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Sample records for 8-20-03 spatio-temporal chaos

  1. 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.

  2. Simulations of the Reaction-Diffusion System demonstrating the Transition from Purely Temporal to Spatio-Temporal Chaos

    NASA Astrophysics Data System (ADS)

    Olsen, Thomas; Hou, Yu; Trail, Collin; Wiener, Richard

    2004-11-01

    The Reaction-Diffusion model (H. Riecke and H.-G. Paap, Europhys. Lett. 14), 1235 (1991).has been applied to a wide variety of pattern forming systems. It correctly predicted a period doubling cascade to chaos in Taylor-Couette flow with hourglass geometry(Richard J. Wiener et al), Phys. Rev. E 55, 5489 (1997).. We have conducted a series of such simulations, varying the length of the system. This has enabled us to study the transition from a purely temporal chaos of the formation of new pairs of Taylor Vortices at a single location, to a spatio-temporal chaos of formation across a range of locations. Application to anticipated experiments will be discussed.

  3. 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.

  4. 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).

  5. The Voronoi spatio-temporal data structure

    NASA Astrophysics Data System (ADS)

    Mioc, Darka

    2002-04-01

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

  6. Spatio-temporal synchronization of recurrent epidemics.

    PubMed Central

    He, Daihai; Stone, Lewi

    2003-01-01

    Long-term spatio-temporal datasets of disease incidences have made it clear that many recurring epidemics, especially childhood infections, tend to synchronize in-phase across suburbs. In some special cases, epidemics between suburbs have been found to oscillate in an out-of-phase ('antiphase') relationship for lengthy periods. Here, we use modelling techniques to help explain the presence of in-phase and antiphase synchronization. The nonlinearity of the epidemic dynamics is often such that the intensity of the outbreak influences the phase of the oscillation thereby introducing 'shear', a factor that is found to be important for generating antiphase synchronization. By contrast, the coupling between suburbs via the immigration of infectives tends to enhance in-phase synchronization. The emerging synchronization depends delicately on these opposite factors. We use theoretical results from continuous time models to provide a framework for understanding the relationship between synchronization patterns for different model structures. PMID:12965019

  7. Spatio-temporal properties of letter crowding

    PubMed Central

    Chung, Susana T. L.

    2016-01-01

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

  8. Spatio-temporal properties of letter crowding.

    PubMed

    Chung, Susana T L

    2016-01-01

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

  9. 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

  10. 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

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

    PubMed

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

    2015-03-01

    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. PMID:25833435

  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 correlations in Coulomb clusters

    NASA Astrophysics Data System (ADS)

    Ghosal, Amit; Ash, Biswarup; Chakrabarti, Jaydeb

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

  14. Network Analysis Using Spatio-Temporal Patterns

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  15. 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)...

  16. Parallel indexing technique for spatio-temporal data

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed Central

    Musolesi, Mirco

    2016-01-01

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

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

    PubMed

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

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

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

    PubMed

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

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

  20. Reaction diffusion equation with spatio-temporal delay

    NASA Astrophysics Data System (ADS)

    Zhao, Zhihong; Rong, Erhua

    2014-07-01

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

  1. 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.

  2. 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.

  3. Spatio-temporal analysis of environmental radiation in Korea

    SciTech Connect

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

    2007-07-01

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

  4. 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.

  5. 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.

  6. Complex spatio-temporal features in meg data.

    PubMed

    Sapuppo, Francesca; Umana, Elena; Frasca, Mattia; Rosa, Manuela La; Shannahoff-Khalsa, David; Fortuna, Luigi; Bucolo, Maide

    2006-10-01

    Magnetoencephalography (MEG) brain signals are studied using a method for characterizing complex nonlinear dynamics. This approach uses the value of d(infinity) (d-infinite) to characterize the system's asymptotic chaotic behavior. A novel procedure has been developed to extract this parameter from time series when the system's structure and laws are unknown. The implementation of the algorithm was proven to be general and computationally efficient. The information characterized by this parameter is furthermore independent and complementary to the signal power since it considers signals normalized with respect to their amplitude. The algorithm implemented here is applied to whole-head 148 channel MEG data during two highly structured yogic breathing meditation techniques. Results are presented for the spatio-temporal distributions of the calculated d(infinity) on the MEG channels, and they are compared for the dirrerent phases of the yogic protocol. The algorithm was applied to six MEG data sets recorded over a three-month period. This provides the opportunity of verifying the consistency of unique spatio-temporal features found in specific protocol phases and the chance to investigate the potential long term effects of these yogic techniques. Differences among the spatio-temporal patterns related to each phase were found, and they were independent of the power spatio-temporal distributions that are based on conventional analysis. This approach also provides an opportunity to compare both methods and possibly gain complementary information.

  7. 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…

  8. 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.

  9. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovič, Dušan; Stopar, Bojan

    2011-02-01

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

  10. 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

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

    PubMed Central

    Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

    2011-01-01

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

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

    PubMed

    Heaton, Matthew J; Gelfand, Alan E

    2012-12-01

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

  13. 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.

  14. Emergence of spatio-temporal dynamics from exact coherent solutions in pipe flow

    NASA Astrophysics Data System (ADS)

    Ritter, Paul; Mellibovsky, Fernando; Avila, Marc

    2016-08-01

    Turbulent-laminar patterns are ubiquitous near transition in wall-bounded shear flows. Despite recent progress in describing their dynamics in analogy to non-equilibrium phase transitions, there is no theory explaining their emergence. Dynamical-system approaches suggest that invariant solutions to the Navier–Stokes equations, such as traveling waves and relative periodic orbits in pipe flow, act as building blocks of the disordered dynamics. While recent studies have shown how transient chaos arises from such solutions, the ensuing dynamics lacks the strong fluctuations in size, shape and speed of the turbulent spots observed in experiments. We here show that chaotic spots with distinct dynamical and kinematic properties merge in phase space and give rise to the enhanced spatio-temporal patterns observed in pipe flow. This paves the way for a dynamical-system foundation to the phenomenology of turbulent-laminar patterns in wall-bounded extended shear flows.

  15. Emergence of spatio-temporal dynamics from exact coherent solutions in pipe flow

    NASA Astrophysics Data System (ADS)

    Ritter, Paul; Mellibovsky, Fernando; Avila, Marc

    2016-08-01

    Turbulent-laminar patterns are ubiquitous near transition in wall-bounded shear flows. Despite recent progress in describing their dynamics in analogy to non-equilibrium phase transitions, there is no theory explaining their emergence. Dynamical-system approaches suggest that invariant solutions to the Navier-Stokes equations, such as traveling waves and relative periodic orbits in pipe flow, act as building blocks of the disordered dynamics. While recent studies have shown how transient chaos arises from such solutions, the ensuing dynamics lacks the strong fluctuations in size, shape and speed of the turbulent spots observed in experiments. We here show that chaotic spots with distinct dynamical and kinematic properties merge in phase space and give rise to the enhanced spatio-temporal patterns observed in pipe flow. This paves the way for a dynamical-system foundation to the phenomenology of turbulent-laminar patterns in wall-bounded extended shear flows.

  16. Effective and efficient analysis of spatio-temporal data

    NASA Astrophysics Data System (ADS)

    Zhang, Zhongnan

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

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

    DOE PAGES

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

    2016-03-01

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

  18. Inverse hydrological modelling of spatio-temporal rainfall patterns

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

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

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

    PubMed

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

    2014-12-01

    Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexisting static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude. PMID:25554062

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

    PubMed

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

    2016-07-01

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

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

    PubMed

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

    2016-07-01

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

  2. Large scale stochastic spatio-temporal modelling with PCRaster

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Jeong, Hawoong

    2005-04-01

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

  5. 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.

  6. Spatio-temporal Granger causality: a new framework

    PubMed Central

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

    2015-01-01

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

  7. 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.

  8. Spatio-temporal processing of tactile stimuli in autistic children.

    PubMed

    Wada, Makoto; Suzuki, Mayuko; Takaki, Akiko; Miyao, Masutomo; Spence, Charles; Kansaku, Kenji

    2014-08-07

    Altered multisensory integration has been reported in autism; however, little is known concerning how the autistic brain processes spatio-temporal information concerning tactile stimuli. We report a study in which a crossed-hands illusion was investigated in autistic children. Neurotypical individuals often experience a subjective reversal of temporal order judgments when their hands are stimulated while crossed, and the illusion is known to be acquired in early childhood. However, under those conditions where the somatotopic representation is given priority over the actual spatial location of the hands, such reversals may not occur. Here, we showed that a significantly smaller illusory reversal was demonstrated in autistic children than in neurotypical children. Furthermore, in an additional experiment, the young boys who had higher Autism Spectrum Quotient (AQ) scores generally showed a smaller crossed hands deficit. These results suggest that rudimentary spatio-temporal processing of tactile stimuli exists in autistic children, and the altered processing may interfere with the development of an external frame of reference in real-life situations.

  9. Stochastic spatio-temporal modelling with PCRaster Python

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  10. Sparse Spatio-temporal Inference of Electromagnetic Brain Sources

    NASA Astrophysics Data System (ADS)

    Stahlhut, Carsten; Attias, Hagai T.; Wipf, David; Hansen, Lars K.; Nagarajan, Srikantan S.

    The electromagnetic brain activity measured via MEG (or EEG) can be interpreted as arising from a collection of current dipoles or sources located throughout the cortex. Because the number of candidate locations for these sources is much larger than the number of sensors, source reconstruction involves solving an inverse problem that is severely underdetermined. Bayesian graphical models provide a powerful means of incorporating prior assumptions that narrow the solution space and lead to tractable posterior distributions over the unknown sources given the observed data. In particular, this paper develops a hierarchical, spatio-temporal Bayesian model that accommodates the principled computation of sparse spatial and smooth temporal M/EEG source reconstructions consistent with neurophysiological assumptions in a variety of event-related imaging paradigms. The underlying methodology relies on the notion of automatic relevance determination (ARD) to express the unknown sources via a small collection of spatio-temporal basis functions. Experiments with several data sets provide evidence that the proposed model leads to improved source estimates. The underlying methodology is also well-suited for estimation problems that arise from other brain imaging modalities such as functional or diffusion weighted MRI.

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  15. 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

  16. 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.

  17. Spatio-temporal processing of tactile stimuli in autistic children

    PubMed Central

    Wada, Makoto; Suzuki, Mayuko; Takaki, Akiko; Miyao, Masutomo; Spence, Charles; Kansaku, Kenji

    2014-01-01

    Altered multisensory integration has been reported in autism; however, little is known concerning how the autistic brain processes spatio-temporal information concerning tactile stimuli. We report a study in which a crossed-hands illusion was investigated in autistic children. Neurotypical individuals often experience a subjective reversal of temporal order judgments when their hands are stimulated while crossed, and the illusion is known to be acquired in early childhood. However, under those conditions where the somatotopic representation is given priority over the actual spatial location of the hands, such reversals may not occur. Here, we showed that a significantly smaller illusory reversal was demonstrated in autistic children than in neurotypical children. Furthermore, in an additional experiment, the young boys who had higher Autism Spectrum Quotient (AQ) scores generally showed a smaller crossed hands deficit. These results suggest that rudimentary spatio-temporal processing of tactile stimuli exists in autistic children, and the altered processing may interfere with the development of an external frame of reference in real-life situations. PMID:25100146

  18. 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.

  19. Spatio-temporal curvature measures for flow-field analysis

    NASA Astrophysics Data System (ADS)

    Zetzsche, Christoph; Barth, Erhardt; Berkmann, Joachim

    1991-09-01

    Intrinsic signal dimensionality, a property closely related to Gaussian curvature, is shown to be an important conceptual tool in multi-dimensional image processing for both biological and engineering sciences. Intrinsic dimensionality can reveal the relationship between recent theoretical developments in the definition of optic flow and the basic neurophysiological concept of 'end-stopping' of visual cortical cells. It is further shown how the concept may help to avoid certain problems typically arising from the common belief that an explicit computation of a flow field has to be the essential first step in the processing of spatio- temporal image sequences. Signals which cause difficulties in the computation of optic flow, mainly the discontinuities of the motion vector field, are shown to be detectable directly in the spatio-temporal input by evaluation of its three-dimensional curvature. The relevance of the suggested concept is supported by the fact that fast and efficient detection of such signals is of vital importance for ambulant observers in both the biological and the technical domain.

  20. 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...

  1. Spatio-Temporal Structure of Hooded Gull Flocks

    PubMed Central

    Yomosa, Makoto; Mizuguchi, Tsuyoshi; Hayakawa, Yoshinori

    2013-01-01

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

  2. 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.

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

    PubMed

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

    2013-12-01

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

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

    PubMed

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

    2013-03-01

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

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

    PubMed

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

    2014-07-16

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

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

    PubMed

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

    2015-01-01

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

  7. Spatio-temporal variability of equatorial noise emissions

    NASA Astrophysics Data System (ADS)

    Nemec, Frantisek; Santolik, Ondrej; Hrbackova, Zuzana; Pickett, Jolene; Cornilleau-Wehrlin, Nicole

    Equatorial noise (EN) emissions (also called "fast magnetosonic waves") are electromagnetic waves at frequencies between the proton cyclotron frequency and the lower hybrid frequency routinely observed near the geomagnetic equator at radial distances between about 2 and 7 Earth radii. They propagate at wave normal angles close to 90 degrees, with magnetic field fluctuations being nearly linearly polarized along the ambient magnetic field. This property, along with a detailed wave analysis, can be conveniently used for their identification. We use multipoint measurements performed by the Cluster spacecraft to determine the spatio-temporal variability of EN emissions. The characteristic time constant, as well as typical scales of intensity changes both in the radial and the azimuthal directions, are determined. The data are further separated according to their position inside/outside the plasmasphere and the respective differences are discussed.

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

    SciTech Connect

    He, Shoujie; Jing, Ha

    2014-01-15

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

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

    PubMed

    Carvalho, José C; Cardoso, Pedro; Rigal, François; 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

  10. High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  11. 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.

  12. 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.

  13. 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

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

    PubMed

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

    2014-07-21

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

  15. 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

  16. 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

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

    PubMed

    Tarasov, Nikita; Sugavanam, Srikanth; Churkin, Dmitry

    2015-09-21

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

  18. Spatio-temporal intensity dynamics of passively mode-locked fiber laser

    NASA Astrophysics Data System (ADS)

    Churkin, Dmitry V.; Sugavanam, Srikanth

    2016-03-01

    We present recent results on measurements of intensity spatio-temporal dynamics in passively mode-locked fibre laser. We experimentally uncover distinct, dynamic and stable spatio-temporal generation regimes of various stochasticity and periodicity properties in though-to-be unstable laser. We present a method to distinguish various types of generated coherent structures, including rogue and shock waves, within the radiation by means of introducing of intensity ACF evolution map. We also discuss how the spectral dynamics could be measured in fiber lasers generating irregular train of pulses of quasi-CW generation via combination of heterodyning and intensity spatio-temporal measurement concept.

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

    PubMed Central

    2011-01-01

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

  20. Research of spatio-temporal analysis of agricultural pest

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  1. 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.

  2. Spatio-Temporal Reconstruction of Vortex Dynamics in Axisymmetric Wakes

    NASA Astrophysics Data System (ADS)

    Brücker, C.

    2001-04-01

    With time recording Digital-Particle-Image Velocimetry and spatio-temporal reconstruction technique, we obtained detailed quantitative results of the evolution of the velocity and vorticity field in the wake of axisymmetric bluff bodies-a sphere and an axially oriented cylinder with an elliptic nose and a blunt base. Experiments were carried out for Reynolds numbers of Re=500, 700 and 1000 in the transition range from ``regular'' to ``irregular'' shedding. DPIV-recordings in radial cross-sections at several distances downstream of the bodies allowed us to reconstruct the dynamics of the streamwise vorticity over a large number of shedding cycles. Our results prove that the wake in this regime consists of a double-sided chain of oppositely oriented hairpin vortices. In addition, the results show a well-defined low-frequency modulation of the vortex shedding, with a distinct peak in the frequency spectrum at a Strouhal number of about Sr~0.05 (in case of the sphere). The wake pattern in this ``irregular'' shedding regime typically exhibits periodic packets of 3-4 ``regular'' shedding cycles which are interrupted by phases with less action. The results indicate the coexistence of a long-wave instability of axisymmetric wakes against helical waves in addition to the primary instability causing the vortex shedding process.

  3. 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.

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

    USGS Publications Warehouse

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

    2015-01-01

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

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

    PubMed

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

    2016-05-01

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

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

    PubMed

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

    2016-05-01

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

  7. Spatio-Temporal Credit Assignment in Neuronal Population Learning

    PubMed Central

    Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

    2011-01-01

    In learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain. PMID:21738460

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

    PubMed

    Demi, Marcello

    2016-06-01

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

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

    PubMed

    Zhou, Feng; Torre, Fernando De la

    2016-08-01

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

  10. 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

  11. Computing Spatio-Temporal Multiple View Geometry from Mutual Projections of Multiple Cameras

    NASA Astrophysics Data System (ADS)

    Wan, Cheng; Sato, Jun

    The spatio-temporal multiple view geometry can represent the geometry of multiple images in the case where non-rigid arbitrary motions are viewed from multiple translational cameras. However, it requires many corresponding points and is sensitive to the image noise. In this paper, we investigate mutual projections of cameras in four-dimensional space and show that it enables us to reduce the number of corresponding points required for computing the spatio-temporal multiple view geometry. Surprisingly, take three views for instance, we no longer need any corresponding point to calculate the spatio-temporal multiple view geometry, if all the cameras are projected to the other cameras mutually for two time intervals. We also show that the stability of the computation of spatio-temporal multiple view geometry is drastically improved by considering the mutual projections of cameras.

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

    NASA Astrophysics Data System (ADS)

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

    2006-10-01

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

  13. "Chaos."

    ERIC Educational Resources Information Center

    Samson, Ilan

    1997-01-01

    Discusses what is meant by a process being described as chaotic and how such situations come about. Argues that clarifying this concept is particularly important because understanding chaos helps cure far more fundamental common misconceptions. (ASK)

  14. Spatio-Temporal Measurements of Short Wind Water Waves

    NASA Astrophysics Data System (ADS)

    Rocholz, Roland; Jähne, Bernd

    2010-05-01

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

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

    PubMed

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

  16. Spatio-temporal representativeness of aerosol remote sensing observations

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  17. 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

  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 Oscillations in Predator-Prey Systems

    NASA Astrophysics Data System (ADS)

    Tomé, T.; de Carvalho, K. Cristina

    2005-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    SciTech Connect

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

    2010-11-15

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

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

    PubMed Central

    Jousimo, Jussi; Ovaskainen, Otso

    2016-01-01

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

  3. 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.

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

    PubMed

    Jousimo, Jussi; Ovaskainen, Otso

    2016-01-01

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

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

    PubMed Central

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

    2010-01-01

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

  6. 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.

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

    PubMed

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

    2016-04-01

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

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

    SciTech Connect

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

    2009-05-01

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

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

    PubMed

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

    2016-04-01

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

  10. Spatio-temporal point processes, partial likelihood, foot and mouth disease.

    PubMed

    Diggle, Peter J

    2006-08-01

    Spatio-temporal point process data arise in many fields of application. An intuitively natural way to specify a model for a spatio-temporal point process is through its conditional intensity at location x and time t, given the history of the process up to time t. Often, this results in an analytically intractable likelihood. Likelihood-based inference then relies on Monte Carlo methods which are computationally intensive and require careful tuning to each application. A partial likelihood alternative is proposed, which is computationally straightforward and can be applied routinely. The method is applied to data from the 2001 foot and mouth epidemic in the UK, using a previously published model for the spatio-temporal spread of the disease.

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

    PubMed Central

    Fritz, Rafael Dominik; Pertz, Olivier

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. [Role of spatio-temporal non uniformities in blood coagulation regulation].

    PubMed

    Shibeko, A M; Ataullakhanov, F I

    2013-01-01

    This paper reviews some contemporary researches of thrombosis and hemostasis process that consider its spatio-temporal dynamics. Among them, there are platelet distribution in the blood vessel and the dependence of the platelet plug growth on the hematocrit level; influence of the tissue factor density on the blood coagulation onset and on the efficacy of some drugs, designed for the hemostasis improvement; regulation of blood coagulation by the flow rate. Mechanisms controlling the mentioned processes are described. Clinical significance and novel diagnostic and therapeutic approaches are discussed from the position of the spatio-temporal non uniformities of thrombosis and hemosatsis.

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

    PubMed

    Pariente, G; Quéré, 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.

  15. Spatio-temporal coupling of random electromagnetic pulses interacting with reflecting gratings.

    PubMed

    Yao, Min; Cai, Yangjian; Korotkova, Olga; Lin, Qiang; Wang, Zhaoying

    2010-10-11

    Matrix optics is applied to a class of random, in time and space, electromagnetic pulsed beam-like (REMPB) radiation interacting with linear optical elements. A 6×6 order matrix describing transformation of a six-dimensional state vector including four spatial and two temporal positions within the field is used to derive conditions for spatio-temporal coupling. An example is included which deals with a spatio-temporal coupling in a typical REMPB on reflection from a reflecting grating. Electromagnetic nature of such interaction is explored via considering dependence of the degree of polarization of the reflected REMPB on its source and on the structure of the grating.

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

    PubMed Central

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

    2007-01-01

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

  17. 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…

  18. Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

    PubMed

    Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

    2015-05-18

    Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  20. 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.

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

    ERIC Educational Resources Information Center

    Chartrel, Estelle; Vinter, Annie

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  3. Aspects of Spatio-Temporal Variability during Consonant Production by Greek Speakers with Hearing Impairment

    ERIC Educational Resources Information Center

    Nicolaidis, Katerina

    2007-01-01

    This paper investigates spatio-temporal variability during the production of the lingual consonants /t, k, s, x, n, l, "r"/ by four Greek speakers with profound hearing impairment and with differences in the intelligibility of their speech. It examines important factors that have been documented to influence intelligibility, i.e. durational…

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  5. Developmental regulation of spatio-temporal patterns of cortical circuit activation

    PubMed Central

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

    2013-01-01

    Neural circuits are refined in an experience-dependent manner during early postnatal development. How development modulates the spatio-temporal propagation of activity through cortical circuits is poorly understood. Here we use voltage-sensitive dye imaging (VSD) to show that there are significant changes in the spatio-temporal patterns of intracortical signals in primary visual cortex (V1) from postnatal day 13 (P13), eye opening, to P28, the peak of the critical period for rodent visual cortical plasticity. Upon direct stimulation of layer 4 (L4), activity spreads to L2/3 and to L5 at all ages. However, while from eye opening to the peak of the critical period, the amplitude and persistence of the voltage signal decrease, peak activation is reached more quickly and the interlaminar gain increases with age. The lateral spread of activation within layers remains unchanged throughout the time window under analysis. These developmental changes in spatio-temporal patterns of intracortical circuit activation are mediated by differences in the contributions of excitatory and inhibitory synaptic components. Our results demonstrate that after eye opening the circuit in V1 is refined through a progression of changes that shape the spatio-temporal patterns of circuit activation. Signals become more efficiently propagated across layers through developmentally regulated changes in interlaminar gain. PMID:23316135

  6. 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...

  7. Sharpening image motion based on the spatio-temporal characteristics of human vision

    NASA Astrophysics Data System (ADS)

    Takeuchi, Tatsuto; De Valois, Karen K.

    2005-03-01

    Images of moving objects in films often appear normal or even sharper than they actually are, a phenomenon called motion sharpening. We sought to clarify which spatio-temporal frequency components of a moving image are sharpened when a pattern is moving. We applied various spatio-temporal filters to moving natural images and evaluated the perceived sharpness of motion by comparing them to a stationary image. On each trial, subjects adjusted three parameters of the still image: overall luminance contrast, the slope of the amplitude function in the spatial frequency domain, and cutoff spatial frequency. We found that the motion sharpening could be described by the relative increase in the amplitude of the higher spatial frequency components. Spatially low-pass filtered movies induced a motion sharpening, but spatially high-pass filtered movies were perceived to be blurred. The strongest motion sharpening was observed when image frames were spatially band-reject filtered. When temporal filters were applied, perceived sharpness became stronger when the movies were temporally band-reject filtered. A high-pass temporal filter drastically reduced the perceived sharpness of images. Our results demonstrate that the perceived contrast of higher spatial frequency components in moving images is enhanced by the interaction between different spatio-temporal frequency channels in the motion sharpening process. This suggests that it is possible to compress and enhance moving images by removing higher spatio-temporal frequency information.

  8. 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

  9. 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.

  10. Synchronizing spatio-temporal chaos with imperfect models: A stochastic surface growth picture

    SciTech Connect

    Pazó, Diego López, Juan M.; Rodríguez, Miguel A.; Gallego, Rafael

    2014-12-01

    We study the synchronization of two spatially extended dynamical systems where the models have imperfections. We show that the synchronization error across space can be visualized as a rough surface governed by the Kardar-Parisi-Zhang equation with both upper and lower bounding walls corresponding to nonlinearities and model discrepancies, respectively. Two types of model imperfections are considered: parameter mismatch and unresolved fast scales, finding in both cases the same qualitative results. The consistency between different setups and systems indicates that the results are generic for a wide family of spatially extended systems.

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

    PubMed

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

    2015-10-07

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

  12. 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.

  13. 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

  14. 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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Manga, Edna; Awang, Norhashidah

    2016-06-01

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

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Clairambault, Jean; Eliaš, Ján

    2016-06-01

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

  1. 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.

  2. 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.

  3. Visual pattern recognition based on spatio-temporal patterns of retinal ganglion cells’ activities

    PubMed Central

    Jing, Wei; Liu, Wen-Zhong; Gong, Xin-Wei; Gong, Hai-Qing

    2010-01-01

    Neural information is processed based on integrated activities of relevant neurons. Concerted population activity is one of the important ways for retinal ganglion cells to efficiently organize and process visual information. In the present study, the spike activities of bullfrog retinal ganglion cells in response to three different visual patterns (checker-board, vertical gratings and horizontal gratings) were recorded using multi-electrode arrays. A measurement of subsequence distribution discrepancy (MSDD) was applied to identify the spatio-temporal patterns of retinal ganglion cells’ activities in response to different stimulation patterns. The results show that the population activity patterns were different in response to different stimulation patterns, such difference in activity pattern was consistently detectable even when visual adaptation occurred during repeated experimental trials. Therefore, the stimulus pattern can be reliably discriminated according to the spatio-temporal pattern of the neuronal activities calculated using the MSDD algorithm. PMID:21886670

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

    NASA Astrophysics Data System (ADS)

    Singh, R.; Kumar, R.

    2015-12-01

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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

  7. 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.

  8. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

  11. 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

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

    NASA Astrophysics Data System (ADS)

    Zhou, Qin; Zhu, Qiuping

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Alkan, M.; Polat, Z. A.

    2016-06-01

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

  14. Spatio-temporal adaptation algorithm for two-dimensional reacting flows

    NASA Astrophysics Data System (ADS)

    Pervaiz, Mehtab M.; Baron, Judson R.

    1988-01-01

    A spatio-temporal adaptive algorithm for solving the unsteady Euler equations with chemical source terms is presented. Quadrilateral cells are used in two spatial dimensions which allow for embedded meshes tracking moving flow features with spatially varying time-steps which are multiples of global minimum time-steps. Blast wave interactions corresponding to a perfect gas (frozen) and a Lighthill dissociating gas (nonequilibrium) are considered for circular arc cascade and 90 degree bend duct geometries.

  15. 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...

  16. Spatio-Temporal Changes in Potential Evaporation Based on Entropy Across the Wei River Basin

    NASA Astrophysics Data System (ADS)

    Huang, S.; Wang, Y.

    2014-12-01

    The distribution of potential evaporation is highly unstable due to complex human activities and climate changes. Therefore, it is of great significance for further understanding hydrological cycle to estimate potential evaporation distribution. Reasonable regionalization of potential evaporation will help to improve the efficiency of irrigation and increase the ability of drought relief, which is of great importance to irrigation planning and management. Hence, the spatio-temporal changes in potential evaporation distribution at monthly and annual scales are investigated based on the modified Mann-Kendall trend test method and the entropy theory in the Wei River Basin. A nonparametric method as an attractive alternative to empirical and parametric approaches is proposed to calculate the univariate and bivariate probability distribution of potential evaporation. The directional information transfer index (DITI) is employed to estimate the similarity among the meteorological stations, and the k-means cluster analysis is used to classify the meteorological stations into several distribution zones with distinct features. Based on the monthly potential evaporation from 1960 to 2008 at 21 meteorological stations, the basin is ultimately classified into 8 zones with their own distinct spatio-temporal distribution features. In view of the distinct spatio-temporal distribution features, the DITI-based model combined with the nonparametric probability estimation method and the k-means cluster analysis offers a more precise classification of potential evaporation distribution zones.

  17. 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.

  18. 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.

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

  3. 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.

  4. 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.

  5. 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.

  6. Hierarchical Bayesian space-time interpolation versus spatio-temporal BME approach

    NASA Astrophysics Data System (ADS)

    Hussain, I.; Pilz, J.; Spoeck, G.

    2010-03-01

    The restrictions of the analysis of natural processes which are observed at any point in space or time to a purely spatial or purely temporal domain may cause loss of information and larger prediction errors. Moreover, the arbitrary combinations of purely spatial and purely temporal models may not yield valid models for the space-time domain. For such processes the variation can be characterized by sophisticated spatio-temporal modeling. In the present study the composite spatio-temporal Bayesian maximum entropy (BME) method and transformed hierarchical Bayesian space-time interpolation are used in order to predict precipitation in Pakistan during the monsoon period. Monthly average precipitation data whose time domain is the monsoon period for the years 1974-2000 and whose spatial domain are various regions in Pakistan are considered. The prediction of space-time precipitation is applicable in many sectors of industry and economy in Pakistan especially; the agricultural sector. Mean field maps and prediction error maps for both methods are estimated and compared. In this paper it is shown that the transformed hierarchical Bayesian model is providing more accuracy and lower prediction error compared to the spatio-temporal Bayesian maximum entropy method; additionally, the transformed hierarchical Bayesian model also provides predictive distributions.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    PubMed

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

    2016-01-01

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

  9. Video Event Detection: From Subvolume Localization To Spatio-Temporal Path Search.

    PubMed

    Tran, Du; Yuan, Junsong; Forsyth, David

    2013-07-23

    Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatio-temporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intra-class variations of the event. Compared to event detection using spatio-temporal sliding windows, the spatio-temporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video datasets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible to different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. PMID:23898011

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

    PubMed

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

    2016-09-01

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

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

    PubMed

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

    2015-10-15

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

  12. 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

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  15. Spatio-temporal characterization imaging of Ca2+ oscillations in rat hippocampal neurons

    NASA Astrophysics Data System (ADS)

    Zhang, Zhihong; Lu, Jinling; Zhou, Wei; Liu, Rengang; Zeng, Shaoqun; Luo, Qingming

    2001-08-01

    Ca2+ is the most common signal transduction element in cells and plays critical rolls in neuronal development and plasticity. Ca2+ signals encode information in their oscillation frequency or amplitude and response time to regular cellular function. In this study, in order to reveal the spatio-temporal characterization of Ca2+ oscillations in rat hippocampal neurons, two kinds of Ca2+ fluorescent probes, yellow cameleons 2.1 (YC2.1) and Fluo-3, were used to monitor the change of the intracellular free Ca2+ concentration (]Ca2+[i). Spontaneous Ca2+ oscillations and glutamate elicited Ca2+ oscillations were observed with multi-photon excitation laser scan microscope (MPELSM) and confocal laser scan microscope (CLSM). The observation showed that the spatio- temporal characterization of either spontaneous or glutamate provoked Ca2+ oscillations had difference between the neurites and somata in individual nerons, especially in some distal end of neurites. The result indicated that Ca2+ oscillations were most important signal transduction pattern in neuronal development and activation. The spatio-temporal characterization of difference of Ca2+ signals between the distal endo of neurites and the somata might be associated with the distribution of ionotropic receptor and metabotropic glutamate receptors, and Ca2+ response mechanism mediated by two kinds of glutamate receptor. Ca2+ signal elicited by glutamate in the distal end of neurites appeared more complex and generated faster than that in the somata. It was suggested that Ca2+ signal in glutamate stimulated hippacamal neurons first generated from the distal end of neurites and then transduted to the somata. The complicated Ca2+ signal characterization in the distal end of neurites might be associated with neuronal activitation, neurotransmitter releasing, and other functions of neurons.

  16. 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.

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

    DOE PAGES

    Sen, Satyabrata

    2015-08-04

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  19. Assessing spatio-temporal eruption forecasts in a monogenetic volcanic field

    NASA Astrophysics Data System (ADS)

    Bebbington, Mark S.

    2013-02-01

    Many spatio-temporal models have been proposed for forecasting the location and timing of the next eruption in a monogenetic volcanic field. These have almost invariably been fitted retrospectively. That is, the model has been tuned to all of the data, and hence an assessment of the goodness of fit has not been carried out on independent data. The low rate of eruptions in monogenetic fields means that there is not the opportunity to carry out a purely prospective test, as thousands of years would be required to accumulate the necessary data. This leaves open the possibility of a retrospective sequential test, where the parameters are calculated only on the basis of prior events and the resulting forecast compared statistically with the location and time of the next eruption. In general, events in volcanic fields are not dated with sufficient accuracy and precision to pursue this line of investigation; An exception is the Auckland Volcanic Field (New Zealand), consisting of c. 50 centers formed during the last c. 250 kyr, for which an age-order model exists in the form of a Monte Carlo sampling algorithm, facilitating repeated sequential testing. I examine a suite of spatial, temporal and spatio-temporal hazard models, comparing the degree of fit, and attempt to draw lessons from how and where each model is particularly successful or unsuccessful. A relatively simple (independent) combination of a renewal model (temporal term) and a spatially uniform ellipse (spatial term) performs as well as any other model. Both avoid over fitting the data, and hence large errors, when the spatio-temporal occurrence pattern changes.

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

    USGS Publications Warehouse

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

    2006-01-01

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

  1. 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

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

    PubMed

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

    2013-05-01

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

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

    PubMed Central

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

    2016-01-01

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

  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. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Gleeson, J. T.

    1997-02-01

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

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

    PubMed

    Yu, Fang; Wang, Lin; Watmough, James

    2016-12-01

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

  9. 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.

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

    PubMed

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

    2012-05-01

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

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

    USGS Publications Warehouse

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

    2005-01-01

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

  12. 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

  13. 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

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

    PubMed

    Kratz, Louis; Nishino, Ko

    2012-05-01

    Tracking pedestrians is a vital component of many computer vision applications, including surveillance, scene understanding, and behavior analysis. Videos of crowded scenes present significant challenges to tracking due to the large number of pedestrians and the frequent partial occlusions that they produce. The movement of each pedestrian, however, contributes to the overall crowd motion (i.e., the collective motions of the scene's constituents over the entire video) that exhibits an underlying spatially and temporally varying structured pattern. In this paper, we present a novel Bayesian framework for tracking pedestrians in videos of crowded scenes using a space-time model of the crowd motion. We represent the crowd motion with a collection of hidden Markov models trained on local spatio-temporal motion patterns, i.e., the motion patterns exhibited by pedestrians as they move through local space-time regions of the video. Using this unique representation, we predict the next local spatio-temporal motion pattern a tracked pedestrian will exhibit based on the observed frames of the video. We then use this prediction as a prior for tracking the movement of an individual in videos of extremely crowded scenes. We show that our approach of leveraging the crowd motion enables tracking in videos of complex scenes that present unique difficulty to other approaches. PMID:21844618

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Spatio-temporal regularization in linear distributed source reconstruction from EEG/MEG: a critical evaluation.

    PubMed

    Dannhauer, Moritz; Lämmel, Eric; Wolters, Carsten H; Knösche, Thomas R

    2013-04-01

    The high temporal resolution of EEG/MEG data offers a way to improve source reconstruction estimates which provide insight into the spatio-temporal involvement of neuronal sources in the human brain. In this work, we investigated the performance of spatio-temporal regularization (STR) in a current density approach using a systematic comparison to simple ad hoc or post hoc filtering of the data or of the reconstructed current density, respectively. For the used STR approach we implemented a frequency-specific constraint to penalize solutions outside a narrow frequency band of interest. The widely used sLORETA algorithm was adapted for STR and generally used for source reconstruction. STR and filtering approaches were evaluated with respect to spatial localization error and spatial dispersion, as well as to correlation of original and reconstructed source time courses in single source and two source scenarios with fixed source locations and oscillating source waveforms. We used extensive computer simulations and tested all algorithms with different parameter settings (noise levels and regularization parameters) for EEG data. To verify our results, we also used data from MEG phantom measurements. For the investigated scenarios, we did not find any evidence that STR-based methods outperform purely spatial algorithms applied to temporally filtered data. Furthermore, the results show very clearly that the performance of STR depends very much on the choice of regularization parameters.

  20. Spatio-temporal parameters and lower-limb kinematics of turning gait in typically developing children.

    PubMed

    Dixon, Philippe C; Stebbins, Julie; Theologis, Tim; Zavatsky, Amy B

    2013-09-01

    Turning is a requirement for most locomotor tasks; however, knowledge of the biomechanical requirements of successful turning is limited. Therefore, the aims of this study were to investigate the spatio-temporal and lower-limb kinematics of 90° turning. Seventeen typically developing children, fitted with full body and multi-segment foot marker sets, having performed both step (outside leg) and spin (inside leg) turning strategies at self-selected velocity, were included in the study. Three turning phases were identified: approach, turn, and depart. Stride velocity and stride length were reduced for both turning strategies for all turning phases (p<0.03 and p<0.01, respectively), while stance time and stride width were increased during only select phases (p<0.05 and p<0.01, respectively) for both turn conditions compared to straight gait. Many spatio-temporal differences between turn conditions and phases were also found (p<0.03). Lower-limb kinematics revealed numerous significant differences mainly in the coronal and transverse planes for the hip, knee, ankle, midfoot, and hallux between conditions (p<0.05). The findings summarized in this study help explain how typically developing children successfully execute turns and provide greater insight into the biomechanics of turning. This knowledge may be applied to a clinical setting to help improve the management of gait disorders in pathological populations, such as children with cerebral palsy.

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

    NASA Astrophysics Data System (ADS)

    Frank, Lawrence R.; Galinsky, Vitaly L.

    2016-09-01

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

  2. 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

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

    PubMed

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Luhtala, Hanna; Tolvanen, Harri

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

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

  6. 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.

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

    PubMed

    Lage, Kasper; Møllgård, 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, Søren; Seidman, Christine E; Seidman, Jonathan G; Larsen, Lars A

    2010-06-22

    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

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

    PubMed Central

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

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Frank, Lawrence R.; Galinsky, Vitaly L.

    2016-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed

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

    2016-08-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  13. 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.

  14. 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

  15. EEG source imaging with spatio-temporal tomographic nonnegative independent component analysis.

    PubMed

    Valdés-Sosa, Pedro A; Vega-Hernández, Mayrim; Sánchez-Bornot, José Miguel; Martínez-Montes, Eduardo; Bobes, María Antonieta

    2009-06-01

    This article describes a spatio-temporal EEG/MEG source imaging (ESI) that extracts a parsimonious set of "atoms" or components, each the outer product of both a spatial and a temporal signature. The sources estimated are localized as smooth, minimally overlapping patches of cortical activation that are obtained by constraining spatial signatures to be nonnegative (NN), orthogonal, sparse, and smooth-in effect integrating ESI with NN-ICA. This constitutes a generalization of work by this group on the use of multiple penalties for ESI. A multiplicative update algorithm is derived being stable, fast and converging within seconds near the optimal solution. This procedure, spatio-temporal tomographic NN ICA (STTONNICA), is equally able to recover superficial or deep sources without additional weighting constraints as tested with simulations. STTONNICA analysis of ERPs to familiar and unfamiliar faces yields an occipital-fusiform atom activated by all faces and a more frontal atom that only is active with familiar faces. The temporal signatures are at present unconstrained but can be required to be smooth, complex, or following a multivariate autoregressive model.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    PubMed

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

    2011-07-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  1. The evolution of meaning: spatio-temporal dynamics of visual object recognition.

    PubMed

    Clarke, Alex; Taylor, Kirsten I; Tyler, Lorraine K

    2011-08-01

    Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel prediction we test here is that recurrent interactivity is driven by increasing semantic integration demands as defined by the complexity of semantic information required by the task and driven by the stimuli. To test this prediction, we recorded magnetoencephalography data while participants named living and nonliving objects during two naming tasks. We found that the spatio-temporal dynamics of neural activity were modulated by the level of semantic integration required. Specifically, source reconstructed time courses and phase synchronization measures showed increased recurrent interactions as a function of semantic integration demands. These findings demonstrate that the cortical dynamics of object processing are modulated by the complexity of semantic information required from the visual input. PMID:20617883

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

    SciTech Connect

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

    1992-06-01

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

  3. 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.

  4. Stabilization of spatio-temporal instabilities in optically injected broad-area lasers

    NASA Astrophysics Data System (ADS)

    Pakhomov, A. V.; Krents, A. A.; Molevich, N. E.; Anchikov, D. A.

    2016-04-01

    In the present paper we investigated the spatio-temporal instabilities of stationary lasing in class-B broad-area lasers. The onset conditions of filamentary instability and its spatio-temporal characteristics were obtained analytically on the basis of Maxwell-Bloch equations without phase-amplitude coupling. The lasing stabilization capabilities through varying laser parameters were considered. We demonstrated that coherent external optical injection can effectively suppress the transverse filamentary instability. We considered the case of weak optical injection, so that the amplitude of injected field is small compared to the amplitude of intracavity laser field. The latter restriction is ascribed to active cavity where injected field doesn't play a driving role in laser operation. We report that injected field can have the stabilizing impact even for such relatively weak injection. Moreover our findings show that both relaxation oscillations and spiking behaviour may be significantly suppressed up to complete elimination in broad-area laser submit to coherent optical injection. All the results were also found to stay principally valid for weak nonzero phase-amplitude coupling.

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

    PubMed

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

    2013-11-01

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

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

    PubMed

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

    2013-11-01

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

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

    PubMed Central

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

    2014-01-01

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

  8. 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.

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

    PubMed

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

    2014-09-01

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

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

    PubMed

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-03-01

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

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

    PubMed Central

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-01-01

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

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

    PubMed

    Li, Lan; Xi, Yuliang; Ren, Fu

    2016-03-07

    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

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

    NASA Astrophysics Data System (ADS)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

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

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

    PubMed

    Pavlovič, Andrej

    2010-11-01

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

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

    PubMed

    Pavlovič, Andrej

    2010-11-01

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

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

    SciTech Connect

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

    2014-09-08

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

  17. 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

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

    SciTech Connect

    Gaffney, S; Smyth, P

    2001-01-10

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

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

    PubMed Central

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

    2009-01-01

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

  20. Two spatio-temporal filters in human vision. 1. Temporal and spatial frequency response characteristics.

    PubMed

    Holliday, I E; Ruddock, K H

    1983-01-01

    We have studied visual detection of a circular target moving across a spatially and/or temporally modulated background. Illumination, It, for threshold detection of the target has been measured as a function of background modulation frequency and changes in It associated with background modulation provide a means of determining the frequency response characteristics of visual channels. Temporal frequency responses obtained with temporally modulated, spatially uniform backgrounds have pass-band characteristics and the temporal frequency for peak response increases with increase in mean background illumination. These temporal frequency responses resemble those of the de Lange (1954) filter, but the latter incorporates the incremental thresholds for steady backgrounds. The amplitude of this temporal response saturates at low (approximately 40%) background modulation, decreases to zero as the target velocity falls to zero, and is maximum for a circular target of diameter 2 degrees. The spatial characteristics of this temporal filter were measured with a background field consisting of alternate steady and flickering bars. The resulting spatial frequency curve peaks at 1 cycle deg-1 for all background illuminations and is independent of the background grating orientation. This spatial response differs significantly from the IMG spatial functions observed with a background grating (Barbur and Ruddock, 1980). The spatial and temporal responses reviewed above exhibit similar parametric variations and we therefore associate them with a single spatio-temporal filter, ST2. A second temporal response, with low-pass frequency characteristics, was observed with a background field consisting of two matched gratings, presented in spatial and temporal antiphase. This response has parametric properties similar to those of the IMG spatial response described previously by Barbur and Ruddock (1980), thus we associated the two sets of data with a single spatio-temporal filter, ST1. We

  1. Three dimensional spatio-temporal instabilities in two-layer flows at high Reynolds numbers

    NASA Astrophysics Data System (ADS)

    Valluri, Prashant; O'Na'Raigh, Lennon; Spelt, Peter

    2010-11-01

    Interfacial instabilities in Newtonian two-layer flows are investigated via three-dimensional direct numerical simulations using the diffuse-interface method to capture the interface. The simulations study the effect of waves, generated by a random 3D noise, at the inlet on the spatio-temporal behaviour of the instabilities. Of specific interest are the conditions of growth/decay of the spanwise interfacial perturbation. Preliminary results show a sustained growth of the spanwise mode, irrespective of the primary streamwise mode, at various streamwise locations in the domain. At positions close to the inlet the spanwise wave grows linearly until a non-linear distortion which eventually saturates the amplitude. This work extends our recently reported two-dimensional studies on spatiotemporal interfacial instabilities (J. Fluid Mech. (2010), vol. 656, pp. 458--480) to i) three dimensions and ii) higher Reynolds numbers.

  2. Multivariate testing of spatio-temporal consistence of daily precipitation records

    NASA Astrophysics Data System (ADS)

    Mächel, H.; Kapala, A.

    2013-06-01

    The project KLIDADIGI of the German Meteorological Service (DWD) systematically rescues historical daily climate data of Germany by keying and imaging. Up to now, daily nearly gap-free precipitation time series at 118 locations for the period 1901-2000 are collected and extended by digitalization of hand-written protocols. To screen the spatio-temporal consistence of these raw data, we apply principal component analysis (PCA) in S (spatial) mode for daily precipitation records as well as for indices such as the number of rainy days above a certain threshold, intensity and absolute daily maximum in monthly, seasonal or annual resolution. Results of this screening test indicate that the PCA is a useful tool for detection of questionable stations and data preprocessing for further quality control and homogenization.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  4. Exploratory analysis of the spatio-temporal deformation of the myocardium during systole from tagged MRI.

    PubMed

    Clarysse, Patrick; Han, Meimei; Croisille, Pierre; Magnin, Isabelle E

    2002-11-01

    Myocardial contractile function is, with perfusion, one of the main affected factors in ischemic heart diseases. In this paper, we propose an original framework based on functional data analysis for the quantitative study of spatio-temporal parameters related to the myocardial contraction mechanics. The mechanical strains in the left-ventricular (LV) myocardium are computed from tagged magnetic resonance imaging cardiac sequences. A statistical functional model of the normal contractile function of the LV is build from the study of eight examinations on healthy subjects. We show that it is possible to detect abnormal strain patterns comparatively to this model, by generating distance maps at rest and under pharmacological stress. We demonstrate the consistency of the results for the circumferential deformation parameter on healthy and pathological data sets. PMID:12450363

  5. 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

  6. 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.

  7. Neural network structure for spatio-temporal long-term memory.

    PubMed

    Nguyen, Vu Anh; Starzyk, Janusz A; Goh, Wooi-Boon; Jachyra, Daniel

    2012-06-01

    This paper proposes a neural network structure for spatio-temporal learning and recognition inspired by the long-term memory (LTM) model of the human cortex. Our structure is able to process real-valued and multidimensional sequences. This capability is attained by addressing three critical problems in sequential learning, namely the error tolerance, the significance of sequence elements and memory forgetting. We demonstrate the potential of the framework with a series of synthetic simulations and the Australian sign language (ASL) dataset. Results show that our LTM model is robust to different types of distortions. Second, our LTM model outperforms other sequential processing models in a classification task for the ASL dataset. PMID:24806767

  8. 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.

  9. 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.

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

    PubMed

    Wang, Xin; Pinto-Duarte, António; Behrens, M Margarita; Zhou, Xianjin; Sejnowski, Terrence J

    2015-01-01

    Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies. PMID:26459883

  11. 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

  12. 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.

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

    PubMed

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

    2014-12-01

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

  14. 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.

  15. Spatio-temporal processing of massive glottic images from high-speed videoendoscopy

    NASA Astrophysics Data System (ADS)

    Yan, Yuling; Izdebski, Krzysztof; Marriott, Emma

    2011-03-01

    We present here development and application of new approaches for quantitative spatio-temporal analyses of vocal fold (VF) vibrations derived from high-speed digital imaging (HSDI) data of the glottis. We develop image processing methods to track the motion of the VF and target the analysis of HSDI-derived glottal area waveform (GAW), glottal width function (GWF) and displacements of the VF tissues for the characterization of the VF dynamic properties. In particular, a combined threshold and region growing method is used for the glottis segmentation, and an analytic signal approach and the Nyquist plot and associated parameters are used to represent and to characterize the VF vibratory behaviors in normal and specific pathologic voice productions.

  16. Assessment of soil organic carbon distribution in Europe scale by spatio-temporal data and geostatistics

    NASA Astrophysics Data System (ADS)

    Aksoy, Ece; Panagos, Panos; Montanarella, Luca

    2013-04-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted using combination of LUCAS soil samples with local soil data and ten spatio-temporal predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, average temperature and precipitation) with Regression-Kriging method in Europe scale. Significant correlation between the covariates and the organic carbon dependent variable was found.

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  18. 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

  19. 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.

  20. Spatio-temporal imaging of light transport in scattering media using white light illumination (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Badon, Amaury; Li, Dayan; Lerosey, Geoffroy; Boccara, Claude; Fink, Mathias; Aubry, Alexandre

    2016-03-01

    We recently showed how the correlations of a broadband and incoherent wave-field can directly yield the time-dependent Green's functions between scatterers of a complex medium [Badon et al., Phys. Rev. Lett., 2015]. In this study, we apply this approach to the imaging of optical transport properties in complex media. A parallel measurement of millions of Green's functions at the surface of several strongly scattering samples (ZnO, TiO2, Teflon tape) is performed. A statistical analysis of this Green's matrix allows to investigate locally the spatio-temporal evolution of the diffusive halo within the scattering sample. An image of diffusion tensor is then obtained. It allows to map quantitatively the local concentration of scatterers and their anisotropy within the scattering medium. The next step of this work is to test this approach on biological tissues and illustrate how it can provide an elegant and powerful alternative to diffuse optical imaging techniques.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed Central

    Wang, Xin; Pinto-Duarte, António; Margarita Behrens, M.; Zhou, Xianjin; Sejnowski, Terrence J.

    2015-01-01

    Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies. PMID:26459883

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

    PubMed Central

    Roy, Priti; Bandyopadhyay, Amitabha

    2014-01-01

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

  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. 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.

  6. 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.

  7. 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

  8. 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

  9. Spatio-temporal evolution of the West African monsoon during the last deglaciation

    NASA Astrophysics Data System (ADS)

    Weldeab, Syee; Frank, Martin; Stichel, Torben; Haley, Brian; Sangen, Mark

    2011-07-01

    On the basis of a multi-proxy data set from the Gulf of Guinea (eastern equatorial Atlantic) we reconstruct the spatio-temporal evolution of the West African monsoon (WAM) and present evidence for a decoupling between latitudinal shifts of the rain belt and WAM intensification. The onset of deglacial monsoon invigoration at ˜16,600 years before present lagged northward migration of a weak rainfall zone by ˜2800 years. Conversely, during the Younger Dryas (YD) time interval, WAM precipitation was severely reduced but we find no evidence for a large-scale retreat of the rainfall front. This observation is not in agreement with the hypothesis of a large-scale shift of the intertropical convergence zone south of the tropical WAM region during the YD. Our results can be better reconciled with the newly emerging concept of a strong influence of Tropical Easterly and African Easterly Jets on modern WAM.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  11. Learning Models of the Negotiation Partner in Spatio-temporal Collaboration

    NASA Astrophysics Data System (ADS)

    Luo, Yi; Bölöni, Ladislau

    We describe an approach for learning the model of the opponent in spatio-temporal negotiation. We use the Children in the Rectangular Forest canonical problem as an example. The opponent model is represented by the physical characteristics of the agents: the current location and the destination. We assume that the agents do not disclose any of their information voluntarily; the learning needs to rely on the study of the offers exchanged during normal negotiation. Our approach is Bayesian learning, with the main contribution being four techniques through which the posterior probabilities are determined. The calculations rely on (a) feasibility of offers, (b) rationality of offers, (c) the assumption of decreasing utility, and (d) the assumption of accepting offer which is better than the next counter-offer.

  12. A probe array for the investigation of spatio-temporal structures in drift wave turbulence

    SciTech Connect

    Latten, A.; Klinger, T.; Piel, A.; Pierre, T.

    1995-05-01

    A probe array with 64 azimuthally arranged Langmuir probes is presented as a new diagnostic tool for the investigation of drift waves. A parallel data acquisition system provides full spatio-temporal data of azimuthally propagating waves. For both regular and turbulent states of current-driven drift waves, the information provided by such space-time patterns is compared with results obtained from conventional two-point correlation methods. The probe array allows one to directly estimate the time-averaged wave number spectrum. In a turbulent state, the spectrum yields to a power law of {ital S}({ital k}){proportional_to}{ital k}{sup {minus}3.6{plus_minus}0.1}. {copyright} {ital 1995} {ital American} {ital Institute} {ital of} {ital Physics}.

  13. 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.

  14. Mass Spectrometric Analysis of Spatio-Temporal Dynamics of Crustacean Neuropeptides

    PubMed Central

    OuYang, Chuanzi; Liang, Zhidan; Li, Lingjun

    2014-01-01

    Neuropeptides represent one of the largest classes of signaling molecules used by nervous systems to regulate a wide range of physiological processes. Over the past several years, mass spectrometry (MS)-based strategies have revolutionized the discovery of neuropeptides in numerous model organisms, especially in decapod crustaceans. Here, we focus our discussion on recent advances in the use of MS-based techniques to map neuropeptides in spatial domain and monitoring their dynamic changes in temporal domain. These MS-enabled investigations provide valuable information about the distribution, secretion and potential function of neuropeptides with high molecular specificity and sensitivity. In situ MS imaging and in vivo microdialysis are highlighted as key technologies for probing spatio-temporal dynamics of neuropeptides in the crustacean nervous system. This review summarizes the latest advancement in MS-based methodologies for neuropeptide analysis including typical workflow and sample preparation strategies as well as major neuropeptide families discovered in decapod crustaceans. PMID:25448012

  15. Spatio-temporal modelling of foot-and-mouth disease outbreaks.

    PubMed

    Malesios, C; Demiris, N; Kostoulas, P; Dadousis, K; Koutroumanidis, T; Abas, Z

    2016-09-01

    We present and analyse data collected during a severe epidemic of foot-and-mouth disease (FMD) that occurred between July and September 2000 in a region of northeastern Greece with strategic importance since it represents the southeastern border of Europe and Asia. We implement generic Bayesian methodology, which offers flexibility in the ability to fit several realistically complex models that simultaneously capture the presence of 'excess' zeros, the spatio-temporal dependence of the cases, assesses the impact of environmental noise and controls for multicollinearity issues. Our findings suggest that the epidemic was mostly driven by the size and the animal type of each farm as well as the distance between farms while environmental and other endemic factors were not important during this outbreak. Analyses of this kind may prove useful to informing decisions related to optimal control measures for potential future FMD outbreaks as well as other acute epidemics such as FMD.

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

    PubMed Central

    2016-01-01

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

  17. Spatio-temporal modelling of foot-and-mouth disease outbreaks.

    PubMed

    Malesios, C; Demiris, N; Kostoulas, P; Dadousis, K; Koutroumanidis, T; Abas, Z

    2016-09-01

    We present and analyse data collected during a severe epidemic of foot-and-mouth disease (FMD) that occurred between July and September 2000 in a region of northeastern Greece with strategic importance since it represents the southeastern border of Europe and Asia. We implement generic Bayesian methodology, which offers flexibility in the ability to fit several realistically complex models that simultaneously capture the presence of 'excess' zeros, the spatio-temporal dependence of the cases, assesses the impact of environmental noise and controls for multicollinearity issues. Our findings suggest that the epidemic was mostly driven by the size and the animal type of each farm as well as the distance between farms while environmental and other endemic factors were not important during this outbreak. Analyses of this kind may prove useful to informing decisions related to optimal control measures for potential future FMD outbreaks as well as other acute epidemics such as FMD. PMID:27150839

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

    PubMed

    Gheghiani, Lilia; Gavet, Olivier

    2014-02-01

    Mitosis has been studied since the early 1880s as a key event of the cell division cycle where remarkable changes in cellular architecture take place and ultimately lead to an equal segregation of duplicated chromosomes into two daughter cells. A detailed description of the complex and highly ordered cellular events taking place is now available. Many regulators involved in key steps including entry into mitosis, nuclear envelope breakdown, microtubule (MT) spindle formation, and chromosome attachment, as well as mitotic exit and cytokinesis, have also been identified. However, understanding the precise spatio-temporal contribution of each regulator in the cell reorganization process has been technically challenging. This review will focus on a number of recent advances in our understanding of the spatial distribution of protein activities and the temporal regulation of their activation and inactivation during entry and progression through mitosis by the use of intramolecular Förster resonance energy transfer (FRET)-based biosensors. PMID:24421267

  19. 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.

  20. 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

  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.

  2. Spatio-temporal dynamcis of a cell signal cascade with negative feedback

    NASA Astrophysics Data System (ADS)

    Maya Bernal, Jose Luis; Ramirez-Santiago, Guillermo

    2014-03-01

    We studied the spatio-temporal dynamics of a system of reactio-diffusion equations that models a cell signal transduction pathway with six cycles and negative feedback. The basic cycle consists of the phosphorylation-dephosphorylation of two antagonic proteins. We found two regimes of saturation of the enzimatic reaction in the kinetic parameters space and determined the conditions for the signal propagation in the steady state. The trajectories for which transduction occurs are defined in terms of the ratio of the enzimatic activities. We found that in spite of the negative feedback the cell signal cascade behaves as an amplifier and produces phosphoprotein concentration gradients within the cell. This model behaves also as a noise filter and as a switch. Supported by DGAPA-UNAM Contract IN118410-3.

  3. 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.

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

    PubMed

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

    2013-07-01

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

  5. 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

  6. 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.

  7. Characterization and application of simultaneously spatio-temporally focused ultrafast laser pulses

    NASA Astrophysics Data System (ADS)

    Greco, Michael J.

    Chirped pulse amplication of ultrafast laser pulses has become an essential technology in the elds of micromachining, tissue ablation, and microscopy. With specically tailored pulses of light we have been able to begin investigation into lab-on-a-chip technology, which has the potential of revolutionizing the medical industry. Advances in microscopy have allowed sub diraction limited resolution to become a reality as well as lensless imaging of single molecules. An intimate knowledge of ultrafast optical pulses, the ability to manipulate an optical spectrum and generate an optical pulse of a specic temporal shape, allows us to continue pushing these elds forward as well as open new ones. This thesis investigates the spatio-temporal construction of pulses which are simultaneously spatio-temporally focused (SSTF) and about their current and future applications. By laterally chirping a compressed laser pulse we have conned the peak intensity to a shorter distance along the optical axis than can be achieved by conventional methods. This also brings about interesting changes to the structure of the pulse intensity such as pulse front tilt (PFT), an eect where the pulse energy is delayed across the focal spot at the focal plane by longer durations than the pulse itself. Though these pulses have found utility in microscopy and micromachining, in-situ methods for characterizing them spatially and temporally are not yet wide spread. I present here an in-situ characterization technique for both spatial and temporal diagnosis of SSTF pulses. By performing a knife-edge scan and collecting the light in a spectrometer, the relative spectral position as well as beam size can be deduced. Temporal characterization is done by dispersion scan, where a second harmonic crystal through the beam focus. Combining the unknown phase of the pulse with the known phase (a result of angular dispersion) allows the unknown phase to be extracted from the second harmonic spectra.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-04-01

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

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

    PubMed

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

    2016-09-01

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

  11. 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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2006-11-01

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

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

    PubMed

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

    2016-10-15

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

  15. 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.

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

    PubMed

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

    2016-09-01

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

  17. Spatio-Temporal Simulation of First Pass Drug Perfusion in the Liver

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-03-01

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

  19. 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.

  20. 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.

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

    PubMed

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

    2016-10-15

    Understanding of the distribution patterns of sediment erosion, concentration and transport in river basins is critically important as sediment plays a major role in river basin hydrophysical and ecological processes. In this study, we proposed an integrated framework for the assessment of sediment dynamics, including soil erosion (SE), suspended sediment load (SSL) and suspended sediment concentration (SSC), and applied this framework to the Mekong River Basin. The Revised Universal Soil Loss Equation (RUSLE) model was adopted with a geographic information system to assess SE and was coupled with a sediment accumulation and a routing scheme to simulate SSL. This framework also analyzed Landsat imagery captured between 1987 and 2000 together with ground observations to interpolate spatio-temporal patterns of SSC. The simulated SSL results from 1987 to 2000 showed the relative root mean square error of 41% and coefficient of determination (R(2)) of 0.89. The polynomial relationship of the near infrared exoatmospheric reflectance and the band 4 wavelength (760-900nm) to the observed SSC at 9 sites demonstrated the good agreement (overall relative RMSE=5.2%, R(2)=0.87). The result found that the severe SE occurs in the upper (China and Lao PDR) and lower (western part of Vietnam) regions. The SSC in the rainy season (June-November) showed increasing and decreasing trends longitudinally in the upper (China and Lao PDR) and lower regions (Cambodia), respectively, while the longitudinal profile of SSL showed a fluctuating trend along the river in the early rainy season. Overall, the results described the unique spatio-temporal patterns of SE, SSL and SSC in the Mekong River Basin. Thus, the proposed integrated framework is useful for elucidating complex process of sediment generation and transport in the land and river systems of large river basins. PMID:27338846

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

    PubMed Central

    2010-01-01

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

  3. An Ethnographic Case Study of Spatio-Temporal Practices Circulating On- and Off-Line in a Distance Learning Class

    ERIC Educational Resources Information Center

    Kabat-Ryan, Katalin Judith

    2013-01-01

    This dissertation examines the spatio-temporal practices of a distance learning class in a graduate institution in the Northeast United States. Guided by a multispatial and temporal perspective, the case study builds on Hine's (2003) and Leander and McKim's (2003) connective ethnography of offline and online research sites, and frames the research…

  4. 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.

  5. Spatio-Temporal Signal Twice-Whitening Algorithms on the hx3100 Ultra-Low Power Multicore Processor

    SciTech Connect

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

    2010-01-01

    While modern signal detection theory fully accounts for spatially distributed sensors, exploiting these techniques for real-time sensing using large, underwater acoustic arrays requires advances in the spatio-temporal signal processing algorithms. In particular, the computational complexity of many spatio-temporal processing techniques is so large that conventional computer processors lack sufficient throughput to provide real-time processing of large spatio-temporal data sets. These limits are exacerbated when constraints, such as power consumption or footprint, reduce the available computational resources. In this report, we demonstrate an implementation of a signal twice-whitening algorithm that is better suited for processing spatio-temporal data in real time. We emphasize these advances by implementing data whitening on the Coherent Logix hx3100 processor, a programmable multicore processor intended for low-power and high-throughput signal processing. These results serve as an example of how the novel capabilities available from emerging multicore processor platforms can provide real-time, software-defined processing of large data sets acquired by spatially distributed sensing.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  7. 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.

  8. Spatio-temporal Uncertainty Quantification of Biospheric Models through Gaussian Processes and Stochastic Collocation: An Example Using the CASA-GFED Model

    NASA Astrophysics Data System (ADS)

    Yadav, V.; Michalak, A. M.

    2013-12-01

    Quantifying the uncertainty associated with predictions of mechanistic biospheric models remains an important problem, and is essential for accurately performing multi-model intercomparisons and syntheses. When individual simulations are computationally inexpensive, a simple Monte-Carlo approach can be adopted to quantify this uncertainity. However, this simple approach becomes intractable for mechanistic models with substantial computational costs. To overcome these computational bottlenecks, sparse sampling based methods that can capture the mechanistic model response using a small number of model simulations are required. Two such methods are explored in this study to quantify the uncertainity of the CASA-GFED mechanistic biosphere model. Random 'Latin hypercube' and deterministic 'polynomial chaos' sampling designs are used to construct Gaussian process (GP), and stochastic collocation (SC) surrogate models of the CASA-GFED biospheric model. With the aid of the GP model, we map the spatio-temporal impact of the uncertainty associated with temperature, precipitation, fraction of photosynthetically active radiation, and light use efficiency on estimates of the Net Primary Productivity produced by CASA-GFED. We find that both GP and SC models can accurately capture the mean and the variance of the mechanistic model output in substantially fewer simulations then a standard Monte-Carlo procedure. The GP model also provides additional details about the influence of uncertain variables on the mechanistic model output. However, this additional information comes with higher computational cost that is dependent on the parameterization of the covariance structure between the sampled variables used to model the response of the mechanistic model.

  9. Automated Spatio-Temporal Analysis of Remotely Sensed Imagery for Water Resources Management

    NASA Astrophysics Data System (ADS)

    Bahr, Thomas

    2016-04-01

    Since 2012, the state of California faces an extreme drought, which impacts water supply in many ways. Advanced remote sensing is an important technology to better assess water resources, monitor drought conditions and water supplies, plan for drought response and mitigation, and measure drought impacts. In the present case study latest time series analysis capabilities are used to examine surface water in reservoirs located along the western flank of the Sierra Nevada region of California. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. A time series from Landsat images (L-5 TM, L-7 ETM+, L-8 OLI) of the AOI was obtained for 1999 to 2015 (October acquisitions). Downloaded from the USGS EarthExplorer web site, they already were georeferenced to a UTM Zone 10N (WGS-84) coordinate system. ENVITasks were used to pre-process the Landsat images as follows: • Triangulation based gap-filling for the SLC-off Landsat-7 ETM+ images. • Spatial subsetting to the same geographic extent. • Radiometric correction to top-of-atmosphere (TOA) reflectance. • Atmospheric correction using QUAC®, which determines atmospheric correction parameters directly from the observed pixel spectra in a scene, without ancillary information. Spatio-temporal analysis was executed with the following tasks: • Creation of Modified Normalized Difference Water Index images (MNDWI, Xu 2006) to enhance open water features while suppressing noise from built-up land, vegetation, and soil. • Threshold based classification of the water index images to extract the water features. • Classification aggregation as a post-classification cleanup process. • Export of the respective water classes to vector layers for further evaluation in a GIS. • Animation of the classification series and export to

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    The spatial distribution of uncontrolled hazardous events, such as forest fires, is largely investigated from the scientific community with the purpose of finding out the more vulnerable areas. Mapping the location of spatio-temporal sequences for a given environmental dataset is of great impact; however, the majority of the studies miss the analysis of the aggregation over time. Nonetheless discovering unusual temporal pattern for a given time sequence is fundamental to understand the phenomena and underlying processes. The present study aims investigating both the spatial and the temporal cluster behaviour of forest fires occurrences registered in Canton Ticino (Switzerland) over a period of about 40 years and testing if space and time interact in generate clusters. To do this, the purely spatial, the time and the space-time extensions of the Ripley's K-function were applied. The Ripley's K-function is a statistic exploratory method which enables detecting whether or not a point process (e.g. the location of the ignition points) is randomly distributed. The purely spatial K-function K(r) is defined as the expected number of further events within an area of radius r around an arbitrary point of the pattern, divided by the intensity of the phenomenon. Under completely spatial randomness, the value of the K(r) is equal to the area around the point (=πr2), while observations above this theoretical value imply a clustering behaviour at the corresponding distance r. For the purely time analysis, the Ripley's K-function K(t) can be taught as a reformulation of the spatial version to detect unexpected aggregation of events over the temporal scale. For its computation, the value of the intensity used in K(r) is replaced by the total duration of the time sequence divided by the total number of observed events, and the distance r is replaced by the time interval t. Under time-regularity, K(t) equals 2t, whereas, observed measures above this theoretical value indicate a

  11. Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

    NASA Astrophysics Data System (ADS)

    Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

    2016-04-01

    Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and

  12. 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

  13. 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

  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 Kármán vortex streets in the deeper layers of the canopy. Using laser-induced fluorescence measurements at two different depths within a rod canopy situated in a large flume, the spatio-temporal statistical properties and concomitant necessary conditions for ergodicity of passive scalar turbulence statistics are evaluated. First, the integral time and length scales are analyzed and their corresponding maximum values are used to guide the construction of an ensemble of independent realizations from repeated spatio-temporal concentration measurements. As a statistical analysis for an operational ergodicity check, a Kolmogorov-Smirnov test on the distributions of temporal and spatial concentration series against the ensemble was conducted. The outcome of this test reveals that ergodicity is reasonably valid over the entire domain except close to the rod elements where wake-induced inhomogeneities and damped turbulence prevail. The spatial concentration statistics within a grid-cell (square domain formed by four corner rods) appear to be less ergodic than their temporal counterparts, which is not surprising given the periodicity and persistence of von Kármán vortices in

  15. 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

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

    USGS Publications Warehouse

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

    2016-01-01

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

  17. Simulating Future Changes in Spatio-temporal Precipitation by Identifying and Characterizing Individual Rainstorm Events

    NASA Astrophysics Data System (ADS)

    Chang, W.; Stein, M.; Wang, J.; Kotamarthi, V. R.; Moyer, E. J.

    2015-12-01

    A growing body of literature suggests that human-induced climate change may cause significant changes in precipitation patterns, which could in turn influence future flood levels and frequencies and water supply and management practices. Although climate models produce full three-dimensional simulations of precipitation, analyses of model precipitation have focused either on time-averaged distributions or on individual timeseries with no spatial information. We describe here a new approach based on identifying and characterizing individual rainstorms in either data or model output. Our approach enables us to readily characterize important spatio-temporal aspects of rainstorms including initiation location, intensity (mean and patterns), spatial extent, duration, and trajectory. We apply this technique to high-resolution precipitation over the continental U.S. both from radar-based observations (NCEP Stage IV QPE product, 1-hourly, 4 km spatial resolution) and from model runs with dynamical downscaling (WRF regional climate model, 3-hourly, 12 km spatial resolution). In the model studies we investigate the changes in storm characteristics under a business-as-usual warming scenario to 2100 (RCP 8.5). We find that in these model runs, rainstorm intensity increases as expected with rising temperatures (approximately 7%/K, following increased atmospheric moisture content), while total precipitation increases by a lesser amount (3%/K), consistent with other studies. We identify for the first time the necessary compensating mechanism: in these model runs, individual precipitation events become smaller. Other aspects are approximately unchanged in the warmer climate. Because these spatio-temporal changes in rainfall patterns would impact regional hydrology, it is important that they be accurately incorporated into any impacts assessment. For this purpose we have developed a methodology for producing scenarios of future precipitation that combine observational data and

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  19. 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

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

    PubMed

    Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

    2012-01-01

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

  1. 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

  2. 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

  3. 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

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

    NASA Astrophysics Data System (ADS)

    de Lavenne, Alban; Cudennec, Christophe

    2013-04-01

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

  5. 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

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

    PubMed

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

    2005-06-01

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

  7. 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

  8. Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

    PubMed Central

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

    2016-01-01

    The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

  9. Spatio-temporal hierarchy in the dynamics of a minimalist protein model.

    PubMed

    Matsunaga, Yasuhiro; Baba, Akinori; Li, Chun-Biu; Straub, John E; Toda, Mikito; Komatsuzaki, Tamiki; Berry, R Stephen

    2013-12-01

    A method for time series analysis of molecular dynamics simulation of a protein is presented. In this approach, wavelet analysis and principal component analysis are combined to decompose the spatio-temporal protein dynamics into contributions from a hierarchy of different time and space scales. Unlike the conventional Fourier-based approaches, the time-localized wavelet basis captures the vibrational energy transfers among the collective motions of proteins. As an illustrative vehicle, we have applied our method to a coarse-grained minimalist protein model. During the folding and unfolding transitions of the protein, vibrational energy transfers between the fast and slow time scales were observed among the large-amplitude collective coordinates while the other small-amplitude motions are regarded as thermal noise. Analysis employing a Gaussian-based measure revealed that the time scales of the energy redistribution in the subspace spanned by such large-amplitude collective coordinates are slow compared to the other small-amplitude coordinates. Future prospects of the method are discussed in detail.

  10. 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.

  11. 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

  12. 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.

  13. Spatio-temporal dynamics of species richness in coastal fish communities.

    PubMed Central

    Lekve, Kyrre; Boulinier, Thierry; Stenseth, Nils Chr; Gjøsaeter, Jakob; Fromentin, Jean-Marc; Hines, James E; Nichols, James D

    2002-01-01

    Determining patterns of change in species richness and the processes underlying the dynamics of biodiversity are of key interest within the field of ecology, but few studies have investigated the dynamics of vertebrate communities at a decadal temporal scale. Here, we report findings on the spatio-temporal variability in the richness and composition of fish communities along the Norwegian Skagerrak coast having been surveyed for more than half a century. Using statistical models incorporating non-detection and associated sampling variance, we estimate local species richness and changes in species composition allowing us to compute temporal variability in species richness. We tested whether temporal variation could be related to distance to the open sea and to local levels of pollution. Clear differences in mean species richness and temporal variability are observed between fjords that were and were not exposed to the effects of pollution. Altogether this indicates that the fjord is an appropriate scale for studying changes in coastal fish communities in space and time. The year-to-year rates of local extinction and turnover were found to be smaller than spatial differences in community composition. At the regional level, exposure to the open sea plays a homogenizing role, possibly due to coastal currents and advection. PMID:12350265

  14. Spatio-temporal regulations and functions of neuronal alternative RNA splicing in developing and adult brains.

    PubMed

    Iijima, Takatoshi; Hidaka, Chiharu; Iijima, Yoko

    2016-08-01

    Alternative pre-mRNA splicing is a fundamental mechanism that generates molecular diversity from a single gene. In the central nervous system (CNS), key neural developmental steps are thought to be controlled by alternative splicing decisions, including the molecular diversity underlying synaptic wiring, plasticity, and remodeling. Significant progress has been made in understanding the molecular mechanisms and functions of alternative pre-mRNA splicing in neurons through studies in invertebrate systems; however, recent studies have begun to uncover the potential role of neuronal alternative splicing in the mammalian CNS. This article provides an overview of recent findings regarding the regulation and function of neuronal alternative splicing. In particular, we focus on the spatio-temporal regulation of neurexin, a synaptic adhesion molecule, by neuronal cell type-specific factors and neuronal activity, which are thought to be especially important for characterizing neural development and function within the mammalian CNS. Notably, there is increasing evidence that implicates the dysregulation of neuronal splicing events in several neurological disorders. Therefore, understanding the detailed mechanisms of neuronal alternative splicing in the mammalian CNS may provide plausible treatment strategies for these diseases.

  15. 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.

  16. Spatial, temporal, and spatio-temporal modulational instabilities in a planar dual-core waveguide

    NASA Astrophysics Data System (ADS)

    Sharma, Vivek Kumar; Goyal, Amit; Raju, Thokala Soloman; Kumar, C. N.; Panigrahi, Prasanta K.

    2015-08-01

    We investigate modulational instability (MI) in a planar dual-core waveguide (DWG), with a Kerr and non-Kerr polarizations based on coupled nonlinear Schrödinger equations in the presence of linear coupling term, coupling coefficient dispersion (CCD) and other higher order effects such as third order dispersion (TOD), fourth order dispersion (FOD), and self-steepening (ss). By employing a standard linear stability analysis, we obtain analytically, an explicit expression for the MI growth rate as a function of spatial and temporal frequencies of the perturbation and the material response time. Pertinently, we explicate three different types of MI-spatial, temporal, and spatio-temporal MI for symmetric/antisymmetric continuous wave (cw), and spatial MI for asymmetric cw, and emphasize that the earlier studies on MI in DWG do not account for this physics. Essentially, we discuss two cases: (i) the case for which the two waveguides are linearly coupled and the CCD term plays no role and (ii) the case for which the linear coupling term is zero and the CCD term is nonzero. In the former case, we find that the MI growth rate in the three different types of MI, seriously depends on the coupling term, quintic nonlinearity, FOD, and ss. In the later case, the presence of quintic nonlinearity, CCD, FOD, and ss seriously enhances the formation of MI sidebands, both in normal as well as anomalous dispersion regimes. For asymmetric cw, spatial MI is dependent on linear coupling term and quintic nonlinearity.

  17. Evaluation of color spatio-temporal interest points for human action recognition.

    PubMed

    Everts, Ivo; van Gemert, Jan C; Gevers, Theo

    2014-04-01

    This paper considers the recognition of realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photometric phenomena, such as shadows and highlights. In addition, valuable information is neglected by discarding chromaticity from the photometric representation. These issues are addressed by color STIPs. Color STIPs are multichannel reformulations of STIP detectors and descriptors, for which we consider a number of chromatic and invariant representations derived from the opponent color space. Color STIPs are shown to outperform their intensity-based counterparts on the challenging UCF sports, UCF11 and UCF50 action recognition benchmarks by more than 5% on average, where most of the gain is due to the multichannel descriptors. In addition, the results show that color STIPs are currently the single best low-level feature choice for STIP-based approaches to human action recognition.

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    1993-01-01

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

  20. 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

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

    PubMed Central

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

    2015-01-01

    With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures and how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data. PMID:25901353

  2. 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.

  3. Mass spectrometric analysis of spatio-temporal dynamics of crustacean neuropeptides.

    PubMed

    OuYang, Chuanzi; Liang, Zhidan; Li, Lingjun

    2015-07-01

    Neuropeptides represent one of the largest classes of signaling molecules used by nervous systems to regulate a wide range of physiological processes. Over the past several years, mass spectrometry (MS)-based strategies have revolutionized the discovery of neuropeptides in numerous model organisms, especially in decapod crustaceans. Here, we focus our discussion on recent advances in the use of MS-based techniques to map neuropeptides in the spatial domain and monitoring their dynamic changes in the temporal domain. These MS-enabled investigations provide valuable information about the distribution, secretion and potential function of neuropeptides with high molecular specificity and sensitivity. In situ MS imaging and in vivo microdialysis are highlighted as key technologies for probing spatio-temporal dynamics of neuropeptides in the crustacean nervous system. This review summarizes the latest advancement in MS-based methodologies for neuropeptide analysis including typical workflow and sample preparation strategies as well as major neuropeptide families discovered in decapod crustaceans. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

  4. Influence of density dependence on predator–prey seabird interactions at large spatio-temporal scales

    PubMed Central

    Oro, Daniel; Martínez-Abraín, Alejandro; Paracuellos, Mariano; Nevado, Juan Carlos; Genovart, Meritxell

    2005-01-01

    Theoretical investigations of competitive dynamics have noted that numbers of predator and prey influence each other. However, few empirical studies have demonstrated how a life-history trait of the prey (such as fecundity) can be affected simultaneously by its own density and the density of predators. For instance, density dependence can reduce fecundity with increasing number of prey, while inverse density dependence or Allee effects may occur especially when the prey is a social organism. Here we analysed an intraguild predator–prey system of two seabird species at a large spatio-temporal scale. As expected, we found that fecundity of prey was negatively affected by predator density. Nevertheless, fecundity of prey also increased nonlinearly with its own density and strikingly with the prey–predator ratio. Small groups of prey were probably not able to defend their nests especially against large number of predators. At the highest prey densities (i.e. when anti-predator strategies should be most efficient), prey fecundity also lowered, suggesting the appearance of density dependence mediated by food competition. Allee effects and density dependence occurred across a broad range of population sizes of both the prey and the predator at several local populations facing different ecological environments. PMID:16543182

  5. Influence of density dependence on predator-prey seabird interactions at large spatio-temporal scales.

    PubMed

    Oro, Daniel; Martínez-Abraín, Alejandro; Paracuellos, Mariano; Nevado, Juan Carlos; Genovart, Meritxell

    2006-02-01

    Theoretical investigations of competitive dynamics have noted that numbers of predator and prey influence each other. However, few empirical studies have demonstrated how a life-history trait of the prey (such as fecundity) can be affected simultaneously by its own density and the density of predators. For instance, density dependence can reduce fecundity with increasing number of prey, while inverse density dependence or Allee effects may occur especially when the prey is a social organism. Here we analysed an intraguild predator-prey system of two seabird species at a large spatio-temporal scale. As expected, we found that fecundity of prey was negatively affected by predator density. Nevertheless, fecundity of prey also increased nonlinearly with its own density and strikingly with the prey-predator ratio. Small groups of prey were probably not able to defend their nests especially against large number of predators. At the highest prey densities (i.e. when anti-predator strategies should be most efficient), prey fecundity also lowered, suggesting the appearance of density dependence mediated by food competition. Allee effects and density dependence occurred across a broad range of population sizes of both the prey and the predator at several local populations facing different ecological environments. PMID:16543182

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

    NASA Astrophysics Data System (ADS)

    Ring, A.; Lampkin, D. J.

    2014-12-01

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

  7. 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

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

    PubMed

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

    2015-01-01

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

  9. On the Relation between Spatio-Temporal Forcing and Structure of Turbulence

    NASA Astrophysics Data System (ADS)

    Carter, Douglas; Coletti, Filippo

    2015-11-01

    The different methods to force turbulence in physical or numerical experiments can have significant effects on the fluid dynamics. Understanding how a given forcing scheme maps on the flow statistics is important both to reproduce desired flow features, and to gain insight in the transfer of energy across the scales. Here we consider the case of the turbulent flow generated by the interaction of pulsating jets. We present a novel installation where pressurized air is issued through 256 independently actuated valves, arranged in symmetric rectangular arrays over two facing planes. The small net mass flux and the randomization of the actuation produces a large region of approximately homogeneous flow at the center of the apparatus, with fluctuations much larger than the mean velocity. The turbulence structure under different firing sequences is statistically analyzed using Particle Image Velocimetry. The forcing parameters include: jet Reynolds number, spacing of the active jets, actuation frequency, and spatio-temporal correlation of the firing patterns. The observables include: integral length scales, turbulent dissipation, energy spectra, and isotropy. We discuss the relation between forcing schemes and flow features, and implications for modeling and flow control.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

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

    PubMed Central

    Ping, Bo; Su, Fenzhen; Meng, Yunshan

    2016-01-01

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

  15. Multichannel spatio-temporal topographic processing for visual search and navigation

    NASA Astrophysics Data System (ADS)

    Szatmari, Istvan; Balya, David; Timar, Gergely; Rekeczky, Csaba; Roska, Tamas

    2003-04-01

    In this paper a biologically motivated image flow processing mechanism is presented for visual exploration systems. The intention of this multi-channel topographic approach was to produce decision maps for salient feature localization and identification. As a unique biological study has recently confirmed mammalian visual systems process the world through a set of separate parallel channels and these representations are embodied in a stack of 'strata' in the retina. Beyond reflecting the biological motivations our main goal was to create an efficient algorithmic framework for real-life visual search and navigation experiments. In the course of this design the retinotopic processing scheme is embedded in an analogic Cellular Neural Network (CNN) algorithm where image flow is analyzed by temporal, spatial and spatio-temporal filters. The output of these sub-channels is then combined in a programmable configuration to form the new channel responses. In the core of the algorithm crisp or fuzzy logic strategies define the global channel interaction and result in a unique binary image flow. This processing mechanism of the algorithmic framework and the hardware architecture of the system are presented along with experimental ACE4k CNN chip results for several video flows recorded in flying vehicles.

  16. 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.

  17. Geographical information system (GIS) mapping of spatio-temporal pollution status of rivers in Ibadan, Nigeria.

    PubMed

    Adeyemo, Olanike K; Babalobi, Olutayo O

    2008-04-01

    More accurate spatio-temporal predictions of urban environment are needed as a basis for assessing exposures as a part of environmental studies and to inform urban protection policy and management. In this study, an information system was developed to manage the physico-chemical pollution information of Ibadan river system, Oyo State, Southwest Nigeria. The study took into account the seasonal influences of point and non-point discharges on the levels of physico-chemical parameters. The overall sensitivity of the watershed to physicochemical environmental pollution revealed that during dry season, of the 22 (100%) sample points, only 3 (13.6%) were unpolluted; 6 (27.3%) were slightly polluted; 10(45.4%) were moderately polluted; 2 (9.1%) were seriously polluted and 1 (4.5%) was exceptionally polluted. During rainy season, 3 (13.6%) were unpolluted; 7 (31.8%) were slightly polluted; 9 (40.9%) were moderately polluted; 2 (9.1%) were seriously polluted and 1 (4.5%) was exceptionally polluted. There is a considerable environmental risk associated with the present level of pollution of the Ibadan river water body on fish health and biodiversity. This research provides a basis for aquatic management and assist in policy making at national and international levels. Appropriate strategies for the control of point and non-point pollution sources, amendments and enforcement of legislation should be developed.

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

    PubMed

    Zhu, Tao

    2014-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. 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.

  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. A novel sensor to map auxin response and distribution at high spatio-temporal resolution.

    PubMed

    Brunoud, Géraldine; Wells, Darren M; Oliva, Marina; Larrieu, Antoine; Mirabet, Vincent; Burrow, Amy H; Beeckman, Tom; Kepinski, Stefan; Traas, Jan; Bennett, Malcolm J; Vernoux, Teva

    2012-01-15

    Auxin is a key plant morphogenetic signal but tools to analyse dynamically its distribution and signalling during development are still limited. Auxin perception directly triggers the degradation of Aux/IAA repressor proteins. Here we describe a novel Aux/IAA-based auxin signalling sensor termed DII-VENUS that was engineered in the model plant Arabidopsis thaliana. The VENUS fast maturing form of yellow fluorescent protein was fused in-frame to the Aux/IAA auxin-interaction domain (termed domain II; DII) and expressed under a constitutive promoter. We initially show that DII-VENUS abundance is dependent on auxin, its TIR1/AFBs co-receptors and proteasome activities. Next, we demonstrate that DII-VENUS provides a map of relative auxin distribution at cellular resolution in different tissues. DII-VENUS is also rapidly degraded in response to auxin and we used it to visualize dynamic changes in cellular auxin distribution successfully during two developmental responses, the root gravitropic response and lateral organ production at the shoot apex. Our results illustrate the value of developing response input sensors such as DII-VENUS to provide high-resolution spatio-temporal information about hormone distribution and response during plant growth and development.

  3. 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.

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

    PubMed

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

    2016-07-27

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

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

    NASA Astrophysics Data System (ADS)

    Dong, B.

    2016-08-01

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

  6. Spatio-temporal receptive field properties of cells in the rat superior colliculus.

    PubMed

    Prévost, François; Lepore, Franco; Guillemot, Jean-Paul

    2007-04-20

    Although the rat is widely used in neurobehavioural research, the spatio-temporal receptive field properties of neurons in superficial layers of the superior colliculus are relatively unknown. Extracellular recordings were carried out in anesthetized Long Evans rats. Neurons in these layers had simple-like and complex-like receptive fields (RFs). Most cells (67%) had RFs showing band-pass and low-pass spatial frequency (SF) tuning profiles. Spatial band-pass profiles showed low optimal SF (mean=0.03 c/deg), low spatial resolution (mean=0.18 c/deg) and large spatial bandwidths (mean=2.3 octaves). More than two-thirds of the RFs (71%) were selective to orientation and only 11% were clearly direction selective. Nearly two-thirds of cells (68%) had band-pass temporal frequency (TF) tuning profiles with narrow bandwidths (mean=1.7 oct.) whereas the others showed low-pass TF tuning profiles. Temporal band-pass profiles had low optimal TFs (mean=3.5 c/s). Although some cells showed relatively low contrast thresholds (6%), most cells only responded to high contrast values (mean=38.2%). These results show that the spatial resolution of collicular cells is poor and that they respond mainly to highly contrasted moving stimuli.

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

    PubMed Central

    Litvak-Hinenzon, Anna; Stone, Lewi

    2009-01-01

    The success of an infectious disease to invade a population is strongly controlled by the population's specific connectivity structure. Here, a network model is presented as an aid in understanding the role of social behaviour and heterogeneous connectivity in determining the spatio-temporal patterns of disease dynamics. We explore the controversial origins of long-term recurrent oscillations believed to be characteristic of diseases that have a period of temporary immunity after infection. In particular, we focus on sexually transmitted diseases such as syphilis, where this controversy is currently under review. Although temporary immunity plays a key role, it is found that, in realistic small-world networks, the social and sexual behaviour of individuals also has a great influence in generating long-term cycles. The model generates circular waves of infection with unusual spatial dynamics that depend on focal areas that act as pacemakers in the population. Eradication of the disease can be efficiently achieved by eliminating the pacemakers with a targeted vaccination scheme. A simple difference equation model is derived, which captures the infection dynamics of the network model and gives insights into their origins and their eradication through vaccination. Illustrative videos may be found in the electronic supplementary material. PMID:18957362

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

    PubMed

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

    2015-01-01

    With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures and how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data. PMID:25901353

  9. 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

  10. Inferring social network structure in ecological systems from spatio-temporal data streams

    PubMed Central

    Psorakis, Ioannis; Roberts, Stephen J.; Rezek, Iead; Sheldon, Ben C.

    2012-01-01

    We propose a methodology for extracting social network structure from spatio-temporal datasets that describe timestamped occurrences of individuals. Our approach identifies temporal regions of dense agent activity and links are drawn between individuals based on their co-occurrences across these ‘gathering events’. The statistical significance of these connections is then tested against an appropriate null model. Such a framework allows us to exploit the wealth of analytical and computational tools of network analysis in settings where the underlying connectivity pattern between interacting agents (commonly termed the adjacency matrix) is not given a priori. We perform experiments on two large-scale datasets (greater than 106 points) of great tit Parus major wild bird foraging records and illustrate the use of this approach by examining the temporal dynamics of pairing behaviour, a process that was previously very hard to observe. We show that established pair bonds are maintained continuously, whereas new pair bonds form at variable times before breeding, but are characterized by a rapid development of network proximity. The method proposed here is general, and can be applied to any system with information about the temporal co-occurrence of interacting agents. PMID:22696481

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

    PubMed

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

    2015-01-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.

    PubMed

    Fried, Patrick; Sánchez-Aragón, Máximo; Aguilar-Hidalgo, Daniel; Lehtinen, Birgitta; Casares, Fernando; Iber, Dagmar

    2016-09-01

    Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF), a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp), Hedgehog (Hh) and the transcription factor Homothorax (Hth) and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment. PMID:27626238

  18. A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development

    PubMed Central

    Fried, Patrick; Sánchez-Aragón, Máximo; Lehtinen, Birgitta; Casares, Fernando; Iber, Dagmar

    2016-01-01

    Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF), a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp), Hedgehog (Hh) and the transcription factor Homothorax (Hth) and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment. PMID:27626238

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

    PubMed

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

    2014-03-01

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

  20. 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.

  1. 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

  2. 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

  3. Spatio-Temporal dependence effects of the 17 March 2015 space weather event

    NASA Astrophysics Data System (ADS)

    Bagiya, Mala; Sunda, Surendra; Sunil, A. S.

    2016-07-01

    The super storm of 17 March 2015 has been the largest space weather event of solar cycle 24 till date. The main phase for this storm occurred in two steps. The present study describes the response of global low latitude ionosphere to this event. Total Electron Content (TEC) observations from low latitude International GNSS Services (IGS) stations and one of our own equatorial GNSS station at Tirunelveli are used to derive the temporal ionospheric variability over a large spatial scale during this storm. Intense equatorial ionisation anomaly (EIA) developed over the longitudes where first step of the main phase coincided with local noon time. Equatorial Spread-F (ESF) irregularities occurred quiet strongly in the dusk sector that coincided in time with the initiation of second step of the main phase. The combined effects of overshielding electric field and the disturbance dynamo electric field reduced TEC during first step of the main phase. The storm effects observed to be mostly absent in the post-midnight to early morning sector. The presented spatio-temporal variabilities of low latitude ionosphere during the 17 March 2015 storm are discussed in view of the local time dependence of storm time electrodynamical coupling between high and low latitudes.

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

    PubMed

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

    2016-07-27

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

  5. 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.

  6. Spatio-temporal variation of the diterpene steviol in Stevia rebaudiana grown under different photoperiods.

    PubMed

    Ceunen, Stijn; Geuns, Jan M C

    2013-05-01

    As part of an ongoing study on the effects of photoperiodism on the metabolism of steviol glycosides (SVglys) in Stevia rebaudiana, the spatio-temporal variations of free steviol (SV) have now been evaluated. For its quantitation, an internal standard method was used, based upon a specific fluorometric detection of SV as its methoxycoumarinyl derivative. The level of free SV in leaves did not exceed 30 μg/g dry wt and was at least 1000-fold smaller than that of its glycosidic conjugates. In other organs, free SV was mainly measured in stem tissue and apices, with relatively large amounts measured in the latter. Similarly to SVglys, the content of free SV was influenced by photoperiod and genotype. In plants grown under long-days (LD) of 16 h, more spatial variations were seen compared to those under short-days (SD) of 8h. In the former, upper leaves contained almost four times more free SV compared to lower ones near the end of vegetative growth. In addition, the correlation between SV and its glycosidic conjugates was more linear under SD. Despite the variability of SV levels, a decrease was noted in all conditions after flower opening, which can be related a decreased transcription of the biosynthetic genes involved.

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

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

    PubMed Central

    Schneider, Johannes; Klein, Teresa; Mielich-Süss, Benjamin; Koch, Gudrun; Franke, Christian; Kuipers, Oscar P.; Kovács, Ákos T.; Sauer, Markus; Lopez, Daniel

    2015-01-01

    Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs) that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium. PMID:25909364

  9. 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.

  10. A comparison of predictive soil-carbon models across multiple spatio-temporal catchment scales.

    NASA Astrophysics Data System (ADS)

    Hancock, G. R.; Kunkel, V.; Wells, T.

    2014-12-01

    Soil's potential as a carbon sink for atmospheric CO2 has been widely discussed. Studies of soil organic carbon (SOC) controls, and the subsequent models derived from their findings, have focussed mainly on North American and European regions, and more recently, in regions such as China. In Australia, agricultural practices have led to losses in SOC. This implies that Australian soils have a large potential for increases in SOC. Building on previous work, here we examine the spatial and temporal variation in soil organic carbon (SOC) and its controlling factors controls across a large catchment of approximately 600 km2 in the Upper Hunter Valley, New South Wales, Australia, using data collected from two sampling campaigns, (April 2006 and June-July 2014). Remote sensing using Landsat (30m) and MODIS (250m) NDVI was used to determine if catchment SOC could be predicted using both low and high resolution remote sensing . Relationships between SOC and elevation, aboveground biomass (as represented by NDVI), topographic wetness index (TWI), and incident solar radiation as a surrogate for soil temperature were compared. Initial results demonstrate that higher spatio-temporal resolution may not be necessary for predicting SOC at larger scales. The relationship between SOC and the environmental tracer 137-Cesium as a surrogate for the loss of SOC by erosion also suggests that sediment transport and deposition influences the distribution of SOC. A model developed for the site suggests that simple linear relationships between vegetation, climate and sediment transport could improve SOC predictions.

  11. 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.

  12. 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

  13. 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.

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  16. Understanding the spatio-temporal variability of phytoplankton biomass distribution in a microtidal Mediterranean estuary

    NASA Astrophysics Data System (ADS)

    Artigas, M. L.; Llebot, C.; Ross, O. N.; Neszi, N. Z.; Rodellas, V.; Garcia-Orellana, J.; Masqué, P.; Piera, J.; Estrada, M.; Berdalet, E.

    2014-03-01

    Understanding the spatio-temporal variability of phytoplankton in aquaculture zones is necessary for the prevention and/or prediction of harmful algal bloom events. Synoptic cruises, time series analyses of physical and biological parameters, and 3D modeling were combined to investigate the variability of phytoplankton biomass in Alfacs Bay at basin scale. This microtidal estuary located in the NW Mediterranean is an important area of shellfish and finfish exploitation, which is regularly affected by toxic outbreaks. Observations showed the existence of a preferential phytoplankton accumulation area on the NE interior of the bay. This pattern can be observed throughout the year, and we show that it is directly linked to the physical forcing in the bay, in particular, the interplay between freshwater input and wind-induced turbulence. Both drivers affect the strength of the estuarine circulation, explaining nearly 75% of the variability in phytoplankton biomass. More cells are retained when stratification is weakened and the estuarine circulation reduced, while flushing rates are higher during times of increased stratification and stronger estuarine flow. This has been confirmed by using a 3D hydrodynamic model with Eulerian tracers. Nutrients, while important to support phytoplankton populations, have been found to play only a secondary role in explaining this variability at basin scale.

  17. Spatio-Temporal Clustering of Hand, Foot, and Mouth Disease at the County Level in Guangxi, China

    PubMed Central

    Xie, Yi-hong; Chongsuvivatwong, Virasakdi; Tang, Zhenzhu; McNeil, Edward B.; Tan, Yi

    2014-01-01

    Background Amid numerous outbreaks of hand, foot and mouth disease (HFMD) in Asia over the past decade, studies on spatio-temporal clustering are limited. Without this information the distribution of severe cases assumed to be sporadic. We analyzed surveillance data with onset dates between 1 May 2008 to 31 October 2013 with the aim to document the spatio-temporal clustering of HFMD cases and severe cases at the county level. Methods Purely temporal and purely spatial descriptive analyses were done. These were followed by a space-time scan statistic for the whole study period and by year to detect the high risk clusters based on a discrete Poisson model. Results The annual incidence rate of HFMD in Guangxi increased whereas the severe cases peaked in 2010 and 2012. EV71 and CoxA16 were alternating viruses. Both HFMD cases and severe cases had a seasonal peak in April to July. The spatio-temporal cluster of HFMD cases were mainly detected in the northeastern, central and southwestern regions, among which three clusters were observed in Nanning, Liuzhou, Guilin city and their neighbouring areas lasting from 1.2 to 2.5 years. The clusters of severe cases were less consistent in location and included around 40–70% of all severe cases in each year. Conclusions Both HFMD cases and severe cases occur in spatio-temporal clusters. The continuous epidemic in Nanning, Liuzhou, Guilin cities and their neighbouring areas and the clusters of severe cases indicate the need for further intensive surveillance. PMID:24505378

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

    PubMed Central

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

    2012-01-01

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

  19. 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

  20. Bayesian spatio-temporal modelling of national milk-recording data of seasonal-calving New Zealand dairy herds.

    PubMed

    Clements, A C A; Pfeiffer, D U; Hayes, D

    2005-10-12

    A spatio-temporal analysis was undertaken with the aim of identifying the dynamics of herd mean individual cow SCCs (MICSCC) in seasonally calving New Zealand dairy herds. Two datasets were extracted from the Livestock Improvement Corporation's extensive national dairy recording database: (1) milk-recording data aggregated at the herd-level and (2) sales questionnaire data containing information on the size, location and infrastructure of each farm. A Bayesian spatio-temporal modelling approach was applied to the analysis. The data were aggregated by 10 km(2) grid cells and linear regression models were developed with spatially structured and unstructured random effects, a linear temporal trend random effect and spatial-temporal interactions for log-transformed median MISCC (ln(median MISCC)). Significant associations were found between ln(median MISCC) and milk yield, milk fat, milk protein, farm area and number of cups in the dairy. This led us to suggest that SCCs should be adjusted for volume and constituents prior to determining a threshold MISCC for identification of subclinical mastitis (SCM) problem herds. Part, or all, of the temporal trend in MISCC in the spatio-temporal model was accounted for by inclusion of yield and milk constituents as independent variables. This supports the hypothesis of a dilution effect with potential consequences for misdiagnosis of SCM, particularly in late lactation. Unmeasured covariates were similarly likely to be spatially structured and unstructured. PMID:16107283

  1. Spatio-temporal auxiliary particle filtering with l1-norm-based appearance model learning for robust visual tracking.

    PubMed

    Kim, Du Yong; Jeon, Moongu

    2013-02-01

    In this paper, we propose an efficient and accurate visual tracker equipped with a new particle filtering algorithm and robust subspace learning-based appearance model. The proposed visual tracker avoids drifting problems caused by abrupt motion changes and severe appearance variations that are well-known difficulties in visual tracking. The proposed algorithm is based on a type of auxiliary particle filtering that uses a spatio-temporal sliding window. Compared to conventional particle filtering algorithms, spatio-temporal auxiliary particle filtering is computationally efficient and successfully implemented in visual tracking. In addition, a real-time robust principal component pursuit (RRPCP) equipped with l(1)-norm optimization has been utilized to obtain a new appearance model learning block for reliable visual tracking especially for occlusions in object appearance. The overall tracking framework based on the dual ideas is robust against occlusions and out-of-plane motions because of the proposed spatio-temporal filtering and recursive form of RRPCP. The designed tracker has been evaluated using challenging video sequences, and the results confirm the advantage of using this tracker.

  2. An agent-based model driven by tropical rainfall to understand the spatio-temporal heterogeneity of a chikungunya outbreak.

    PubMed

    Dommar, Carlos J; Lowe, Rachel; Robinson, Marguerite; Rodó, Xavier

    2014-01-01

    Vector-borne diseases, such as dengue, malaria and chikungunya, are increasing across their traditional ranges and continuing to infiltrate new, previously unaffected, regions. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. We develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure vs. precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission. PMID:23958228

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

    NASA Astrophysics Data System (ADS)

    Rupin, Matthieu; Roux, Philippe; Catheline, Stefan

    2014-06-01

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

  4. Adaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces.

    PubMed

    Lu, Jun; Xie, Kan; McFarland, Dennis J

    2014-07-01

    Movement related potentials (MRPs) are used as features in many brain-computer interfaces (BCIs) based on electroencephalogram (EEG). MRP feature extraction is challenging since EEG is noisy and varies between subjects. Previous studies used spatial and spatio-temporal filtering methods to deal with these problems. However, they did not optimize temporal information or may have been susceptible to overfitting when training data are limited and the feature space is of high dimension. Furthermore, most of these studies manually select data windows and low-pass frequencies. We propose an adaptive spatio-temporal (AST) filtering method to model MRPs more accurately in lower dimensional space. AST automatically optimizes all parameters by employing a Gaussian kernel to construct a low-pass time-frequency filter and a linear ridge regression (LRR) algorithm to compute a spatial filter. Optimal parameters are simultaneously sought by minimizing leave-one-out cross-validation error through gradient descent. Using four BCI datasets from 12 individuals, we compare the performances of AST filter to two popular methods: the discriminant spatial pattern filter and regularized spatio-temporal filter. The results demonstrate that our AST filter can make more accurate predictions and is computationally feasible.

  5. Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+.

    PubMed

    Karakaya, Nusret; Evrendilek, Fatih

    2011-10-01

    The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO₃-N), silicate (SiO₄), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO₂-N (P = 0.008) to 0.79 for S (depth) (P < 0.001). Parsimonious MLR models built in this study appear to be promising for monitoring and predicting spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay.

  6. 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

    2015-10-20

    It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

  7. An agent-based model driven by tropical rainfall to understand the spatio-temporal heterogeneity of a chikungunya outbreak.

    PubMed

    Dommar, Carlos J; Lowe, Rachel; Robinson, Marguerite; Rodó, Xavier

    2014-01-01

    Vector-borne diseases, such as dengue, malaria and chikungunya, are increasing across their traditional ranges and continuing to infiltrate new, previously unaffected, regions. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. We develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure vs. precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission.

  8. Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+.

    PubMed

    Karakaya, Nusret; Evrendilek, Fatih

    2011-10-01

    The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO₃-N), silicate (SiO₄), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO₂-N (P = 0.008) to 0.79 for S (depth) (P < 0.001). Parsimonious MLR models built in this study appear to be promising for monitoring and predicting spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay. PMID:21181257

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

    PubMed Central

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

    2008-01-01

    Diffusion is an important mechanism for molecular transport in living biological tissues. Diffusion magnetic resonance imaging (dMRI) provides a unique probe to examine microscopic structures of the tissues in vivo, but current dMRI techniques usually ignore the spatio-temporal evolution process of the diffusive medium. In the present study, we demonstrate the feasibility to reveal the spatio-temporal diffusion process inside the human brain based on a numerical solution of the diffusion equation. Normal human subjects were scanned with a diffusion tensor imaging (DTI) technique on a 3-Tesla MRI scanner, and the diffusion tensor in each voxel was calculated from the DTI data. The diffusion equation, a partial-derivative description of Fick’s Law for the diffusion process, was discretized into equivalent algebraic equations. A finite-difference method was employed to obtain the numerical solution of the diffusion equation with a Crank-Nicholson iteration scheme to enhance the numerical stability. By specifying boundary and initial conditions, the spatio-temporal evolution of the diffusion process inside the brain can be virtually reconstructed. Our results exhibit similar medium profiles and diffusion coefficients as those of light fluorescence dextrans measured in integrative optical imaging experiments. The proposed method highlights the feasibility to non-invasively estimate the macroscopic diffusive transport time for a molecule in a given region of the brain. PMID:18440744

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

    NASA Astrophysics Data System (ADS)

    Liu, X.

    2015-12-01

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

  11. Spatio-temporal surface-subsurface water exchanges: from the local to the watershed scale

    NASA Astrophysics Data System (ADS)

    Rivière, Agnès; Flipo, Nicolas; Mouhri, Amer; Ansart, Patrick; Baudin, Aurélien; Berrhouma, Asma; Bodet, Ludovic; Cocher, Emmanuel; Cucchi, Karina; Durand, Véronique; Flageul, Sébastien; de Fouquet, Chantal; Goblet, Patrick; Hovhannissian, Gaghik; Jost, Anne; Pasquet, Sylvain; Rejiba, Fayçal; Rubin, Yoram; Tallec, Gaëlle; Mouchel, Jean-Marie

    2016-04-01

    Understanding the temporal and spatial variations of the surface-subsurface water exchanges is a prerequisite to achieve sustainable water use in basin. The concept of nested stream-aquifer interfaces (Flipo et al., 2014) is used to simulate the variation of the spatio-temporal surface-subsurface exchanges at the watershed scale from LOcal MOnitoring Stations (LOMOSs) measurements of the stream-aquifer exchanges. This method is applied along the stream network of the Avenelles basin. The Avenelles basin (46 km2) is located 70 km east from Paris. The basin is composed of a multi-layer aquifer system which consists of two limestone aquifers: the Brie aquifer (Oligocene) and the Champigny aquifer (Eocene) separated by a clayey aquitard. The meandering river is shallow, connected with the Brie aquifer in its upstream part and the Champigny aquifer in its downstream part. A high-frequency hydrologic monitoring network was deployed on the basin from 1960. The network measures water levels and water temperatures in the aquifers, and in-stream discharge rates. Five LOMOSs have been operating since 2012 along the stream-network (two upstream, two intermediate, and one downstream site) to monitor spatio-temporal stream-aquifer exchanges over years. LOMOSs are composed of one or two shallow piezometers to monitor the temperature and the hydraulic head variations in the aquifers, two hyporheic zone (HZ) temperature profiles located close to each river bank and one water level and temperature monitoring system in the river. A local 2D thermo-hydro model is used to determine hydrogeological and thermal properties of the aquifer and the HZ by inversion and to quantify the stream-aquifer exchanges at the local scale. We performed a pseudo 3D hydro(geo)logical simulation, over 23 years, at the Avenelles basin scale by the used of CAWAQS modelling platform. The CAWAQS platform is composed of four spatially distributed modules (Surface, Sub-surface, River and Groundwater

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

    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.

  14. Lung diaphragm tracking in CBCT images using spatio-temporal MRF.

    PubMed

    Sundarapandian, Manivannan; Kalpathi, Ramakrishnan; Siochi, R Alfredo C; Kadam, Amrut S

    2016-10-01

    In EBRT in order to monitor the intra fraction motion of thoracic and abdominal tumors, one of the standard approaches is to use the lung diaphragm apex as an internal marker. However, tracking the position of the apex from image based observations is a challenging problem, as it undergoes both position and shape variation. The purpose of this paper is to propose an alternative method for tracking the ipsi-lateral hemidiaphragm apex (IHDA) position on Cone Beam Computed Tomography (CBCT) projection images. A hierarchical method is proposed to track the IHDA position across the frames. The diaphragm state is modeled as a spatio-temporal Markov Random Field (MRF). The likelihood function is derived from the votes based on 4D-Hough space. The optimal state of the diaphragm is obtained by solving the associated energy minimization problem using graph-cuts. A heterogeneous GPU implementation is provided for the method using CUDA framework and the performance is compared with that of CPU implementation. The method was tested using 15 clinical CBCT images. The results demonstrate that the MRF formulation outperforms the full search method in terms of accuracy. The GPU based heterogeneous implementation of the proposed algorithm takes about 25s, which is 16% improvement over the existing benchmark. The proposed MRF formulation considers all the possible combinations from the 4D-Hough space and therefore results in better tracking accuracy. The GPU based implementation exploits the inherent parallelism in our algorithm to accelerate the performance thereby increasing the viability of the approach for clinical use. PMID:27471097

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

    PubMed

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

    2010-12-28

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

  16. Spatio-temporal image correlation (STIC): new technology for evaluation of the fetal heart.

    PubMed

    DeVore, G R; Falkensammer, P; Sklansky, M S; Platt, L D

    2003-10-01

    Spatio-temporal image correlation (STIC) is a new approach for clinical assessment of the fetal heart. It offers an easy to use technique to acquire data from the fetal heart and to aid in visualization with both two-dimensional and three-dimensional (3D) cine sequences. The acquisition is performed in two steps: first, images are acquired by a single, automatic volume sweep. Second, the system analyzes the image data according to their spatial and temporal domain and processes an online dynamic 3D image sequence that is displayed in a multiplanar reformatted cross-sectional display and/or a surface rendered display. The examiner can navigate within the heart, re-slice, and produce all of the standard image planes necessary for a comprehensive diagnosis. The advantages of STIC for use in evaluation of the fetal heart are as follows: the technique delivers a temporal resolution which corresponds to a B-mode frame rate of approximately 80 frames/s; it provides the examiner with an unlimited number of images for review; it allows for correlation between image planes that are perpendicular to the main image acquisition plane; it may shorten the evaluation time when complex heart defects are suspected; it enables the reconstruction of a 3D rendered image that contains depth and volume which may provide additional information that is not available from the thin multiplanar image slices (e.g. for pulmonary veins, septal thickness); it lends itself to storage and review of volume data by the examiner or by experts at a remote site; it provides the examiner with the ability to review all images in a looped cine sequence. PMID:14528474

  17. 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

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

    PubMed

    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

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  1. 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.

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

    SciTech Connect

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

    2013-08-20

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  4. Mathematical modeling of spatio-temporal dynamics of a single bone multicellular unit.

    PubMed

    Ryser, Marc D; Nigam, Nilima; Komarova, Svetlana V

    2009-05-01

    During bone remodeling, bone-resorbing osteoclasts and bone-forming osteoblasts are organized in bone multicellular units (BMUs), which travel at a rate of 20-40 mum/d for 6-12 mo, maintaining a cylindrical structure. However, the interplay of local BMU geometry with biochemical regulation is poorly understood. We developed a mathematical model of BMU describing changes in time and space of the concentrations of proresorptive cytokine RANKL and its inhibitor osteoprotegerin (OPG), in osteoclast and osteoblast numbers, and in bone mass. We assumed that osteocytes surrounding a microfracture produce RANKL, which attracted osteoclasts. OPG and RANKL were produced by osteoblasts and diffused through bone, RANKL was eliminated by binding to OPG and RANK. Osteoblasts were coupled to osteoclasts through paracrine factors. The evolution of the BMU arising from this model was studied using numerical simulations. Our model recapitulated the spatio-temporal dynamics observed in vivo in a cross-section of bone. In response to a RANKL field, osteoclasts moved as a well-confined cutting cone. The coupling of osteoclasts to osteoblasts allowed for sufficient recruitment of osteoblasts to the resorbed surfaces. The RANKL field was the highest at the microfracture in front of the BMU, whereas the OPG field peaked at the back of the BMU, resulting in the formation of a RANKL/OPG gradient, which strongly affected the rate of BMU progression and its size. Thus, the spatial organization of a BMU provides important constraints on the roles of RANKL and OPG as well as possibly other regulators in determining the outcome of remodeling in the BMU.

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

    NASA Astrophysics Data System (ADS)

    Olsson, J.

    2006-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Karanth, Krithi K.

    2016-01-01

    Wildlife reserves are becoming increasingly isolated from the surrounding human-dominated landscapes particularly in Asia. It is imperative to understand how species are distributed spatially and temporally in and outside reserves, and what factors influence their occurrence. This study surveyed 7500 km2 landscape surrounding five reserves in the Western Ghats to examine patterns of occurrence of five herbivores: elephant, gaur, sambar, chital, and pig. Species distributions are modeled spatio-temporally using an occupancy approach. Trained field teams conducted 3860 interview-based occupancy surveys in a 10-km buffer surrounding these five reserves in 2012. I found gaur and wild pig to be the least and most wide-ranging species, respectively. Elephant and chital exhibit seasonal differences in spatial distribution unlike the other three species. As predicted, distance to reserve, the reserve itself, and forest cover were associated with higher occupancy of all species, and higher densities of people negatively influenced occurrence of all species. Park management, species protection, and conflict mitigation efforts in this landscape need to incorporate temporal and spatial understanding of species distributions. All species are known crop raiders and conflict prone locations with resources (such as water and forage) have to be monitored and managed carefully. Wildlife reserves and adjacent areas are critical for long-term persistence and habitat use for all five herbivores and must be monitored to ensure wildlife can move freely. Such a large-scale approach to map and monitor species distributions can be adapted to other landscapes to identify and monitor critical habitats shared by people and wildlife.

  7. 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

  8. Modeling spatio-temporal variations of seismicity in the San Jacinto Fault Zone

    NASA Astrophysics Data System (ADS)

    Zöller, G.; Ben-Zion, Y.

    2012-04-01

    We investigate spatio-temporal properties of earthquake patterns in the San Jacinto fault zone (SJFZ), California, between Cajon Pass and the Superstition Hill Fault, using long records of simulated seismicity constrained by available data. The model provides an effective realization (e.g. Ben-Zion 1996; Zöller et al. 2007) of a large segmented strike-slip fault zone in 3D elastic half space, with heterogeneous distributions of static/kinetic friction and creep properties, and boundary conditions consisting of constant velocity motion around the fault. The computational section of the fault contains small brittle slip patches which fail during earthquakes and may undergo some creep deformation between events. The creep rates increase to the end points of the computational section and with depth. Two significant offsets of the SJFZ at San Jacinto Valley and Coyote Ridge are modeled by strength heterogeneities. The simulated catalogs are compared to the seismicity recorded at the SJFZ since 1932 and to recently reported results on paleoearthquakes at sites along the SJFZ at Hog Lake (HL) and Mystic Lake (ML) in the last 1500 years (e.g. Onderdonk et al., 2012; Rockwell et al., 2012). We address several questions including the following intriguing issue raised by the available paleoseismological data: are large earthquakes with signatures in ML and HL typically correlated? In particular: is a typical paleoevent in HL an incomplete rupture that is continued later in ML, and vice versa? The simulation results provide insights on the statistical significance of these and other patterns, and the ability of the SJFZ to produce large earthquakes which have not been observed in recent decades.

  9. Examining Spatio-Temporal Intensity-Frequency Variations in Extreme Monsoon Rainfall using High Resolution Data

    NASA Astrophysics Data System (ADS)

    Devak, M.; Rajendran, V.; C T, D.

    2015-12-01

    The study of extreme events has gained the attention of hydrologists in recent times. Though these events are rare, the effects are catastrophic. It is reported that the frequency of the occurrence of these events has increased in recent decades, and is attributed to the recent revelation of climate change. Numerous studies have pointed out significant changes in extremely heavy precipitation over India, using coarse resolution data. Though there are disagreements in the results and its spatial uniformity, all these studies emphasize the need of fine resolution analysis. Fine resolution analysis is necessary mainly due to the highly heterogeneous characteristics of Indian monsoon, and for the proper employment in flood hazard preparedness and water resources management. The present study aims to analyse the spatio-temporal variation and trends in the intensity and frequency of heavy precipitation during Indian monsoon using 0.25°×0.25° resolution gridded data for a period of 113 years (1901-2013). The exceedance threshold is fixed at 90th percentile of rainfall over 113 years and parameters are defined accordingly. The maximum intensity of each extreme rainfall episode of 30 year moving window has been modelled using Peak Over Threshold based Extreme Value Theory to compute return level (considered for intensity). In addition, the number of such episodes in a particular year has been termed as frequency. Non-parametric Mann-Kendall test has been carried out for both intensity and frequency, to compute the statistical trend. In addition, moving block bootstrap approach has been used to incorporate the serial correlation. The significance of the trend has been evaluated at different significance levels and finally, change in trend over last century has been examined.

  10. Reconstructing spatio-temporal patterns of debris-flow activity using dendrogeomorphological methods

    NASA Astrophysics Data System (ADS)

    Bollschweiler, Michelle; Stoffel, Markus; Ehmisch, Melanie; Monbaron, Michel

    2007-07-01

    Debris flows are a major threat in many parts of the Alps, where they repeatedly cause severe damage to infrastructure and transportation corridors or even loss of life. Nonetheless, the spatial behavior of past debris-flow activity and the analysis of areas affected during particular events have been widely neglected in reconstructions so far. It was therefore the purpose of this study to reconstruct spatio-temporal patterns of past debris flows on a forested cone in the Swiss Alps (Bruchji torrent, Blatten, Valais). The analysis of past events was based on a detailed geomorphic map (1:1000) of all forms related to debris flows as well as on tree-ring series from 401 heavily affected trees ( Larix decidua Mill. and Picea abies (L.) Karst.) growing in or next to deposits. The samples were analyzed and growth disturbances related to debris-flow activity assessed, such as tangential rows of traumatic resin ducts, the onset of reaction wood or abrupt growth suppression or release. In total, 960 growth disturbances were identified in the samples, belonging to 40 different event years between A.D. 1867 and 2005. In addition, the coupling of tree-ring data with the geomorphic map allowed reconstruction of eleven formerly active channels and spatial representation of individual events. Based on our results we believe that before 1935, debris flows preferentially used those channels located in the western part of the cone, whereas the eastern part of the cone remained widely unaffected. The spatial representation of the 40 events also allowed identification of five different spatial patterns for debris flows at the study site.

  11. 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.

  12. 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

  13. Spatio-temporal variation in chemical characteristics of PM10 over Indo Gangetic Plain of India.

    PubMed

    Sharma, S K; Mandal, T K; Srivastava, M K; Chatterjee, A; Jain, Srishti; Saxena, M; Singh, B P; Saraswati; Sharma, A; Adak, A; K Ghosh, S

    2016-09-01

    The paper presents the spatio-temporal variation of chemical compositions (organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ionic components (WSIC)) of particulate matter (PM10) over three locations (Delhi, Varanasi, and Kolkata) of Indo Gangetic Plain (IGP) of India for the year 2011. The observational sites are chosen to represent the characteristics of upper (Delhi), middle (Varanasi), and lower (Kolkata) IGP regions as converse to earlier single-station observation. Average mass concentration of PM10 was observed higher in the middle IGP (Varanasi 206.2 ± 77.4 μg m(-3)) as compared to upper IGP (Delhi 202.3 ± 74.3 μg m(-3)) and lower IGP (Kolkata 171.5 ± 38.5 μg m(-3)). Large variation in OC values from 23.57 μg m(-3) (Delhi) to 12.74 μg m(-3) (Kolkata) indicating role of formation of secondary aerosols, whereas EC have not shown much variation with maximum concentration over Delhi (10.07 μg m(-3)) and minimum over Varanasi (7.72 μg m(-3)). As expected, a strong seasonal variation was observed in the mass concentration of PM10 as well as in its chemical composition over the three locations. Principal component analysis (PCA) identifies the contribution of secondary aerosol, biomass burning, fossil fuel combustion, vehicular emission, and sea salt to PM10 mass concentration at the observational sites of IGP, India. Backward trajectory analysis indicated the influence of continental type aerosols being transported from the Bay of Bengal, Pakistan, Afghanistan, Rajasthan, Gujarat, and surrounding areas to IGP region. PMID:27316652

  14. Spatio-temporal modelling and assessment of within-species phenological variability using thermal time methods

    NASA Astrophysics Data System (ADS)

    Thompson, R.; Clark, R. M.

    2006-05-01

    Phenological observations of flowering date, budding date or senescence provide very valuable time series. They hold out the prospect for relating plant growth to environmental and climatic factors and hence for engendering a better understanding of plant physiology under natural conditions. The statistical establishment of associations between time series of phenological data and climatic factors provides a means of aiding forecasts of the biological impacts of future climatic change. However, it must be kept in mind that plant growth and behaviour vary spatially as well as temporally. Environmental, climatic and genetic diversity can give rise to spatially structured variation on a range of scales. The variations extend from large-scale geographical (clinal) trends, through medium-scale population and sub-population fluctuations, to micro-scale differentiation among neighbouring plants, where spatially close individuals are found to be genetically more alike than those some distance apart. We developed spatio-temporal phenological models that allow observations from multiple locations to be analysed simultaneously. We applied the models to the first-flowering dates of Prunus padus and Tilia cordata from localities as far apart as Norway and the Caucasus. Our growing-degree-day approach yielded a good fit to the available phenological data and yet involved only a small number of model parameters. It indicated that plants should display different sensitivities to temperature change according to their geographical location and the time of year at which they flower. For spring-flowering plants, we found strong temperature sensitivities for islands and archipelagos with oceanic climates, and low sensitivities in the interiors of continents.

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

    PubMed Central

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

    2016-01-01

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

  16. 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.

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

    PubMed Central

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

    2012-01-01

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

  18. Spatio-temporal 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 seasonal drought patterns in Europe from 1950 to 2015

    NASA Astrophysics Data System (ADS)

    Spinoni, Jonathan; Naumann, Gustavo; Vogt, Jürgen

    2016-04-01

    Drought is one of the natural disasters with severe impacts in Europe, not only in areas which frequently experience water scarcity such as the Mediterranean, but also in temperate or continental climates such as Central and Eastern Europe and even in cold regions such as Scandinavia and Iceland. In this study the spatio-temporal patterns of seasonal meteorological droughts in Europe between 1950 and 2015 are investigated using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). Since the focus is on the analysis of seasonal drought trends, indicators were calculated for 3 monthly accumulation periods. The input variables of precipitation and temperature were derived from E-OBS grids (v11-v12) at a spatial resolution of 0.25°x0.25°. Seasonal trends of drought frequency and severity were analyzed for moderate (SPI or SPEI <-1.0) and extreme (SPI or SPEI <-2.0) events during the periods 1950-2015 and 1981-2015. For the moderate events, results of the SPI analysis (precipitation driven) demonstrate a significant tendency towards less frequent and severe droughts in Northern Europe and Russia, especially in winter and spring; oppositely, an increasing trend is visible in Southern Europe, mainly in spring and summer. According to the SPEI analysis (precipitation and temperature driven) Northern Europe shows wetting patterns, while Southern and Eastern Europe show a more remarkable drying tendency, especially in summer and autumn for drought frequency and in every season for drought severity. The evolution towards drier conditions is more relevant from 1981 onwards, both in terms of frequency and severity. This is especially true for Central Europe in spring, for the Mediterranean in summer, and for Eastern Europe in autumn. Extreme events follow similar patterns, but in autumn no spatially coherent trend can be found.

  20. 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.

  1. Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey

    NASA Astrophysics Data System (ADS)

    Dubovyk, Olena; Sliuzas, Richard; Flacke, Johannes

    In less developed countries, the recent high rates of urban expansion are often associated with the emergence of informal settlements that may exaggerate social and environmental problems and impede sustainable development. An enhanced understanding of informal development may, therefore, be a key for future success in its effective management. This paper explores the possibilities offered by progress in Geo-Information Science and spatial modelling to improve understanding of informal settlement development through comprehensive spatio-temporal analyses. First, it investigates spatial and temporal patterns of the growth of the informal settlements in Sancaktepe district of Istanbul between 1990 and 2005. Second, using a logistic regression model, an analysis of the driving forces of informal development and prediction of probable locations of new informal settlements are performed. A list of spatial factors that are correlated to informal development is compiled and used to build six logistic regression models for different time steps between 1990 and 2005. Population density, slope, and proportion of informal settlements in the neighbourhood were found to be the main predictors influencing the spatial development of informal settlements during the study period. The performance of the models is evaluated and validated to identify those which best explain the informal development in the study area. As a result, three models built for 1990-1995 and 1995-2000 were selected to generate probability maps of informal settlement development, showing the likelihood for each location to be informally developed in the future. These results can be used as a basis for the evaluation of the process of informal development in other parts of Istanbul, as well as in other cities and countries. At the same time, the technique may serve as a decision-making tool for urban planners and policy makers.

  2. 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.

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

    PubMed

    Jakoby, O; Quaas, M F; Baumgärtner, 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.

  4. Spatio-Temporal Expression Pattern of Frizzled Receptors after Contusive Spinal Cord Injury in Adult Rats

    PubMed Central

    Arenas, Ernest; Rodriguez, Francisco Javier

    2012-01-01

    Background Wnt proteins are a large family of molecules that are critically involved in multiple central nervous system (CNS) developmental processes. Experimental evidences suggest a role for this family of proteins in many CNS disorders, including spinal cord injury (SCI), which is a major neuropathology owing to its high prevalence and chronic sensorimotor functional sequelae. Interestingly, most Wnt proteins and their inhibitors are expressed in the uninjured spinal cord, and their temporal expression patterns are dramatically altered after injury. However, little is known regarding the expression of their better-known receptors, the Frizzled family, after SCI. Thus, the aim of the present study was to evaluate the expression of Frizzled receptors in the damaged spinal cord. Findings Based on the evidence that Wnts are expressed in the spinal cord and are transcriptionally regulated by SCI in adulthood, we analysed the spatio-temporal mRNA and protein expression patterns of Frizzled receptors after contusive SCI using quantitative RT-PCR and single and double immunohistochemistry, respectively. Our results show that almost all of the 10 known Frizzled receptors were expressed in specific spatial patterns in the uninjured spinal cords. Moreover, the Frizzled mRNAs and proteins were expressed after SCI, although their expression patterns were altered during the temporal progression of SCI. Finally, analysis of cellular Frizzled 5 expression pattern by double immunohistochemistry showed that, in the uninjured spinal cord, this receptor was expressed in neurons, oligodendrocytes, astrocytes, microglia and NG2+ glial precursors. After injury, Frizzled 5 was not only still expressed in oligodendrocytes, astrocytes and NG2+ glial precursors but also in axons at all evaluated time points. Moreover, Frizzled 5 was expressed in reactive microglia/macrophages from 3 to 14 days post-injury. Conclusions Our data suggest the involvement of Frizzled receptors in physiological

  5. 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.

  6. 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

  7. Spatio-temporal gait analysis in children with cerebral palsy using, foot-worn inertial sensors.

    PubMed

    Brégou Bourgeois, A; Mariani, B; Aminian, K; Zambelli, P Y; Newman, C J

    2014-01-01

    A child's natural gait pattern may be affected by the gait laboratory environment. Wearable devices using body-worn sensors have been developed for gait analysis. The purpose of this study was to validate and explore the use of foot-worn inertial sensors for the measurement of selected spatio-temporal parameters, based on the 3D foot trajectory, in independently walking children with cerebral palsy (CP). We performed a case control study with 14 children with CP aged 6-15 years old and 15 age-matched controls. Accuracy and precision of the foot-worn device were measured using an optical motion capture system as the reference system. Mean accuracy ± precision for both groups was 3.4 ± 4.6 cm for stride length, 4.3 ± 4.2 cm/s for speed and 0.5 ± 2.9° for strike angle. Longer stance and shorter swing phases with an increase in double support were observed in children with CP (p=0.001). Stride length, speed and peak angular velocity during swing were decreased in paretic limbs, with significant differences in strike and lift-off angles. Children with cerebral palsy showed significantly higher inter-stride variability (measured by their coefficient of variation) for speed, stride length, swing and stance. During turning trajectories speed and stride length decreased significantly (p<0.01) for both groups, whereas stance increased significantly (p<0.01) in CP children only. Foot-worn inertial sensors allowed us to analyze gait spatiotemporal data outside a laboratory environment with good accuracy and precision and congruent results with what is known of gait variations during linear walking in children with CP.

  8. Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

    NASA Astrophysics Data System (ADS)

    Holton, L.; Deshayes, J.; Backeberg, B. C.; Loveday, B. R.; Hermes, J. C.; Reason, C. J. C.

    2016-05-01

    Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermohaline structure at the Good Hope line, a transect to the south west of the southern tip of Africa , is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution ({<} 1/10°) hindcast models agree on the temporal (2-4 cycles per year) and spatial (300-500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models ({<} 1/4°) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2°) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

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

    SciTech Connect

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

    2013-07-26

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

  10. 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 7500 km(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 buffer surrounding these five reserves in 2012. I found gaur and wild pig to be the least and most wide-ranging species, respectively. Elephant and chital exhibit seasonal differences in spatial distribution unlike the other three species. As predicted, distance to reserve, the reserve itself, and forest cover were associated with higher occupancy of all species, and higher densities of people negatively influenced occurrence of all species. Park management, species protection, and conflict mitigation efforts in this landscape need to incorporate temporal and spatial understanding of species distributions. All species are known crop raiders and conflict prone locations with resources (such as water and forage) have to be monitored and managed carefully. Wildlife reserves and adjacent areas are critical for long-term persistence and habitat use for all five herbivores and must be monitored to ensure wildlife can move freely. Such a large-scale approach to map and monitor species distributions can be adapted to other landscapes to identify and monitor critical habitats shared by people and wildlife.

  11. 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

  12. 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

  13. 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

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

    DOE PAGES

    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

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

    PubMed

    Ghosh, Erina; Kovács, Sándor J

    2012-03-01

    Global left ventricular (LV) isovolumic relaxation rate has been characterized: 1) via the time constant of isovolumic relaxation τ or 2) via the logistic time constant τ(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 μ 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 (τ) or kinematic model (μ 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 τ, μ, 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 μ 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.

  16. Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia.

    PubMed

    Suepa, Tanita; Qi, Jiaguo; Lawawirojwong, Siam; Messina, Joseph P

    2016-05-01

    The spatio-temporal characteristics of remote sensing are considered to be the primary advantage in environmental studies. With long-term and frequent satellite observations, it is possible to monitor changes in key biophysical attributes such as phenological characteristics, and relate them to climate change by examining their correlations. Although a number of remote sensing methods have been developed to quantify vegetation seasonal cycles using time-series of vegetation indices, there is limited effort to explore and monitor changes and trends of vegetation phenology in the Monsoon Southeast Asia, which is adversely affected by changes in the Asian monsoon climate. In this study, MODIS EVI and TRMM time series data, along with field survey data, were analyzed to quantify phenological patterns and trends in the Monsoon Southeast Asia during 2001-2010 period and assess their relationship with climate change in the region. The results revealed a great regional variability and inter-annual fluctuation in vegetation phenology. The phenological patterns varied spatially across the region and they were strongly correlated with climate variations and land use patterns. The overall phenological trends appeared to shift towards a later and slightly longer growing season up to 14 days from 2001 to 2010. Interestingly, the corresponding rainy season seemed to have started earlier and ended later, resulting in a slightly longer wet season extending up to 7 days, while the total amount of rainfall in the region decreased during the same time period. The phenological shifts and changes in vegetation growth appeared to be associated with climate events such as EL Niño in 2005. Furthermore, rainfall seemed to be the dominant force driving the phenological changes in naturally vegetated areas and rainfed croplands, whereas land use management was the key factor in irrigated agricultural areas.

  17. 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, 2010–January 30, 2011) displayed a centrifugal spread of a damping wave that suddenly emerged from Mirebalais. The second outbreak began at the end of May 2011, concomitant with the onset of the rainy season, and displayed a highly fragmented epidemic pattern. Environmental factors (river and rice fields: p<0.003) played a role in disease dynamics exclusively during the early phases of the epidemic. Conclusion Our findings demonstrate that the epidemic is still evolving, with a changing transmission pattern as time passes. Such an evolution could have hardly been anticipated, especially in a country struck by cholera for the first time. These results argue for the need for control measures involving intense efforts in rapid and exhaustive case tracking. PMID:23593516

  18. Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia.

    PubMed

    Suepa, Tanita; Qi, Jiaguo; Lawawirojwong, Siam; Messina, Joseph P

    2016-05-01

    The spatio-temporal characteristics of remote sensing are considered to be the primary advantage in environmental studies. With long-term and frequent satellite observations, it is possible to monitor changes in key biophysical attributes such as phenological characteristics, and relate them to climate change by examining their correlations. Although a number of remote sensing methods have been developed to quantify vegetation seasonal cycles using time-series of vegetation indices, there is limited effort to explore and monitor changes and trends of vegetation phenology in the Monsoon Southeast Asia, which is adversely affected by changes in the Asian monsoon climate. In this study, MODIS EVI and TRMM time series data, along with field survey data, were analyzed to quantify phenological patterns and trends in the Monsoon Southeast Asia during 2001-2010 period and assess their relationship with climate change in the region. The results revealed a great regional variability and inter-annual fluctuation in vegetation phenology. The phenological patterns varied spatially across the region and they were strongly correlated with climate variations and land use patterns. The overall phenological trends appeared to shift towards a later and slightly longer growing season up to 14 days from 2001 to 2010. Interestingly, the corresponding rainy season seemed to have started earlier and ended later, resulting in a slightly longer wet season extending up to 7 days, while the total amount of rainfall in the region decreased during the same time period. The phenological shifts and changes in vegetation growth appeared to be associated with climate events such as EL Niño in 2005. Furthermore, rainfall seemed to be the dominant force driving the phenological changes in naturally vegetated areas and rainfed croplands, whereas land use management was the key factor in irrigated agricultural areas. PMID:26922262

  19. Swim-training changes the spatio-temporal dynamics of skeletogenesis in zebrafish larvae (Danio rerio).

    PubMed

    Fiaz, Ansa W; Léon-Kloosterziel, Karen M; Gort, Gerrit; Schulte-Merker, Stefan; van Leeuwen, Johan L; Kranenbarg, Sander

    2012-01-01

    Fish larvae experience many environmental challenges during development such as variation in water velocity, food availability and predation. The rapid development of structures involved in feeding, respiration and swimming increases the chance of survival. It has been hypothesized that mechanical loading induced by muscle forces plays a role in prioritizing the development of these structures. Mechanical loading by muscle forces has been shown to affect larval and embryonic bone development in vertebrates, but these investigations were limited to the appendicular skeleton. To explore the role of mechanical load during chondrogenesis and osteogenesis of the cranial, axial and appendicular skeleton, we subjected zebrafish larvae to swim-training, which increases physical exercise levels and presumably also mechanical loads, from 5 until 14 days post fertilization. Here we show that an increased swimming activity accelerated growth, chondrogenesis and osteogenesis during larval development in zebrafish. Interestingly, swim-training accelerated both perichondral and intramembranous ossification. Furthermore, swim-training prioritized the formation of cartilage and bone structures in the head and tail region as well as the formation of elements in the anal and dorsal fins. This suggests that an increased swimming activity prioritized the development of structures which play an important role in swimming and thereby increasing the chance of survival in an environment where water velocity increases. Our study is the first to show that already during early zebrafish larval development, skeletal tissue in the cranial, axial and appendicular skeleton is competent to respond to swim-training due to increased water velocities. It demonstrates that changes in water flow conditions can result into significant spatio-temporal changes in skeletogenesis.

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

    PubMed

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

    2016-07-01

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

  1. Spatio-temporal recharge patterns in a semi-arid alluvial basin with irrigated crops

    NASA Astrophysics Data System (ADS)

    Ruud, N. C.; Harter, T.; Naugle, A. W.

    2001-12-01

    Recharge in semi-arid regions with irrigated crops is predominantly driven by irrigation technology and cropping patterns, but also by the seasonal distribution of rainfall and the availability of irrigation water. A significant amount of basin recharge occurs from ephemeral streams and unlined irrigation canals. A spatially distributed, GIS-based hydrologic model of water application and water use at the land-atmosphere interface was developed to estimate transient recharge to the deep vadose zone and into the unconfined alluvial aquifer. The spatial basis for the hydrologic model are individual landuse units (diffuse recharge) and a network of streams and canals with water seepage (lineal recharge). The land-atmosphere interface and unsaturated zone model component (LAIUZ) is coupled to a surface water supply model component (SWSM) that provides surface water deliveries by district or sub-district, depending on available information. Using LAIUZ and SWSM, we investigate the regional behavior and spatio-temporal variability of deep vadose zone recharge in the 3,800 square kilometer Tule groundwater basin of the San Joaquin Valley, California. Surface water management in the topographically flat basin is divided between two dozen irrigation and water districts. All surface water is imported or is natural discharge into the basin. Groundwater extractions are managed by landowners on a field-by-field basis. Monthly varying recharge and groundwater pumping rates are computed for the hydrologic years 1970 through 2000. The average size of the GIS landuse units is 0.4 sq. kilometers. The GIS coverage distinguishes over 60 landuse types. Applied and consumptive water use are computed based on actual evapotranspiration and known irrigation or water use efficiencies for each landuse unit. Seepage from streams is computed by mass balance. The resulting model estimates of groundwater recharge and pumping are in good agreement with measured groundwater level changes for the

  2. 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

  3. Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran

    PubMed Central

    Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

    2016-01-01

    HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug

  4. Spatio-Temporal Patterns of Demyelination and Remyelination in the Cuprizone Mouse Model

    PubMed Central

    Tagge, Ian; O’Connor, Audrey; Chaudhary, Priya; Pollaro, Jim; Berlow, Yosef; Chalupsky, Megan; Bourdette, Dennis; Woltjer, Randy; Johnson, Mac; Rooney, William

    2016-01-01

    Cuprizone administration in mice provides a reproducible model of demyelination and spontaneous remyelination, and has been useful in understanding important aspects of human disease, including multiple sclerosis. In this study, we apply high spatial resolution quantitative MRI techniques to establish the spatio-temporal patterns of acute demyelination in C57BL/6 mice after 6 weeks of cuprizone administration, and subsequent remyelination after 6 weeks of post-cuprizone recovery. MRI measurements were complemented with Black Gold II stain for myelin and immunohistochemical stains for associated tissue changes. Gene expression was evaluated using the Allen Gene Expression Atlas. Twenty-five C57BL/6 male mice were split into control and cuprizone groups; MRI data were obtained at baseline, after 6 weeks of cuprizone, and 6 weeks post-cuprizone. High-resolution (100μm isotropic) whole-brain coverage magnetization transfer ratio (MTR) parametric maps demonstrated concurrent caudal-to-rostral and medial-to-lateral gradients of MTR decrease within corpus callosum (CC) that correlated well with demyelination assessed histologically. Our results show that demyelination was not limited to the midsagittal line of the corpus callosum, and also that opposing gradients of demyelination occur in the lateral and medial CC. T2-weighted MRI gray/white matter contrast was strong at baseline, weak after 6 weeks of cuprizone treatment, and returned to a limited extent after recovery. MTR decreases during demyelination were observed throughout the brain, most clearly in callosal white matter. Myelin damage and repair appear to be influenced by proximity to oligodendrocyte progenitor cell populations and exhibit an inverse correlation with myelin basic protein gene expression. These findings suggest that susceptibility to injury and ability to repair vary across the brain, and whole-brain analysis is necessary to accurately characterize this model. Whole-brain parametric mapping across

  5. Spatio-temporal variation of water flow and sediment discharge in the Mahanadi River, India

    NASA Astrophysics Data System (ADS)

    Bastia, Fakira; Equeenuddin, Sk. Md.

    2016-09-01

    The transport of sediments by rivers to the oceans represents an important link between the terrestrial and marine ecosystem. Therefore, this work aims to study spatio-temporal variation of the sediment discharge and erosion rate in the Mahanadi river, one of the biggest rivers in India, over past three decades vis-à-vis their controlling factors. To understand the sediment load variation, the trend analysis in the time series data of rainfall, water and sediment discharge of the Mahanadi river were also attempted. The non-parametric Mann-Kendall and Sen's methods were used to determine whether there was a positive or negative trend in the time series data with their statistical significance. The occurrence of abrupt changes was detected using Pettitt test. The trend test result represents that sediment load delivered from the Mahanadi river to the global ocean has decreased sharply at the rate of 0.515 × 106 tons/year between 1980 and 2010. Water discharge and rainfall in the basin showed no significant decreasing trend except at only one tributary. The decline in sediment discharge from the basin to the Bay of Bengal is mainly due to the increase in the number of dams, which has recorded the increase from 70 to 253 during the period of 1980 to 2010. Over the past 30 years the Mahanadi river has discharged about 49.0 ± 20.5 km3 of water and 17.4 ± 12.7 × 106 tons of sediment annually to the Bay of Bengal whereas the mean erosional rate is 265 ± 125 tons/km2/year over the period of 30 years in the basin. Based on the current data (2000-2001 to 2009-2010), sediment flux and water discharge to the ocean are 12 ± 5 × 106 tons/year and 49 ± 16 km3/year respectively; and ranking Mahanadi river second in terms of water discharge and sediment flux to the ocean among the peninsular rivers in India.

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  10. How geomorphology and groundwater level affect the spatio-temporal variability of riverine cold water patches?

    NASA Astrophysics Data System (ADS)

    Wawrzyniak, Vincent; Piégay, Hervé; Allemand, Pascal; Vaudor, Lise; Goma, Régis; Grandjean, Philippe

    2016-04-01

    . Nonetheless, amongst all patch types, some are quite stable over time, while others are transient. These results can be used to target areas with high densities of stable and spatially extensive cold water patches that are considered ecological refuges, in the context of pronounced low flow and a rise in water temperature. Key words: River temperature; Thermal Infrared (TIR) remote sensing; groundwater; fluvial geomorphic features; side channels; spatio-temporal variability; lower Ain River (France).

  11. Spatio-temporal dynamics in the flood exposure due to land use changes

    NASA Astrophysics Data System (ADS)

    Cammerer, H.; Thieken, A.

    2012-04-01

    Flood risk is expected to intensify in the future in many regions of the world. Consequently, the resulting flood damage is very likely to increase further on. Comprehensive flood risk analyses which are not only reliable for the contemporary state require therefore the consideration of the main drivers that influence flood risk. Human-induced changes in land use as well as climate change impacts on hydrological processes turned out to play a key role in future-orientated flood risk assessments. Even if there is strong evidence that global climate change will amplify flood risk especially in mountainous areas like the European Alps the accumulation of people and their assets in flood plains are seen as main causes of increasing flood risk. Therefore the analysis of spatio-temporal dynamics in the flood exposure due to land use changes is a crucial part for long-term and more robust flood risk analyses. Within the frame of a study in the region of Reutte in Tyrol (Austria) flood risk time series for the next decades are developed by estimating the hazard potential as well as the flood impact, i.e. the flood losses. For the latter, future flood exposed residential and industrial areas are assessed by applying a spatially explicit land use change model and various inundation scenarios. The land use simulations for the alpine study area were calculated by means of the CLUE-S model, respectively the newer Version Dyna-CLUE. This model simulates the spatial pattern of land-use in reaction to pre-defined changes of the future land use demand, suitable locations which are identified by means of logistic regression and user-specified decision rules as well as spatial policies (e.g. area zoning plans and danger zoning plans). For now, inundation areas were derived from the past flood event in August 2005 and the HORA project where flood extents for different recurrence intervals were simulated. The intersection of these flood plains with various land use scenarios allows

  12. Spatio-temporal Characteristics of Actual Evapotranspiration Trends in sub-Saharan Africa

    NASA Astrophysics Data System (ADS)

    Marshall, M. T.; Funk, C. C.; Michaelsen, J.

    2010-12-01

    Actual evapotranspiration (AET) is an important moisture flux linking the Earth’s surface to the atmospheric hydrologic cycle. Global warming is expected to intensify this cycle, leading to moisture deficits over the sub-tropics, which will influence climate at higher latitudes. The spatio-temporal characterization of tropical AET is critical to understanding regional and global climate. To date, many studies on the temporal characteristics of AET across sub-Saharan Africa have employed vegetation-based indices derived from satellite imagery. Although these studies implicitly reflect trends in AET, they quantify the magnitude of change. In this study, we used the latest developments in remote sensing and land-surface modeling to characterize the magnitude and timing of AET in sub-Saharan Africa. We considered several models were evaluated from 1981-2000 using monthly discharge and precipitation from ten sub-basins representative of hydrology in sub-Saharan Africa. Discharge data was provided by the Global Runoff Data Centre, while precipitation data was comprised of ECMWF, NCAR, NOAA/GDAS, and CMAP reanalysis fields synthesized in the Global Land Data Assimilation System (GLDAS). The AET models included the Community Land Model, Variable Infiltration Capacity (VIC) model, Noah, and two hybrids that we developed driven by a dynamic vegetation component defined in Fisher et al. 2008. The dynamic canopy components in our hybrid models were driven by the LTDR AVHRR daily corrected reflectance data over the evaluation period. The evaluation revealed that VIC was superior to the other models in capturing the magnitude and variability of runoff in the sub-basins. A trend analysis was then performed on VIC AET from 1979-2009 using standard parametric and non-parametric techniques. Linear and median trend analysis was performed on seasonal and annual AET totals to measure the magnitude of change. The analysis revealed several alarming patterns, including large and

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

    PubMed

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

    2016-07-01

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

  14. Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

    PubMed

    Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

    2016-01-01

    HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug

  15. A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)

    NASA Astrophysics Data System (ADS)

    Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng

    2016-05-01

    Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a

  16. Spatio-temporal variability of vertical gradients of major meteorological observations around the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Guo, X.; Wang, L.; Tian, L.

    2015-12-01

    The near-surface air temperature lapse rate (TLR), wind speed gradient (WSG), and precipitation gradient (PG) provide crucial parameters used in models of mountain climate and hydrology. The complex mountain terrain and vast area of the Tibetan Plateau (TP) make such factors particularly important. With daily data from 161 meteorological stations over the past 43 years (1970-2012), we analyse the spatio-temporal variations of TLRs, WSGs, and PGs over and around TP, derived using linear regression methods and dividing the study area into zones based on spatial variations. Results of this study include: (1) The observed TLR varies from -0.46 to -0.73 ∘C (100 m) -1, with averaged TLRs of -0.60,-0.62, and -0.59 ∘C (100 m) -1 for Tmax, Tmin,and Tmean , respectively. The averaged TLR is slightly less than the global mean of -0.65 ∘C (100 m) -1 . The spatial variability of TLR relates to climate conditions, wherein the TLR increases in dry conditions and in cold months (October-April), while it lessens in humid regions and during warm months (May-September). (2) The estimated annual WSG ranges from 0.07 to 0.17m s -1 (100 m) -1. Monthly WSGs show a marked seasonal shift, in which higher WSGs can be explained by the high intensity of prevailing wind. (3) Positive summer PGs vary from 12.08 in the central TP to 26.14 mm (100 m) -1 in northeastern Qinghai and the southern TP, but a reverse gradient prevails in Yunnan and parts of Sichuan Province. (4) The regional warming over TP is more evident in winter, and Tmin demonstrated the most prominent warming compared with Tmax and Tmean. Environments at high elevations experience more rapid changes in temperatures (Tmax, Tmin,and Tmean) than those at low elevations, which is especially true in winter and for Tmin. Furthermore, inter-annual variation of TLRs is linked to elevation-dependent warming.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  18. Spatio-Temporal Patterns of Demyelination and Remyelination in the Cuprizone Mouse Model.

    PubMed

    Tagge, Ian; O'Connor, Audrey; Chaudhary, Priya; Pollaro, Jim; Berlow, Yosef; Chalupsky, Megan; Bourdette, Dennis; Woltjer, Randy; Johnson, Mac; Rooney, William

    2016-01-01

    Cuprizone administration in mice provides a reproducible model of demyelination and spontaneous remyelination, and has been useful in understanding important aspects of human disease, including multiple sclerosis. In this study, we apply high spatial resolution quantitative MRI techniques to establish the spatio-temporal patterns of acute demyelination in C57BL/6 mice after 6 weeks of cuprizone administration, and subsequent remyelination after 6 weeks of post-cuprizone recovery. MRI measurements were complemented with Black Gold II stain for myelin and immunohistochemical stains for associated tissue changes. Gene expression was evaluated using the Allen Gene Expression Atlas. Twenty-five C57BL/6 male mice were split into control and cuprizone groups; MRI data were obtained at baseline, after 6 weeks of cuprizone, and 6 weeks post-cuprizone. High-resolution (100 μm isotropic) whole-brain coverage magnetization transfer ratio (MTR) parametric maps demonstrated concurrent caudal-to-rostral and medial-to-lateral gradients of MTR decrease within corpus callosum (CC) that correlated well with demyelination assessed histologically. Our results show that demyelination was not limited to the midsagittal line of the corpus callosum, and also that opposing gradients of demyelination occur in the lateral and medial CC. T2-weighted MRI gray/white matter contrast was strong at baseline, weak after 6 weeks of cuprizone treatment, and returned to a limited extent after recovery. MTR decreases during demyelination were observed throughout the brain, most clearly in callosal white matter. Myelin damage and repair appear to be influenced by proximity to oligodendrocyte progenitor cell populations and exhibit an inverse correlation with myelin basic protein gene expression. These findings suggest that susceptibility to injury and ability to repair vary across the brain, and whole-brain analysis is necessary to accurately characterize this model. Whole-brain parametric mapping

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

    NASA Astrophysics Data System (ADS)

    Schwarz, Massimiliano; Cohen, Denis

    2016-04-01

    Rainfall is one of the major triggering factor of shallow landslide around the world. The increase of soil moisture in the soil influences the stability of a slope through the increase of soil bulk density, the reduction of soil apparent cohesion (due to suction stress), and the increase in pore water pressure.The spatio-temporal transformations of such properties of soil are know to be heterogeneous and under constant change. For instance, there may be a condition where, in cracked clay-soil, water, during a rain event, produces a rapid increase of pore water pressure along preferential flow-paths (crack or roots), while soil moisture and suction within the soil matrix change minimally. An another site in a sandy soil, the situation might be very different where the increase of soil moisture and pore water pressure, and the decrease of soil suction take place more or less simultaneously across the entire soil profile. In both of these cases topography plays a major role in determining the accumulation of water along the slope through different subsurface flows intensities and directions. In many documented cases in the Alps, shallow landslides may also be triggered by the punctual exfiltration of water from bedrock or weathered geological strata. The hydro-geological characteristics of the catchment control this mechanism. These different situations aim to give an idea of the large spectrum of hydrological triggering conditions of shallow landslides. The heterogeneities of these hydrological conditions represent a difficult issue in modeling shallow landslide triggering mechanisms. In the simplest models, hydrology is assumed to influence changes in pore water pressure only, mostly using one dimensional vertical infiltration models. More advanced models consider changes in apparent cohesion due to changes in soil moisture or include more complex hydrological models to simulate water flow and distribution during a rainfall event. However, most models at the

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  1. Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt.

    PubMed

    Kühling, Insa; Broll, Gabriele; Trautz, Dieter

    2016-02-15

    The Western Siberian grain belt covers 1millionkm² in Asiatic Russia and is of global importance for agriculture. Massive land-use changes took place in that region after the dissolution of the Soviet Union and the collapse of the state farm system. Decreasing land-use intensity (LUI) in post-Soviet Western Siberia was observed on grassland due to declining livestock whilst on cropland trends of land abandonment reversed in the early 2000s. Recultivation of abandoned cropland as well as increasing fertilizer inputs and narrowing crop rotations led to increasing LUI on cropland during the last two decades. Beyond that general trend, no information is available about spatial distribution and magnitude but a crucial precondition for the development of strategies for sustainable land management. To quantify changes and patterns in LUI, we developed an intensity index that reflects the impacts of land-based agricultural production. Based on subnational yearly statistical data, we calculated two separate input-orientated indices for cropland and grassland, respectively. The indices were applied on two spatial scale: at seven provinces covering the Western Siberian grain belt (Altay Kray, Chelyabinsk, Kurgan, Novosibirsk, Omsk, Sverdlovsk and Tyumen) and at all districts of the central province Tyumen. The spatio-temporal analysis clearly showed opposite trends for the two land-use types: decreasing intensity on grassland (-0.015 LUI units per year) and intensification on cropland (+0.014 LUI units per year). Furthermore, a spatial concentration towards intensity centres occurred during transition from a planned to a market economy. A principal component analysis enabled the individual calculations of both land-use types to be combined and revealed a strong link between biophysical conditions and LUI. The findings clearly showed the need for having a different strategy for future sustainable land management for grassland (predominantly used by livestock of households

  2. Fusion of spatio-temporal UAV and proximal sensing data for an agricultural decision support system

    NASA Astrophysics Data System (ADS)

    Katsigiannis, P.; Galanis, G.; Dimitrakos, A.; Tsakiridis, N.; Kalopesas, C.; Alexandridis, T.; Chouzouri, A.; Patakas, A.; Zalidis, G.

    2016-08-01

    Over the last few years, multispectral and thermal remote sensing imagery from unmanned aerial vehicles (UAVs) has found application in agriculture and has been regarded as a means of field data collection and crop condition monitoring source. The integration of information derived from the analysis of these remotely sensed data into agricultural management applications facilitates and aids the stakeholder's decision making. Whereas agricultural decision support systems (DSS) have long been utilised in farming applications, there are still critical gaps to be addressed; as the current approach often neglects the plant's level information and lacks the robustness to account for the spatial and temporal variability of environmental parameters within agricultural systems. In this paper, we demonstrate the use of a custom built autonomous UAV platform in providing critical information for an agricultural DSS. This hexacopter UAV bears two cameras which can be triggered simultaneously and can capture both the visible, near-infrared (VNIR) and the thermal infrared (TIR) wavelengths. The platform was employed for the rapid extraction of the normalized difference vegetation index (NDVI) and the crop water stress index (CWSI) of three different plantations, namely a kiwi, a pomegranate, and a vine field. The simultaneous recording of these two complementary indices and the creation of maps was advantageous for the accurate assessment of the plantation's status. Fusion of UAV and soil scanner system products pinpointed the necessity for adjustment of the irrigation management applied. It is concluded that timely CWSI and NDVI measures retrieved for different crop growing stages can provide additional information and can serve as a tool to support the existing irrigation DSS that had so far been exclusively based on telemetry data from soil and agrometeorological sensors. Additionally, the use of the multi-sensor UAV was found to be beneficial in collecting timely, spatio-temporal

  3. Spatio-temporal Patterns and Landscape-Associated Risk of Buruli Ulcer in Akonolinga, Cameroon

    PubMed Central

    Landier, Jordi; Gaudart, Jean; Carolan, Kevin; Lo Seen, Danny; Guégan, Jean-François; Eyangoh, Sara; Fontanet, Arnaud; Texier, Gaëtan

    2014-01-01

    Background Buruli ulcer (BU) is an extensively damaging skin infection caused by Mycobacterium ulcerans, whose transmission mode is still unknown. The focal distribution of BU and the absence of interpersonal transmission suggest a major role of environmental factors, which remain unidentified. This study provides the first description of the spatio-temporal variations of BU in an endemic African region, in Akonolinga, Cameroon. We quantify landscape-associated risk of BU, and reveal local patterns of endemicity. Methodology/Principal Findings From January 2002 to May 2012, 787 new BU cases were recorded in 154 villages of the district of Akonolinga. Incidence per village ranged from 0 (n = 59 villages) to 10.4 cases/1000 person.years (py); median incidence was 0.4 cases/1,000py. Villages neighbouring the Nyong River flood plain near Akonolinga town were identified as the highest risk zone using the SPODT algorithm. We found a decreasing risk with increasing distance to the Nyong and identified 4 time phases with changes in spatial distribution. We classified the villages into 8 groups according to landscape characteristics using principal component analysis and hierarchical clustering.