) 15-18 satellites data was chosen as the particle modeled. We used two weeks data to perform the model fitting on a 5x5 grid of longitude and latitude, and 31 August 2007 was set as the date of forecast. Three statistical validations were performed on the data, i.e. the root mean square error (RMSE), mean absolute percentage error (MAPE) and bias (BIAS). The statistical analysis showed that GP model performed better than AR with the average of RMSE = 0.38 and 0.63, MAPE = 11.98 and 17.30, and BIAS = 0.32 and 0.24, for GP and AR, respectively. Visual validation on both models with the NOAA map's also confirmed the superior of the GP than the AR. The variance of log flux minimum = 0.09 and 1.09, log flux maximum = 1.15 and 1.35, and in successively represents GP and AR.

  18. Spatio-temporal dynamics of a multi-section tunable laser with and without optical injection

    NASA Astrophysics Data System (ADS)

    Stolz, C. A.; Labukhin, D.; Zakhleniuk, N.; Loudon, R.; Adams, M. J.

    2010-04-01

    Optically-injected semiconductor lasers have been investigated for many years. The attention has nowadays shifted towards multi-section lasers as they provide new kinds of applications. Recently, an improved travelling-wave (TW) method for simulation of multi-section lasers was presented in which spatio-temporal effects were included. An automated analysis tool was presented for the simulated data to distinguish between different states of dynamics outside the locking bandwidth as this was not possible before. Here, a three-section tunable laser, with and without optical injection, is simulated with the improved TW method and two new results are found. Firstly, the penetration depth of the optical power inside the DBR section of a solitary three-section laser strongly depends on its position on the tuning characteristic curve. It is shown that even with a small variation of the carrier density in the tuning region a large variation of the penetration depth can be observed and, hence, the optical power emitted out of the grating section changes significantly. Secondly, the dynamics of an optically-injected tunable laser for middle and high injection strengths are presented and it is demonstrated that the locking bandwidth becomes symmetric around zero detuning and new regions of higher-order instabilities appear outside the locking region.

  19. 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

  20. 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.

  1. 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

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

    NASA Astrophysics Data System (ADS)

    Grunwald, Ruediger; Kebbel, Volker; Neumann, Uwe; Griebner, Uwe; Piche, Michel

    2003-11-01

    For spatio-temporal processing of ultrashort-pulse laser beams, design constraints arise from dispersion and diffraction. In sub-10-fs region, temporal and spatial coordinates of propagating wavepackets get non-separable. To enable controlled shaping and detection with spatial resolution, specific advantages of thin-film microoptical arrays are exploited. Transmitting and reflecting components of extremely small conical angles were used to generate multiple nondiffracting beams and self imaging patterns. With novel-type metal-dielectric microaxicons, low-dispersion reflective devices were realized. Beam propagation was simulated with Rayleigh-Sommerfeld diffraction theory. For time-space conversion, matrix processors consisting of thin-film microaxicons were tested. Transversally resolving linear and nonlinear autocorrelation techniques were applied to characterize the space-time-structure of localized few-cycle wavepackets shaped from Ti:sapphire laser beams at pulse durations down to 8 fs. Bessel-like X-waves were shaped and their propagation was studied. In combination with autocorrelation, wavefront analysis of ultrashort-pulse lasers with Bessel-Shack-Hartmann sensors operated in reflection setup was demonstrated.

  3. 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.

  4. 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.

    2015-12-01

    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.

  5. 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

  6. Insight into others' minds: spatio-temporal representations by intrinsic frame of reference.

    PubMed

    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

  7. 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.

  8. Spatio-temporal patterns of stratification on the Northwest Atlantic shelf

    NASA Astrophysics Data System (ADS)

    Li, Yun; Fratantoni, Paula S.; Chen, Changsheng; Hare, Jonathan A.; Sun, Yunfang; Beardsley, Robert C.; Ji, Rubao

    2015-05-01

    A spatially explicit stratification climatology is constructed for the Northwest Atlantic continental shelf using daily averaged hydrographic fields from a 33-year high-resolution, data-assimilated reanalysis dataset. The high-resolution climatology reveals considerable spatio-temporal heterogeneity in seasonal variability with strong interplay between thermal and haline processes. Regional differences in the magnitude and phasing of the seasonal cycle feature earlier development/breakdown in the Middle Atlantic Bight (MAB) and larger peaks on the shelf than in the Gulf of Maine (GoM). The relative contribution of the thermal and haline components to the overall stratification is quantified using a novel diagram composed of two key ratios. The first relates the vertical temperature gradient to the vertical salinity gradient, and the second relates the thermal expansion coefficient to the haline contraction coefficient. Two distinct regimes are identified: the MAB region is thermally-dominated through a larger portion of the year, whereas the Nova Scotian Shelf and the eastern GoM have a tendency towards haline control during the year. The timing of peak stratification and the beginning/end of thermally-positive and thermally-dominant states are examined. Their spatial distributions indicate a prominent latitudinal shift and regionality, having implications for the seasonal cycle of ecosystem dynamics and its interannual variability.

  9. On the angle between the first and second Lyapunov vectors in spatio-temporal chaos

    NASA Astrophysics Data System (ADS)

    Paz, D.; Lpez, J. M.; Rodrguez, M. A.

    2013-06-01

    In a dynamical system the first Lyapunov vector (LV) is associated with the largest Lyapunov exponent and indicatesat any point on the attractorthe direction of maximal growth in tangent space. The LV corresponding to the second largest Lyapunov exponent generally points in a different direction, but tangencies between both vectors can in principle occur. Here we find that the probability density function (PDF) of the angle ? spanned by the first and second LVs should be expected to be approximately symmetric around ?/4 and to peak at 0 and ?/2. Moreover, for small angles we uncover a scaling law for the PDF Q of ?l = ln?? with the system size L: Q(?l) = L-1/2f(?lL-1/2). We give a theoretical argument that justifies this scaling form and also explains why it should be universal (irrespective of the system details) for spatio-temporal chaos in one spatial dimension. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to Lyapunov analysis: from dynamical systems theory to applications.

  10. Spatio-temporal distribution and emergence of beetles in arable fields in relation to soil moisture.

    PubMed

    Holland, J M; Thomas, C F G; Birkett, T; Southway, S

    2007-02-01

    Predatory beetles contribute to the control of crop pests and are an important food resource for farmland birds. Many of these beetle species overwinter as larvae within agricultural soils, however, their spatio-temporal emergence patterns are poorly understood, even though such knowledge can assist with their management for biocontrol. Soil moisture is considered to be a key factor influencing oviposition site selection and larval survival. The time, density and spatial pattern of Carabidae and Staphylidae emergence was therefore measured across two fields and compared to soil moisture levels in the previous winter and adult distribution in the previous July. The mean density of Carabidae and Staphylidae that emerged between April and harvest within each field was 157 and 86 m-2, indicating that soils are an important over-wintering habitat for beneficial invertebrates and should be managed sympathetically if numbers are to be increased. Of the species that were sufficiently numerous to allow their spatial pattern to be analysed, all showed a heterogeneous emergence pattern, although patches with high emergence were stable over the sampling period. The distribution of eight species was influenced by soil moisture levels in the previous winter and eight species, although not the same, were spatially associated with the distribution of adults in the previous summer suggesting that the females selected oviposition areas with the appropriate soil wetness. PMID:17298686

  11. 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 ?g/day) and heavy smoking (>30 cigarettes/day) in the 1970s and 1980s, and a possible cancer cluster around automotive, paint, and organic chemical industries in the early 1970s. These tools have broad application for examining spatially- and temporally-specific relationships between exposures to environmental risk factors and disease.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    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.

  19. 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.

  20. Spatio-temporal analysis of type 2 diabetes mellitus based on differential expression networks.

    PubMed

    Sun, Shao-Yan; Liu, Zhi-Ping; Zeng, Tao; Wang, Yong; Chen, Luonan

    2013-01-01

    T2DM is complex in its dynamical dependence on multiple tissues, disease states, and factors' interactions. However, most existing work devoted to characterizing its pathophysiology from one static tissue, individual factors, or single state. Here we perform a spatio-temporal analysis on T2DM by developing a new form of molecular network, i.e. 'differential expression network' (DEN), which can reflect phenotype differences at network level. Static DENs show that three tissues (white adipose, skeletal muscle, and liver) all suffer from severe inflammation and perturbed metabolism, among which metabolic functions are seriously affected in liver. Dynamical analysis on DENs reveals metabolic function changes in adipose and liver are consistent with insulin resistance (IR) deterioration. Close investigation on IR pathway identifies 'disease interactions', revealing that IR deterioration is earlier than that on SlC2A4 in adipose and muscle. Our analysis also provides evidence that rising of insulin secretion is the root cause of IR in diabetes. PMID:23881262

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

    PubMed

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

    2015-01-01

    Apocarotenoids are a class of compounds that play important roles in nature. In recent years, a prominent role for these compounds in arbuscular mycorrhizal (AM) symbiosis has been shown. They are derived from carotenoids by the action of the carotenoid cleavage dioxygenase (CCD) enzyme family. In the present study, using tomato as a model, the spatio-temporal expression pattern of the CCD genes during AM symbiosis establishment and functioning was investigated. In addition, the levels of the apocarotenoids strigolactones (SLs), C13 α-ionol and C14 mycorradicin (C13/C14) derivatives were analyzed. The results suggest an increase in SLs promoted by the presence of the AM fungus at the early stages of the interaction, which correlated with an induction of the SL biosynthesis gene SlCCD7. At later stages, induction of SlCCD7 and SlCCD1 expression in arbusculated cells promoted the production of C13/C14 apocarotenoid derivatives. We show here that the biosynthesis of apocarotenoids during AM symbiosis is finely regulated throughout the entire process at the gene expression level, and that CCD7 constitutes a key player in this regulation. Once the symbiosis is established, apocarotenoid flux would be turned towards the production of C13/C14 derivatives, thus reducing SL biosynthesis and maintaining a functional symbiosis. PMID:25480008

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

    PubMed

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

    2007-01-01

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

  3. 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

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

    PubMed Central

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

    2011-01-01

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

  5. Spatio-temporal requirements for transposable element piRNA-mediated silencing during Drosophila oogenesis

    PubMed Central

    Dufourt, Jérémy; Dennis, Cynthia; Boivin, Antoine; Gueguen, Nathalie; Théron, Emmanuelle; Goriaux, Coline; Pouchin, Pierre; Ronsseray, Stéphane; Brasset, Emilie; Vaury, Chantal

    2014-01-01

    During Drosophila oogenesis, transposable element (TE) repression involves the Piwi-interacting RNA (piRNA) pathway which ensures genome integrity for the next generation. We developed a transgenic model to study repression of the Idefix retrotransposon in the germline. Using a candidate gene KD-approach, we identified differences in the spatio-temporal requirements of the piRNA pathway components for piRNA-mediated silencing. Some of them (Aub, Vasa, Spn-E) are necessary in very early stages of oogenesis within the germarium and appear to be less important for efficient TE silencing thereafter. Others (Piwi, Ago3, Mael) are required at all stages of oogenesis. Moreover, during early oogenesis, in the dividing cysts within the germarium, Idefix anti-sense transgenes escape host control, and this is associated with very low piwi expression. Silencing of P-element-based transgenes is also strongly weakened in these cysts. This region, termed the ‘Piwiless pocket’ or Pilp, may ensure that new TE insertions occur and are transmitted to the next generation, thereby contributing to genome dynamics. In contrast, piRNA-mediated silencing is strong in germline stem cells in which TE mobilization is tightly repressed ensuring the continued production of viable germline cysts. PMID:24288375

  6. 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.

  7. 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.

  8. 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

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

    PubMed Central

    Paireau, Juliette; Girond, Florian; Collard, Jean-Marc; Manassara, Halima B.; Jusot, Jean-Franois

    2012-01-01

    Background Meningococcal meningitis is a major health problem in the African Meningitis Belt where recurrent epidemics occur during the hot, dry season. In Niger, a central country belonging to the Meningitis Belt, reported meningitis cases varied between 1,000 and 13,000 from 2003 to 2009, with a case-fatality rate of 515%. Methodology/Principal Findings In order to gain insight in the epidemiology of meningococcal meningitis in Niger and to improve control strategies, the emergence of the epidemics and their diffusion patterns at a fine spatial scale have been investigated. A statistical analysis of the spatio-temporal distribution of confirmed meningococcal meningitis cases was performed between 2002 and 2009, based on health centre catchment areas (HCCAs) as spatial units. Anselin's local Moran's I test for spatial autocorrelation and Kulldorff's spatial scan statistic were used to identify spatial and spatio-temporal clusters of cases. Spatial clusters were detected every year and most frequently occurred within nine southern districts. Clusters most often encompassed few HCCAs within a district, without expanding to the entire district. Besides, strong intra-district heterogeneity and inter-annual variability in the spatio-temporal epidemic patterns were observed. To further investigate the benefit of using a finer spatial scale for surveillance and disease control, we compared timeliness of epidemic detection at the HCCA level versus district level and showed that a decision based on threshold estimated at the HCCA level may lead to earlier detection of outbreaks. Conclusions/Significance Our findings provide an evidence-based approach to improve control of meningitis in sub-Saharan Africa. First, they can assist public health authorities in Niger to better adjust allocation of resources (antibiotics, rapid diagnostic tests and medical staff). Then, this spatio-temporal analysis showed that surveillance at a finer spatial scale (HCCA) would be more efficient for public health response: outbreaks would be detected earlier and reactive vaccination would be better targeted. PMID:22448297

  10. 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; Rod, 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

  11. 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 Ficks 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

  12. Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing.

    PubMed

    Wiklund, Urban; Karlsson, Marcus; Ostlund, Nils; Berglin, Lena; Lindecrantz, Kaj; Karlsson, Stefan; Sandsj, Leif

    2007-06-01

    Intermittent disturbances are common in ECG signals recorded with smart clothing: this is mainly because of displacement of the electrodes over the skin. We evaluated a novel adaptive method for spatio-temporal filtering for heartbeat detection in noisy multi-channel ECGs including short signal interruptions in single channels. Using multi-channel database recordings (12-channel ECGs from 10 healthy subjects), the results showed that multi-channel spatio-temporal filtering outperformed regular independent component analysis. We also recorded seven channels of ECG using a T-shirt with textile electrodes. Ten healthy subjects performed different sequences during a 10-min recording: resting, standing, flexing breast muscles, walking and pushups. Using adaptive multi-channel filtering, the sensitivity and precision was above 97% in nine subjects. Adaptive multi-channel spatio-temporal filtering can be used to detect heartbeats in ECGs with high noise levels. One application is heartbeat detection in noisy ECG recordings obtained by integrated textile electrodes in smart clothing. PMID:17440762

  13. Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

    PubMed

    Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

    2015-10-01

    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

  14. 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

  15. 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 (NO?-N), silicate (SiO?), 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 NO?-N (P?=?0.008) to 0.79 for S (depth) (P?spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay. PMID:21181257

  16. Blind source deconvolution for deep Earth seismology

    NASA Astrophysics Data System (ADS)

    Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.

    2007-12-01

    We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.

  17. 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-dimensional flow field in the rotating flow. For this purpose, we generated artificial images for lid-driven cavity flow where true velocity field can be manipulated and validated with respect to the proposed CASTI algorithm. As a result, the CASTI was successfully performed to capture two-dimensional velocity vector in the given cavity flow.

  18. 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

    Neuroscience research suggests that inferring neutral intentions of other people recruits a specific brain network within the inferior fronto-parietal action observation network as well as a putative social network including brain areas subserving theory of mind, such as the posterior superior temporal sulcus (pSTS), the temporo-parietal junction (TPJ), and also the anterior cingulate cortex (ACC). Recent studies on harmful intentions have refined this network by showing the specific involvement of the ACC, amygdala, and ventromedial prefrontal cortex (vmPFC) in early stages (within 200 ms) of information processing. However, the functional dynamics for kind intentions within and among these networks remains unclear. To address this question, we measured electrical brain activity from 18 healthy adult participants while they were performing an intention inference task with three different types of intentions: kind, hostile and non-interactive. Electrophysiological results revealed that kind intentions were characterized by significantly larger peak amplitudes of N2 over the frontal sites than those for hostile and non-interactive intentions. On the other hand, there were no significant differences between hostile and non-interactive intentions at N2. The source analysis suggested that the vicinity of the left cingulate gyrus contributed to the N2 effect by subtracting the kindness condition from the non-interactive condition within 250-350 ms. At a later stage (i.e., during the 270-500 ms epoch), the peak amplitude of the P3 over the parietal sites and the right hemisphere was significantly larger for hostile intentions compared to the kind and non-interactive intentions. No significant differences were observed at P3 between kind and non-interactive intentions. The source analysis showed that the vicinity of the left anterior cingulate cortex contributed to the P3 effect by subtracting the hostility condition from the non-interactive condition within 450-550 ms. 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

  19. Blind source separation using temporal predictability.

    PubMed

    Stone, J V

    2001-07-01

    A measure of temporal predictability is defined and used to separate linear mixtures of signals. Given any set of statistically independent source signals, it is conjectured here that a linear mixture of those signals has the following property: the temporal predictability of any signal mixture is less than (or equal to) that of any of its component source signals. It is shown that this property can be used to recover source signals from a set of linear mixtures of those signals by finding an un-mixing matrix that maximizes a measure of temporal predictability for each recovered signal. This matrix is obtained as the solution to a generalized eigenvalue problem; such problems have scaling characteristics of O(N3), where N is the number of signal mixtures. In contrast to independent component analysis, the temporal predictability method requires minimal assumptions regarding the probability density functions of source signals. It is demonstrated that the method can separate signal mixtures in which each mixture is a linear combination of source signals with supergaussian, subgaussian, and gaussian probability density functions and on mixtures of voices and music. PMID:11440597

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

    NASA Astrophysics Data System (ADS)

    Zuluaga-Arias, Manuel D.

    2011-12-01

    Earth's radiation budget is directly influenced by aerosols through the absorption of solar radiation and subsequent heating of the atmosphere. Aerosols modulate the hydrological cycle indirectly by modifying cloud properties, precipitation and ocean heat storage. In addition, polluting aerosols impose health risks in local, regional and global scales. In spite of recent advances in the study of aerosols variability, uncertainty in their spatio-temporal distributions still presents a challenge in the understanding of climate variability. For example, aerosol loading varies not only from year to year but also on higher frequency intraseasonal time scales producing strong variability on local and regional scales. An assessment of the impact of aerosol variability requires long period measurements of aerosols at both regional and global scales. The present dissertation compiles a large database of remotely sensed aerosol loading in order to analyze its spatio-temporal variability, and how this load interacts with different variables that characterize the dynamic and thermodynamic states of the environment. Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as measures of the atmospheric aerosol load. In addition, atmospheric and oceanic satellite observations, and reanalysis datasets is used in the analysis to investigate aerosol-environment interactions. A diagnostic study is conducted to produce global and regional aerosol satellite climatologies, and to analyze and compare the validity of aerosol retrievals. We find similarities and differences between the aerosol distributions over various regions of the globe when comparing the different satellite retrievals. A nonparametric approach is also used to examine the spatial distribution of the recent trends in aerosol concentration. A significant positive trend was found over the Middle East, Arabian Sea and South Asian regions strongly influenced by increases in dust events. Spectral and composite analyses of surface temperature, atmospheric wind, geopotential height, outgoing longwave radiation, water vapor and precipitation together with the climatology of aerosols provide insight on how the variables interact. Different modes of variability, especially in intraseasonal time scales appear as strong modulators of the aerosol distribution. In particular, we investigate how two modes of variability related to the westward propagating synoptic African Easterly Waves of the Tropical Atlantic Ocean affect the horizontal and vertical structure of the environment. The statistical significance of these two modes is tested with the use of two different spectral techniques. The pattern of propagation of aerosol load shows good correspondence with the progression of the atmospheric and oceanic conditions suitable for dust mobilization over the Atlantic Ocean. We present extensions to previous studies related with dust variability over the Atlantic region by evaluating the performance of the long period satellite aerosol retrievals in determining modes of aerosol variability. Results of the covariability between aerosols-environment motivate the use of statistical regression models to test the significance of the forecasting skill of daily AOD time series. The regression models are calibrated using atmospheric variables as predictors from the reanalysis variables. The results show poor forecasting skill with significant error growing after the 3 rd day of the prediction. It is hypothesized that the simplicity of linear models results in an inability to provide a useful forecast.

  1. MUSIC seeded multi-dipole MEG modeling using the Constrained Start Spatio-Temporal modeling procedure.

    PubMed

    Ranken, D M; Stephen, J M; George, J S

    2004-01-01

    The Constrained Start Spatio-Temporal modeling program (CSST) is an objective multi-dipole, multi-start MEG/EEG analysis procedure that randomly selects from 100 to 100,000 initial dipole configurations, and runs a nonlinear simplex search on each of these configurations employing a reduced Chi-square statistic as the minimization criterion, to obtain a set of dipole configurations that best fit the data [Ranken, 2002]. A parallel version of CSST is implemented in IDL and MPI, making CSST usable on a single computer, or on a Linux cluster. We have now developed a multi-resolution version of MUSIC [Mosher, 1992] [Mosher, 1998] that provides an 80% or more reduction in the number of forward calculations needed to obtain results comparable to a 160,000 point MUSIC scan, on a 2 mm grid that defines a brain volume. The multi-resolution MUSIC scan provides an improved set of initial dipole estimates for the CSST analysis. In preliminary tests on real and simulated MEG data, with model orders ranging between 5 and 7 dipoles, the best performance improvements were obtained by mixing in 1 to 3 dipole locations randomly drawn from the best MUSIC locations, with randomly selected locations from the brain volume to complete the selected model order. We have also developed an improved method for sampling the brain volume for initial configurations. These improvements have led to a 75% reduction in the number of starting configurations required to obtain 5-10 best solutions with equal or lower reduced Chi-square values, when compared to the best solutions from the previous version of CSST. PMID:16012631

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

    DOE PAGESBeta

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

    2015-04-22

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  4. Propagation of Seismic Waves Through a Spatio-temporally Fluctuating Medium: Homogenization

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  5. Associations of Dragonflies (Odonata) to Habitat Variables within the Maltese Islands: A Spatio-Temporal Approach

    PubMed Central

    Balzan, Mario V.

    2012-01-01

    Relatively little information is available on environmental associations and the conservation of Odonata in the Maltese Islands. Aquatic habitats are normally spatio-temporally restricted, often located within predominantly rural landscapes, and are thereby susceptible to farmland water management practices, which may create additional pressure on water resources. This study investigates how odonate assemblage structure and diversity are associated with habitat variables of local breeding habitats and the surrounding agricultural landscapes. Standardized survey methodology for adult Odonata involved periodical counts over selected water-bodies (valley systems, semi-natural ponds, constructed agricultural reservoirs). Habitat variables relating to the type of water body, the floristic and physiognomic characteristics of vegetation, and the composition of the surrounding landscape, were studied and analyzed through a multivariate approach. Overall, odonate diversity was associated with a range of factors across multiple spatial scales, and was found to vary with time. Lentic water-bodies are probably of high conservation value, given that larval stages were mainly associated with this habitat category, and that all species were recorded in the adult stage in this habitat type. Comparatively, lentic and lotic seminatural waterbodies were more diverse than agricultural reservoirs and brackish habitats. Overall, different odonate groups were associated with different vegetation life-forms and height categories. The presence of the great reed, Arundo donax L., an invasive alien species that forms dense stands along several water-bodies within the Islands, seems to influence the abundance and/or occurrence of a number of species. At the landscape scale, roads and other ecologically disturbed ground, surface water-bodies, and landscape diversity were associated with particular components of the odonate assemblages. Findings from this study have several implications for the use of Odonata as biological indicators, and for current trends with respect to odonate diversity conservation within the Maltese Islands. PMID:23427906

  6. Spatio-temporal features of vegetation restoration and variation after the Wenchuan earthquake with satellite images

    NASA Astrophysics Data System (ADS)

    Peng, Hou; Qiao, Wang; Yipeng, Yang; Weiguo, Jiang; Bingfeng, Yang; Qiang, Chen; Lihua, Yuan; Fanming, Kong; Xi, Chen; Guanjie, Wang

    2014-01-01

    The Wenchuan earthquake was a deadly earthquake that occurred on May 12, 2008, in Sichuan province of China. With the help of classic statistic methods, including arithmetic mean, standard deviation and linear trend estimation, vegetation restoration was recognized by analyzing spatio-temporal features of normalized difference vegetation index (NDVI) before and after this earthquake. Results indicate: (1) spatial distribution of NDVI mean values remains similar from 1998 to 2011. Higher values are mainly found in north, whereas lower values are mainly distributed over southeast, which is in good correlation with elevation and landform. Vegetation damage is at different levels in different seismic intensity (SI) regions: the higher SI is, the worse vegetation damage is. (2) Over the whole region, standard deviation is bigger after earthquake than before. Both absolute and relative changes in ecosystem stability increase with increasing SI. In different counties, variation of ecosystem stability is more obvious after earthquake, increase of standard deviation is approximately 6.5 times. Relatively, vegetation regionalization is the smallest analysis unit. Consequently, changes resulting from earthquake are unobvious. (3) Linear trend estimation coefficient increases from 0.0079 before the earthquake to 0.0359 after the earthquake in this whole region. This indicates that the plant ecosystem is rapidly restored between 2009 and 2011. The biggest linear trend is for the hill region, indicating good plant restoration and increase after earthquake. Fluctuation of linear trend estimation coefficient in different counties is more obvious after earthquake. Vegetation restoration after earthquake is most obvious in the regions that suffered the greatest SI (SI10 and SI11). In contrast, fluctuation in linear trend estimation coefficient of annual NDVI mean value for different classes of vegetation is more obvious before earthquake.

  7. The Ecuadorian Artisanal Fishery for Large Pelagics: Species Composition and Spatio-Temporal Dynamics.

    PubMed

    Martnez-Ortiz, Jimmy; Aires-da-Silva, Alexandre M; Lennert-Cody, Cleridy E; Maunder, Mark N

    2015-01-01

    The artisanal fisheries of Ecuador operate within one of the most dynamic and productive marine ecosystems of the world. This study investigates the catch composition of the Ecuadorian artisanal fishery for large pelagic fishes, including aspects of its spatio-temporal dynamics. The analyses of this study are based on the most extensive dataset available to date for this fishery: a total of 106,963 trip-landing inspection records collected at its five principal ports during 2008 ? 2012. Ecuadorian artisanal fisheries remove a substantial amount of biomass from the upper trophic-level predatory fish community of the eastern tropical Pacific Ocean. It is estimated that at least 135 thousand metric tons (mt) (about 15.5 million fish) were landed in the five principal ports during the study period. The great novelty of Ecuadorian artisanal fisheries is the "oceanic-artisanal" fleet component, which consists of mother-ship (nodriza) boats with their towed fiber-glass skiffs (fibras) operating with pelagic longlines. This fleet has fully expanded into oceanic waters as far offshore as 100W, west of the Galapagos Archipelago. It is estimated that nodriza operations produce as much as 80% of the total catches of the artisanal fishery. The remainder is produced by independent fibras operating in inshore waters with pelagic longlines and/or surface gillnets. A multivariate regression tree analysis was used to investigate spatio-environmental effects on the nodriza fleet (n = 6,821 trips). The catch species composition of the nodriza fleet is strongly influenced by the northwesterly circulation of the Humboldt Current along the coast of Peru and its associated cold waters masses. The target species and longline gear-type used by nodrizas change seasonally with the incursion of cool waters (< 25C) from the south and offshore. During this season, dolphinfish (Coryphaena hippurus) dominates the catches. However, in warmer waters, the fishery changes to tuna-billfish-shark longline gear and the catch composition becomes much more diverse. PMID:26317751

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  9. Spatio-temporal variability of groundwater nitrate concentration in Texas: 1960 to 2010.

    PubMed

    Chaudhuri, Sriroop; Ale, Srinivasulu; Delaune, Paul; Rajan, Nithya

    2012-01-01

    Nitrate (NO) is a major contaminant and threat to groundwater quality in Texas. High-NO groundwater used for irrigation and domestic purposes has serious environmental and health implications. The objective of this study was to evaluate spatio-temporal trends in groundwater NO concentrations in Texas on a county basis from 1960 to 2010 with special emphasis on the Texas Rolling Plains (TRP) using the Texas Water Development Board's groundwater quality database. Results indicated that groundwater NO concentrations have significantly increased in several counties since the 1960s. In 25 counties, >30% of the observations exceeded the maximum contamination level (MCL) for NO (44 mg L NO) in the 2000s as compared with eight counties in the 1960s. In Haskell and Knox Counties of the TRP, all observations exceeded the NO MCL in the 2000s. A distinct spatial clustering of high-NO counties has become increasingly apparent with time in the TRP, as indicated by different spatial indices. County median NO concentrations in the TRP region were positively correlated with county-based area estimates of crop lands, fertilized croplands, and irrigated croplands, suggesting a negative impact of agricultural practices on groundwater NO concentrations. The highly transmissive geologic and soil media in the TRP have likely facilitated NO movement and groundwater contamination in this region. A major hindrance in evaluating groundwater NO concentrations was the lack of adequate recent observations. Overall, the results indicated a substantial deterioration of groundwater quality by NO across the state due to agricultural activities, emphasizing the need for a more frequent and spatially intensive groundwater sampling. PMID:23128738

  10. Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand

    PubMed Central

    Jeefoo, Phaisarn; Tripathi, Nitin Kumar; Souris, Marc

    2011-01-01

    In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999–2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999–2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well. PMID:21318014

  11. Adapting livestock management to spatio-temporal heterogeneity in semi-arid rangelands.

    PubMed

    Jakoby, O; Quaas, M F; Baumgrtner, S; Frank, K

    2015-10-01

    Management strategies in rotational grazing systems differ in their level of complexity and adaptivity. Different components of such grazing strategies are expected to allow for adaptation to environmental heterogeneities in space and time. However, most models investigating general principles of rangeland management strategies neglect spatio-temporal system properties including seasonality and spatial heterogeneity of environmental variables. We developed an ecological-economic rangeland model that combines a spatially explicit farm structure with intra-annual time steps. This allows investigating different management components in rotational grazing systems (including stocking and rotation rules) and evaluating their effect on the ecological and economic states of semi-arid grazing systems. Our results show that adaptive stocking is less sensitive to overstocking compared to a constant stocking strategy. Furthermore, the rotation rule becomes important only at stocking numbers that maximize expected income. Altogether, the best of the tested strategies is adaptive stocking combined with a rotation that adapts to both spatial forage availability and seasonality. This management strategy maximises mean income and at the same time maintains the rangeland in a viable condition. However, we could also show that inappropriate adaptation that neglects seasonality even leads to deterioration. Rangelands characterised by higher inter-annual climate variability show a higher risk of income losses under a non-adaptive stocking rule, and non-adaptive rotation is least able to buffer increasing climate variability. Overall, all important system properties including seasonality and spatial heterogeneity of available resources need to be considered when designing an appropriate rangeland management system. Resulting adaptive rotational grazing strategies can be valuable for improving management and mitigating income risks. PMID:26241933

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    PubMed Central

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

    2016-01-01

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

  14. Spatio-temporal tuning of motion coherence detection at different luminance levels.

    PubMed

    Lankheet, M J M; van Doorn, A J; van de Grind, W A

    2002-01-01

    We studied effects of dark adaptation on spatial and temporal tuning for motion coherence detection. We compared tuning for step size and delay for moving random pixel arrays (RPAs) at two adaptation levels, one light adapted (50 cd/m(2)) and the other relatively dark adapted (0.05 cd/m(2)). To study coherence detection rather than contrast detection, RPAs were scaled for equal contrast detection at each luminance level, and a signal-to-noise ratio paradigm was used in which the RPA is always at a fixed, supra-threshold contrast level. The noise consists of a spatio-temporally incoherent RPA added to the moving RPA on a pixel-by-pixel basis. Spatial and temporal limits for coherence detection were measured using a single step pattern lifetime stimulus, in which patterns on alternate frames make a coherent step and are being refreshed. Therefore, the stimulus contains coherent motion at a single combination of step size and delay only. The main effect of dark adaptation is a large shift in step size, slightly less than the adjustment of spatial scale required for maintaining equal contrast sensitivity. A similar change of preferred step size occurs also for scaled stimuli at a light-adapted level, indicating that the spatial effect is not directly linked to dark adaptation, but more generally related to changes in the available low-level spatial information. Dark-adaptation shifts temporal tuning by about a factor of 2. Long delays are more effective at low luminance levels, whereas short delays no longer support motion coherence detection. Luminance-invariant velocity tuning curves, as reported previously [Lankheet, M.J.M., van Doorn, A.J., Bouman, M.A., & van de Grind, W.A. (2000) Motion coherence detection as a function of luminance in human central vision. Vision Research, 40, 3599-3611], result from recruitment of different sets of motion detectors, and an adjustment of their temporal properties. PMID:11804632

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

    PubMed Central

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

    2013-01-01

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

  16. Associations of dragonflies (Odonata) to habitat variables within the Maltese Islands: a spatio-temporal approach.

    PubMed

    Balzan, Mario V

    2012-01-01

    Relatively little information is available on environmental associations and the conservation of Odonata in the Maltese Islands. Aquatic habitats are normally spatio-temporally restricted, often located within predominantly rural landscapes, and are thereby susceptible to farmland water management practices, which may create additional pressure on water resources. This study investigates how odonate assemblage structure and diversity are associated with habitat variables of local breeding habitats and the surrounding agricultural landscapes. Standardized survey methodology for adult Odonata involved periodical counts over selected water-bodies (valley systems, semi-natural ponds, constructed agricultural reservoirs). Habitat variables relating to the type of water body, the floristic and physiognomic characteristics of vegetation, and the composition of the surrounding landscape, were studied and analyzed through a multivariate approach. Overall, odonate diversity was associated with a range of factors across multiple spatial scales, and was found to vary with time. Lentic water-bodies are probably of high conservation value, given that larval stages were mainly associated with this habitat category, and that all species were recorded in the adult stage in this habitat type. Comparatively, lentic and lotic seminatural waterbodies were more diverse than agricultural reservoirs and brackish habitats. Overall, different odonate groups were associated with different vegetation life-forms and height categories. The presence of the great reed, Arundo donax L., an invasive alien species that forms dense stands along several water-bodies within the Islands, seems to influence the abundance and/or occurrence of a number of species. At the landscape scale, roads and other ecologically disturbed ground, surface water-bodies, and landscape diversity were associated with particular components of the odonate assemblages. Findings from this study have several implications for the use of Odonata as biological indicators, and for current trends with respect to odonate diversity conservation within the Maltese Islands. PMID:23427906

  17. Spatio-Temporal Variation of Stream Metabolism in a Managed River System

    NASA Astrophysics Data System (ADS)

    Villamizar, S. R.; Pai, H.; Butler, C. A.; Barnes, P. A.; Harmon, T. C.

    2010-12-01

    Metabolism estimates (gross primary production, GPP and community respiration, CR) obtained through the continuous monitoring of physicochemical properties in managed rivers may be used to evaluate the effects of various disturbances on ecosystem function. This work highlights the development of a GPP/CR observational network on the human-dominated Lower Merced River, currently the southern-most extent of Chinook salmon habitat in the Central Valley of California. Our investigations include spatial (both longitudinal and transverse gradients) and temporal (daily, seasonal and interannual) variation of these metabolism estimates as we are interested in relating responses of this type of lotic system to disturbances such as short- or long-term reservoir operational changes for drought management, flood control, fish habitat enhancement, or alleviation of salinity and nutrient discharges due to land management practices. The observational network will be described in terms of: (1) design and installation of a reproducible infrastructure of GPP/CR monitoring stations, (2) analysis aimed at linking the spatio-temporal metabolic trends to natural factors such as the seasonal radiation availability or nutrient input from leaf decay, and (3) separating natural effects from the ones triggered by human disturbances in order to better inform water resources management decisions. Observations over the 2009-10 water year, demonstrate that the Lower Merced River behaves as a heterotrophic system, with large temporal changes in metabolism clearly observable by the monitoring network. For example, the GPP/CR ratio decreased from 0.6 to 0.2 as a consequence of a large flow disturbance associated with short-term reservoir releases mandated biannually to support salmon migration. This and other examples set at different temporal and spatial scales will be presented and discussed in terms of management implications.

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  19. Spatio-temporal dynamics of oscillatory network activity in the neonatal mouse cerebral cortex.

    PubMed

    Sun, Jyh-Jang; Luhmann, Heiko J

    2007-10-01

    We used a 60-channel microelectrode array to study in thick (600-1000 microm) somatosensory cortical slices from postnatal day (P)0-P3 mice the spatio-temporal properties of early network oscillations. We recorded local non-propagating as well as large-scale propagating spontaneous oscillatory activity. Both types of activity patterns could never be observed in neocortical slices of conventional thickness (400 microm). Local non-propagating spontaneous oscillations with an average peak frequency of 15.6 Hz, duration of 1.7 s and maximal amplitude of 66.8 microV were highly synchronized in a network of approximately 200 microm in diameter. Spontaneous oscillations of lower frequency (10.4 Hz), longer duration (23.8 s) and larger amplitude (142.9 microV) propagated with 0.11 mm/s in the horizontal direction over at least 1 mm. These propagating oscillations were also synchronized in a columnar manner, but these waves synchronized the activity in a larger neuronal network of 300-400 microm in diameter. Both types of spontaneous network activity could be blocked by the gap junction antagonist carbenoxolone. Electrical stimulation of the subplate (SP) or bath application of the cholinergic agonist carbachol also elicited propagating network oscillations, emphasizing the role of the SP and the cholinergic system in the generation of early cortical network oscillations. Our data demonstrate that a sufficiently large network in thick neocortical slice preparations is capable of generating spontaneous and evoked network oscillations, which are highly synchronized via gap junctions in 200-400-microm-wide columns. These via synchronized oscillations coupled networks may represent a self-organized functional template for the activity-dependent formation of neocortical modules during the earliest stages of development. PMID:17868367

  20. The spatio-temporal distribution of attention within a face during identification.

    PubMed

    Chen, Wei; Gaspar, Carl

    2015-09-01

    Whole objects, like faces, can strongly attract visual attention. However, little is known about how spatial attention is distributed across the face. During 10AFC identification, we presented a small probe pattern at random locations 106ms after each target-face display. Probe patterns were small squares consisting of high-contrast black and white strips. On the premise that detection speed for probes is enhanced by local attention on the face, probe reaction times should reveal how attention is distributed across the face, in both space and time. We used 3 target-face durations. Face identification accuracy, above-chance for the lowest duration, improved with duration for all 4 subjects. The main data are maps of speed, 1/log(RT), across 3 face durations, for 4 subjects. Each map is based on 60 locations, arranged in an elliptical fashion around fixation (the average center of contrast energy across all faces). Using bootstrap percentile tests, we identified probe locations whose speed was significantly above the spatio-temporal average; these locations show us where attention is. At 12ms, attention is weak and spatially uniform; while at 106ms and 200ms, attention is biased to bottom and right parts of the face from the viewers' perspective. Our results seem surprising given that eye movements (Butler et al, 2005; Peterson & Eckstein, 2012) and classification images (Sekuler et al, 2004) suggest biases toward the top and left. However, the distribution of attention across the face does not necessarily have to match the distribution of extracted information, or fixations. For example, attention might be required to use weak information, less visible regions of the face, or to plan the next fixation. We are currently exploring these possibilities. Meeting abstract presented at VSS 2015. PMID:26326751

  1. Phlegra Montes - Spatio-Temporal Distribution of Ice and Debris at Martian Mid-Latitudes

    NASA Astrophysics Data System (ADS)

    Schulz, J.; van Gasselt, S.; Orgel, C.

    2014-04-01

    Mars hosts an abundance of landforms indicative of near-subsurface ice. Lobate debris aprons belong to a group of well-studied but still enigmatic ice-related landforms which have been identified at mid-latitudes between 30o and 50o in both hemispheres. While nature and origin of ice in these aprons are still controversially debated there is a general consensus that these features are sensitive to climate variability and, consequently, a potential indicator of past climate conditions, and potential water reservoirs today. The northern hemisphere hosts three populations of debris aprons: the Tempe Terra/Mareotis Fossae(TT) region [2, 5], the Deuteronilus/Protonilus Mensae (DPM) [1, 4, 9], and the Phlegra Montes region (PM) [3]. In southern latitudes the impact-basins rims of Argyre (AP) and Hellas Planitiae/Promethei Terra (HP) host a similar, albeit less well-pronounced set of features [1, 2, 6]. While most research is being concentrated on the HP, TT and DPM areas, studies discussing the population of the PM (located at 165o E, 30-50o N, see figure 1) are rather sparse [3, 14, 15, 16] although features are generally well-developed, representative due to their spatial distribution and wellimaged by high-resolution instruments. We performed an integrated spatio-temporal analysis of the PM population and focus on the age distribution of debris aprons in order to constrain their formation age. Our research is motivated by the assumption that if young-Amazonian climate variations have controlled formation and appearance of geomorphic landforms on Mars, we should observe traces of this process in PM as latitudinal trends and variations should provide measurable characteristics. If so, and if surface ages based on crater-frequency analysis are consistent with these assumptions, the exact timing of climate shifts may be assessable.

  2. Injectable system for spatio-temporally controlled delivery of hypoxia-induced angiogenic signalling.

    PubMed

    Hadjipanayi, E; Cheema, U; Hopfner, U; Bauer, A; Machens, H G; Schilling, A F

    2012-08-10

    While chronically ischaemic tissues are continuously exposed to hypoxia, the primary angiogenic stimulus, they fail to appropriately respond to it, as hypoxia-regulated angiogenic factor production gradually undergoes down-regulation, thus hindering adaptive angiogenesis. We have previously reported on two strategies for delivering on demand hypoxia-induced signalling (HIS) in vivo, namely, implanting living or non-viable hypoxic cell-matrix depots that actively produce factors or act as carriers of factors trapped within the matrix during in vitro pre-conditioning, respectively. This study aims to improve this approach through the development of a novel, injectable system for delivering cell-free matrix HIS-carriers. 3D spiral collagen constructs, comprising an inner cellular and outer acellular compartment, were cultured under hypoxia (5% O₂). Cell-produced angiogenic factors (e.g. VEGF, FGF, PLGF, IL-8) were trapped within the nano-porous matrix of the acellular compartment as they radially diffused through it. The acellular matrix was mechanically fragmented into micro-fractions and added into a low temperature (5 °C) thermo-responsive type I collagen solution, which underwent a collagen concentration-dependent solution-to-gel phase transition at 37 °C. Levels of VEGF and IL-8, delivered from matrix fractions into media by diffusion through collagen sol-gel, were up-regulated by day 4 of hypoxic culture, peaked at day 8, and gradually declined towards the baseline by day 20, while FGF levels were stable over this period. Factors captured within matrix fractions were bioactive after 3 months freeze storage, as shown by their ability to induce tubule formation in an in vitro angiogenesis assay. This system provides a minimally invasive, and repeatable, method for localised delivery of time-specific, cell-free HIS factor mixtures, as a tool for physiological induction of spatio-temporally controlled angiogenesis. PMID:22634070

  3. Long-term spatio-temporal changes in a West African bushmeat trade system.

    PubMed

    McNamara, J; Kusimi, J M; Rowcliffe, J M; Cowlishaw, G; Brenyah, A; Milner-Gulland, E J

    2015-10-01

    Landscapes in many developing countries consist of a heterogeneous matrix of mixed agriculture and forest. Many of the generalist species in this matrix are increasingly traded in the bushmeat markets of West and Central Africa. However, to date there has been little quantification of how the spatial configuration of the landscape influences the urban bushmeat trade over time. As anthropogenic landscapes become the face of rural West Africa, understanding the dynamics of these systems has important implications for conservation and landscape management. The bushmeat production of an area is likely to be defined by landscape characteristics such as habitat disturbance, hunting pressure, level of protection, and distance to market. We explored (SSG, tense) the role of these four characteristics in the spatio-temporal dynamics of the commercial bushmeat trade around the city of Kumasi, Ghana, over 27 years (1978 to 2004). We used geographic information system methods to generate maps delineating the spatial characteristics of the landscapes. These data were combined with spatially explicit market data collected in the main fresh bushmeat market in Kumasi to explore the relationship between trade volume (measured in terms of number of carcasses) and landscape characteristics. Over time, rodents, specifically cane rats (Thryonomys swinderianus), became more abundant in the trade relative to ungulates and the catchment area of the bushmeat market expanded. Areas of intermediate disturbance supplied more bushmeat, but protected areas had no effect. Heavily hunted areas showed significant declines in bushmeat supply over time. Our results highlight the role that low intensity, heterogeneous agricultural landscapes can play in providing ecosystem services, such as bushmeat, and therefore the importance of incorporating bushmeat into ecosystem service mapping exercises. Our results also indicate that even where high bushmeat production is possible, current harvest levels may cause wildlife depletion. PMID:26104770

  4. Spatio-temporal attributes of left ventricular pressure decay rate during isovolumic relaxation.

    PubMed

    Ghosh, Erina; Kovcs, Sndor J

    2012-03-01

    Global left ventricular (LV) isovolumic relaxation rate has been characterized: 1) via the time constant of isovolumic relaxation ? or 2) via the logistic time constant ?(L). An alternate kinematic method, characterizes isovolumic relaxation (IVR) in accordance with Newton's Second Law. The model's parameters, stiffness E(k), and damping/relaxation ? result from best fit of model-predicted pressure to in vivo data. All three models (exponential, logistic, and kinematic) characterize global relaxation in terms of pressure decay rates. However, IVR is inhomogeneous and anisotropic. Apical and basal LV wall segments untwist at different times and rates, and transmural strain and strain rates differ due to the helically variable pitch of myocytes and sheets. Accordingly, we hypothesized that the exponential model (?) or kinematic model (? and E(k)) parameters will elucidate the spatiotemporal variation of IVR rate. Left ventricular pressures in 20 subjects were recorded using a high-fidelity, multipressure transducer (3 cm apart) catheter. Simultaneous, dual-channel pressure data was plotted in the pressure phase-plane (dP/dt vs. P) and ?, ?, and E(k) were computed in 1631 beats (average: 82 beats per subject). Tau differed significantly between the two channels (P < 0.05) in 16 of 20 subjects, whereas ? and E(k) differed significantly (P < 0.05) in all 20 subjects. These results show that quantifying the relaxation rate from data recorded at a single location has limitations. Moreover, kinematic model based analysis allows characterization of restoring (recoil) forces and resistive (crossbridge uncoupling) forces during IVR and their spatio-temporal dependence, thereby elucidating the relative roles of stiffness vs. relaxation as IVR rate determinants. PMID:22210748

  5. Spatio-temporal footprints of urbanisation in Surat, the Diamond City of India (1990-2009).

    PubMed

    Sharma, Richa; Ghosh, Aniruddha; Joshi, Pawan Kumar

    2013-04-01

    Urbanisation is a ubiquitous phenomenon with greater prominence in developing nations. Urban expansion involves land conversions from vegetated moisture-rich to impervious moisture-deficient land surfaces. The urban land transformations alter biophysical parameters in a mode that promotes development of heat islands and degrades environmental health. This study elaborates relationships among various environmental variables using remote sensing dataset to study spatio-temporal footprint of urbanisation in Surat city. Landsat Thematic Mapper satellite data were used in conjugation with geo-spatial techniques to study urbanisation and correlation among various satellite-derived biophysical parameters, [Normalised Difference Vegetation Index, Normalised Difference Built-up Index, Normalised Difference Water Index, Normalised Difference Bareness Index, Modified NDWI and land surface temperature (LST)]. Land use land cover was prepared using hierarchical decision tree classification with an accuracy of 90.4 % (kappa = 0.88) for 1990 and 85 % (kappa = 0.81) for 2009. It was found that the city has expanded over 42.75 km(2) within a decade, and these changes resulted in elevated surface temperatures. For example, transformation from vegetation to built-up has resulted in 5.5 ± 2.6 °C increase in land surface temperature, vegetation to fallow 6.7 ± 3 °C, fallow to built-up is 3.5 ± 2.9 °C and built-up to dense built-up is 5.3 ± 2.8 °C. Directional profiling for LST was done to study spatial patterns of LST in and around Surat city. Emergence of two new LST peaks for 2009 was observed in N-S and NE-SW profiles. PMID:22828979

  6. Wildlife in the Matrix: Spatio-Temporal Patterns of Herbivore Occurrence in Karnataka, India.

    PubMed

    Karanth, Krithi K

    2016-01-01

    Wildlife reserves are becoming increasingly isolated from the surrounding human-dominated landscapes particularly in Asia. It is imperative to understand how species are distributed spatially and temporally in and outside reserves, and what factors influence their occurrence. This study surveyed 7500km(2) landscape surrounding five reserves in the Western Ghats to examine patterns of occurrence of five herbivores: elephant, gaur, sambar, chital, and pig. Species distributions are modeled spatio-temporally using an occupancy approach. Trained field teams conducted 3860 interview-based occupancy surveys in a 10-km buffe