It is proposed to extract multi-location image features at maxima points of a spatio-temporal attention operator, which indicates locations with high intensity contrast, region homogeneity, shape saliency and temporal change. The scale-adaptive estimation of local change (motion) and its aggregation with the region shape saliency contribute to robust detection of moving objects. Experiments on the accuracy of interest-point detection have proved the operator consistency and its high potential for object detection in image sequences.
Palenichka, Roman M.; Zaremba, Marek B.
The perception of spatio-temporal pattern is a fundamental part of visual cognition. In order to understand more about the principles behind these biological processes, we are analyzing and modeling the presentation of spatio-temporal structures on different levels of abstraction. For the low- level processing of motion information we have argued for the existence of a spatio-temporal memory in early vision. The basic properties of this structure are reflected in a neural network model which is currently developed. Here we discuss major architectural features of this network which is base don Kohonens SOMs. In order to enable the representation, processing and prediction of spatio-temporal pattern on different levels of granularity and abstraction the SOMs are organized in a hierarchical manner. The model has the advantage of a 'self-teaching' learning algorithm and stored temporal information try local feedback in each computational layer. The constraints for the neural modeling and data set for training the neural network are obtained by psychophysical experiments where human subjects' abilities for dealing with spatio-temporal information is investigated.
Schill, Kerstin; Baier, Volker; Roehrbein, Florian; Brauer, Wilfried
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.
Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon (EAM) system are reviewed in this paper. The understanding of the EAM system has improved in many aspects: the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon (EASM) system and the East Asian winter monsoon (EAWM) system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific (EAP) teleconnection over East Asia and the North Pacific, the "Silk Road" teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.
Huang, Ronghui; Chen, Jilong; Wang, Lin; Lin, Zhongda
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, ?18O, ?2H, 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.
Arora, B.; Mohanty, B. P.; McGuire, J. T.
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. PMID:21440069
Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos
This paper proposes a method for the detection and extraction of poorly contrasted linear structures in textured flat areas. The method is a spatio-temporal processing based on an irregular Markov random field (MRF) modeling of the image plane. It combines in an appropriate way a pure intra-frame processing based on an irregular graph-based MRF modeling and a time recursive nonlinear
Dominique BARBA; Philippe DELAGNES
For spatio-temporal processing of ultrashort-pulse laser beams, design constraints arise from dispersion and diffraction. In sub-10-fs region, temporal and spatial coordinates of propagating wavepackets get non-separable. To enable controlled shaping and detection with spatial resolution, specific advantages of thin-film microoptical arrays are exploited. Transmitting and reflecting components of extremely small conical angles were used to generate multiple nondiffracting beams and self imaging patterns. With novel-type metal-dielectric microaxicons, low-dispersion reflective devices were realized. Beam propagation was simulated with Rayleigh-Sommerfeld diffraction theory. For time-space conversion, matrix processors consisting of thin-film microaxicons were tested. Transversally resolving linear and nonlinear autocorrelation techniques were applied to characterize the space-time-structure of localized few-cycle wavepackets shaped from Ti:sapphire laser beams at pulse durations down to 8 fs. Bessel-like X-waves were shaped and their propagation was studied. In combination with autocorrelation, wavefront analysis of ultrashort-pulse lasers with Bessel-Shack-Hartmann sensors operated in reflection setup was demonstrated.
Grunwald, Rüdiger; Kebbel, Volker; Neumann, Uwe; Griebner, Uwe; Piché, Michel
Capturing the functionality of active dendritic processing into abstract mathematical models will help us to understand the role of complex biophysical neurons in neuronal computation and to build future useful neuromorphic analog Very Large Scale Integrated (aVLSI) neuronal devices. Previous work based on an aVLSI multi-compartmental neuron model demonstrates that the compartmental response in the presence of either of two widely studied classes of active mechanisms, is a nonlinear sigmoidal function of the degree of either input temporal synchrony OR input clustering level. Using the same silicon model, this work expounds the interaction between both active mechanisms in a compartment receiving input patterns of varying temporal AND spatial clustering structure and demonstrates that this compartmental response can be captured by a combined sigmoid and radial-basis function over both input dimensions. This paper further shows that the response to input spatio-temporal patterns in a one-dimensional multi-compartmental dendrite, can be described by a radial-basis like function of the degree of temporal synchrony between the inter-compartmental inputs. PMID:23853330
Wang, Yingxue; Liu, Shih-Chii
This paper is devoted to imaging defects in liquid and solid ultrasonic waveguides. A new ultrasonic imaging technique, based on the spatio-temporal Green functions computation and cross-correlation, is presented. This technique extends the concept of matched field processing (MFP) used in ocean acoustics. Results of experiments conducted in water and in a solid Duralumin bar show that a strong improvement of the spatial resolution is observed with this MFP. PMID:11370351
Ing, R K; Fink, M
Understanding the changes in streamflow and associated driving forces is crucial for formulating a sustainable regional water\\u000a resources management strategy in the environmentally fragile karst area of the southwest China. This study investigates the\\u000a spatio-temporal changes in streamflow of the Guizhou region and their linkage with meteorological influences using the Mann–Kendall\\u000a trend analysis, singular-spectrum analysis (SSA), Lepage test, and flow
Tao Yang; Xi Chen; Chong-Yu Xu; Zhi-Cai Zhang
A typical analog image-processing neural network consists of a 2D array of simple processing elements. When it is implemented with CMOS LSI, two dynamics issues naturally arise: (1) parasitic capacitors of MOS transistors induce temporal dynamics. Since a processed image is given as the stable equilibrium point of temporal dynamics, a temporally unstable chip is unusable; and (2) because of
Haruo Kobayashi; Takashi Matsumoto; Jun Sanekata
Different levels of organization distinguished by characteristics spatial dimensions, Ec, and relaxation times, Tr, of biological processes ranging from electron transport in energy transduction to growth of microbial and plant cells, are shown to be related through a relation that may be interpreted as allometric and characterized by two different slopes. Processes, at levels of organization occurring in spatial dimensions of micrometers and relaxing in the order of minutes, delimit a 'transition point' between the two curves, that we interpret as a limit for the emergence of macroscopic coherence. The characteristic spatial dimension, Ec, and the relaxation time, Tr, contain dynamical information about the processes occurring at a given level of organization. When a steady state of a biological process at a certain level of organization becomes unstable, the system undergoes a transition to another level of organization. To exemplify the appearance of macroscopic order at levels of organization further from the 'transition point' we present in this report various experimental systems involving many levels of organization allometrically related that exhibit different kinds of self-organized behavior, i.e. bi-stability, oscillations, changes in (a)symmetry. PMID:8459799
Aon, M A; Cortassa, S
Detection is an essential aspect in analytical approaches. In liquid phase separations, many attempts have been focused on the capability to detect a partial or an entire column. However, detection in both spatial and temporal resolutions has not gained much attention yet. Here we present the concept of spatio-temporally resolved detection (STRD) and a proof-of-the-concept microchip electrophoresis (MCE)-STRD system. The MCE-STRD system was mainly composed of a microchip and an STRD unit, which were designed completely based on the requirements for spatial and temporal resolutions. In the STRD unit, a linear light beam expanded from a UV LED light source was employed to illuminate the whole separation channel of the microchip while a linear CCD sensor that has an identical effective length as the separation channel and more pixels per unit length was used to detect the absorbance signals through the separation channel. As each pixel of the CCD sensor can detect a corresponding channel space in real time, the CCD provides both spatial and temporal resolutions. A significant advantage of STRD over conventional detection schemes is its capability for monitoring the dynamic processes of molecular events occurring in the separation channel. This was demonstrated through the monitoring of the dynamic processes of protein-DNA and protein-drug interactions in chip isoelectric focusing (chip IEF). The MCE-STRD system provided not only whole pictures of the entire dynamic processes at-a-glance but also quantitative kinetic information (dissociation rate constants) of the dynamic processes. With further development, we anticipate that STRD could be a promising tool for the characterization of biomolecular interactions and the observation of migration behaviours of analytes. PMID:22785350
Bi, Xiaodong; Yu, Jianzhao; Li, Li; Jiang, Hancheng; Huang, Fengliang; Liu, Zhen
Different levels of organization distinguished by characteristics spatial dimensions, Ec, and relaxation times, Tr, of biological processes ranging from electron transport in energy transduction to growth of microbial and plant cells, are shown to be related through a relation that may be interpreted as allometric and characterized by two different slopes. Processes, at levels of organization occurring in spatial dimensions
Miguel Antonio Aon; Sonia Cortassa
Grain storage and processing facilities consist of a landscape of indoor and outdoor habitats that can potentially support stored-product insect pests, and understanding patterns of species diversity and spatial distribution in the landscape surrounding structures can provide insight into how the ou...
The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework (NEF) offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify—arbitrarily—neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times.
Tapson, Jonathan C.; Cohen, Greg K.; Afshar, Saeed; Stiefel, Klaus M.; Buskila, Yossi; Wang, Runchun Mark; Hamilton, Tara J.; van Schaik, Andre
The last decade has seen the rise of the research fields of DNA analysis and population or ecological genetics.They have the\\u000a potential to allow the revision of landscape ecological concepts such as habitat connectivity or fragmentation. In this chapter,\\u000a we first ask how population genetics can support and extend landscape ecological research from analysing patterns to understanding\\u000a processes, and we
Rolf Holderegger; Felix Gugerli; Christoph Scheidegger; Pierre Taberlet
The morphology of soil covered hillslopes tends to a characteristic convex-concave shape. In hilly landscapes, where erosion rates do not exceed the weathering rates of bedrock material, the form of hillslopes is convex near the hilltop and becomes increasingly planar further downslope with the steepest descent in the middle of the slope. This typical shape is the result of long term erosion and sediment redistribution processes driven by a topographic gradient and climatic forcing. Erosion rates depend on slope, soil properties, vegetation cover and rainfall/runoff rates. The morphology of hillslopes is thus the result of a trade-off between all these parameters controlling the relation of detachment, transport and deposition rates of sediments as well as feedback mechanisms on the driving gradient. Sediment flux increases with increasing slope but higher sediment transport rates deplete the driving gradient and thus reduce sediment export. We hypothesize that sediment export is maximized under the condition of maintaining the driving gradient and that this trade-off implies a typical shape and steepness of slopes. We used the process based model CATFLOW-SED to verify this hypothesis and to better understand the spatio-temporal organisation of sediment dynamics at the hillslope scale. CATFLOW-SED is a continuous, dynamic, spatially distributed model. Soil water dynamics is described by the Richards equation, including an effective approach for preferential flow that is numerically solved by an implicit mass conservative Picard iteration. Evaporation and transpiration is simulated, using an advanced approach based on the Penman-Monteith equation. The model simulates overland flow as sheet flow using the diffusion wave equation. Soil detachment is related to the attacking forces of rainfall and overland flow. The detachment rate further depends on the model parameter erosion resistance, which is characterized by soil properties, land use and management practice. Transport capacity and deposition are quantified using the equation of Engelund and Hansen (1967) and the sinking velocity of grain size fractions. For the model runs, we used data of the Weiherbach catchment located in a hilly loess region in Southwest Germany.
Scherer, U.; Zehe, E.; Ehret, U.; Kleidon, A.
Spectral multi-scaling postulates a power-law type of scaling of spectral distribution functions of stationary processes of spatial averages, over nested and geometrically similar sub-regions of the spatial parameter space of a given spatio-temporal random field. Presently a new framework is formulated for down-scaling processes of spatial averages, following naturally from the postulate of spectral multi-scaling, and key ingredients required for its implementation are described. Moreover, results from an extensive diagnostic study are presented, seeking statistical evidence supportive of spectral multi-scaling. Such evidence emerges from two sources of data. One is a 13 year long historical record of radar observations of rainfall in southeastern UK (Chenies radar), with high spatial (2 km) and temporal (5 min) resolution. The other is an ensemble of rain rate fields simulated by a spatio-temporal random pulse model fitted to the historical data. The results are consistent between historical and simulated rainfall data, indicating frequency-dependent scaling relationships interpreted as evidence of spectral multi-scaling across a range of spatial scales.
Recently, a polarimetric data reduction technique has been developed that in the presence of a time varying signals and noise free measurement process can achieve an error free reconstruction provided that the signal was band limited. Error free reconstruction for such a signal is not possible using conventional data reduction methods. The new approach provides insight for processing arbitrary modulation schemes in space, time, and wavelength. Theory predicts that a polarimeter that employs a spatio-temporal modulation scheme may be able to use the high temporal resolution of a spatially modulated device combined with the high spatial resolution of a temporally modulated system to attain greater combined resolution capabilities than either modulation on scheme can produce alone. A polarimeter that contains both spatial and temporal modulation can be constructed (for example) by placing a rotating retarder in front of a micropolarizer array (microgrid). This study develops theory and analysis for the rotating retarder microgrid polarimeter to show how the available bandwidth for each channel is affected by additional dimensions of modulation and demonstrates a working polarimeter with a simulation of Stokes parameters that are band limited in both space and time with a noisy measurement process.
Lacasse, Charles F.; Ririe, Tyson; Chipman, Russell A.; Tyo, J. Scott
Spatio-temporal databases store information about the positions of individual objects over time. However, in many applications such as traffic supervision or mobile communication systems, only summarized data, like the number of cars in an area for a specific period, or phone-calls serviced by a cell each day, is required. Although this information can be obtained from operational databases, its computation
Yufei Tao; Dimitris Papadias
In dynamic spatio-temporal environments where objects may continuously move in space, maintaining consistent information about the location of objects and processing motion-specic queries is a chal- lenging problem. In this paper, we focus on indexing and query process- ing techniques for mobile objects. Specically, we develop a classication of dierent types of selection queries that arise in mobile environments and
Kriengkrai Porkaew; Iosif Lazaridis; Sharad Mehrotra
Poyang Lake is the largest freshwater lake in China, and plays a major role in flood mitigation, restoration and conservation of the ecological environment in the middle Yangtze River basin. Sediment load and streamflow variations in Poyang Lake basin are important for the scouring and deposition changes of this lake. However, these hydrological processes are heavily influenced by human activities,
Qiang Zhang; Peng Sun; Tao Jiang; Xinjun Tu; Xiaohong Chen
Using example applications from our recent research we illustrate the development of an integrated approach to modelling biological processes based on stochastic modelling techniques. The goal of this programme of research is to provide a suite of mathematical and statistical methods to enable models to play a more central role in the development of scientific understanding of complex biological systems.
Glenn Marion; David M. Walker; Alex Cook; David L. Swain; Mike R. Hutchings
Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.
Blume, T.; Zehe, E.; Bronstert, A.
The paper is an investigation into different notions of spat ial, temporal, and spatio-temporal continuity. A formal framework is proposed in which a number of different notions of continuity is situated.
Anthony G Cohn; Shyamanta M Hazarika
Spatio-temporal segmentation video sequences attempts to extract backgrounds and independent objects in the dynamic scenes captured in the sequences. It is an essential step of video analysis. It has important applications in video coding, video logging, ...
D. DeMenthon R. Megret
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.
Wan, Cheng; Sato, Jun
Spatio-temporal patterns of soil moisture status highly affect the heterogeneity of soil water and solute transport and leaching of chemicals to the groundwater. In order to quantify and describe spatial variability of ecologically highly relevant spatial and temporal processes linked to soil moisture at the land surface, the spatio-temporal covariance structure and the reasons for its change in time need
O. Wendroth; W. Pohl; S. Koszinski; H. Rogasik; C. J. Ritsema; D. R. Nielsen
Low dose X-ray image sequences, as obtained in fluoroscopy, exhibit high levels of noise that must be suppressed in real-time, while preserving diagnostic structures. Multi-step adaptive filtering approaches, often involving spatio-temporal filters, are typically used to achieve this goal. In this work typical fluoroscopic image sequences, corrupted with Poisson noise, were processed using various filtering schemes. The noise suppression of the schemes was evaluated using objective image quality measures. Two adaptive spatio-temporal schemes, the first one using object detection and the second one using unsharp masking, were chosen as representative approaches for different fluoroscopy procedures and mapped on to Texas Instrument's (TI) high performance digital signal processors (DSP). The paper explains the fixed point design of these algorithms and evaluates its impact on overall system performance. The fixed point versions of these algorithms are mapped onto the C64x+TM core using instruction-level parallelism to effectively use its VLIW architecture. The overall data flow was carefully planned to reduce cache and data movement overhead, while working with large medical data sets. Apart from mapping these algorithms on to TI's single core DSP architecture, this work also distributes the operations to leverage multi-core DSP architectures. The data arrangement and flow were optimized to minimize inter-processor messaging and data movement overhead.
Dasgupta, Udayan; Ali, Murtaza
We study evolutionary processes induced by spatio-temporal dynamics in prebiotic evolution. Using numerical simulations, we demonstrate that hypercycles emerge from complex interaction structures in multispecies systems. In this work, we also find that ‘hypercycle hybrid’ protects the hypercycle from its environment during the growth process. There is little selective advantage for one hypercycle to maintain coexistence with others. This brings the possibility of the outcompetition between hypercycles resulting in the negative effect on information diversity. To enrich the information in hypercycles, symbiosis with parasites is suggested. It is shown that symbiosis with parasites can play an important role in the prebiotic immunology.
Kim, Pan-Jun; Jeong, Hawoong
Recently, a hierarchy of spatio-temporal logics based on the propositional temporal logic PTL and the spatial languages RCC-8, BRCC-8 and S4u has been introduced. Although a number of results on their computational properties were obtained, the most important questions were left open. In this paper, we solve almost all of these problems and provide a clear picture of the balance
David Gabelaia; Roman Kontchakov; Agi Kurucz; Frank Wolter; Michael Zakharyaschev
Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection. PMID:19550494
Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J
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.
Caucci, Luca; Barrett, Harrison H.; Rodriguez, Jeffrey J.
Designs toward TeV-range electron-positron linear colliders include a non-zero crossing angle colliding scheme at the interaction point to mitigate instabilities and possible background. Maximizing the luminosity when operating with non-zero crossing angles requires the use of 'crab' cavities to impart a well-defined spatio-temporal correlation. In this paper we propose a novel noninterceptive diagnostic capable of measuring and monitoring the spatio-temporal correlation, i.e. the transverse position of sub-picosecond time slices, within bunch. An analysis of the proposed scheme, its spatio-temporal resolution and its limitations are quantified. Finally, the design of a proof-of-principle experiment in preparation for the Fermilab's A0 photoinjector is presented.
Maxwell, T.; Piot, P.; /Northern Illinois U. /Fermilab
PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model builders as Python functions. The software comes with Python framework classes providing control flow for spatio-temporal modelling, Monte Carlo simulation, and data assimilation (Ensemble Kalman Filter and Particle Filter). Models are built by combining the spatial operations in these framework classes. This approach enables modellers without specialist programming experience to construct large, rather complicated models, as many technical details of modelling (e.g., data storage, solving spatial operations, data assimilation algorithms) are taken care of by the PCRaster toolbox. Exploratory modelling is supported by routines for prompt, interactive visualisation of stochastic spatio-temporal data generated by the models. The high computational requirements for stochastic spatio-temporal modelling, and an increasing demand to run models over large areas at high resolution, e.g. in global hydrological modelling, require an optimal use of available, heterogeneous computing resources by the modelling framework. Current work in the context of the eWaterCycle project is on a parallel implementation of the modelling engine, capable of running on a high-performance computing infrastructure such as clusters and supercomputers. Model runs will be distributed over multiple compute nodes and multiple processors (GPUs and CPUs). Parallelization will be done by parallel execution of Monte Carlo realizations and sub regions of the modelling domain. In our approach we use multiple levels of parallelism, improving scalability considerably. On the node level we will use OpenCL, the industry standard for low-level high performance computing kernels. To combine multiple nodes we will use software from the eScience Technology Platform (eSTeP), developed at the Netherlands eScience Center. This will allow us to scale up to hundreds of machines, with thousands of compute cores. A key requirement is not to change the user experience of the software. PCRaster operations and the use of the Python framework classes should work in a similar manner on machines ranging from a laptop to a supercomputer. This enables a seamless transfer of models from small machines, where model development is done, to large machines used for large-scale model runs. Domain specialists from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies, currently use the PCRaster Python software within research projects. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows, Linux operating systems, and OS X.
Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.
An increasing amount of observations from different applications such as long-term environmental monitoring or disaster management is published in the Web using Sensor Web technologies. The standardization of these technologies eases the integration of heterogeneous observations into several applications. However, as observations differ in spatio-temporal coverage and resolution, aggregation of observations in space and time is needed. We present an approach for spatio-temporal aggregation in the Sensor Web using the Geoprocessing Web. In particular, we define a tailored observation model for different aggregation levels, a process model for aggregation processes and a Spatio-Temporal Aggregation Service. The presented approach is demonstrated by a case study of delivering aggregated air quality observations on-demand in the Sensor Web.
Stasch, Christoph; Foerster, Theodor; Autermann, Christian; Pebesma, Edzer
Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined by Laube et al., 2004. These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction, heading for the same
Joachim Gudmundsson; Marc J. van Kreveld; Bettina Speckmann
Both structural and behavioral aspects need to be modeled in some spatio-temporal databases. There existing initial efforts to represent behavioral aspects of the spatio-temporal applications via events gave their priority to some local or partial behaviors rather than an overview of the system's behavior. In this paper, an event-based approach is proposed for modeling the system's behavior of the spatio-temporal
Jun CHEN; Jie JIANG
An ecological model is a mathematical statement of the rules governing ecosystem changes. Traditional models based on system dynamics approach provide a useful way to represent and comprehend changing behaviors in time, but it does not adequately represent spatial processes. Although Geographic Information System (GIS) and Remote Sensing (RS) are powerful tools for spatial analyses, they maintain an inherently static
Qiuwen Chen; Rui Han; Fei Ye; Weifeng Li
To elucidate perceptual filling-in mechanisms in peripheral vision, we investigated dependency of filling-in occurrence on spatio-temporal frequency of dynamic textures surrounding the filling-in target. We first measured spatial frequency sensitivity of the filling-in target in static texture. Then, the time to filling-in, when dynamic textures which have variously limited spatio-temporal frequency are surrounding the filling-in target, were measured. According to the hypothesis of filling-in process which has already proposed by the authors, the tendency of inducing filling-in, i.e., the attenuation factor of perceptual power for filling-in target in dynamic textures, is estimated as a function of spatio-temporal frequency. It was suggested that surrounding texture with stronger perception promotes filling-in more intensively.
Yokota, Masae; Yokota, Yasunari
The process of generation of current density filaments has been investigated in a dc driven gas discharge systems consisting of a metal and a high ohmic semiconductor electrode and in an ac driven gas discharge system between two dielectrically covered electrodes. By means of a streak camera system we find that the generation process is accompanied by spatio-temporal filament oscillations.
Willebrand, H.; Niedernostheide, F.-J.; Ammelt, E.; Dohmen, R.; Purwins, H.-G.
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.
Ito, Kentaro; Sumpter, David; Nakagaki, Toshiyuki
The spatio-temporal data is our cognition to external matter and the spatio-temporal data model is the fundamental basic to manage the spatio-temporal data. The spatio-temporal object is always changing so we need a spatio-temporal data model which can reflect the change information and change reason and roundly and exactly describe the spatio-temporal world. At the same time more and more
XiaoChun Wua; Weihong Cuib; YongQi Huang; XiaoDong Yang
The evaluation of spatially and temporally distributed records of translational shallow landslides in heterogeneous watersheds provides insights needed to understand disastrous processes. Recurrent slope instability events occurred between 1953 and 1998 in two watersheds of Mt. Aso, western Japan. This paper investigates (1) the spatio-temporal characteristics of translational shallow landslides (dimensions, numbers, densities, and area subjected to failure) observed at
Prem P. Paudel; H. Omura; T. Kubota; T. Inoue
|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…
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.
Quantification of the complexity of fibrillatory processes may objectify the modifications induced by a therapy. However, its evaluation is usually restricted to a subjective visual inspection. The objective of this work is to classify isochronal maps attending to their organization into 3 types. An automatic classification method based on spatio-temporal isolation of activation wavefronts is presented. The method was tested
X Ibanez-Catala; A M Climent; E Roses; F J Chorro; I Trapero; F Pelechano; L Such-Miquel; J Millet; M S Guillem
Health outcomes are linked to air pollution, demographic, or socioeconomic factors which vary across space and time. Thus, it is often found that relative risks in space-time health data have locally different temporal patterns. In such cases, latent modeling is useful in the disaggregation of risk profiles. In particular, spatio-temporal mixture models can help to isolate spatial clusters each of which has a homogeneous temporal pattern in relative risks. In mixture modeling, various weight structures can be used and two situations can be considered: the number of underlying components is known or unknown. In this paper, we compare spatio-temporal mixture models with different weight structures in both situations. In addition, spatio-temporal Dirichlet process mixture models are compared to them when the number of components is unknown. For comparison, we propose a set of spatial cluster detection diagnostics based on the posterior distribution of the weights. We also develop new accuracy measures to assess the recovery of true relative risks. Based on the simulation study, we examine the performance of various spatio-temporal mixture models in terms of proposed methods and goodness-of-fit measures. We apply our models to a county-level chronic obstructive pulmonary disease data set from the state of Georgia.
Choi, Jungsoon; Lawson, Andrew B.; Cai, Bo; Hossain, Md. Monir
DL, short for Description Logic, is aimed at getting a balance between describing ability and reasoning complexity. Users can adopt DL to write clear and formalized concept description for domain model, which makes ontology description possess well-defined syntax and semantics and helps to resolve the problem of spatio-temporal reasoning based on ontology. This paper studies on basic theory of DL and relationship between DL and OWL at first. By analyzing spatio-temporal concepts and relationship of spatio-temporal GIS, the purpose of this paper is adopting ontology language based on DL to express spatio-temporal ontology, and employing suitable ontology-building tool to build spatio-temporal ontology. With regard to existing spatio-temporal ontology based on first-order predicate logic, we need to transform it into spatio-temporal ontology based on DL so as to make the best of existing research fruits. This paper also makes a research on translating relationships between DL and first-order predicate logic.
Huang, Yongqi; Ding, Zhimin; Zhao, Zhui; Ouyang, Fucheng
The paper describes a collaborative assistance approach with spatio-temporal planning, which requires user's active participation in the problem solving task. The proposed collaborative assistance system operates on a region-based representation structure, which allows for partial specification of constraints at different levels of granularity. Weakly specified constraints contribute on the one hand to high computational complexity when generating alternative solutions and on the other hand to large solution spaces. The paper introduces Partial Order, Neighboring Regions and Partial Order of Neighboring Regions heuristics, which allow for pruning of significant parts of the search space, and produce hierarchical structuring of the solution space. Resulting hierarchical organization of the solution space reflects human mental processing of geographic information. To reduce cognitive load during observation of solution space, filtering of certain aspects, set-oriented structuring and case-based reasoning approaches are introduced.
Spatially and temporally resolved emission spectra of laser-induced air plasma in the stage of laser pulse action were studied. Due to the expansion of laser supported detonation wave and shielding effect at the critical surface for CO2 laser radiation, a behavior of spatial separation of the radiative plasma along the radial direction was clearly recognized. Based on the Stark broadening, we investigated the spatio-temporal evolution of the electron density and temperature of the plasma, which was evaluated by fitting the measured spectral profile to the summation of Voigt profiles of all spectral lines in a selected spectral range. The electron density was distributed densely around the focal point and thinly near the plasma edge at early times. On the contrary, the electron temperature around the focal point was a minimum at early times but became a maximum at later times. Unlike the spatio-temporal resolution results of post-pulse in previous work, the results in the present work revealed the information related to the processes of laser energy deposition.
Tang, Jian; Zuo, Duluo; Wu, Tao; Cheng, Zuhai
Background Gliomas are the most common types of brain cancer, well known for their aggressive proliferation and the invasive behavior leading to a high mortality rate. Several mathematical models have been developed for identifying the interactions between glioma cells and tissue microenvironment, which play an important role in the mechanism of the tumor formation and progression. Methods Building and expanding on existing approaches, this paper develops a continuous three-dimensional model of avascular glioma spatio-temporal evolution. The proposed spherical model incorporates the interactions between the populations of four different glioma cell phenotypes (proliferative, hypoxic, hypoglychemic and necrotic) and their tissue microenvironment, in order to investigate how they affect tumor growth and invasion in an isotropic and homogeneous medium. The model includes two key variables involved in the proliferation and invasion processes of cancer cells; i.e. the extracellular matrix and the matrix-degradative enzymes concentrations inside the tumor and its surroundings. Additionally, the proposed model focuses on innovative features, such as the separate and independent impact of two vital nutrients, namely oxygen and glucose, in tumor growth, leading to the formation of cell populations with different metabolic profiles. The model implementation takes under consideration the variations of particular factors, such as the local cell proliferation rate, the variable conversion rates of cells from one category to another and the nutrient-dependent thresholds of conversion. All model variables (cell densities, ingredients concentrations) are continuous and described by reaction-diffusion equations. Results Several simulations were performed using combinations of growth and invasion rates, for different evolution times. The model results were evaluated by medical experts and validated on experimental glioma models available in the literature, revealing high agreement between simulated and experimental results. Conclusions Based on the experimental validation, as well as the evaluation by clinical experts, the proposed model may provide an essential tool for the patient-specific simulation of different tumor evolution scenarios and reliable prognosis of glioma spatio-temporal progression.
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 spatio-temporal decompositions 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 spatio-temporal patterns and the dynamics of source amplitude across trials; on two brain-computer interface (BCI) data sets we show that our VB algorithm can extract physiologically meaningful spatio-temporal patterns and make more accurate predictions than other two widely used algorithms: the common spatial patterns (CSP) algorithm and the Infomax algorithm for independent component analysis (ICA). The results demonstrate that our statistical modeling framework can serve as a powerful tool for extracting brain patterns, characterizing trial-to-trial brain dynamics, and decoding brain states by exploiting useful structures in the data. PMID:21420499
Wu, Wei; Chen, Zhe; Gao, Shangkai; Brown, Emery N
Our development of an ideal-observer framework and a test-pedestal methodology for modeling vision without the numerous assumptions of previous models has provided a comprehensive understanding of the spatio-temporal characteristics of human vision. The m...
S. A. Klein
We describe a simple new technique for spatio-temporal segmenta- tion of video sequences. Each pixel of a 3D space-time video stack is mapped to a 7D feature point whose coordinates include three color components, two motion angle components and two motion position components. The clustering of these feature points pro- vides color segmentation and motion segmentation, as well as a
ABSTRACT Location-detection devices are used ubiquitously in moving objects due to the everyday decreasing cost and simplified technology. Usually, these devices will send the moving ob- jects’ location information to a spatio-temporal data stream management,system that will be then responsible for an- swering spatio-temporal queries related to these moving ob- jects. Most of the existing work focused on the continu-
Hicham G. Elmongui
This paper proposes a biologically inspired incremental learning method for spatio-temporal patterns based on our recently\\u000a reported “Incremental learning through sleep (ILS)” method. This method alternately repeats two learning phases: awake and\\u000a sleep. During the awake phase, the system learns new spatio-temporal patterns by rote, whereas in the sleep phase, it rehearses\\u000a the recorded new memories interleaved with old memories.
Koichiro Yamauchi; Masayoshi Sato
Research in spatio-temporal databases has largely focused on extensions of access methods for the proper handling of time changing spatial information. In this paper, we present the Multiversion Linear Quadtree (MVLQ), a spatio-temporal access method based on Multiver- sion B-trees (MVBT) (2), embedding ideas from Linear Region Quadtrees (4). More specically, instead of storing independent numerical data ha- ving a
Theodoros Tzouramanis; Michael Vassilakopoulos; Yannis Manolopoulos
Spatio-temporal co-occurrence patterns represent subsets of object-types that are often located together in space and time. The aim of the discovery of partial spatio-temporal co- occurrence patterns (PACOPs) is to find co-occurrences of the object-types that are partially present in the database. Discovering PACOPs is an important problem with many applications such as discovering interactions between animals and identifying tactics
A growing number of medical datasets now contain both a spatial and a temporal dimension. Trajectories, from tools or body features, are thus becoming increasingly important for their analysis. In this paper, we are interested in recovering the spatial and temporal differences between trajectories coming from different datasets. In particular, we address the case of surgical gestures, where trajectories contain both spatial transformations and speed differences in the execution. We first define the spatio-temporal registration problem between multiple trajectories. We then propose an optimization method to jointly recover both the rigid spatial motions and the non-linear time warpings. The optimization generates also a generic trajectory template, in which spatial and temporal differences have been factored out. This approach can be potentially used to register and compare gestures side-by-side for training sessions, to build gesture trajectory models for automation by a robot, or to register the trajectories of natural or artificial markers which follow similar motions. We demonstrate its usefulness with synthetic and real experiments. In particular, we register and analyze complex surgical gestures performed by tele-manipulation using the da Vinci robot. PMID:22003611
Padoy, Nicolas; Hager, Gregory D
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\\midast-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\\midast-trees. The proposed approach provides a potential parallel indexing solution for fast data retrieval of massive four-dimensional or higher dimensional spatio-temporal data.
He, Zhenwen; Kraak, Menno-Jan; Huisman, Otto; Ma, Xiaogang; Xiao, Jing
PAPER Special Section on Adaptive Signal Processing and Its Applications Spatio-Temporal Equalization for Space-Time Block Coded Transmission over Frequency Selective Fading Channel with Co-channel Interference
SUMMARY In this paper, we propose a spatio-temporal equalizer for the space-time block coded transmission over the frequency selective fad- ing channels with the presence of co-channel interference (CCI). The pro- posed equalizer, based on the tapped delay line adaptive array (TDLAA), performs signal equalization and CCI suppression simultaneously using the minimum mean square error (MMSE) method. It is to
Xuan Nam TRAN; Tetsuki TANIGUCHI; Yoshio KARASAWA
BACKGROUND: While there is a general agreement that picture-plane inversion is more detrimental to face processing than to other seemingly complex visual objects, the origin of this effect is still largely debatable. Here, we address the question of whether face inversion reflects a quantitative or a qualitative change in processing mode by investigating the pattern of event-related potential (ERP) response
Boutheina Jemel; Julie Coutya; Caroline Langer; Sylvain Roy
Research on brain or cognitive\\/affective processes, culture, social interaction, and structural analysis are overlapping but often independent ways humans have attempted to understand the origins of their evolution, historical, and contemporary development. Each level seeks to employ its own theoretical concepts and methods for depicting human nature and categorizing objects and events in the world, and often relies on different
Aaron V. Cicourel
The detection of errors is known to be associated with two successive neurophysiological components in EEG, with an early time-course following motor execution: the error-related negativity (ERN/Ne) and late positivity (Pe). The exact cognitive and physiological processes contributing to these two EEG components, as well as their functional…
Vocat, Roland; Pourtois, Gilles; Vuilleumier, Patrik
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 recordings during this task revealed a highly ordered temporal progression of high gamma (HG, 70–200
Edward F. Chang; Erik Edwards; Srikantan S. Nagarajan; Noa Fogelson; Sarang S. Dalal; Ryan T. Canolty; Heidi E. Kirsch; Nicholas M. Barbaro; Robert T. Knight
Shallow fluvial lakes are heterogeneous ecosystems in which marked spatio-temporal variation renders diffi- cult the analysis of key ecological processes, such as growth. In this study, we used generalized additive modelling of the RNA\\/DNA ratio, an index of short-term growth, to investigate the influence of environmental variables and spatio- temporal variation on growth of yellow perch (Perca flavescens) in Lake
Hélène Glémet; Marco A. Rodríguez
Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the “average” spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled “spatio-temporal kernel density estimation (stKDE)” that employs hybrid kernel (i.e., weight) functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also “borrows” information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based) kernel density estimation (trKDE) which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method.
Chen, Dongmei; Racine, Jeffrey S.; Ong, SengHuat; Chen, Yue; Zhao, Genming; Jiang, Qingwu
Radioactive particle movement analysis in any environment gives valuable information about the effects of the concerned environment on the particle and the transportation phenomenon. In this study, the spatio-temporal point cumulative semivariogram (STPCSV) approach is proposed for the analysis of the spatio-temporal changes in the radioactive particle movement within a surface water body. This methodology is applied to the (210)Pb radioactive isotope measurements at 44 stations, which are determined beforehand in order to characterize the Keban Dam water environment on the Euphrates River in the southeastern part of Turkey. It considers the contributions coming from all the stations and provides information about the spatio-temporal behavior of (210)Pb in the water environment. After having identified the radii of influences at each station it is possible to draw maps for further interpretations. In order to see holistically the spatial changes of the radioisotope after 1st, 3rd and 5th hours, the radius of influence maps are prepared and interpreted accordingly. PMID:19027230
Külahci, Fatih; Sen, Zekâi
We propose a novel ?1?2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard ?1-norm inverse solvers, this sparse distributed inverse solver integrates the ?1-norm spatial model with a temporal model of the source signals in order to avoid unstable activation patterns and “spiky” reconstructed signals often produced by the currently used sparse solvers. The joint spatio-temporal model leads to a cost function with an ?1?2-norm regularizer whose minimization can be reduced to a convex second-order cone programming (SOCP) problem and efficiently solved using the interior-point method. The efficient computation of the SOCP problem allows us to implement permutation tests for estimating statistical significance of the inverse solution. Validation with simulated and human MEG data shows that the proposed solver yields source time course estimates qualitatively similar to those obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. Furthermore, the ?1?2-norm solver achieves fewer false positives and a better representation of the source locations than the conventional ?2 minimum-norm estimates.
Ou, Wanmei; Hamalainen, Matti S.; Golland, Polina
We propose a novel ?1?2-norm inverse solver for estimating the sources of EEG/MEG signals. Developed based on the standard ?1-norm inverse solvers, this sparse distributed inverse solver integrates the ?1-norm spatial model with a temporal model of the source signals in order to avoid unstable activation patterns and “spiky” reconstructed signals often produced by the currently used sparse solvers. The joint spatio-temporal model leads to a cost function with an ?1?2-norm regularizer whose minimization can be reduced to a convex second-order cone programming (SOCP) problem and efficiently solved using the interior-point method. The efficient computation of the SOCP problem allows us to implement permutation tests for estimating statistical significance of the inverse solution. Validation with simulated and real MEG data shows that the proposed solver yields source time course estimates qualitatively similar to those obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. Furthermore, the ?1?2-norm solver achieves fewer false positives and a better representation of the source locations than the conventional ?2 minimum-norm estimates.
Hamalainen, Matti S.; Golland, Polina
Background Epidemiologic studies are often confounded by the human and environmental interactions that are complex and dynamic spatio-temporal processes. Hence, it is difficult to discover nuances in the data and generate pertinent hypotheses. Dynamic mapping, a method to simultaneously visualize temporal and spatial information, was introduced to elucidate such complexities. A conceptual framework for dynamic mapping regarding principles and implementation methods was proposed. Methods The spatio-temporal dynamics of Salmonella infections for 2002 in the U.S. elderly were depicted via dynamic mapping. Hospitalization records were obtained from the Centers of Medicare and Medicaid Services. To visualize the spatial relationship, hospitalization rates were computed and superimposed onto maps of environmental exposure factors including livestock densities and ambient temperatures. To visualize the temporal relationship, the resultant maps were composed into a movie. Results The dynamic maps revealed that the Salmonella infections peaked at specific spatio-temporal loci: more clusters were observed in the summer months and higher density of such clusters in the South. The peaks were reached when the average temperatures were greater than 83.4°F (28.6°C). Although the relationship of salmonellosis rates and occurrence of temperature anomalies was non-uniform, a strong synchronization was found between high broiler chicken sales and dense clusters of cases in the summer. Conclusions Dynamic mapping is a practical visual-analytic technique for public health practitioners and has an outstanding potential in providing insights into spatio-temporal processes such as revealing outbreak origins, percolation and travelling waves of the diseases, peak timing of seasonal outbreaks, and persistence of disease clusters.
The electric field of an ultrashort laser pulse often fails to separate into a product of purely temporal and purely spatial factors. These so-called spatio-temporal couplings constitute a broad range of physical effects, which often become important in applications. In this review, we compile some recent experimental and theoretical work on the understanding, avoidance and applications of these effects. We first present a discussion of the characteristics of pulses containing spatio-temporal couplings, including their sources, a mathematical description and the interdependence of different couplings. We then review different experimental methods for their characterization. Finally, we describe different applications of spatio-temporal couplings and suggest further schemes for their exploitation and avoidance.
Akturk, Selcuk; Gu, Xun; Bowlan, Pamela; Trebino, Rick
Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.
Tauber, C.; Stute, S.; Chau, M.; Spiteri, P.; Chalon, S.; Guilloteau, D.; Buvat, I.
The pitch of harmonic complex tones plays an important role in speech and music perception and the analysis of auditory scenes, yet traditional rate-place and temporal models for pitch processing provide only an incomplete description of the psychophysical data. In order to test physiologically a model based on spatio-temporal pitch cues created by the cochlear traveling wave (Shamma, J Acoust Soc Am 78: 1622–1632), we recorded from single fibers in the auditory nerve of anesthetized cat in response to harmonic complex tones with missing fundamentals and equal-amplitude harmonics. We used the principle of scaling invariance in cochlear mechanics to infer the spatiotemporal response pattern to a given stimulus from a series of measurements made in a single fiber as a function of fundamental frequency F0. We found that spatio-temporal cues to resolved harmonics are available for F0s between 350 Hz and 1100 Hz and that these cues are more robust than traditional rate-place cues at high stimulus levels. The lower F0-limit is determined by the limited frequency selectivity of the cochlea, while the upper limit is caused by the degradation of phase-locking to the stimulus fine structure at high frequencies. The spatio-temporal representation is consistent with the upper F0-limit to the perception of the pitch of complex tones with a missing fundamental, and its effectiveness does not depend on the relative phase between resolved harmonics. The spatio-temporal representation is thus consistent with key trends in human psychophysics.
Cedolin, Leonardo; Delgutte, Bertrand
It is known that focusing of an acoustic field by a time-reversal mirror (TRM) is equivalent to a spatio-temporal matched filter under conditions where the Green's function of the field satisfies reciprocity and is time invariant, i.e. the Green's function is independent of the choice of time origin. In this letter, it is shown that both reciprocity and time invariance can be replaced by a more general constraint on the Green's function that allows a TRM to implement the spatio-temporal matched filter even when conditions are time varying.
Lehman, S K; Poggio, A J; Kallman, J S; Meyer, A W; Candy, J V
When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream. PMID:16532730
Clement, L; Thas, O; Vanrolleghem, P A; Ottoy, J P
The recent concerns for world-wide extreme events related to climate change phenomena have motivated the development of large scale models that simulate the global water cycle. In this context, analyses of extremes is an important topic that requires the adaptation of methods used for river basin and regional scale models. This paper presents two methodologies that extend the tools to analyze spatio-temporal drought development and characteristics using large scale gridded time series of hydrometeorological data. The methodologies are distinguished and defined as non-contiguous and contiguous drought area analyses (i.e. NCDA and CDA). The NCDA presents time series of percentages of areas in drought at the global scale and for pre-defined regions of known hydroclimatology. The CDA is introduced as a complementary method that generates information on the spatial coherence of drought events at the global scale. Spatial drought events are found through CDA by clustering patterns (contiguous areas). In this study the global hydrological model WaterGAP was used to illustrate the methodology development. Global gridded time series (resolution 0.5°) simulated with the WaterGAP model from land points were used. The NCDA and CDA were applied to identify drought events in subsurface runoff. The percentages of area in drought calculated with both methods show complementary information on the spatial and temporal events for the last decades of the 20th century. The NCDA provides relevant information on the average number of droughts, duration and severity (deficit volume) for pre-defined regions (globe, 2 selected climate regions). Additionally, the CDA provides information on the number of spatially linked areas in drought as well as their geographic location on the globe. An explorative validation process shows that the NCDA results capture the overall spatio-temporal drought extremes over the last decades of the 20th century. Events like the El Niño Southern Oscillation (ENSO) in South America and the pan-European drought in 1976 appeared clearly in both analyses. The methodologies introduced provide an important basis for the global characterization of droughts, model inter-comparison, and spatial events validation.
Corzo Perez, G. A.; van Huijgevoort, M. H. J.; Voß, F.; van Lanen, H. A. J.
Dynamic inverse problems, which occur in medical imaging and other fields, are inverse problems in which the quantities to be reconstructed vary in time, although they are related to the measurements through spatial operators only. Traditional methods solve these problems by frame-by-frame reconstruction, then extract temporal behaviour of the objects or regions of interest through curve fitting and other image-based processing. These approaches solve the inverse problem while exploiting only the spatial relationship between the object and the measurement data at each time instant, without using any temporal dynamics of the underlying process, and thus are not optimal unless the solution is temporally uncorrelated. If the spatial operators are linear, and if one, by contrast, solves the whole spatio-temporal process jointly, it falls into the category of general linear least-squares problems. Such approaches are generally difficult, both due to the challenge of modelling the temporal dynamics appropriately as well as to the high dimensionality of the associated large linear system. Several recent reports have approached this problem in different ways, making different prior assumptions on the spatial and temporal behaviour. In this paper we discuss three such approaches, which have been introduced from different points of view, in a common statistical regularization framework, and illuminate their relationships. The three methods are a state-space model, the separability condition and a multiple constraints model. The key result is that there is a clear relationship among the three methods; specifically, the inverse of the spatio-temporal autocovariance matrix has a block tri-diagonal form, a Kronecker product form or a Kronecker sum form, respectively. Some simple simulation examples are presented to illustrate the theoretical analysis.
Zhang, Yiheng; Ghodrati, Alireza; Brooks, Dana H.
Autoassociations of spatio-temporal sequences have been discussed by a number of authors. We propose a mechanism for storing and retrieving pairs of spatio-temporal sequences with the network architecture of the standard bidirectional associative memory (BAM), thereby achieving hetero-associations of spatio-temporal sequences. PMID:18249876
Autoassociations of spatio-temporal sequences have been discussed by a number of authors. We propose a mechanism for storing and retrieving pairs of spatio-temporal sequences with the network architecture of the standard bidirectional associative memory (BAM), thereby achieving heteroassociations of spatio-temporal sequences.
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.
Triglav, Joc; Petrovi?, Dušan; Stopar, Bojan
Data structures with spatial and temporal dependencies are not uncom- mon in environmental and agronomic flelds. We consider the modeling and estima- tion problem for these type of structures, in particular we consider proportional odds models with spatio-temporal covariables with estimation via maximum pseudlikeli- hood. We end by presenting a testing problem on treatment efiects on data from a fleld
Rogelio Ramos-Quiroga; Graciela Gonzalez-Far
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.
Wang, Lang; Fontanini, Alfredo; Maffei, Arianna
Spatio-temporal data sets are often very large and difficult to analyze and display. Since they are fundamental for decision support in many application contexts, recently a lot of interest has arisen toward data-mining techniques to filter out relevant subsets of very large data repositories as well as visualization tools to effectively display the results. In this paper we propose a
P. Compieta; Sergio Di Martino; Michela Bertolotto; Filomena Ferrucci; M. Tahar Kechadi
|Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…
McGuire, Michael Patrick
In applications where covariates and responses are observed across space and time, a common goal is to quantify the effect of a change in the covariates on the response while adequately accounting for the spatio-temporal structure of the observations. The most common approach for building such a model is to confine the relationship between a covariate and response variable to a single spatio-temporal location. However, oftentimes the relationship between the response and predictors may extend across space and time. In other words, the response may be affected by levels of predictors in spatio-temporal proximity to the response location. Here, a flexible modeling framework is proposed to capture such spatial and temporal lagged effects between a predictor and a response. Specifically, kernel functions are used to weight a spatio-temporal covariate surface in a regression model for the response. The kernels are assumed to be parametric and non-stationary with the data informing the parameter values of the kernel. The methodology is illustrated on simulated data as well as a physical data set of ozone concentrations to be explained by temperature.
Gelfand, Alan E.
This paper presents new algorithms for estimating the spatio-temporal spectrum of the signals received by a passive array. The algorithms are based on the eigenstructure of the covariance and spectral density matrices of the received signals. They allow partial correlation between the sources and thus are applicable to certain kinds of multipath problems. Simulation results that illustrate the performance of
M. Wax; Tie-Jun Shan; T. Kailath
We present a fully Bayesian approach to modeling in functional magnetic resonance imaging (FMRI), incorporating spatio-temporal noise modeling and haemodynamic response function (HRF) modeling. A fully Bayesian approach allows for the uncertainties in the noise and signal modeling to be incorporated together to provide full posterior distributions of the HRF parameters. The noise modeling is achieved via a nonseparable space-time
Mark William Woolrich; Mark Jenkinson; J. Michael Brady; Stephen M. Smith
We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.
Mennis, J.; Viger, R.; Tomlin, C. D.
Compared with the video programs taken by professionals, home videos are always with low-quality content resulted from lack of professional capture skills. In this paper, we present a novel spatio-temporal quality assessment scheme in terms of low-level content features for home videos. In contrast to existing frame-level-based quality assessment ap- proaches, a type of temporal segment of video, sub-shot, is
Tao Mei; Cai-Zhi Zhu; He-Qin Zhou; Xian-Sheng Hua
Compared with the video programs taken by professionals, home videos are always with low-quality content resulted from lack of professional capture skills. In this paper, we present a novel spatio-temporal quality assessment scheme in terms of low-level content features for home videos. In contrast to existing frame-level-based quality assessment approaches, a type of temporal segment of video, sub-shot, is selected
Tao Mei; Cai-Zhi Zhu; He-Qin Zhou; Xian-Sheng Hua
\\u000a Sports video is characterized with strict game rules, numerable events and well defined structures. In this paper, we proposed\\u000a a generic framework for spatio-temporal pattern mining in sports video. Specifically, the periodicities in sports video are\\u000a identified using unsupervised clustering and data mining method. In this way sports video analysis never needs priori domain\\u000a knowledge about video genres, producers or
Dong-jun Lan; Yu-fei Ma; Wei-ying Ma; Hong-Jiang Zhang
It is demonstrated that spatio-temporal chaos can be induced by applying smooth spatial ramps to systems which under homogeneous conditions exhibit only steady spatially-periodic structures. This dynamics is investigated by numerical simulations of a simple reaction-diffusion model. They show that nonadiabatic effects, which are not contained in the usual amplitude equations, are relevant in the dynamics. It is expected that
H. Riecke; H.-G. Paap
We present a method for spatio-temporal filtration of dynamic CT data, to increase the signal-to-noise ratio (SNR) of image data at the same time maintaining image quality, in particular spatial and temporal sharpness of the images. Alternatively, the radiation dose applied to the patient can be reduced at the same time maintaining the noise level and the image sharpness. In contrast to classical methods, which generally operate on the three spatial dimensions of image data, noise statistics is improved by extending the filtration to the temporal dimension. Our approach is based on nonlinear and anisotropic diffusion filters, which are based on a model of heat diffusion adapted to medical CT data. Bilateral filters are a special class of diffusion filters, which do not need iteration to reach a convergence image, but represent the fixed point of a dedicated diffusion filter. Spatio-temporal, anisotropic bilateral filters are developed and applied to dynamic CT image data. The potential was evaluated using data from perfusion CT and cardiac dual source CT (DSCT) data, respectively. It was shown, that in perfusion CT, SNR can be improved by a factor of 4 at the same radiation dose. On basis of clinical data it was shown, that alternatively the radiation dose to the patient can be reduced by a factor of at least 2. A more accurate evaluation of the perfusion parameters blood flow, blood volume and time-to-peak is supported. In DSCT noise statistics can be improved using more projection data than needed for image reconstruction, however, as a consequence the temporal resolution is significantly impaired. Due to the anisotropy of the spatio-temporal bilateral filter temporal contrast edges between adjacent time samples are preserved, at the same time substantially smoothing image data in homogeneous regions. Also temporal contrast edges are preserved, maintaining the very high temporal resolution of DSCT acquisitions (~ 80 ms). CT examinations of the heart require careful dose management to reduce the radiation dose burden to the patient. The use of spatio-temporal diffusion filters allows for dose reduction at the same noise level, at the same time preserving spatial and temporal image resolution. Our approach can be extended to any imaging method, that is based on dynamic data, as an efficient tool for edge-preserving noise reduction.
Bruder, H.; Raupach, R.; Klotz, E.; Stierstorfer, K.; Flohr, T.
This paper introduces and describes the hourly high resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR) probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a cold and snowy climate and to capture soil moisture transitions in areas that have different topography, soil and land-cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal Canadian climate causes a transition in soil moisture patterns at seasonal time scales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was equally dominated by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm) or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting http://www.hydrology.mcmaster.ca.
Kornelsen, K. C.; Coulibaly, P.
A focusing technique based on the inversion of the propagation operator relating an array of transducers to a set of control points inside a medium was proposed in previous work [Tanter et al., J. Acoust. Soc. Am. 108, 223-234 (2000)] and is extended here to the time domain. As the inversion of the propagation operator is achieved both in space and time, this technique allows calculation of the set of temporal signals to be emitted by each element of the array in order to optimally focus on a chosen control point. This broadband inversion process takes advantage of the singular-value decomposition of the propagation operator in the Fourier domain. The physical meaning of this decomposition is explained in a homogeneous medium. In particular, a definition of the number of degrees of freedom necessary to define the acoustic field generated by an array of limited aperture in a focal plane of limited extent is given. This number corresponds to the number of independent signals that can be created in the focal area both in space and time. In this paper, this broadband inverse-focusing technique is compared in homogeneous media with the classical focusing achieved by simple geometrical considerations but also with time-reversal focusing. It is shown that, even in a simple medium, slight differences appear between these three focusing strategies. In the companion paper [Aubry et al., J. Acoust. Soc. Am. 110, 48-58 (2001)] the three focusing techniques are compared in heterogeneous, absorbing, or complex media where classical focusing is strongly degraded. The strong improvement achieved by the spatio-temporal inverse-filter technique emphasizes the great potential of multiple-channel systems having the ability to apply completely different signal waveforms on each transducer of the array. The application of this focusing technique could be of great interest in various ultrasonic fields such as medical imaging, nondestructive testing, and underwater acoustics. PMID:11508962
Tanter, M; Aubry, J F; Gerber, J; Thomas, J L; Fink, M
Many hydrological and agricultural studies require simulations of weather variables reflecting observed spatial and temporal dependence at multiple point locations. This paper assesses three multi-site daily rainfall generators for their ability to model different spatio-temporal rainfall attributes over the study area. The approaches considered consist of a multi-site modified Markov model (MMM), a reordering method for reconstructing space–time variability, and
R. Mehrotra; Ashish Sharma
Spatio-temporal modeling for urban applications has received special attention lately. Due to the recent advances in computer\\u000a and geospatial technologies, the temporal aspect of urban applications which was ignored in conventional systems, is under\\u000a consideration nowadays. This new interest in spatio-temporal modeling, in spite of all its deficiencies, has brought about\\u000a great advances in spatio-temporal modeling and will enhance the
Majeed Pooyandeh; Saadi Mesgari; Abbas Alimohammadi; Rouzbeh Shad
The spatio-temporal data simulating Ice-Land-Ocean interaction of Antarctic are used to demonstrate the Clifford algebra-based data model construction, spatio-temporal query and data analysis. The results suggest that Clifford algebra provides a powerful mathematical tool for the whole modelling and analysis chains for complex geo-simulation data. It can also help implement spatio-temporal analysis algorithms more clearly and simply.
Luo, Wen; Yu, Zhaoyuan; Hu, Yong; Yuan, Linwang
Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.
Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.
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 spinal cord function and in the cellular and molecular events that characterise its neuropathology.
Arenas, Ernest; Rodriguez, Francisco Javier
Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed. PMID:22830962
Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola
We have studied a spontaneous self-organization dynamics in a closed, dissipative (in terms of guansine 5'-triphosphate energy dissipation), reaction-diffusion system of acentrosomal microtubules (those nucleated and organized in the absence of a microtubule-organizing centre) multitude constituted of straight and curved acentrosomal microtubules, in highly crowded conditions, in vitro. Our data give experimental evidence that cross-diffusion in conjunction with excluded volume is the underlying mechanism on basis of which acentrosomal microtubule multitudes of different morphologies (straight and curved) undergo a spatial-temporal demix. Demix is constituted of a bifurcation process, manifested as a slow isothermal spinodal decomposition, and a dissipative process of transient periodic spatio-temporal pattern formation. While spinodal decomposition is an energy independent process, transient periodic spatio-temporal pattern formation is accompanied by energy dissipative process. Accordingly, we have determined that the critical threshold for slow, isothermal spinodal decomposition is 1.0 ± 0.05 mg/ml of microtubule protein concentration. We also found that periodic spacing of transient periodic spatio-temporal patterns was, in the overall, increasing versus time. For illustration, we found that a periodic spacing of the same pattern was 0.375 ± 0.036 mm, at 36 °C, at 155th min, while it was 0.540 ± 0.041 mm at 31 °C, and at 275th min after microtubule assembly started. The lifetime of transient periodic spatio-temporal patterns spans from half an hour to two hours approximately. The emergence of conditions of macroscopic symmetry breaking (that occur due to cross-diffusion in conjunction with excluded volume) may have more general but critical importance in morphological pattern development in complex, dissipative, but open cellular systems. PMID:23822485
Buljan, Vlado A; Holsinger, R M Damian; Brown, D; Bohorquez-Florez, J J; Hambly, B D; Delikatny, E J; Ivanova, E P; Banati, R B
We have studied a spontaneous self-organization dynamics in a closed, dissipative (in terms of guansine 5'-triphosphate energy dissipation), reaction-diffusion system of acentrosomal microtubules (those nucleated and organized in the absence of a microtubule-organizing centre) multitude constituted of straight and curved acentrosomal microtubules, in highly crowded conditions, in vitro. Our data give experimental evidence that cross-diffusion in conjunction with excluded volume is the underlying mechanism on basis of which acentrosomal microtubule multitudes of different morphologies (straight and curved) undergo a spatial-temporal demix. Demix is constituted of a bifurcation process, manifested as a slow isothermal spinodal decomposition, and a dissipative process of transient periodic spatio-temporal pattern formation. While spinodal decomposition is an energy independent process, transient periodic spatio-temporal pattern formation is accompanied by energy dissipative process. Accordingly, we have determined that the critical threshold for slow, isothermal spinodal decomposition is 1.0 +/- 0.05 mg/ml of microtubule protein concentration. We also found that periodic spacing of transient periodic spatio-temporal patterns was, in the overall, increasing versus time. For illustration, we found that a periodic spacing of the same pattern was 0.375 +/- 0.036 mm, at 36 °C, at 155th min, while it was 0.540 +/- 0.041 mm at 31 °C, and at 275th min after microtubule assembly started. The lifetime of transient periodic spatio-temporal patterns spans from half an hour to two hours approximately. The emergence of conditions of macroscopic symmetry breaking (that occur due to cross-diffusion in conjunction with excluded volume) may have more general but critical importance in morphological pattern development in complex, dissipative, but open cellular systems.
Buljan, Vlado A.; Damian Holsinger, R. M.; Brown, D.; Bohorquez-Florez, J. J.; Hambly, B. D.; Delikatny, E. J.; Ivanova, E. P.; Banati, R. B.
Effective drought planning and mitigation requires an understanding of water supply and demand, including historical biophysical and legal conditions that lead to water shortages among various end-users. With the goal of providing information that is useful for managing current drought risks and for adapting to changing climate, this project aims to fill the gaps in the knowledge about spatio-temporal variations in water demand patterns in the Upper Colorado River Basin (UCRB). This information will help to identify vulnerabilities in the water management structure for more targeted drought preparedness and early warning. Though monitoring of hydro-meteorological properties is important to the forecast of drought conditions, the availability of water is complicated by the administration of existing water rights. The picture is increasingly complicated by the common practice of transmountain diversion, in which water in one basin is transported to another basin for use. This presentation will discuss development of a water demand data model and a spatio-temporal database that will support topological relationships among water users and their respective sources of water supply, including transfers and exchanges. GIS processes for linking water supply to the end users and their water demands will be discussed.
Sampson, K. M.; Wilhelmi, O.
Rapid eye movements (saccades) induce visual misperceptions. A number of studies in recent years have investigated the spatio-temporal profiles of effects like saccadic suppression or perisaccadic mislocalization and revealed substantial functional similarities. Saccade induced chronostasis describes the subjective overestimation of stimulus duration when the stimulus onset falls within a saccade. In this study we aimed to functionally characterize saccade induced chronostasis in greater detail. Specifically we tested if chronostasis is influenced by or functionally related to saccadic suppression. In a first set of experiments, we measured the perceived duration of visual stimuli presented at different spatial positions as a function of presentation time relative to the saccade. We further compared perceived duration during saccades for isoluminant and luminant stimuli. Finally, we investigated whether or not saccade induced chronostasis is dependent on the execution of a saccade itself. We show that chronostasis occurs across the visual field with a clear spatio-temporal tuning. Furthermore, we report chronostasis during simulated saccades, indicating that spurious retinal motion induced by the saccade is a prime origin of the phenomenon. PMID:23458677
Knöll, Jonas; Morrone, M Concetta; Bremmer, Frank
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.
Sabir, Azhin; Al-jawad, Naseer; Jassim, Sabah
This work describes the application of a spatio-temporal modeling to the study of glaucoma, a very serious ocular illness. The aim of this modeling is to solve various significant medical problems, namely the forecasting of future observations, the classification of observations as normal or defective, and the simulation of new longitudinal data sets. In order to ascertain whether a patient suffers from glaucoma, a perimetry is performed. The output of a perimetry is called a visual field and consists of a map with 52 numerical values plotted on a regular grid. In this work, a data set of healthy patients' visual fields is used. The work begins with an exploratory spatial data analysis. A semi-parametric approach is used to model the mean, and the variogram is fitted using a Matérn function. Once the spatial structure has been analysed, the spatial mean is subtracted from all the observations in the data set and the spatio-temporal correlation of the residuals is explored. All this information is used to build a space-time model, the parameters of which are estimated by maximum likelihood. Different methods are used to check the goodness of fit. PMID:17698932
Ibáñez, M V; Simó, A
A spatio-temporal model of housing price trends is developed that focuses on individual housing sales over time. The model allows for both the spatio-temporal lag effects of previous sales in the vicinity of each housing sale, and for general autocorrelation effects over time. A key feature of this model is the recognition of the unequal spacing between individual housing sales
Tony E. Smith; Peggy Wu
This report consists of a dissertation submitted to the faculty of the Department of Electrical and Computer Engineering, in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Graduate College, The University of Arizona, 2008. Spatio-temporal systems with heterogeneity in their structure and behavior have two major problems associated with them. The first one is that such complex real world systems extend over very large spatial and temporal domains and consume so many computational resources to simulate that they are infeasible to study with current computational platforms. The second one is that the data available for understanding such systems is limited because they are spread over space and time making it hard to obtain micro and macro measurements. This also makes it difficult to get the data for validation of their constituent processes while simultaneously considering their global behavior. For example, the valley fever fungus considered in this dissertation is spread over a large spatial grid in the arid Southwest and typically needs to be simulated over several decades of time to obtain useful information. It is also hard to get the temperature and moisture data (which are two critical factors on which the survival of the valley fever fungus depends) at every grid point of the spatial domain over the region of study. In order to address the first problem, we develop a method based on the discrete event system specification which exploits the heterogeneity in the activity of the spatio-temporal system and which has been shown to be effective in solving relatively simple partial differential equation systems. The benefit of addressing the first problem is that it now makes it feasible to address the second problem. We address the second problem by making use of a multilevel methodology based on modeling and simulation and systems theory. This methodology helps us in the construction of models with different resolutions (base and lumped models). This allows us to refine an initially constructed lumped model with detailed physics-based process models and assess whether they improve on the original lumped models. For that assessment, we use the concept of experimental frame to delimit where the improvement is needed. This allows us to work with the available data, improve the component models in their own experimental frame and then move them to the overall frame. In this dissertation, we develop a multilevel methodology and apply it to a valley fever model. Moreover, we study the model's behavior in a particular experimental frame of interest, namely the formation of new sporing sites.
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.
Koss, Jordan; Coppersmith, Susan
Forest fire is one of the major phenomena causing degradation of environment, landscape, natural ecosystems, human health and economy. One of the main topic in forest fire data studies deals with the detection, analysis and modelling of spatio-temporal patterns of clustering. Spatial patterns of forest fire locations, their sizes and their sequence in time are of great interest for fire prediction and for forest fire management planning and distribution in optimal way necessary resources. Currently, fires can be analyzed and monitored by using different statistical tools, for example, Ripley's k-function, fractals, Allan factor, scan statistics, etc. Some of them are adapted to temporal or spatial data and are either local or global. In the present study the main attention is paid to the application of geostatistical tools - variography and methods for the analysis of monitoring networks (MN) clustering techniques (topological, statistical and fractal measures), in order to detect and to characterize spatio-temporal forest fire patterns. The main studies performed include: a) analysis of forest fires temporal sequences; b) spatial clustering of forest fires; c) geostatistical spatial analysis of burnt areas. Variography was carried out both for temporal and spatial data. Real case study is based on the forest-fire event data from Canton of Ticino (Switzerland) for a period of 1969 to 2008. The results from temporal analysis show the presence of clustering and seasonal periodicities. Comprehensive analysis of the variograms shows an anisotropy in the direction 30° East-North where smooth changes are detected, while on the direction 30° North-West a greater variability was identified. The research was completed with an application of different MN analysis techniques including, analysis of distributions of distances between events, Morisita Index (MI), fractal dimensions (sandbox counting and box counting methods) and functional fractal dimensions, adapted and applied to characterize spatio-temporal events. The results are compared with the reference patterns (no spatial clustering) simulated within the natural validity domains (forests). The research was partly supported by SNSF projects IZAIZO-12777 and 200020-121835.
Vega Orozco, Carmen D.; Kanevski, Mikhail; Tonini, Marj; Conedera, Marc
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 infected corals surviving a disease season appear to play a major role in the re-introduction of the disease to the coral community in the following season.
Zvuloni, Assaf; Artzy-Randrup, Yael; Stone, Lewi; Kramarsky-Winter, Esti; Barkan, Roy; Loya, Yossi
With the increasing availability of massive observational and experimental data sets (across a wide variety of scientific disciplines) there is an increasing need to provide scientists with efficient computational tools to explore such data in a systematic manner. For example, techniques such as classification and clustering are now being widely used in astronomy to categorize and organize stellar objects into groups and catalogs, which in turn provide the impetus for scientific hypothesis formation and discovery (e.g., see Fayyad, Djorgovski and Weir (1996); or Cheeseman and Stutz (1996) or Fayyad and Smyth (1999) in a more general context). Data-driven exploration of massive spatio-temporal data sets is an area where there is particular need of data mining techniques. Scientists are overwhelmed by the vast quantities of data which simulations, experiments, and observational instruments can produce. Analysis of spatio-temporal data is inherently challenging, yet most current research in data mining is focused on algorithms based on more traditional feature-vector data representations. Scientists are often not particularly interested in raw grid-level data, but rather in the phenomena and processes which are ''driving'' the data. In particular, they are often interested in the temporal and spatial evolution of specific ''spatially local'' structures of interest, e.g., birth-death processes for vortices and interfaces in fluid-flow simulations and experiments, trajectories of extra-tropical cyclones from sea-level pressure data over the Atlantic and Pacific oceans, and sunspot shape and size evolution over time from daily chromospheric images of the Sun. The ability to automatically detect, cluster, and catalog such objects in principle provides an important ''data reduction front-end'' which can convert 4-d data sets (3 spatial and 1 temporal dimension) on a massive grid to a much more abstract representation of local structures and their evolution. In turn, these higher-level representations provide a general framework and basis for further scientific hypothesis generation and investigation, e.g., investigating correlations between local phenomena (such as storm paths) and global trends (such as temperature changes). In this work we focused on detecting and clustering trajectories of individual objects in massive spatio-temporal data sets. There are two primary technical problems involved. First, the local structures of interest must be detected, characterized, and extracted from the mass of overall data. Second, the evolution (in space and/or time) of these structures needs to be modeled and characterized in a systematic manner if the overall goal of producing a reduced and interpretable description of the data is to be met.
Gaffney, S; Smyth, P
The spatio-temporal distribution pattern of malaria in Yunnan Province, China was studied using a geographic information system technique. Both descriptive and temporal scan statistics revealed seasonal fluctuation in malaria incidences in Yunnan Province with only one peak during 1995-2000, and two apparent peaks from 2001 to 2005. Spatial autocorrelation analysis indicated that malaria incidence was not randomly distributed in the province. Further analysis using spatial scan statistics discovered that the high risk areas were mainly clustered at the bordering areas with Myanmar and Laos, and in Yuanjiang River Basin. There were obvious associations between Plasmodium vivax and Plasmodoium falciparum malaria incidences and climatic factors with a clear 1-month lagged effect, especially in cluster areas. All these could provide information on where and when malaria prevention and control measures would be applied. These findings imply that countermeasures should target high risk areas at suitable times, when climatic factors facilitate the transmission of malaria. PMID:19706922
Hui, Feng-Ming; Xu, Bing; Chen, Zhang-Wei; Cheng, Xiao; Liang, Lu; Huang, Hua-Bing; Fang, Li-Qun; Yang, Hong; Zhou, Hong-Ning; Yang, Heng-Lin; Zhou, Xiao-Nong; Cao, Wu-Chun; Gong, Peng
Despite a number of risk-factor studies in different countries, the epidemiology of Campylobacter colonization in broilers, particularly spatial dependencies, is still not well understood. A series of analyses (visualization and exploratory) were therefore conducted in order to obtain a better understanding of the spatial and temporal distribution of Campylobacter in the Danish broiler population. In this study, we observed a non-random temporal occurrence of Campylobacter, with high prevalence during summer and low during winter. Significant spatio-temporal clusters were identified in the same areas in the summer months from 2007 to 2009. Range of influence between broiler farms were estimated at distances of 9.6 km and 13.5 km in different years. Identification of areas and time with greater risk indicates variable presence of risk factors with space and time. Implementation of safety measures on farms within high-risk clusters during summer could have an impact in reducing prevalence. PMID:22814565
Chowdhury, S; Themudo, G E; Sandberg, M; Ersbøll, A K
Several studies have shown that wildfires in Portugal presenthigh temporal as well as high spatial variability (Pereira et al., 2005, 2011). The identification and characterization of spatio-temporal clusters contributes to a comprehensivecharacterization of the fire regime and to improve the efficiency of fire prevention and combat activities. The main goalsin this studyare: (i) to detect the spatio-temporal clusters of burned area; and, (ii) to characterize these clusters along with the role of human and environmental factors. The data were supplied by the National Forest Authority(AFN, 2011) and comprises: (a)the Portuguese Rural Fire Database, PRFD, (Pereira et al., 2011) for the 1980-2007period; and, (b) the national mapping burned areas between 1990 and 2009. In this work, in order to complement the more common cluster analysis algorithms, an alternative approach based onscan statistics and on the permutation modelwas used. This statistical methodallows the detection of local excess events and to test if such an excess can reasonably have occurred by chance.Results obtained for different simulations performed for different spatial and temporal windows are presented, compared and interpreted.The influence of several fire factors such as (climate, vegetation type, etc.) is also assessed. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005:"Synoptic patterns associated with large summer forest fires in Portugal".Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 AFN, 2011: AutoridadeFlorestalNacional (National Forest Authority). Available at http://www.afn.min-agricultura.pt/portal.
Costa, R.; Pereira, M. G.; Caramelo, L.; Vega Orozco, C.; Kanevski, M.
Three-oscillator systems with plasmodia of true slime mold, Physarum polycephalum, which is an oscillatory amoeba-like unicellular organism, were experimentally constructed and their spatio-temporal patterns were investigated. Three typical spatio-temporal patterns were found: rotation (R), partial in-phase (PI), and partial anti-phase with double frequency (PA). In pattern R, phase differences between adjacent oscillators were almost 120?. In pattern PI, two oscillators were in-phase and the third oscillator showed anti-phase against the two oscillators. In pattern PA, two oscillators showed anti-phase and the third oscillator showed frequency doubling oscillation with small amplitude. Actually each pattern is not perfectly stable but quasi-stable. Interestingly, the system shows spontaneous switching among the multiple quasi-stable patterns. Statistical analyses revealed a characteristic in the residence time of each pattern: the histograms seem to have Gamma-like distribution form but with a sharp peak and a tail on the side of long period. That suggests the attractor of this system has complex structure composed of at least three types of sub-attractors: a “Gamma attractor”—involved with several Poisson processes, a “deterministic attractor”—the residence time is deterministic, and a “stable attractor”—each pattern is stable. When the coupling strength was small, only the Gamma attractor was observed and switching behavior among patterns R, PI, and PA almost always via an asynchronous pattern named O. A conjecture is as follows: Internal/external noise exposes each pattern of R, PI, and PA coexisting around bifurcation points: That is observed as the Gamma attractor. As coupling strength increases, the deterministic attractor appears then followed by the stable attractor, always accompanied with the Gamma attractor. Switching behavior could be caused by regular existence of the Gamma attractor.
In this paper, a combined cross-section and time-series econometric analysis of Spanish regional growth is presented. This analysis operates with a database where the number of cross-sectional units is small for a typical panel of data, while the time dimension is clearly dominant. First, using recent techniques in the econometric analysis of panel data (both panel unit root and panel co-integration tests), a co-integrating relationship between the level of regional output and the level of regional input factors is found, and the steady-state equilibrium production function is estimated. Second, a dynamic spatio-temporal panel error correction model is used in order to describe the short-run regional growth adjustment process in space and time. As conclusion, it is possible to identify significant spatial effects in the Spanish regional growth after controlling for temporal variation of the implied variables.
Márquez, Miguel A.; Ramajo, Julián; Hewings, Geoffrey J. D.
Yes/No discrimination using spatio-temporal characteristics of EEG is investigated. For the correlation between EEG signals, we introduce two new representations useful in time domain calculation, synchronization rate and polarity. Using synchronization r...
M. Kim S. Shin Y. Song C. S. Ryu
We experimentally observe an intriguing phenomenon of complex spatio-temporal dynamics in a commercial optically pumped semiconductor laser with intracavity second harmonic generation. We numerically verify that the experimental results come from the total mode locking of TEM00 and higher-order modes with significant astigmatism. The scenarios of the spatio-temporal dynamics are quite similar to the phenomena in soft-aperture Kerr-lens mode locked Ti:sapphire lasers.
Lee, Y. C.; Liang, H. C.; Tung, J. C.; Su, K. W.; Chen, Y. F.; Huang, K. F.
We have proposed a new ictal source analysis approach by combining a spatio-temporal source localization approach, and causal interaction estimation technique. The FINE approach is used to identify neural electrical sources from spatio-temporal scalp-EEGs. The Granger causality estimation uses source waveforms estimated by FINE to characterize the causal interaction between the neural electrical sources in order to distinguish primary sources,
L. Ding; G. A. Worrell; T. D. Lagerlund; B. He
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
Sabrina Fossette; Victoria J. Hobson; Charlotte Girard; Beatriz Calmettes; Philippe Gaspar; Jean-Yves Georges; Graeme C. Hays
The spatio-temporal characteristics of the human visual system vary widely across the visual field. Recently, we have developed a display capable of sim-ulating arbitrary visual fields on high-resolution natural videos in real time by means of a gaze-contingent spatio-temporal filtering . While such a system can also be a useful tool for psychophysical research, our main motivation is to develop
Michael Dorr; Martin Böhme; Thomas Martinetz; Erhardt Barth
A theoretical analysis of the relationship between cognitive complexity and the perception of time and distance is presented and experimentally verified. Complex tasks produce high rates of mental representation which affect the subjective sense of duration and, through the subjective time scale, the percept of distance derived from dynamic visual cues (i.e., visual cues requiring rate integration). The analysis of the interrelationship of subjective time and subjective distance yields the prediction that, as a function of cognitive complexity, distance estimates derived from dynamic visual cues will be longer than the actual distance whereas estimates based on perceived temporal duration will be shorter than the actual distance. This prediction was confirmed in an experiment in which subjects (both pilots and non-pilots) estimated distances using either temporal cues or dynamic visual cues. The distance estimation task was also combined with secondary loading tasks in order to vary the overall task complexity. The results indicated that distance estimates based on temporal cues were underestimated while estimates based on visual cues were overestimated. This spatio-temporal distortion effect increased with increases in overall task complexity. 30 refs., 6 figs., 1 tab.
Barrett, C.L.; Weisgerber, S.A. (Los Alamos National Lab., NM (USA); Naval Weapons Center, China Lake, CA (USA))
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.
Dewers, Thomas A.
The main goal of the project supported in this grant is to contribute to the understanding of localized spatial and spatio-temporal structures far from thermodynamic equilibrium. Here we report on our progress in the study of two classes of systems. (1) We have started to investigate localized wave-pulses in binary-mixture convection. This work is based on our recently derived extension of the conventionally used complex Ginzburg-Landau equations. We are considering three regimes: Dispersion-less supercritical waves; strongly dispersive subcritical waves; and localized waves as bound states of fronts between dispersionless subcritical waves and the motionless conductive state. (2) We have completed our investigation of steady domain structures in which domains of structures with different wave numbers alternate, separated by domain walls. In particular, we have studied their regimes of existence and stability within the framework of a Ginzburg-Landau equation and have compared it to previous results. Those were based on a long-wavelength approximation, which misses certain aspects which turn out to be important for the stability of the domain structures in realistic situations. In addition, we give a description of our work on resonantly forced waves in two-dimensional anisotropic systems.
Shales and other mudstones are the most abundant rock types in sedimentary basins, yet have received comparatively little attention. Common as hydrocarbon seals, these are increasingly being targeted as unconventional gas reservoirs, caprocks for CO2 sequestration, and storage repositories for waste. The small pore and grain size, large specific surface areas, and clay mineral structures lend themselves to rapid reaction rates, high capillary pressures, and semi-permeable membrane behavior accompanying changes in stress, pressure, temperature and chemical conditions. Under far from equilibrium conditions, mudrocks display a variety of spatio-temporal self-organized phenomena arising from nonlinear thermo-mechano-chemo-hydro coupling. Beginning with a detailed examination of nano-scale pore network structures in mudstones, we discuss the dynamics behind such self-organized phenomena as pressure solitons in unconsolidated muds, chemically-induced flow self focusing and permeability transients, localized compaction, time dependent well-bore failure, and oscillatory osmotic fluxes as they occur in clay-bearing sediments. Examples are draw from experiments, numerical simulation, and the field. These phenomena bear on the ability of these rocks to serve as containment barriers. This work is funded by the US Department of Energy, Office of Basic Energy Sciences. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000
Dewers, T. A.
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.
Liu, Renyi; Liu, Nan; Bao, Weizheng; Zhu, Yan
Geo-scientific datasets often contain numerous and possibly systematically distributed gaps. This data fragmentation which may be due to instrument failures, sparse measurement protocols or unfavorable conditions (e.g. clouds or vegetation thickness in case of remote sensing data). It affects and often inhibits most statistical analysis which often require continuously sampled data points. Hence, gap filling is an undesired but often necessary task in geo-sciences. In cases where multivariate relationships are investigated they are often biased similar relationships which are used by the preceeding gap filling algorithm. In these cases univariate methods are needed. Kondrashov and Ghil (2006) proposed a gap filling approach which exploits the temporal (possibly multidimensional) patterns as identified by Singular Spectrum Analysis (SSA). Here we propose an univariate extension of this method in order to additionally consider the spatial processes and patterns underlying most geo-scientific data sets. The latter has been made possible by including a novel 2D-SSA approach recently introduced by Golyandina and Usevich (2010). Using both artificial and real-world test data we show that considering spatial and temporal patterns simultaneously improves the gapfilling substantially. We outperform the conventional approach particularly for large and systematically recurring gaps. Our method is fast, can be applied with a minimum of a priori assumptions on the data structure and is implemented ready-to-use in an open source software package. N. E. Golyandina and K. D. Usevich. 2D-extension of singular spectrum analysis: algorithm and elements of theory. In Matrix Methods: Theory, Algorithms, Applications, pages 449-474. World Scientific, 2010. D. Kondrashov and M. Ghil. Spatio-temporal filling of missing points in geophysical data sets. Nonlinear Processes in Geophysics, 13:151-159, 2006.
von Buttlar, J.; Zscheischler, J.; Mahecha, M. D.
Grasping an object involves shaping the hand and fingers in relation to the object’s physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation.
Riehle, Alexa; Wirtssohn, Sarah; Grun, Sonja; Brochier, Thomas
Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data from time-lapse microscopy are combined together to construct a transformed 3D volume. The trajectories are then generated from the minimal energy path
Quan Xue; Mark C. Leake
ABSTRACT: BACKGROUND: Development of the cerebral cortex requires highly specific spatio-temporal regulation of gene expression. It is proposed that transcriptome profiling of the cerebral cortex at various developmental time points or regions will reveal candidate genes and associated molecular pathways involved in cerebral corticogenesis. RESULTS: Serial analysis of gene expression (SAGE) libraries were constructed from C57BL\\/6 mouse cerebral cortices of
King-Hwa Ling; Chelsee A Hewitt; Tim Beissbarth; Lavinia Hyde; Kakoli Banerjee; Pike-See Cheah; Ping Z Cannon; Christopher N Hahn; Paul Q Thomas; Gordon K Smyth; Seong-Seng Tan; Tim Thomas; Hamish S Scott
Spatio-temporal clustering of microseismicity in the central forearc of the Hellenic Subduction Zone in the area of Crete is investigated. Data for this study were gathered by temporary short period networks which were installed on the islands of Crete and Gavdos between 1996 and 2004. The similarity of waveforms is quantified systematically to identify clusters of microseismicity. Waveform similarities are calculated using an adaptive time window containing both the P- and S-wave onsets. The cluster detection is performed by applying a single linkage approach. Clusters are found in the interplate seismicity as well as in the intraplate seismicity of the continental crust in the region of the transtensional Ptolemy structure. The majority of the clusters are off the southern coast of Crete, in a region of elevated intraplate microseismic activity within the Aegean plate. Clusters in the Gavdos region are located at depths compatible with the plate interface while cluster activity in the region of the Ptolemy trench is distributed along a nearly vertical structure throughout the crust extending down to the plate interface. Most clusters show swarm-like behaviour with seismic activity confined to only a few hours or days, without a dominant earthquake and with a power law distribution of the interevent times. For the largest cluster, precise relocations of the events using travel time differences of P- and S-waves derived from waveform cross correlations reveal migration of the hypocenters. This cluster is located in the region of the Ptolemy trench and migration occurs along the strike of the trench at ˜ 500 m/day. Relocated hypocenters as well as subtle differences in the waveforms suggest an offset between the hypocenters and thus the activation of distinct patches on the rupture surface. The observed microseismicity patterns may be related to fluids being transported along the plate interface and escaping towards the surface in zones of crustal weakness (Ptolemy structure), triggering swarm-like cluster activity along its way.
Becker, Dirk; Meier, Thomas; Rische, Martina; Bohnhoff, Marco; Harjes, Hans-Peter
Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.
Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald
The intensive developments of terawatt Ti:Sa lasers permit to extend laser-plasma interactions into the relativistic regime, providing very-short electron or proton bunches. Experimental researches developed at the interface of laser physics and radiation biology, using the combination of sub-picosecond electron beams in the energy range 2-15 MeV with femtosecond near-IR optical pulses might conjecture the real-time investigation of penetrating radiation effects. A perfect synchronization between the particle beam (pump) and optical beam at 820 nm (probe) allows subpicosecond time resolution. This emerging domain involves high-energy radiation femtochemistry (HERF) for which the early spatial energy deposition is decisive for the prediction of cellular and tissular radiation damages. With vacuum-focused intensities of 2.7 x 1019 W cm-2 and a high energy electron total charge of 2.5 nC, radiation events have been investigated in the temporal range 10-13 - 10-10s. The early radiation effects of secondary electron on biomolecular sensors may be investigated inside sub-micrometric ionisation, considering the radial direction of Gaussian electron bunches. It is shown that short range electron-biosensor interactions lower than 10 A take place in nascent track structures triggered by penetrating radiation bunches. The very high dose delivery 1013 Gy s-1 performed with laser plasma accelerator may challenge our understanding of nanodosimetry on the time scale of molecular target motions. High-quality ultrashort penetrating radiation beams open promising opportunities for the development of spatio-temporal radiation biology, a crucial domain of cancer therapy, and would favor novating applications in nanomedicine such as highly-selective shortrange pro-drug activation.
Gauduel, Y. A.; Faure, J.; Malka, V.
Analysis of pedobarographical data requires geometric identification of specific anatomical areas extracted from recorded plantar pressures. This approach has led to ambiguity in measurements that may underlie the inconsistency of conclusions reported in pedobarographical studies. The goal of this study was to design a new analysis method less susceptible to the projection accuracy of anthropometric points and distance estimation, based on rarely used spatio-temporal indices. Six pedobarographic records per person (three per foot) from a group of 60 children aged 11-12 years were obtained and analyzed. The basis of the analysis was a mutual relationship between two spatio-temporal indices created by excursion of the peak pressure point and the center-of-pressure point on the dynamic pedobarogram. Classification of weight-shift patterns was elaborated and performed, and their frequencies of occurrence were assessed. This new method allows an assessment of body weight shift through the plantar pressure surface based on distribution analysis of spatio-temporal indices not affected by the shape of this surface. Analysis of the distribution of the created index confirmed the existence of typical ways of weight shifting through the plantar surface of the foot during gait, as well as large variability of the intrasubject occurrence. This method may serve as the basis for interpretation of foot functional features and may extend the clinical usefulness of pedobarography. PMID:21782441
Latour, Ewa; Latour, Marek; Arlet, Jaros?aw; Adach, Zdzis?aw; Bohatyrewicz, Andrzej
According to Water Framework Directive requirements, Member States must identify and analyze effects derived from human pressures in aquatic systems. As different kind of pressures can impact water bodies at different scales, analyses of spatio-temporal evolution of water bodies becomes essential in order to understand ecosystem responses. In this investigation, an analysis of spatio-temporal evolution of sedimentary metal pollution (Cd, Cr, Cu, Hg, Ni, Pb, Zn) in 12 Basque estuaries (Bay of Biscay) is presented. Data collected in extensive sampling surveys is the basis for the GIS-based statistical approach used. The implementation of pollution abatement measures is reflected in a long-term decontamination process, mostly evident in estuaries with highest historical sediment pollution levels. Spatial evolution is determined by either naturally occurring or human driven processes. Such spatial processes are more obviously being reflected in estuaries with lower historical sediment pollution levels. PMID:23218773
Legorburu, Irati; Rodríguez, José Germán; Borja, Angel; Menchaca, Iratxe; Solaun, Oihana; Valencia, Victoriano; Galparsoro, Ibon; Larreta, Joana
This research demonstrates the application of association rule mining to spatio-temporal data. Association rule mining seeks to discover associations among transactions encoded in a database. An association rule takes the form A ? B where A (the antecedent) and B (the consequent) are sets of predicates. A spatio-temporal association rule occurs when there is a spatio-temporal relationship in the antecedent
Jeremy L. Mennis; Jun Wei Liu
The recent concerns for world-wide extreme events related to climate change have motivated the development of large scale models that simulate the global water cycle. In this context, analysis of hydrological extremes is important and requires the adaptation of identification methods used for river basin models. This paper presents two methodologies that extend the tools to analyze spatio-temporal drought development and characteristics using large scale gridded time series of hydrometeorological data. The methodologies are classified as non-contiguous and contiguous drought area analyses (i.e. NCDA and CDA). The NCDA presents time series of percentages of areas in drought at the global scale and for pre-defined regions of known hydroclimatology. The CDA is introduced as a complementary method that generates information on the spatial coherence of drought events at the global scale. Spatial drought events are found through CDA by clustering patterns (contiguous areas). In this study the global hydrological model WaterGAP was used to illustrate the methodology development. Global gridded time series of subsurface runoff (resolution 0.5°) simulated with the WaterGAP model from land points were used. The NCDA and CDA were developed to identify drought events in runoff. The percentages of area in drought calculated with both methods show complementary information on the spatial and temporal events for the last decades of the 20th century. The NCDA provides relevant information on the average number of droughts, duration and severity (deficit volume) for pre-defined regions (globe, 2 selected hydroclimatic regions). Additionally, the CDA provides information on the number of spatially linked areas in drought, maximum spatial event and their geographic location on the globe. Some results capture the overall spatio-temporal drought extremes over the last decades of the 20th century. Events like the El Niño Southern Oscillation (ENSO) in South America and the pan-European drought in 1976 appeared clearly in both analyses. The methodologies introduced provide an important basis for the global characterization of droughts, model inter-comparison of drought identified from global hydrological models and spatial event analyses.
Corzo Perez, G. A.; van Huijgevoort, M. H. J.; Voß, F.; van Lanen, H. A. J.
Generalizable process knowledge on hillslope hydrological dynamics is still very poor, yet indispensable for numerous theoretical and practical applications. To gain insight into the organization of hillslope hydrological dynamics we intercompared 90 observations of shallow water table dynamics at three neighboring large-scale (33 × 75 m) hillslopes with similar slope, aspect, curvature, geologic, and pedologic properties but differences in vegetation cover (grassland, coniferous forest, and mixed forest) over a time period of 9 months. High-resolution measurements of water table fluctuations, rainfall, and discharge in the creek at the foot of all hillslopes allowed a good system characterization. The aim of this study was to explore the spatio-temporal variability of water table fluctuations within and between hillslopes, the effect of event and antecedent characteristics on the observed dynamics, and how the hillslope subsurface flow (SSF) response is reflected in the runoff response. To intercompare the SSF behavior we conducted an event-based analysis of the percentage of well activation, several metrics characterizing the shape and timing of the water table response curves, rainfall characteristics, antecedent wetness conditions, and several runoff response metrics. The analysis reveals that there are distinct differences in SSF response between the grassland hillslope and the forested hillslopes, with a lower frequency of well activation and absolute water table rise at the grassland hillslope. Second, spatial patterns of water table dynamics differ between wet fall/winter/spring (predominantly saturation of the lower part of the hillslope, weaker water table response, and slower response times) and dry summer conditions (whole-hillslope activation but higher spatial variability, generally stronger water table dynamics, and quicker response times). The observed seasonally changing water table dynamics suggest the development of a preferential flow network during high-intensity rainstorms under dry summer conditions. Third, catchment runoff is strongly driven by hillslope dynamics, yet contrasting hydrographs during events with similar hillslope dynamics indicate the influence of additional processes. Overall, the observed high spatio-temporal variability of seemingly homogeneous hillslopes calls for rethinking of current monitoring strategies and developing and testing new conceptual models of hillslope hydrologic processes.
Bachmair, S.; Weiler, M.; Troch, P. A.
We present a novel spatio-temporal descriptor to efficiently represent a video object for the purpose of content-based video retrieval. Features from spatial along with temporal information are integrated in a unified framework for the purpose of retrieval of similar video shots. A sequence of orthogonal processing, using a pair of 1-D multiscale and multispectral filters, on the space-time volume (STV)
A. Dyana; Sukhendu Das
Intensity and spatio-temporal variability of fluvial sediment transfers and mechanical fluvial denudation were analyzed in the periglacial Latnjavagge catchment (9km2; 950–1440m a.s.l.; 68.20N, 18.30E) in Arctic-oceanic northernmost Swedish Lapland. The present-day rates of fluvial sediment transfer are low. The mean annual mechanical fluvial denudation rate at the inlet of lake Latnjajaure, as calculated after five years of process monitoring (2000–2004),
Achim A. Beylich; Olga Sandberg; Ulf Molau; Susan Wache
1.?Flows of nutrients and energy across ecosystem boundaries have the potential to subsidize consumer populations and modify the dynamics of food webs, but how spatio-temporal variations in autochthonous and allochthonous resources affect consumers' subsidization remains largely unexplored. 2.?We studied spatio-temporal patterns in the allochthonous subsidization of a predator living in a relatively simple ecosystem. We worked on Bylot Island (Nunavut, Canada), where arctic foxes (Vulpes lagopus L.) feed preferentially on lemmings (Lemmus trimucronatus and Dicrostonyx groenlandicus Traill), and alternatively on colonial greater snow geese (Anser caerulescens atlanticus L.). Geese migrate annually from their wintering grounds (where they feed on farmlands and marshes) to the Canadian Arctic, thus generating a strong flow of nutrients and energy across ecosystem boundaries. 3.?We examined the influence of spatial variations in availability of geese on the diet of fox cubs (2003-2005) and on fox reproductive output (1996-2005) during different phases of the lemming cycle. 4.?Using stable isotope analysis and a simple statistical routine developed to analyse the outputs of a multisource mixing model (SIAR), we showed that the contribution of geese to the diet of arctic fox cubs decreased with distance from the goose colony. 5.?The probability that a den was used for reproduction by foxes decreased with distance from the subsidized goose colony and increased with lemming abundance. When lemmings were highly abundant, the effect of distance from the colony disappeared. The goose colony thus generated a spatial patterning of reproduction probability of foxes, while the lemming cycle generated a strong temporal variation of reproduction probability of foxes. 6.?This study shows how the input of energy owing to the large-scale migration of prey affects the functional and reproductive responses of an opportunistic consumer, and how this input is spatially and temporally modulated through the foraging behaviour of the consumer. Thus, perspectives of both landscape and foraging ecology are needed to fully resolve the effects of subsidies on animal demographic processes and population dynamics. PMID:22268371
Giroux, Marie-Andrée; Berteaux, Dominique; Lecomte, Nicolas; Gauthier, Gilles; Szor, Guillaume; Bêty, Joël
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 of different factors that interrelate both directly and through density dependence. This highlights the importance of performing more comprehensive studies to reveal combined effects and complex relationships that help us to better understand the mechanisms underlying population dynamics. PMID:21815891
Tablado, Zulima; Revilla, Eloy; Palomares, Francisco
Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal autoregressive filter models are considered, for a prediction of EEG signal values. Thus Signal features values for successive, short, quasi stationary segments of brain electrical activity can be obtained, with the objective of detecting distinct changes prior to impending epileptic seizures. Furthermore long term recordings gained during presurgical diagnostics in temporal lobe epilepsy are analyzed and the predictive performance of the extracted features is evaluated statistically. Therefore a Receiver Operating Characteristic analysis is considered, assessing the distinguishability between distributions of supposed preictal and interictal periods.
Gollas, Frank; Tetzlaff, Ronald
Chryssomalakos and Okon, through a uniqueness analysis, have strengthened the Vilela Mendes suggestion that the immunity to infinitesimal perturbations in the structure constants of a physically-relevant Lie algebra should be raised to the status of a physical principle. Since the Poincaré-Heisenberg algebra does not carry the indicated immunity, it is suggested that the Lie algebra for the interface of the gravitational and quantum realms (IGQR) is its stabilized form. It carries three additional parameters: a length scale pertaining to the Planck/unification scale, a second length scale associated with cosmos, and a new dimensionless constant. Here, we show that the adoption of the stabilized Poincaré-Heisenberg algebra (SPHA) for the IGQR has the immediate implication that a "point particle" ceases to be a viable physical notion. It must be replaced by objects which carry a well-defined, representation space-dependent, minimal spatio-temporal extent. The ensuing implications have the potential, without spoiling any of the successes of the Standard Model of particle physics, to resolve the cosmological constant problem while concurrently offering a first-principle hint as to why there exists a coincidence between cosmic vacuum energy density and neutrino masses. The main theses which the essay presents is the following: an extension of the present-day physics to a framework which respects SPHA should be seen as the most natural and systematic path towards gaining a deeper understanding of outstanding questions, if not providing answers to them.
Ahluwalia-Khalilova, D. V.
The temporal deployment of attention to tactile stimuli delivered to the same or to a symmetrical position of the body was assessed in 6 Right-Brain Damaged (RBD) patients with left tactile extinction and 6 healthy controls. Two different tasks called Temporal (T) and Spatio-Temporal (ST) extinction were used. In the T task single or double electro tactile stimuli were delivered to the same point to the left or, in separate blocks, to the right index finger. Double stimuli were separated by different Stimulus Onset Asynchronies (SOAs). In the ST task, stimuli could be single (left or right) or double (left and right). Double stimuli were delivered to the index finger of both hands simultaneously or sequentially. In both tasks subjects were asked to report the number of the stimuli they perceived. In the ST task, subjects were also requested to report the stimuli location. Results show that in both tasks RBD patients' detection of left sided stimuli was significantly lower than of right sided stimuli detection, mainly at shortest SOAs. Moreover, detection of left sided stimuli was higher when two stimuli were delivered in sequence and in symmetrical body areas and in different sides of the space than when stimuli were delivered in sequence in the same body area. Results suggest that the interaction between spatial and temporal variables enhances the ability of tactile extinction patients to detect left sided stimuli. PMID:16509105
Guerrini, Chiara; Aglioti, Salvatore M
Early in his career, Bela Julesz introduced the stereo matching problem while working at Bell Labs on an encryption project. The common belief at that time was based on Wheatstone"s proposal that 2-D space perception of form preceded coding of disparity for 3-D space perception. However, with the random-dot stereogram, Julesz demonstrated that stereoscopic depth could be perceived in the absence of any identifiable objects or perspective cues available to either eye alone. This work inspired many algorithms for binocular matching including the smoothness constraint. Wheatstone"s and Julesz"s proposals as to whether binocular matches are solved at a low level, prior to form perception, or after form is perceived are still debated. We have examined spatio-temporal interactions that promote binocular matches and yield percepts of smooth surfaces in depth. We identified low-level processes for estimating depth differences between surface patches that require their proximity in both time and space, and a high level process that minimizes their depth differences when surface texture of adjacent patches appears to belong to the same surface. This suggests that the stereo-matching solution is influenced by a priori assumptions about the surface configuration of the scene and by monocular and binocular spatial cues.
Schor, Clifton M.; Zhang, Zhi-Lei
The use of real-time feedback has expanded fMRI from a brain probe to include potential brain interventions with significant therapeutic promise. However, whereas time-averaged blood oxygenation level-dependent (BOLD) signal measurement is usually sufficient for probing a brain state, the real-time (frame-to-frame) BOLD signal is noisy, compromising feedback accuracy. We have developed a new real-time processing technique (STAR) that combines noise-reduction properties of multi-voxel (e.g., whole-brain) techniques with the regional specificity critical for therapeutics. Nineteen subjects were given real-time feedback in a cognitive control task (imagining repetitive motor activity vs. spatial navigation), and were all able to control a visual feedback cursor based on whole-brain neural activity. The STAR technique was evaluated, retrospectively, for five a priori regions of interest in these data, and was shown to provide significantly better (frame-by-frame) classification accuracy than a regional BOLD technique. In addition to regional feedback signals, the output of the STAR technique includes spatio-temporal activity maps (movies) providing insight into brain dynamics. The STAR approach offers an appealing optimization for real-time fMRI applications requiring an anatomically-localized feedback signal.
Magland, Jeremy F.; Tjoa, Christopher W.; Childress, Anna Rose
One potential way to reduce patient and staff x-ray fluoroscopy dose is to reduce the quantum exposure to the detector and compensate the additional noise with digital filtering. A new filtering method, spatio-temporal filtering with object detection, is described that reduces noise while minimizing motion and spatial blur. As compared to some conventional motion-detection filtering schemes, this object-detection method incorporates additional a priori knowledge of image content; i.e. much of the motion occurs in isolated long thin objects (catheters, guide wires, etc.). The authors create object-likelihood images and use these to control spatial and recursive temporal filtering such as to reduce blurring the objects of interest. They use automatically computed receiver operating characteristic (ROC) curves to optimize the object-likelihood enhancement method and determine that oriented matched filter kernels with 4 orientations are appropriate. The matched filter kernels are simple projected cylinders. The authors demonstrate the method on several representative x-ray fluoroscopy sequences to which noise is added to simulate very low dose acquisitions. With processing, they find that noise variance is significantly reduced with slightly less noise reduction near moving objects. They estimate an effective exposure reduction greater than 80%.
Aufrichtig, R. [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering; Wilson, D.L. [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering]|[University Hospitals of Cleveland, OH (United States). Dept. of Radiology
Two major factors determine the spatial and temporal distributions of fecal indicator bacteria (FIB) at a given beach: local circulation & mixing patterns, and bacterial inactivation rates. High frequency and spatial resolution bacterial sampling combined with measurements of physical processes can be used to infer inactivation rates, enabling differentiation between dilution & mortality as factors driving variability in nearshore FIB abundance. A FIB sampling experiment (HB06) took place on 16 October 2006, at Huntington State Beach, a site selected due to its persistent problems with FIB pollution. Water samples were taken at 20-minute intervals (from 6:50am to 11:50am) at ten locations; four in an alongshore transect spanning 1 km at the shoreline, and the remainder in a 300-m long cross-shore transect. All samples were analyzed for FIB concentration (Total Coliforms, E. coli & Enterococci) and, for a subset, species level Enterococcus composition was determined. As part of the HB06 experiment, currents, temperature, waves, and chlorophyll fluorescence were measured simultaneously in the cross-shore direction with rapid CTD casts 300 m offshore. Results indicate that E. coli and Enterococcus concentrations exhibit exponential decreases with time, with smaller decay rates associated with depth and with sites in the Talbert Marsh and Santa Ana River. FIB concentrations are also noticeably lower farther offshore (300 m). Spatio-temporal patterns in FIB concentration will be presented in conjunction with the nearshore physical data allowing the relationship between physical dynamics and biological variability to be addressed.
Rippy, M. A.; Feddersen, F.; Leichter, J.; Omand, M.; Moore, D. F.; McGee, C.; Franks, P. J.
The time evolution of the axial velocity of a metastable Xe+ ion was examined in the crossed-field discharge of a PPS100-ML Hall thruster fired at 250 V by means of laser-induced fluorescence spectroscopy at 834.72 nm. A pulse-counting detection technique was employed to achieve a time resolution of 0.1 µs. A periodic break of 10 µs duration of the anode current is used to stabilize the discharge and allow the investigation of both forced and natural plasma oscillations. Measurements were carried out along the channel axis throughout the region of large magnetic field strength. The mean ion flow velocity was found to oscillate at the discharge breathing mode frequency of about 21 kHz. By contrast, the ion velocity dispersion appears not to depend on time, which suggests a strong correlation between ionization and acceleration processes. The spatio-temporal behavior of the electric field was computed from experimental data using a Lagrangian description of the ion fluid motion. As expected, the field amplitude varies significantly at 21 kHz. More surprisingly, an electric field front seems to propagate periodically from the exterior toward the interior of the discharge chamber with a speed close to the thermal speed of the Xe atom.
Mazouffre, S.; Bourgeois, G.
We analyze spatio-temporal patterns in rotation angles of double-couple-constrained mechanisms of aftershocks of the 1992 Landers earthquake. The rotation angles provide information on the distribution of source geometries in different regions of space and time with respect to the mainshock focal mechanism. The results indicate that the mechanisms of the early aftershocks are more scattered and less aligned with the mainshock than those of the long-term events. This is most pronounced around the northern end of the Landers rupture, least pronounced around the central section, and intermediate around the southern end of the rupture. The relatively large scatter and misalignment of the mean rotation angles of the early focal mechanisms around the edges of the Landers rupture suggest possible volumetric earthquake strain in these regions. The results may reflect isotropic source terms produced by dynamic generation of rock damage. Synthetic tests indicate that the observed differences in the rotation distributions of the early and long-term events around the end regions of the Landers rupture can result from neglecting in the inversion process isotropic components that are 0.03-0.15 of the total event moments.
Ross, Z. E.; Ben-Zion, Y.
The structural and functional organization and the spatio-temporal interrelations of three sympatric vole species (Microtus oeconomus, Clethrionomys, rutilus, and C. rufocanus) were analyzed on territories different in the type of their functional significance to the animals (survival stations, zones of temporary dispersal, and transit zones). The study was conducted in the environs of the Iremel massif (54 degrees 31'25" N 58 degrees 50'18" E) in 1979-1981, in four 1 ha marking-areas in four different altitudinal zones. It is shown that the abundance and demographic structure is different for each species pair in each area, whereas their dynamics in synchronous. The overlap of niches in two Clethrionomys species is small and cannot cause their competition for food. The distribution of voles within the areas is usually independent, but has some peculiarities depending on the type of territory usage by the animals. Preferred microterritories that help species to avoid competition are revealed for each species to occur in different areas. These are cases of spatial separation, not of ecological isolation of sympatric species. Spatial and temporal division of environmental resources is controlled by mechanisms that have developed in the process of the community's evolution. PMID:18257290
Zhigal'ski?, O A
This paper deals with multivariable control problem of spatio-temporal systems modelled by non linear partial differential equations (PDEs). SISO control of distributed parameter systems (DPS) can be achieved either by late or by early approaches. In practice, there are mainly two reasons why MIMO control of DPS, which can provide an analytical law of a distributed controller, could be impossible
Ova BOUBAKER; F. Cherif
This paper introduces a video copy detection system which efficiently matches individual frames and then verifies their spatio-temporal consistency. The approach for matching frames relies on a recent local feature indexing method, which is at the same time robust to significant video transformations and efficient in terms of memory usage and computation time. We match either keyframes or uniformly sampled
Matthijs Douze; Herve Jegou; Cordelia Schmid
Moving objects equipped with locating devices can re- port their locations periodically to data stream sewers. With the pervasiveness of moving objects, one single sewer cannot support all objects and queries in a wide area. As a result, multiple spatio-temporal data stream management systems must be deployed and thus result in a sewer net- work. It is vital for sewers
Xiaopeng Xiong; Hicham G. Elmongui; Xiaoyong Chai; Walid G. Aref
This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.
Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter
This paper presents a formal theory for reason- ing about motion of spatial entities, in a qualita- tive framework. Taking over a theory intended for spatial entities, we enrich it to achieve a theory whose intended models are spatio-temporal enti- ties, an idea sometimes proposed by philosophers or AI authors but never fully exploited. We show what kind of properties
Nitrate (NO3-) is considered the most prevalent contaminant in groundwater (GW). NO3- in GW shows significant spatio-temporal variability which comes from interaction among multiple geophysical factors such as source availability (land use), thickness and composition of the vadose zone, types of aquifers (confined or unconfined), aquifer heterogeneity (geological and alluvial), and precipitation characteristics etc. The present work seeks to describe
D. Dwivedi; B. P. Mohanty
Planning and assessment in maintenance, renewal and working status of oil field facilities and oil production management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with object-oriented spatio- temporal data models that can restore, manage, query and visualize various historic and updated basic information concerning with oil field facilities and production activities as well
L. H. Cui; S. J. Xu
Do police firearm arrests reduce later shootings in nearby locations and in the days immediately following the arrest? This question is examined at a more detailed level than in previous work in order to better describe the spatio-temporal dynamics linking these two event types. All firearm arrests (n = 5,687) and shootings (n = 5,870) in Philadelphia from 2004 to
Brian R. Wyant; Ralph B. Taylor; Jerry H. Ratcliffe; Jennifer Wood
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
Anna Litvak-Hinenzon; Lewi Stone
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
M. T. Marshall; C. C. Funk; J. Michaelsen
3D reconstruction has been widely used in many important applications. While extensive research has been done in 3D reconstruction, several key issues are still open and the precision of the recovered regions is still far from satisfaction. In this paper, we propose a novel approach to selecting regions of interest in video frames by analyzing multiple spatio-temporal characteristics and reconstructing
Xian Xiao; Changsheng Xu; Yong Rui
We used magnetic source imaging (MSI) to investigate the spatio-temporal patterns of brain activity associated with line bisection judgments and double simultaneous visual stimulation in 14 healthy adults. Consistent with lesion and hemodynamic neuroimaging studies, we found the greatest number of activity sources in right inferior parietal cortex. These sources were most prominent, on average, between 200 and 300ms after
R. L Billingsley; P. G Simos; S Sarkari; J. M Fletcher; A. C Papanicolaou
Hypermedia is currently the trend in delivering information composed of various forms of media. Up to now most systems lack the ability to present the user with hypermedia information containing various media that have specific spatio-temporal relations. In this paper we propose and describe a model that can describe such kinds of hypermedia presentations. The core of the model is
C. Bouras; V. Kapoulas; V. Ouzounis; P. Spirakis; A. Tatakis
The rapidity with which digital information, particularlyvideo, is being gener- ated, has necessitated the development of tools for efficien t search of these media. Content based visual queries have been primarily focused on still image retrieval. In this paper, we propose a novel, interactive system on the W eb, based on the visual paradigm, with spatio-temporal attributes playinga key role
Shih-Fu Chang; William Chen; Horace J. Meng; Hari Sundaram
Neural circuits are refined in an experience-dependent manner during early postnatal development. How development modulates the spatio-temporal propagation of activity through cortical circuits is poorly understood. Here we use voltage-sensitive dye imaging (VSD) to show that there are significant changes in the spatio-temporal patterns of intracortical signals in primary visual cortex (V1) from postnatal day 13 (P13), eye opening, to P28, the peak of the critical period for rodent visual cortical plasticity. Upon direct stimulation of layer 4 (L4), activity spreads to L2/3 and to L5 at all ages. However, while from eye opening to the peak of the critical period, the amplitude and persistence of the voltage signal decrease, peak activation is reached more quickly and the interlaminar gain increases with age. The lateral spread of activation within layers remains unchanged throughout the time window under analysis. These developmental changes in spatio-temporal patterns of intracortical circuit activation are mediated by differences in the contributions of excitatory and inhibitory synaptic components. Our results demonstrate that after eye opening the circuit in V1 is refined through a progression of changes that shape the spatio-temporal patterns of circuit activation. Signals become more efficiently propagated across layers through developmentally regulated changes in interlaminar gain.
Griffen, Trevor C.; Wang, Lang; Fontanini, Alfredo; Maffei, Arianna
Space-time communications can help combat fading and hence can significantly increase the capacity of ad hoc net- works. Cooperative diversity or virtual antenna arrays facilitate spatio-temporal communications without actually requiring the de- ployment of physical antenna arrays. Virtual MISO entails the si- multaneous transmission of appropriately encoded information by multiple nodes to effectively emulate a transmission on an antenna array.
Gentian Jakllari; Srikanth V. Krishnamurthy; Michalis Faloutsos; Prashant V. Krishnamurthy; Özgür Erçetin
A suspended aid is popular for learning circles and for refining circle technique on pommel horse. The aim of this study was to investigate the effect of using a suspended aid on the biomechanical characteristics of circles. This first study focused specifically on the spatio-temporal characteristics of circles. Eighteen gymnasts performed three sets of 10 circles with and without a
Toshiyuki Fujihara; Pierre Gervais
Recently it is proposed that theta phase precession contributes to the encoding and memory of the temporal sequence of experience in the hippocampus. By using a hippocampal network model, the potential advantage of theta phase precession on encoding and storage of temporal sequence has been shown in our previous work. But the ability on memory and retrieval for spatio- temporal
Zhihua Wu; Yoko Yamaguchi
This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE (catch per unit effort). We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales, with a combination of four levels of temporal scale (weekly, biweekly, monthly, and bimonthly) and six levels of spatial scale (longitude×latitude: 0.5°×0.5°, 0.5°×1°, 0.5°×2°, 1°×0.5°, 1°×1°, and 1°×2°). We applied generalized additive models and generalized linear models to analyze the 24 scenarios for CPUE standardization, and then the differences in the standardized CPUE among these scenarios were quantified. This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE. However, at a fine temporal scale (weekly) different spatial scales yielded similar results for standardized CPUE. The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management. To identify a cost-effective spatio-temporal scale for data collection, we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.
Tian, Siquan; Han, Chan; Chen, Yong; Chen, Xinjun
In many remote sensing applications it is important to use multiple sensors to be able to understand the major spatio-temporal distribution patterns of an observed phenomenon. A particular remote sensing application addressed in this study is estimation of an important property of atmosphere, called Aerosol Optical Depth (AOD). Remote sensing data for AOD estimation are collected from ground and satellite-based
Vladan Radosavljevic; Slobodan Vucetic; Zoran Obradovic
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
J. C. Mosher; P. S. Lewis; R. m. Leahy
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…
In this study we describe an ambulatory system for estimation of spatio-temporal parameters during long periods of walking. This original method based on wavelet analysis is proposed to compute the values of temporal gait parameters from the angular velocity of lower limbs. Based on a mechanical model, the medio-lateral rotation of the lower limbs during stance and swing, the stride
K. Aminian; B. Najafi; C. Büla; P.-F. Leyvraz; Ph. Robert
Recently developed statistical methods for background subtraction have made increasingly complicated environ- ments amenable to automated analysis. Here we illustrate results for spatio-temporal background modeling, anomaly detection, shape description, and object localization on rel- evant parts of the PETS2005 data set. The results are ana- lyzed both to distinguish between difficulties caused by dif- ferent challenges within the data set,
Richard Souvenir; John Wright; Robert Pless
Abstract. Querying about the time-varying locations of moving objects is particularly cumbersome in environments composed of a very large number of distributed spatio temporal database servers. In particular, searching for a speci c object can require to visit each server. In this paper we propose a strategy to avoid such an exhaustive search that is based on the use of
Mauricio Marín; Andrea Rodríguez; Tonio Fincke; Carlos Román
A linear mixed effects (LME) model previously used for a spatial analysis of mortality data for a single time period is extended to include time trends and spatio-temporal interactions. This model includes functions of age and time period that can account for increasing and decreasing death rates over time and age, and a change-point of rates at a predetermined age. A geographic hierarchy is included that provides both regional and small area age-specific rate estimates, stabilizing rates based on small numbers of deaths by sharing information within a region. The proposed log-linear analysis of rates allows the use of commercially available software for parameter estimation, and provides an estimator of overdispersion directly as the residual variance. Because of concerns about the accuracy of small area rate estimates when there are many instances of no observed deaths, we consider potential sources of error, focusing particularly on the similarity of likelihood inferences using the LME model for rates as compared to an exact Poisson-normal mixed effects model for counts. The proposed LME model is applied to breast cancer deaths which occurred among white women during 1979-1996. For this example, application of diagnostics for multiparameter likelihood comparisons suggests a restriction of age to a minimum of either 25 or 35, depending on whether small area rate estimates are required. Investigation into a convergence problem led to the discovery that the changes in breast cancer geographic patterns over time are related more to urbanization than to region, as previously thought. Published in 2000 by John Wiley & Sons, Ltd. PMID:10960851
Pickle, L W
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.
Zöller, G.; Ben-Zion, Y.
Through adulthood the rodent subventricular zone (SVZ) stem cell niche generates new olfactory bulb interneurons. We had previously reported that the number of new neurons produced in the SVZ declines through aging; however, age-related changes due specifically to the SVZ neural stem cell (NSC) population have not been fully characterized. Here, we conducted a spatio-temporal evaluation of adult SVZ NSCs. We assessed ventricle-contacting NSCs, which together with ependymal cells form regenerative units (pinwheels) along the lateral wall of the lateral ventricle. Based on their apical GFAP+ process, individual NSCs were identified across the ventricle surface using serial reconstruction of the SVZ. We observed an 86% decline in total NSCs per mm2 of intact ependyma in 2-year old versus 3-month old mice, with fewer NSC processes within each aged pinwheel. This resulted in an associated 78% decline in total pinwheel units per mm2. Regional analysis along the lateral ventricle surface revealed that the age-dependent decline of NSCs and pinwheels is spatially uniform, and ultimately maintains the conserved ratio of olfactory bulb interneuron subtypes generated in young mice. However, the overall neurogenic output of the aged SVZ is reduced. Surprisingly, we found no significant change in the number of actively proliferating NSCs per mm2 of ventricle surface. Instead, our data reveal that although the total NSC number, pinwheel units and NSCs per pinwheel decline with age, the percentage of actively, mitotic NSCs increases, indicating that age-related declines in SVZ-mediated olfactory bulb neurogenesis occur downstream of NSC proliferation.
Shook, Brett A.; Manz, David H.; Peters, John J.; Kang, Sangwook; Conover, Joanne C.
Beyond removing forest, deforestation in the Amazon creates a lot of forest edges. These edges change the microclimate and ecosystem dynamics of the remaining tropical rain forests, contributing directly to forest degradation in the Amazon. Edge-induced changes such as tree mortality and fire vulnerability occur as a function of distance from edges and time since forest fragmentation. New edges are created and older edges are eliminated constantly as deforestation advances. However, Amazon forest edge dynamics over time and space are not well understood. We need to improve our knowledge about forest edge dynamics in order to estimate the actual amount of forest degradation caused by forest fragmentation. In this study, we performed deep spatio-temporal analyses of forest fragmentation for Rondônia, in the southwestern Amazon, using a multitemporal Landsat dataset (1984-2005). Our goals were to: 1) calculate erosion/persistence of forest edges; 2) detect edge age-composition of all forest edges and; 3) estimate total degraded forest area due to forest edge effects. Two counties of different stages of deforestation were selected. Campo Novo de Rondônia (early stage) and Ouro Preto (final stage). Overall, more than 50% of forest edges were eliminated in the first four years, while only 20% of edges survived more than 10 years after edge creation. The composition of edge-ages differs according to the stage of deforestation. Between 2001 and 2005, nearly 60% of forest edges in recently developed Campo Novo de Rondônia were 0-4 years old, with only 20% > 10 years old. Conversely, in the old frontier Ouro Preto region, only 23% of forest edges were 0-4 years old and 50% were > 10 years old. These results suggest that high edge erosion rates in the years following edge creation may cause many edges disappear before they experience the complete process of edge-induced changes such as biomass collapse, potentially reducing the estimated impact of existing forest edges on the remaining forests.
Numata, I.; Cochrane, M. A.; Roberts, D. A.; Soares, J. V.
The evaluation of spatially and temporally distributed records of translational shallow landslides in heterogeneous watersheds provides insights needed to understand disastrous processes. Recurrent slope instability events occurred between 1953 and 1998 in two watersheds of Mt. Aso, western Japan. This paper investigates (1) the spatio-temporal characteristics of translational shallow landslides (dimensions, numbers, densities, and area subjected to failure) observed at a particular location, (2) DEM based landform characteristics (elevation, slope angles, curvatures and their control on landslide distribution), and (3) rainfall characteristics. The evaluation of the landslide history, consequences and characteristics of spatially and temporally distributed landslides are based on the series of inventory maps for years 1954, 1977, 1990 and 1998. Geologically, the watersheds consist of pyroxene olivine andesite basalt lava, pyroclastics deposits, gravel, sand and clay deposits originated from Takadake, Nekodake, and Washigamine volcanoes. During 45 years (1953 1998), a total of 619 and 976 numbers of shallow landslides have been recognized in the Sakurakigawa and Furuegawa watersheds, respectively. Repeated sliding denuded a total surface area of 0.372 km2 in the Sakurakigawa watershed representing 35% of the watershed area. Similarly slides denuded a total of 0.534 km2 in the Furuegawa watershed representing 12% of the watershed area. For example, storm events of June 1953 and July 1990 with rainfall intensities of 49 and 61 mm h- 1, respectively triggered numerous landslides. About 25% and 47% of Sakurakigawa and Furuegawa watersheds, respectively still bears the potential to produce landslides. Landslides were commonly observed where thick unconsolidated tephra layers and pyroclastics rocks overlain by thin tephra bed existed, and for a slope inclination range of 30 35°.
Paudel, Prem P.; Omura, H.; Kubota, T.; Inoue, T.
While studying the distribution of Earth planetary seismicity, a group of factors, which have effect on the onset of the earthquakes, was examined. Among such factors are the following: geological (related to the Earth's tectonic development, to the border's of lithosphere plates location and ), astrophysical (related to the influence of the celestial bodies), and distribution of geophysical fields (as variation in the direction and the value of the physical fields, gravitational anomaly and other), etc. This approach made possible to reveal spatio-temporal migration of seismic activity (as strong earthquakes) in certain traditional zones of high seismicity, such as on the border of lithosphere plates, at disruption of deep crust fractures and fault space, as well as in volcanic areas. Seismic activity migration as distribution of strong earthquakes on the surface of the Earth was analyzed during five ten-year periods from 1963 to 2009. It was found out that for that period of time, by 2000-2009, the maximum N of the earthquakes had concentrated in the area S. Such migration may be explained by the fact that the geosphere is affected by internal geological processes, moving of the lithosphere plates. Recent stirring up of the endogenous activity in this area could be explained by particularities of the Earth's geological structure (in accordance with the Earth's gravitation map) and by changes in the Earth's lithospheric stratum caused by other geospheres, such as hydro- and atmosphere, as well as by changing celestial bodies physical fields (gravitational and other) related to the dynamics of the oscillatory movement.
Accurate blood flow measurements during surgery can improve the operations chance of success. We developed Near-infrared Spatio-Temporal Image Spectroscopy (NIR-STICS), which has the potential to make blood flow measurements that are difficult to accomplish with existing methods. Specifically, we propose the technique and we show feasibility on phantom measurements. NIR-STICS has the potential of measuring the fluid velocity in small blood vessels (less than 1mm in diameter) and of creating a map of blood flow rates over an area of approximately 1cm2. NIR-STICS employs near-infrared spectroscopy to probe inside blood vessel walls and spatio-temporal image correlation spectroscopy to directly—without the use of a model—extract fluid velocity from the fluctuations within an image. Here we present computer simulations and experiments on a phantom system that demonstrate the effectiveness of NIR-STICS.
Rossow, Molly; Mantulin, William W.; Gratton, Enrico
The identification of fatigue cracks in a beam is investigated in this paper. It is shown that due to the influence of the elastic nonlinearity of fatigue cracks, the homogeneity, along the length of the beam, of the spatio-temporal dynamics of the vibrating beam is destroyed. By using spatio-temporal dynamical system identification techniques, a new approach is developed to detect this nonhomogeneity. The cracked beam is divided into several spatial regions and a coupled map lattice (CML) model is identified and verified in one of the regions using an orthogonal forward regression (OFR) least-squares algorithm. This CML model is then used to predict the dynamical behaviour of the other regions and in this way to detect the nonhomogeneity of the overall system.
Guo, L. Z.; Billings, S. A.
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.
Sánchez-Garduño, Faustino; Breña-Medina, Víctor F.
Tomographic reconstruction from PET data is an ill-posed problem that requires regularization. Recently, Daubechies et al.  proposed an l (1) regularization of the wavelet coefficients that can be optimized using iterative thresholding schemes. In this paper, we extend this approach for the reconstruction of dynamic (spatio-temporal) PET data. Instead of using classical wavelets in the temporal dimension, we introduce exponential-spline wavelets that are specially tailored to model time activity curves (TACs) in PET. We show the usefulness of spatio-temporal regularization and the superior performance of E-spline wavelets over conventional Battle-Lemarié wavelets for a 1-D TAC fitting experiment and a tomographic reconstruction experiment. PMID:18003524
Verhaeghe, Jeroen; Van De Ville, Dimitri; Khalidov, Ildar; Unser, Michael; D'Asseler, Yves; Lemahieu, Ignace
Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.
Karssenberg, Derek; Bierkens, Marc F. P.
Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculation DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.
Kurt Derr; Milos Manic
Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. In this study, we present a spatio-temporal analysis of the incidence of schizophrenia in Quebec from 2004 to 2007 using administrative databases from the Régie de l'Assurance Maladie du Quebec and the hospital discharge database. We conducted purely spatial analyses for each age group adjusted by sex for the whole period using SatScan (version 9.1.1). Findings from the study indicated variations in the spatial clustering of schizophrenia according to sex and age. In term of incidence rate, there are high differences between urban and rural-remote areas, as well as between the two main metropolitan areas of the province of Quebec (Island of Montreal and Quebec-City). PMID:23973179
Ngui, André Ngamini; Apparicio, Philippe; Fleury, Marie-Josée; Lesage, Alain; Grégoire, Jean-Pierre; Moisan, Jocelyne; Vanasse, Alain
Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data. PMID:22388709
Heaton, Matthew J; Banks, David L; Zou, Jian; Karr, Alan F; Datta, Gauri; Lynch, James; Vera, Francisco
Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century under different emissions scenarios? (3) How would perceived drought characteristics evolve under theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective" adaptation) or over a 30-year period centred around the date considered ("prospective" adaptation). These adaptation scenarios are translated into local-scale transient drought thresholds, as opposed to a non-adaptation scenario where the drought threshold remains constant. The perceived spatio-temporal characteristics derived from the theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of local-scale adaptation and global-scale mitigation. This study thus proposes a proof of concept for using standardized drought indices for (1) assessing projections of spatio-temporal drought characteristics and (2) building theoretical adaptation scenarios and associated perceived changes in hydrological impact studies (Vidal et al., submitted). Vidal J.-P., Martin E., Franchistéguy L., Habets F., Soubeyroux J.-M., Blanchard M. & Baillon M. (2010) Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite. Hydrology and Earth System Sciences, 14, 459-478.doi: 10.5194/hess-14-459-2010 Vidal J.-P., Martin E., Kitova N., Najac J. & Soubeyroux, J. M. (submitted) Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios. Submitted to Hydrology and earth System Sciences
Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.
Complex spatio-temporal systems may exhibit irregular behaviors when driven far from equilibrium. Reaction-diffusion systems often lead to the formation of patterns and spatio-temporal chaos. When a limited number of observations is available, the reconstruction and identification of complex dynamical regimes become challenging problems. A method based on spatial recurrence properties is proposed to deal with this problem: generalized recurrence plots and generalized recurrence quantification analysis are exploited to show that detection of structural changes in spatially distributed systems can be performed by setting up appropriate diagrams accounting for different spatial recurrences. The method has been tested on two prototypical systems forming complex patterns: the complex Ginzburg–Landau equation and the Schnakenberg system. This work allowed us to identify changes in the stability of spiral wave solutions in the former system and to analyze the Turing bifurcations in the latter.
Mocenni, Chiara; Facchini, Angelo; Vicino, Antonio
We describe our approach to segmenting moving objects from the color video data supplied by a nominally stationary camera.\\u000a There are two main contributions in our work. The first contribution augments Zivkovic and Heijden’s recursively updated Gaussian\\u000a mixture model approach, with a multi-dimensional Gaussian kernel spatio-temporal smoothing transform. We show that this improves\\u000a the segmentation performance of the original approach,
Zezhi Chen; Nick Pears; Michael Freeman; Jim Austin
In this paper, a new spatio-temporal method for adaptively detecting events based on Allen temporal algebra and external information\\u000a support is presented. The temporal information is captured by presenting events as the temporal sequences using a lexicon\\u000a of non-ambiguous temporal patterns. These sequences are then exploited to mine undiscovered sequences with external text information\\u000a supports by using class associate rules
Minh-Son Dao; Noboru Babaguchi
The spatio-temporal variations of the water budget components in the Amazon region are investigated by using a combination of hydrometeorological observations and moisture fluxes derived from the NCEP\\/NCAR reanalyses, for the period 1970–1999. The key new finding of this study identifies the major differences in the water balance characteristics and variability between the northern and southern parts of the basin.
Jose A. Marengo
To what extent can a computational model of the bottom-up visual attention predict what an observer is looking at? What is the contribution of the low-level visual fea- tures in the attention deployment? To answer these questions, a new spatio-temporal computational model is proposed. This model incorporates several visual features; therefore, a fusion algorithm is required to combine the dierent
Olivier Le Meur; Patrick Le Callet; Dominique Barba
Successful state-of-the-art video retrieval and classification applications are predominantly carried out by means of spatio-temporal features. Typically, the evaluation of these tasks is exclusively done based on their final performance but no systematic analysis of feature robustness, invariance and stability has been done yet for large scale video retrieval. In this work, we analyze the impact of visual transformation on
Julian Stöttinger; Bogdan Tudor Goras; Nicu Sebe; Allan Hanbury
Sustained emerging spatio-temporal co-occurrence patterns (SECOPs) represent subsets of object-types that are increasingly located together in space and time. Discovering SECOPs is important due to many applications, e.g., predicting emerging infectious diseases, predicting defensive and offensive intent from troop movement patterns, and novel predator-prey interactions. However, mining SECOPs is computationally very expensive because the interest measures are computationally complex, datasets
Mete Celik; Shashi Shekhar; James P. Rogers; James A. Shine
We demonstrate a time-lapse video approach that allows rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations. Quantitative information was gathered by sampling life histories of more than 2,000 mutant clones from\\u000a a large mutagenesis collection. Approximately 4% of the clonal lines showed a mutant phenotype at one stage. Many of these\\u000a could be ordered by clustering into functional
Satoshi Sawai; Xiao-Juan Guan; Adam Kuspa; Edward C Cox
Our recent study [O'Carroll et al. (1996). Nature 382, 63–66) described a correlation between the spatio-temporal properties of motion detecting neurons in the optic lobes of flying insects and behaviour. We consider here theoretical properties of insect motion detectors at very low image velocities and measure spatial and temporal sensitivity of neurons in the lobula complex of two specialised hovering
D. C. O'Carroll; S. B. Laughlin; N. J. Bidwell; R. A. Harris
SUMMARY We present the spatio-temporal evolution of seismicity recorded by eight three-component digital seismographs in operation continuously during a 3 yr period (1994 August to 1997 May) at Acu reservoir, NE Brazil. The Acu dam is a 34 m high earth-filled dam constructed in 1983 May on an area of Precambrian shield. Based on seismic monitoring between 1987 and 1989
A. F. do Nascimento; P. A. Cowie; R. J. Lunn; R. G. Pearce
The spatio-temporal correlation of micro-earthquakes occuring in a mining-induced seismic system (Creighton mine, Ontario, Canada) is investigated. It is shown that, when considering only the after-events correlated to a main event, i.e., not accounting for the uncorrelated regime of `background' activity, the spatial distribution of these after-events occurring at t after the main event change with t. This change takes
David Marsan; Christopher J. Bean; Sandy Steacy; John McCloskey
The transition regime to spatio-temporal chaos via the quasiperiodic route as well as the period-doubling route is examined for coupled-map lattices. Space-time renormalization-group analysis is carried out and the scaling exponents for the coherence length, the Lyapunov exponent, and the size of the phase fluctuations are determined. Universality classes for the different types of coupling at various routes to chaos are identified. PMID:12779978
Alstrom, Preben; Stassinopoulos, Dimitris
In this work, transcoding of pre-encoded MPEG-1, 2 video into lower bit rates is realized through altering the coding algorithm into H.261\\/H.263 standards with lower spatio-temporal resolutions. For this heterogeneous transcoding, we extract and compose a set of candidate motion vectors, from the incoming bit stream, to comply with the encoding format of the output bit stream. For the spatial
Tamer Shanableh; Mohammed Ghanbari
The aim of two experiments was to investigate the relationship between spatio-temporal contrast sensitivity and visual backward masking in normal observers and in subgroups with positive or negative symptoms in schizophrenia. Experiment 1 measured contrast sensitivity for stationary and counterphase-modulated sinusoidal gratings at four spatial (0.5, 2.0, 4.0, 8.0 cycles\\/degree) and four temporal frequencies (0, 4.0, 8.0, 16.0 Hz). The results showed
Walter L. Slaghuis
Words correctly recognized as previously studied (i.e. old) elicit greater amounts of positive event-related brain potential (ERP) activity over posterior scalp between 400 and 800 ms than do previously unstudied (i.e. new) words. While investigators have reported that this old\\/new effect consists of more than one subcomponent, the spatio-temporal parameters of these possible subcomponents, as well as any other patterns
Ray Johnson Jr; Kurt Kreiter; Britt Russo; John Zhu
In this paper a new research tool called FastBEE (Fast Estimation of Expected Big Earthquake) is proposed, for the analysis of three basic seismic parameters, (the number of earthquakes N, b-value, and the seismic energy released in the form logE2\\/3), in order to examine their spatio-temporal variation behavior. The developed research tool is suited to analyze earthquake catalogs and it
G. A. Papadopoulos; I. Baskoutas
\\u000a In this paper, we investigate how discourse context in the form of short-term memory can be exploited to automatically group\\u000a consecutive strokes in digital freehand sketching. With this machine learning approach, no database of explicit object representations\\u000a is used for template matching on a complete scene—instead, grouping decisions are based on limited spatio-temporal context.\\u000a We employ two different classifier formalisms
Lutz Dickmann; Tobias Lensing; Robert Porzel; Rainer Malaka; Christoph Lischka
Kuethe T. H. and Pede V. O. Regional housing price cycles: a spatio-temporal analysis using US state-level data, Regional Studies. A study is presented of the effects of macroeconomic shocks on housing prices in the Western United States using quarterly state-level data from 1988:1 to 2007:4. The study contributes to the existing literature by explicitly incorporating locational spillovers through a
Todd H. Kuethe; Valerien O. Pede
Real-world objects are inherently spatially and temporally referenced, and many database applicationsrely on databases that record the past, present, and anticipated future locations of, e.g., people orland parcels. As a result, indices that efficiently support queries on the spatio-temporal extents of objectsare needed. In contrast, past indexing research has progressed in largely separate spatial and temporalstreams. In the former, focus
Christian S. Jensen
\\u000a Myocardial deformation is a critical indicator of many cardiac diseases and dysfunctions. The goal of this paper is to use\\u000a myocardial deformation patterns to identify and localize regional abnormal cardiac function in human subjects. We have developed\\u000a a novel tensor-based classification framework that better conserves the spatio-temporal structure of the myocardial deformation\\u000a pattern than conventional vector-based algorithms. In addition, the
Zhen Qian; Qingshan Liu; Dimitris N. Metaxas; Leon Axel
Experimental investigation  of spatio-temporal evolution of charged plasma species in afterglow oxygen plasma have been continued. The temporal probe current-voltage characteristics at different distances along the radius of the tube and the time dependence of the saturation currents to a probe in a fixed bias voltage were performed. It was confirmed that the decay of oxygen low-pressure plasma takes
A. A. Kudryavtsev; V. G. Mishakov; I. N. Skoblo; T. L. Tkachenko; M. O. Chayka
China's rapid economic development in the last 20 years has resulted in increased demand for electricity and ensuing shortages in electric power supply. It is necessary to derive accurate and timely information regarding changing spatio-temporal patterns and trends of electric power consumption to inform future electricity allocation. Night-time annual image composites for 1995–2005 were obtained from the Defense Meteorological Satellite
Naizhuo Zhao; Tilottama Ghosh; Eric L. Samson
\\u000a Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications\\u000a including targeted content service, advertisement dissemination for mobile users, and recreational social networking tools\\u000a for smart-phones. Existing techniques based on linear and probabilistic models are not able to provide accurate prediction\\u000a of the location patterns from a spatio-temporal perspective, especially for long-term estimation. More
Salvatore Scellato; Mirco Musolesi; Cecilia Mascolo; Vito Latora; Andrew T. Campbell
Bags-of-visual-Words (BoW) and Spatio-Temporal Shapes (STS) are two very popular approaches for action recognition from video. The former (BoW) is an un-structured global representation of videos which is built using a large set of local features. The latter (STS) uses a single feature located on a region of interest (where the actor is) in the video. Despite the popularity of
Teofilo de Campos; Mark Barnard; Krystian Mikolajczyk; Josef Kittler; Fei Yan; William Christmas; David Windridge
There is now extensive interest in reasoning about moving objects. A probabilistic spatio-temporal (PST) knowledge base (KB) contains atomic statements of the form “Object o is\\/was\\/will be in region r at time t with probability in the interval [?,u]”. In this paper, we study mechanisms for belief revision in PST KBs. We propose multiple methods for revising PST KBs. These
John Grant; Francesco Parisi; Austin Parker; V. S. Subrahmanian
\\u000a Discovering and tracking of spatio-temporal patterns in noisy sequences of events is a difficult task that has become increasingly\\u000a pertinent due to recent advances in ubiquitous computing, such as community-based social networking applications. The core\\u000a activities for applications of this class include the sharing and notification of events, and the importance and usefulness\\u000a of these functionalites increases as event-sharing expands
Anis Yazidi; Ole-Christoffer Granmo; Min Lin; Xifeng Wen; B. John Oommen; Martin Gerdes; Frank Reichert
decision making, SDSS, public participation GIS, conjunctive water administration, spatio-temporal decision support Abstract Collaborative spatial decision support systems (C-SDSS) have been used to help groups of stakeholders understand data and search for opportunities at resolving local and regional decision problems in various domains including land use, trans- portation, and water resources. The key issue in designing an effective C-SDSS is
Piotr Jankowski; Steven Robischon; David Tuthill; Timothy L. Nyerges; Kevin Ramsey
The technique of spatially resolved cross-correlation spectroscopy (CCS) is used to carry out diagnostic measurements of the barrier discharge (BD) in air at atmospheric pressure. Quantitative estimates for electric field strength E(x,t) and for relative electron density ne(x,t)\\/nemax are derived from the experimentally determined spatio-temporal distributions of the luminosity for the spectral bands of the 0-0 transitions of the second
K. V. Kozlov; H.-E. Wagner; R. Brandenburg; P. Michel
Traffic video analysis can provide a wide range of useful information such as vehicle identification, traffic flow, to traffic planners. In this paper, a framework is proposed to analyze the traffic video sequence using unsupervised vehicle detection and spatio-temporal tracking that includes an image\\/video segmentation method, a background learning\\/subtraction method and an object tracking algorithm. A real-life traffic video sequence
Chengcui Zhang; Shu-Ching Chen; Mei-Ling Shyu; Srinivas Peeta
We review the spatio-temporal dynamical features of the Ananthakrishna model for the Portevin-Le Chatelier effect, a kind of plastic instability observed under constant strain rate deformation conditions. We then establish a qualitative correspondence between the spatio-temporal structures that evolve continuously in the instability domain and the nature of the irregularity of the scalar stress signal. Rest of the study is on quantifying the dynamical information contained in the stress signals about the spatio-temporal dynamics of the model. We show that at low applied strain rates, there is a one-to-one correspondence with the randomly nucleated isolated bursts of mobile dislocation density and the stress drops. We then show that the model equations are spatio-temporally chaotic by demonstrating the number of positive Lyapunov exponents and Lyapunov dimension scale with the system size at low and high strain rates. Using a modified algorithm for calculating correlation dimension density, we show that the stress-strain signals at low applied strain rates corresponding to spatially uncorrelated dislocation bands exhibit features of low dimensional chaos. This is made quantitative by demonstrating that the model equations can be approximately reduced to space independent model equations for the average dislocation densities, which is known to be low-dimensionally chaotic. However, the scaling regime for the correlation dimension shrinks with increasing applied strain rate due to increasing propensity for propagation of the dislocation bands. The stress signals in the partially propagating to fully propagating bands turn to have features of extensive chaos.
Ananthakrishna, G.; Sarmah, R.
Mixed-drove spatio-temporal co-occurrence patterns (MDCOPs) represent subsets of object-types that are located together in space and time. Discovering MDCOPs is an important problem with many applications such as identifying tactics in battlefields, games, and predator-prey interactions. However, mining MDCOPs is computationally very expensive because the interest measures are computationally complex, datasets are larger due to the archival history, and the
Mete Celik; Shashi Shekhar; James P. Rogers; James A. Shine; Jin Soung Yoo
We experimentally observe an intriguing phenomenon of complex spatio-temporal dynamics in a commercial optically pumped semiconductor laser with intracavity second harmonic generation. We numerically verify that the experimental results come from the total mode locking of transverse electromagnetic modes (TEM00) and higher-order modes with significant astigmatism. The scenarios of the spatio-temporal dynamics are quite similar to the phenomena in soft-aperture Kerr-lens mode locked Ti:sapphire lasers. PMID:23164854
Liang, Hsing-Chih; Lee, Yi-Chun; Tung, Jung-Chen; Su, Kuan-Wei; Huang, Kai-Feng; Chen, Yung-Fu
Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.
Serinaldi, F.; Kilsby, C. G.
In fluid dynamical systems, it is not known a priori whether disturbances grow either in space or in time or as spatio-temporal structures. However, for boundary layers, it is customary to treat it as a spatial problem and some limited comparison between prediction and laboratory experiments exist. In the present work, the receptivity problem of a zero pressure gradient boundary layer excited by a localized harmonic source is investigated under the general spatio-temporal framework, using the Bromwich contour integral method. While this approach has been shown to be equivalent to the spatial study, for unstable systems excited by a single frequency source [T. K. Sengupta, M. Ballav, and S. Nijhawan, Phys. Fluids 6, 1213 (1994)], here we additionally show, how the boundary layer behaves when it is excited (i) at a single frequency that corresponds to a stable condition (given by spatial normal-mode analysis) and (ii) by wideband frequencies, that shows the possibility of flow transition due to a spatio-temporally growing forerunner or wave front. An energy based receptivity analysis tool is also developed as an alternative to traditional instability theory. Using this, we reinterpret the concept of critical layer that was originally postulated to explain the mathematical singularity of inviscid disturbance field in traditional instability theory of normal modes.
Sengupta, T. K.; Rao, A. Kameswara; Venkatasubbaiah, K.
Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.
Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu
The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO is frequently proposed as the generator of timing signals to the cerebellum. Electrophysiological and imaging recordings show that the IO network generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. Our modeling reproduces and helps to understand important phenomena observed in IO in vitro and in vivo experiments, and draws new predictions regarding the computational properties of this network and the associated cerebellar circuits. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop (IL). The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of the IO neurons that nevertheless remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts. These results can be generalized beyond IO studies, as the control of wave pattern propagation is a highly relevant problem in the context of normal and pathological states in neural systems (e.g., related to tremor, migraine, epilepsy) where the study of the modulation of activity sinks and sources can have a potential large impact. PMID:24046731
Latorre, Roberto; Aguirre, Carlos; Rabinovich, Mikhail I; Varona, Pablo
The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO is frequently proposed as the generator of timing signals to the cerebellum. Electrophysiological and imaging recordings show that the IO network generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. Our modeling reproduces and helps to understand important phenomena observed in IO in vitro and in vivo experiments, and draws new predictions regarding the computational properties of this network and the associated cerebellar circuits. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop (IL). The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of the IO neurons that nevertheless remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts. These results can be generalized beyond IO studies, as the control of wave pattern propagation is a highly relevant problem in the context of normal and pathological states in neural systems (e.g., related to tremor, migraine, epilepsy) where the study of the modulation of activity sinks and sources can have a potential large impact.
Latorre, Roberto; Aguirre, Carlos; Rabinovich, Mikhail I.; Varona, Pablo
In hilly landscapes, where erosion rates do not exceed the weathering rates of bedrock material, the shape of hillslopes is typically convex near the hilltop and becomes increasingly planar further downslope with the steepest descent in the middle of the slope and a concave shaped hillfoot. This convex-concave shape is the result of long term erosion and sediment redistribution processes driven by climatic forcing. We hypothesize that this typical shape is related to optimized sediment transport dynamics when examined in a thermodynamic perspective. We used the process based model CATFLOW-SED to analyze the spatio-temporal organization of sediment dynamics at the hillslope scale. The model simulates overland flow using the diffusion wave equation. Soil detachment is a threshold process and depends on the attacking forces of rainfall and overland flow and the model parameter erosion resistance, which is characterized by soil properties, land use and management practice. Transport capacity and deposition are modeled for different grain size fractions. For the hillslope studies, data of the Weiherbach catchment was used, which is located in an intensively cultivated loess region in Southwest Germany. We designed convex and convex/concave shaped slopes similar to the hillslopes in the Weiherbach catchment, with identical gradients, slope lengths, soil properties and vegetation but varying curvatures. Then we modeled sediment dynamics using observed rainfall and climate data and quantified the power generated by water and sediment flux for the different slopes. We found a minimum of the power generated by sediment flux for the convex-concave shaped hillslopes which represent the hypsometric curve of the Weiherbach catchment. The typically shaped hillslopes are thus in a state of minimum work performed on the hillslope, resulting in a steady hillslope shape and minimum sediment export. This tendency for a hillslope to develop towards an 'optimal' shape and sediment export rate should be generally applicable; a thermodynamically formulated principle of minimum work performed on hillslopes in steady state could hence serve as a constraint when estimating sediment export rates in similar landscapes.
Scherer, Ulrike; Zehe, Erwin; Ehret, Uwe; Kleidon, Axel
This paper presents a synopsis of the doctoral thesis 'a spatial-tempo ral approach to forest economics'. The thesis argues the need for a new modelling approach to enable analysis of spatial interactive effects. In particular, the case of windthrow is considered to exemplify the modelling approach proposed. The traditional Faustmann model is taken as a starting point. This model has
Fundamental barriers in practical filtering of nonlinear spatio-temporal chaotic systems are model errors attributed to the stiffness in resolving multiscale features. Recently, reduced stochastic filters based on linear stochastic models have been introduced to overcome such stiffness; one of them is the Mean Stochastic Model (MSM) based on a diagonal Ornstein-Uhlenbeck process in Fourier space. Despite model errors, the MSM shows very encouraging filtering skill, especially when the hidden signal of interest is strongly chaotic. In this regime, the dynamical system statistical properties resemble to those of the energy-conserving equilibrium statistical mechanics with Gaussian invariant measure; therefore, the Ornstein-Uhlenbeck process with appropriate parameters is sufficient to produce reasonable statistical estimates for the filter model.In this paper, we consider a generalization of the MSM with a diagonal autoregressive linear stochastic model in Fourier space as a filter model for chaotic signals with long memory depth. With this generalization, the filter prior model becomes slightly more expensive than the MSM, but it is still less expensive relative to integrating the perfect model which is typically unknown in real problems. Furthermore, the associated Kalman filter on each Fourier mode is computationally as cheap as inverting a matrix of size D, where D is the number of observed variables on each Fourier mode (in our numerical example, D=1). Using the Lorenz 96 (L-96) model as a testbed, we show that the non-Markovian nature of this autoregressive model is an important feature in capturing the highly oscillatory modes with long memory depth. Second, we show that the filtering skill with autoregressive models supersedes that with MSM in weakly chaotic regime where the memory depth is longer. In strongly chaotic regime, the performance of the AR(p) filter is still better or at least comparable to that of the MSM. Most importantly, we find that this reduced filtering strategy is not as sensitive as standard ensemble filtering strategies to additional intrinsic model errors that are often encountered when model parameters are incorrectly specified.
Kang, Emily L.; Harlim, John
Rainfall reliability in West Africa has important societal consequences. However, our understanding of the rainfall generating processes in this region remains incomplete. This study aims at the detection of different rainfall producing processes and their characteristics during the later part of the rainy season in Northern Ghana. Rainfall in this region has three main origins: monsoonal advection, local convection, and
J. Friesen; N. van de Giesen
The recent progress in environmental monitoring technologies allows capturing extensive amount of data that can be used to assist in avalanche forecasting. While it is not straightforward to directly obtain the stability factors with the available technologies, the snow-pack profiles and especially meteorological parameters are becoming more and more available at finer spatial and temporal scales. Being very useful for improving physical modelling, these data are also of particular interest regarding their use involving the contemporary data-driven techniques of machine learning. Such, the use of support vector machine classifier opens ways to discriminate the ``safe'' and ``dangerous'' conditions in the feature space of factors related to avalanche activity based on historical observations. The input space of factors is constructed from the number of direct and indirect snowpack and weather observations pre-processed with heuristic and physical models into a high-dimensional spatially varying vector of input parameters. The particular system presented in this work is implemented for the avalanche-prone site of Ben Nevis, Lochaber region in Scotland. A data-driven model for spatio-temporal avalanche danger forecasting provides an avalanche danger map for this local (5x5 km) region at the resolution of 10m based on weather and avalanche observations made by forecasters on a daily basis at the site. We present the further work aimed at overcoming the ``black-box'' type modelling, a disadvantage the machine learning methods are often criticized for. It explores what the data-driven method of support vector machine has to offer to improve the interpretability of the forecast, uncovers the properties of the developed system with respect to highlighting which are the important features that led to the particular prediction (both in time and space), and presents the analysis of sensitivity of the prediction with respect to the varying input parameters. The purpose of the sensitivity analysis is to shed light on the particular abilities of the model in assessing the likelihood of avalanche releases under evolving meteorological/snowpack conditions. Both spatial resolution (the abilities to produce reliable forecasts for individual avalanche paths) and temporal behaviour of the model are explored in details. Based on the sensitivity analysis, the uncertainty estimation for the provided forecasts is discussed. Particularly, the ensembles of prediction models are run and analysed in order to estimate the variability of the provided forecast and assess the uncertainty coming from the variety of sources: imprecise input data, uncertainty in weather forecast, sub-optimal parameters of the prediction model and variability in the choice of the training dataset.
Matasci, G.; Pozdnoukhov, A.; Kanevski, M.
China's Grain-For-Green Policy (GFGP) of returning marginal cropland to forest or grassland is one of the most important large-scale initiatives to combat land degradation in its ecologically vulnerable regions. In order to maintain and increase crop production from decreasing areas of cropland, substantial spatio-temporal changes in agrochemical inputs have occurred, which have strongly influenced the ecological and environmental status of land in China. Based on the agrochemical inputs (chemical fertilizer, pesticide, plastic sheeting, and agricultural diesel oil) at the provincial level between 1993 and 2009, cluster analysis and gravity center modeling were used to trace these spatio-temporal changes. A regional comparative study was also undertaken to investigate the changes in the relative size of agrochemical inputs in the eastern, central, and western regions of China. It was found that the agrochemical inputs increased considerably at the nation level after the GFGP, which in order of increasing rate were: plastic sheeting > agricultural diesel oil > pesticide > chemical fertilizer. The gravity centers of agrochemical inputs moved substantially towards the northwest or west during the latter period of GFGP and regional comparative analysis showed that the agrochemical inputs increased substantially in the western region between 2004 and 2009. The ecological degradation caused by the expansion of the area devoted to crop production in the western region and the potential risk of agricultural non-point pollution caused by the increasing agrochemical inputs are the main factors restricting this area's sustainable development. PMID:22585404
The decomposition of the time reversal operator, known by the French acronym DORT, is a technique to extract point scatterers' monochromatic Green's functions from a medium. It is used to detect, locate, and focus on scatterers in various domains such as underwater acoustics, medical ultrasound, and nondestructive evaluation. A limitation of the method arises from its single-frequency nature, when the signals used in acoustics are often broadband. Reconstruction of the broadband Green's functions from the single-frequency Green's functions can be very difficult when numerous scatterers are present in the medium. Moreover, the method does not take advantage of the axial resolution associated with broadband signals. Time domain methods are investigated here as an answer to these problems. It is shown that the time reversal operator in the time domain takes the form of a tensor. The properties of the invariants are discussed. It is shown they do not have all the expected properties. Another method is proposed that requires a priori information on the medium. PMID:21117741
Robert, Jean-Luc; Fink, Mathias
Traditional visualization of earth surface features has been addressed through visual exploration, analysis, synthesis, and presentation of observable geospatial data. However, characterizing the changes in their observable and unobservable properties of geospatial features is critical for planning and policy formulation. Recent approaches are addressing modeling and visualization of the temporal dynamics that describe observed and/or predicted physical and socioeconomic processes using vast volumes of earth observation (imagery and other geophysical) data from remote sensor networks. This paper provides an overview of selected geospatial modeling and simulation, exploratory analysis of earth observation data, and high performance visualization research at Oak Ridge National Laboratory for developing novel data driven approaches for geospatial knowledge discovery and visualization relevant to environmental decision support.
Bhaduri, Budhendra L [ORNL; Shankar, Mallikarjun [ORNL; Sorokine, Alexandre [ORNL; Ganguly, Auroop R [ORNL
Geovisualization is an important means to understand the geographic features and phenomena. Urban space, especially buildings, keeps changing with social development. However, traditional 2D visualization can only represent the plane geometric description, which is unable to support 3D dynamic visualization. Only with 3D dynamic visualization can the buildings' spatial morphology be exhibited temporally, including buildings' creation, expansion, removing, etc. But these buildings' changes are impossible to be studied in traditional 2D and 3D static visualization systems. As a result, it becomes urgent to find an effective solution to implement 3D spatial-temporal visualization of buildings. Inspired by 2D spatial-temporal visualization methods, like snapshot and event-based spatio-temporal data model(ESTDM), we propose a new data model called Spatio-Temporal Page Model(STPM) and implement 3D spatial-temporal visualization in Google SketchUp based on STPM. This paper studies 3D visualization of real estate focusing on its spatio-temporal characteristics. First of all, 3D models are built for every temporal scenario by the Google SketchUp. And every Geo-object is identified by a unique and permanent ObjectID, the linkage of Geo-objects between different time spots. Then, each temporal scenario is represented as page. After having the page series, finally, it is possible to display its spatial-temporal changes and create an animation. Underlying this solution, we have built a prototype system on part of real estate data. It is proven that users are able to understand clearly the real estate's changes from our prototype system. Consequently, we believe our method for 3D spatial-temporal visualization definitely has many merits.
Li, Linhai; Qu, Lina; Ying, Shen; Liang, Dongdong; Hu, Zhenlong
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. PMID:23733286
Jürgens, Verena; Ess, Silvia; Phuleria, Harish C; Früh, Martin; Schwenkglenks, Matthias; Frick, Harald; Cerny, Thomas; Vounatsou, Penelope
The spatio-temporal characteristics of cat retinal ganglion cells showing linear summation have been studied by measuring both magnitude and phase of the responses of these cells to drifting or sinusoidally contrast-modulated sinusoidal grating patterns. It has been demonstrated not only that X cells behave approximately linearly when responding with amplitudes of less than about 10 impulses/sec to stimuli of low contrast but also that cells of another type with larger receptive field centres (Q cells) behave approximately linearly under the same conditions. These Q cells appear to form a homogeneous group which is probably a subset of the tonic W cells (Stone & Fukuda, 1974) or sluggish centre-surround cells (Cleland & Levick, 1974). The over-all spatio-temporal frequency characteristics of cells showing linear spatial summation are not separable in space and time. The form of the spatial frequency responsivity function of these cells depends upon the temporal frequency at which it is measured while the temporal phase of their resonse measured at any constant temporal frequency depends upon the spatial frequency of the stimulus. The behaviour of X and Q cells is quite well explained by an extension of the model in which signals from centre and surround mechanisms with radially Gaussian weighting functions are summed to provide the drive to the retinal ganglion cell. While the general form of the temporal frequency response characteristics of these ganglion cells are probably provided by the characteristics of elements common to the centre and surround pathways, the spatio-temporal interactions can be explained by assuming that the surround signal is delayed relative to the centre signal by a few milliseconds.
Enroth-Cugell, C; Robson, J G; Schweitzer-Tong, D E; Watson, A B
This paper assesses the use of Independent Component Analysis (ICA) as applied to epileptic scalp electroencephalographic (EEG) recordings. In particular we address the newly introduced Spatio-Temporal ICA algorithm (ST-ICA), which uses both spatial and temporal information derived from multi-channel biomedical signal recordings to inform (or update) the standard ICA algorithm. ICA is a technique well suited to extracting underlying sources from multi-channel EEG recordings - for ictal EEG recordings, the goal is to both de-noise the EEG recordings (i.e. remove artifacts) as well as isolate and extract epileptic processes. As part of any ICA application, there is an interim stage whereby relevant components (or processes) need to be identified - either objectively or subjectively (usually the latter). In previous work with ST-ICA we used spectral information alone to identify the underlying processes subspaces extracted by the ST-ICA. Here we assess the joint use of spatial as well as spectral information for this purpose. We test this on ictal EEG segments where it can be seen that different underlying processes possess characteristic signatures in both modalities which can be utilized for the clustering (or process selection) stage. PMID:19964610
James, Christopher J; Demanuele, Charmaine
The live cell is a highly dynamical system with complicated biophysical and biochemical processes taking place at diverse spatiotemporal scales. Though it is well known that microtubules and actin filaments play important roles in intracellular transport, their dynamic behavior is not entirely understood. We propose a unified approach to studying transport in live cells. We used Spatial Light Interference Microscopy, a quantitative phase imaging method developed in our laboratory, to extract cell mass distributions over broad spatiotemporal scales. The dispersion relations for this transport dynamics, i.e. frequency bandwidth vs. spatial frequencies, reveal deterministic mass transport at large spatial scales (w˜q) and diffusive transport at small spatial scales (w˜q?2). At submicron scales, we observed a w˜q?3 behavior, which indicates whip-like movements of protein filaments. Further control experiments where both the microtubule and actin polymerization were blocked suggests that essentially actin governs the long spatial scales behavior and microtubules the short scales. This label-free method enables us to access different components of cell dynamics and quantify diffusion coefficients and speed of motor proteins.
Wang, Ru; Wang, Zhuo; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel
Since ITER will operate close to threshold and with limited control, the H --> L back transition is a topic important for machine operations as well as physics. Using a reduced mesoscale model [Miki et al., Phys. Plasmas 19, 092306 (2012)], we investigate ELM-free H --> L back transition dynamics in order to isolate transport physics effects. Model studies indicate that turbulence spreading is the key process which triggers the back transition. The transition involves a feedback loop linking turbulence and profiles. The I-phase appears during the back transition following a slow power ramp down, while fast ramp-downs reveal a single burst of zonal flow during the back transition. The I-phase nucleates at the pedestal shoulder, as this is the site of the residual turbulence in H-mode. Hysteresis in the profile gradient scale length is characterized by the Nusselt number, where Nu=?i,turb/?i,neo. Relative hysteresis of temperature gradient vs density gradient is sensitive to the pedestal Prandtl number, where Prped=Dped/?i,neo. We expect the H-mode to be somewhat more resilient in density than in temperature.
Miki, K.; Diamond, P. H.; Schmitz, L.; McDonald, D. C.; Estrada, T.; Gürcan, Ö. D.; Tynan, G. R.
Land-use and land-cover change (LUCC) is an essential environmental process that should be monitored and prognosticated to provide a basis for better land management policy. However, LUCC modeling is a challenge due to the complex nature and unexpected behavior of both human drivers and natural constraints. This paper presents a multi-agent-based model to simulate spatio-temporal land-use changes and the interdependent
Q. Le; P. L. Vlek
Spatio-temporal dynamics of alpha activity during the resting state is characterized by alternation between ordered and disordered states. The ordered state exhibits a variety of phase patterns. We found that the duration distributions of these states and phase patterns obey power laws. These results suggest that the appearance of phase patterns and the alternation between ordered and disordered states are not just due to noise but products of internal dynamics of the brain. We discuss the possibility that these dynamics are manifestation of chaotic itinerancy in the brain dynamics.
Ito, Junji; Nikolaev, Andrey R.; van Leeuwen, Cees
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.
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. PMID:22639132
Winkler, Mirko S; Krieger, Gary R; Divall, Mark J; Singer, Burton H; Utzinger, Jürg
In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.
Coupled Map Lattices (CML) can be interpreted as spatio-temporal fitness landscapes which may pose a dynamic optimization problem. In this paper, we analyze such dynamic fitness landscapes in terms of the landscape measures modality, ruggedness, information content and epistasis. These measures account for different aspects of problem hardness. We use an evolutionary algorithm to solve the dynamic optimization problem and study the relationship between performance criteria of the algorithm and the landscape measures. In this way we relate problem hardness to expectable performance.
The complex spatio-temporal dynamics generated by electrohydrodynamics instabilities in a nematic liquid crystal under the action of a driving oscillating electric field is investigated. Quasi-stationary convective structures which are visible at large scales are broken into chaotic patterns at higher driving voltages, thus generating small-scale structures. Scaling analysis reveals that these small-scale structures self-organize in a network of subleading structures which are reminescent of convective rolls. This network persists well inside the chaotic regimes, disappearing only at very high voltages, where stochastic dynamical scattering mode takes place. PMID:21805393
Carbone, F; Vecchio, A; Sorriso-Valvo, L
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.
Gleeson, J. T.
This paper presents a method to detect the spatio-temporal parameters of gait by using wearable motion sensors with a gyro, accelerometer, and magnetic sensor. The detected gait parameters are as follows: stance (ST), double support (DS), and gait cycle (GC) time as temporal parameters, and the stride length (SL) as spatial parameter. Four motion sensors are attached on both thighs and shanks of users, and the sensor data are collected in a portable PC. The temporal parameters are estimated by finding walking events, and then the stride length is calculated with two gait models. The estimated parameters are compared to those obtained from a motion capture system (VICON system). PMID:17281844
Lee, Seon-Woo; Mase, Kenji; Kogure, Kiyoshi
Neuroimaging data demonstrate that carpal tunnel syndrome, a peripheral neuropathy, is accompanied by maladaptive central neuroplasticity. To further investigate this phenomenon, we collected magnetoencephalography data from 12 patients with carpal tunnel syndrome and 12 healthy control subjects undergoing somatosensory stimulation of the median nerve-innervated Digits 2 and 3, as well as Digit 5, which is innervated by the ulnar nerve. Nerve conduction velocity and psychophysical data were acquired to determine whether standard clinical measures correlated with brain response. In subjects with carpal tunnel syndrome, but not healthy controls, sensory nerve conduction velocity for Digits 2 and 3 was slower than Digit 5. However, somatosensory M20 latencies for Digits 2 and 3 were significantly longer than those of Digit 5. The extent of the M20 delay for median nerve-innervated Digit 2 was positively correlated with decreasing nerve conduction velocity and increasing pain severity. Thus, slower peripheral nerve conduction in carpal tunnel syndrome corresponds to greater delays in the first somatosensory cortical response. Furthermore, spectral analysis demonstrated weaker post-stimulus beta event-related desynchronization and earlier and shorter event-related synchronization in subjects with carpal tunnel syndrome. The extent of the decreased event-related desynchronization for median nerve-innervated digits was positively correlated with paraesthesia severity. We propose that ongoing paraesthesias in median nerve-innervated digits render their corresponding sensorimotor cortical areas ‘busy’, thus reducing their capacity to process external stimulation. Finally, subjects with carpal tunnel syndrome demonstrated a smaller cortical source separation for Digits 2 and 3 compared with healthy controls. This supports our hypothesis that ongoing paraesthesias promote blurring of median nerve-innervated digit representations through Hebbian plasticity mechanisms. In summary, this study reveals significant correlation between the clinical severity of carpal tunnel syndrome and the latency of the early M20, as well as the strength of long latency beta oscillations. These temporal magnetoencephalography measures are novel markers of neuroplasticity in carpal tunnel syndrome and could be used to study central changes that may occur following clinical intervention.
Ruzich, Emily; Witzel, Thomas; Maeda, Yumi; Malatesta, Cristina; Morse, Leslie R.; Audette, Joseph; Hamalainen, Matti; Kettner, Norman; Napadow, Vitaly
Numerical flow models are nowadays a powerful and widely used tool for groundwater management. Their reliability requires both an accurate physical representation of an aquifer system and appropriate boundary conditions. While the hydraulic parameters like hydraulic conductivity (K) and storativity (S) are spatially dependent and time invariant, groundwater fluxes such as recharge (R), evapotranspiration from groundwater (ETg) and groundwater inflow/outflow (Qgw) can vary in both space and time. Multiplicity of combinations between parameters and fluxes leads to a non-uniqueness of model solutions which limits their reliability and forecasting capability. We propose to constrain groundwater models at the catchment scale by the spatio-temporal assessment of fluxes in the unsaturated zone. Although the physically based models that involve the Darcy's law and the conservation of mass through the Richard's equation constitute the most appropriate tools for fluxes assessment in the unsaturated zone, they are computationally demanding and require a complex parameterization and boundary condition definition, which restricts their application to large and regional scales. We have thus chosen to develop and apply a lumped-parameter unsaturated zone model because it uses simplified representations of the physical processes and limits the number of parameters. We present in this study the development and application of a spatio-temporal recharge model (pyEARTH-2D) coupled with the numerical flow model MODFLOW at the catchment scale. pyEARTH-2D is a lumped-parameter distributed (grid-based) model that shares the same spatial discretization of the MODFLOW model for coupling purpose. pyEARTH-2D solves the water balance in the topsoil layer using linear relations between fluxes and soil moisture on a daily basis. The partitioning of rainfall is done by taking into consideration interception, evapotranspiration, percolation, soil moisture storage and surface storage and runoff. The input driving forces (rainfall and potential evapotranspiration) and the calibration state variables (hydraulic heads, soil moisture) time series are obtained through Automatic Data Acquisition System (ADAS) monitoring network. Parameterization of the soil reservoir requires basic soil hydraulic properties (soil porosity, specific retention, wilting point, saturated hydraulic conductivity and thickness) that can be obtained by standard field survey and laboratory measurements in the different soil zones of the catchment. Data integration using a combination of techniques such as remote sensing and statistics are used to determine soil properties spatially. The transient calibration of the coupled models is typically done against: (i) soil moisture of the recharge model pyEARTH-2D; (ii) hydraulic heads of the MODFLOW groundwater model. The coupling of pyEARTH-2D and MODFLOW is done through dynamic link of the parameter estimation algorithm PEST in which the simultaneous calibration of both models takes place. For each iterative cycle, recharge output is implemented in the MODFLOW model while the depth of the water table computed by MODFLOW is returned back to pyEARTH-2D in the next time step. The developed coupling procedure was tested in the Pisões (Portugal) and Sardon (Spain) catchments. In these two study case, the pyEARTH-2D and MODFLOW coupling approach solution was compared with the standard solution applying Recharge and Evapotranspiration packages of MODFLOW with regard to the goodness of fit and the similarity of the temporal trends between the simulated and observed hydraulic heads. Current developments of the pyEARTH-2D recharge model focus towards: i) improving the depth-wise discretization and parametrization of the unsaturated zone to represent the several soil horizons (pyEARTH-q3D); ii) partitioning of subsurface fluxes into unsaturated and saturated zone components to be able to quantify groundwater uptake by plants and loss of groundwater by direct evaporation from water table.
Francés, Alain Pascal; Berhe, Ermias; Lubczynski, Maciek
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. PMID:23112100
Dannhauer, Moritz; Lämmel, Eric; Wolters, Carsten H; Knösche, Thomas R
The rational design of interventions is critical to controlling communicable diseases, especially in urban environments. In the case of the Chagas disease vector Triatoma infestans, successful control is stymied by the return of the insect after the effectiveness of the insecticide wanes. Here, we adapt a genetic algorithm, originally developed for the travelling salesman problem, to improve the spatio-temporal design of insecticide campaigns against T. infestans, in a complex urban environment. We find a strategy that reduces the expected instances of vector return 34-fold compared with the current strategy of sequential insecticide application to spatially contiguous communities. The relative success of alternative control strategies depends upon the duration of the effectiveness of the insecticide, and it shows chaotic fluctuations in response to unforeseen delays in a control campaign. We use simplified models to analyse the outcomes of qualitatively different spatio-temporal strategies. Our results provide a detailed procedure to improve control efforts for an urban Chagas disease vector, as well as general guidelines for improving the design of interventions against other disease agents in complex environments.
Levy, Michael Z.; Malaga Chavez, Fernando S.; Cornejo del Carpio, Juan G.; Vilhena, Daril A.; McKenzie, F. Ellis; Plotkin, Joshua B.
Nitrate (NO3-) is considered the most prevalent contaminant in groundwater (GW). NO3- in GW shows significant spatio-temporal variability which comes from interaction among multiple geophysical factors such as source availability (land use), thickness and composition of the vadose zone, types of aquifers (confined or unconfined), aquifer heterogeneity (geological and alluvial), and precipitation characteristics etc. The present work seeks to describe the spatio-temporal variability of NO3- at multiple scales in two different hydrogeologic settings— the Trinity and Ogallala Aquifers in Texas at three spatial scales, fine (25 km.×25 km.), intermediate (50 km.×50 km.), and coarse (100 km.×100 km.) grids. An entropy-based approach was used to analyze spatial-temporal variability of NO3- within the aquifers. The Hurst exponent was used to evaluate the long-term persistence and trend in the variability of NO3-. The results demonstrate that the spatial variability of NO3- is controlled by the effect of soil type, irrigation-pumping, and local flow at the small scale and by the complex interactions between rivers and aquifers along with land use at the intermediate scale, and by lithology and geology at the coarse scale. The trends of variability of NO3- show long term persistence at the intermediate and coarse scales.
Dwivedi, D.; Mohanty, B. P.
Place names are signs of geographic entities, and the database of which, a digital gazetteer, is an increasingly important form of geographic information. So the construction and the application of digital gazetteers are growing research areas. And significant progress has been made in the development of which, but there are still some vital issues that require further work: (1) Places and attributes related would inevitably change over time, but few gazetteer services model temporal ranges; (2) Current gazetteers do not normally hold historical information; (3) The relationships between place name entries are few considered in most existing digital gazetteers; (4) Geographic footprints currently used in gazetteers are usually confined to simple representations. In this paper, we proposed a spatio-temporal data model for administrative division place names, which are in a significant and large proportion of place names. We took Xiamen City as a case, located in coastal areas of Fujian Province, Southeast of China, to describe our model. In the model, we considered spatio-temporal changes and relationships between entries in gazetteers, and the footprints used are multiscale patches adapting to hierarchical administrative system. Accordingly, our model could provide an important reference for digitizing gazetteers and further for implementing digital earth.
Yang, Liping; Lin, Guangfa; Chen, Ailing; Chen, Youfei; Wen, Xiaohuan
In this study, we evaluated the driving forces exerted by a large set of environmental and biological parameters on the spatial and temporal dynamics of archaeal community structure in two neighbouring peri-alpine lakes that differ in terms of trophic status. We analysed monthly data from a 2-year sampling period at two depths corresponding to the epi- and hypolimnetic layers. The archaeal communities seemed to be mainly composed of ammonia-oxidizing archaea belonging to the thaumarchaeotal phylum. The spatio-temporal dynamics of these communities were very similar in the two lakes and were characterized by (1) disparities in archaeal community structure in both time and space and (2) no seasonal reproducibility between years. The archaeal communities were regulated by a complex combination of abiotic factors, including temperature, nutrients, chlorophyll a and dissolved oxygen, and biotic factors such as heterotrophic nanoflagellates and ciliates. However, in most cases, these factors explained < 52% of the variance in archaeal community structure, while we showed in a previous study that these factors explained 70-90% of the temporal variance for bacteria. This suggests that Bacteria and Archaea may be influenced by different factors and could occupy different ecological niches despite similar spatio-temporal dynamics. PMID:23730709
Berdjeb, Lyria; Pollet, Thomas; Chardon, Cécile; Jacquet, Stéphan
Carnivorous plants have evolved modified leaves into the traps that assist in nutrient uptake from captured prey. It is known that the traps of carnivorous plants usually have lower photosynthetic rates than assimilation leaves as a result of adaptation to carnivory. However, a few recent studies have indicated that photosynthesis and respiration undergo spatio-temporal changes during prey capture and retention, especially in the genera with active trapping mechanisms. This study describes the spatio-temporal changes of effective quantum yield of photochemical energy conversion in photosystem II (?PSII) in response to ant-derived formic acid during its capture and digestion.
Reliable assessment of spatio-temporal variability of observed rainfall is difficult in the current climate because of the complex spatial variability displayed by daily and shorter time scale rainfall data. As demonstrated in a recent analysis of Canadian daily precipitation data by Hutchinson et al. (2009), direct interpolation of short time scale precipitation data is a poor way to address spatial patterns of rainfall extremes. Addressing the behaviour of projected future precipitation extremes is made even more difficult by the limited temporal and spatial resolution of precipitation as simulated by global climate models. The “uniform drizzle” that tends to be produced by these models makes the assessment of even straightforward statistics, such as daily rainfall occurrence, problematic. Putting aside significant inter-model variability, the more reliable outputs of global models include mean fluxes, such as monthly rainfall amounts, and associated insight into the nature of the modelled precipitation in relation to forcing synoptic systems. The truncated power of normal distribution, as described by Hutchinson (1995), offers a relatively simple way to make progress. Two of the three model parameters are simply calibrated in terms of monthly mean fluxes and the model is able to accurately describe precipitation extremes. These model parameters can also be robustly determined from serially incomplete data. It can be argued that the model has a broad physical process basis by modelling rainfall as an event that occurs as an appropriate threshold is exceeded. This analysis extends the approach of Stidd (1954, 1973) who suggested the cube root as a universal normalising power. We show that the power parameter, once robustly calibrated, displays a broadly spatially varying distribution of around 0.5. This corresponds well with the two dimensional synoptic convergence that is required to produce precipitation. The power parameter appears to be related to the degree of convection associated with observed precipitation, a key aspect of current and projected future precipitation. The paper demonstrates the accuracy and interpretability of the model in describing daily rainfall variability and extremes in the current climate. The mean rainfall is a dominant factor in the observed trends but there are also significant departures from this dependence. The model offers a robust observational benchmark against which more sophisticated models of atmospheric variability can be compared. References: Hutchinson, M.F., Mckenney, D.W., Lawrence, K., Pedlar, J., Hopkinson, R., Milewska, E. and Papadopol, P. 2009. Development and testing of Canada-wide interpolated spatial models of daily minimum/maximum temperature and precipitation for 1961-2003. Journal of Applied Meteorology and Climatology 48(4): 725-741. Hutchinson, M.F. 1995. Stochastic space-time weather models from ground-based data. Agricultural and Forest Meteorology 73: 237-264. Stidd, C.K., 1954. The use of correlation fields in relating precipitation to circulation. Journal of Meteorology 11:202-213. Stidd, C.K., 1973. Estimating the precipitation climate. Water Resources Research 9: 1235-1241.
Hutchinson, M. F.; Xu, T.; Kesteven, J.
Malaria is the leading cause of morbidity and mortality in Malawi with more than 6 million episodes reported each year. Malaria poses a huge economic burden to Malawi in terms of the direct cost of treating malaria patients and also indirect costs resulting from workdays lost in agriculture and industry and absenteeism from school. Malawi implements malaria control activities within the Roll Back Malaria framework, with the objective to provide those most at risk (i.e. children under five years, pregnant woman and individuals with suppressed immune systems) access to personal and community protective measures. However, at present there is no mechanism by which to target the most 'at risk' populations ahead of an impending epidemic. Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the mosquito and the availability of breeding sites, but also socio-economic conditions such as levels of urbanisation, poverty and education, which influence human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for modelling of malaria risk in space and time. Using an age-stratified spatio-temporal dataset of malaria cases at the district level from July 2004 - June 2011, we use a spatio-temporal modelling framework to model variations in malaria risk in Malawi. Climatic and topographic variations are accounted for using an interpolation method to relate gridded products to administrative districts. District level data is tested in the model to account for confounding factors, including the proportion of the population living in urban areas; residing in traditional housing; with no toilet facilities; who do not attend school, etc, the number of health facilities per population and yearly estimates of insecticide-treated mosquito net distribution. In order to account for the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a negative binomial generalised linear mixed model (GLMM) is adopted, which includes structured and unstructured spatial and temporal random effects. The parameters in this spatio-temporal Bayesian hierarchical model are estimated using Markov Chain Monte Carlo (MCMC). This allows posterior predictive distributions for disease risk to be derived for each spatial location and time period. A novel visualisation technique is then used to display seasonal probabilistic forecasts of malaria risk, derived from the developed model using pre-defined risk category thresholds, on a map. This technique allows decision makers to identify areas where the model predicts with certainty a particular malaria risk category (high, medium or low); in order to effectively target limited resources to those districts most at risk for a given season.
Lowe, R.; Chirombo, J.; Tompkins, A. M.
Flume experiments were conducted to investigate the spatio temporal structure of subaqueous particulate gravity flows with an initial concentration of 14% by volume. Time series of downstream flow velocity and its calculated degree of turbulence, median grain size and sediment concentration at different positions along the path of nominally identical flows are analysed and combined to constrain the spatio temporal evolution of a single idealised flow. Comparison of the 14% flow with a flow of 5% initial concentration reveals similarities in the basic spatio temporal structure of velocity, turbulence, grain size and concentration. Both flow types exhibit a velocity maximum at about 1 / 3 of the flow height above the flume floor. At that level, velocity decreases slowly in the flows' body and more rapidly in their tails. Moreover, turbulence intensity is highest in the head and at the base of the flows, whereas the level of maximum velocity and the tail of the flows typically are weakly turbulent. The zones of high turbulence are associated with shear at the front and base of the gravity flows. The flow of 5% and 14% initial concentration also agree in stratification patterns of median grain size and concentration. Grain populations are relatively well mixed in the head, show normal grading in the main part of the body and normal to inverse grading in the rear of the body and tail. The inverse grading is thought to originate from particles transported from the head upward and backward into the body of the flows, where they subsequently settle. The main difference between the flow of 5% and 14% initial concentration is that the higher-density flows appear to develop from a jet into a turbidity current closer to the inception point than the lower-density flow. This difference is interpreted from dimensionless vertical profiles of the flow parameters: horizontal velocity, concentration and grain size distribution. In the turbidity current phase of both flows, the dimensionless variables collapse well. This indicates that the flows behave in a dynamically similar manner and inspires confidence that the dimensionless variables can be used to predict the dynamic behaviour of particulate gravity flows across the measured concentration range in the flume, which due to dilution/sedimentation effects, was from ˜7 to < 1 vol.% concentration.
Choux, C. M. A.; Baas, J. H.; McCaffrey, W. D.; Haughton, P. D. W.
The 2004 Sumatra-Andaman earthquake occurred in an oblique subduction zone. The plate convergence direction significantly changes along the trench in the source region. The aftershocks activity and its variety of source mechanisms indicate the stress field in the source region is very complex. We conducted seismological analyses to investigate spatio-temporal variation of the stress filed in detail. We calculate angular
M. Oishi; T. Sagiya; T. Sato
The spatio-temporal distribution of epileptiform activity was investigated in slices from human temporal neocortex resected during epilepsy surgery. Activity was recorded by use of a voltage-sensitive dye and an optical recording system. Epileptiform activity was induced with 10 ?M bicuculline and electrical stimulation of layer I. In 10 slices from six patients investigated, epileptiform activity spread across most of the
B Albowitz; U Kuhnt; R Köhling; A Lücke; H Straub; E.-J Speckmann; I Tuxhorn; P Wolf; H Pannek; F Oppel
As part of the 2002 Western Arctic Shelf Basin Interactions (SBI) project, spatio-temporal variability of dissolved inorganic carbon (DIC) was employed to determine rates of net community production (NCP) for the Chukchi and western Beaufort Sea shelf and slope, and Canada Basin of the Arctic Ocean. Seasonal and spatial distributions of DIC were characterized for all water masses (e.g., mixed
Nicholas R. Bates; Margaret H. P. Best; Dennis A. Hansell
The effects of incline (vertical versus horizontal) on spatio-temporal gait characteristics (stride and step length, frequency, duty factor, degree of sprawling) were measured over a range of speeds in a ground-dwelling (Eublepharis macularius) and a climbing (Gekko gecko) species of gecko. Surprisingly, the climbing species also performs very well when moving on the horizontal substratum. In the present experiments, climbing
A. ZAAF; R. VAN DAMME; A. HERREL; P. AERTS
We study acoustic emission (AE) activity caused by cyclic thermal loading due to the backfilling of a cavity in an abandoned salt mine to answer questions regarding the stress memory effect of rock (Kaiser effect), the dependence of AE rates and b-value on the stress state as well as the stress rate and the spatio-temporal evolution of the AE activity.
D. Becker; B. Cailleau; T. Dahm; S. Shapiro; D. Kaiser
The spatio-temporal population dynamics of the subtidal snail Umbonium costatum (Kiener) in Hakodate Bay, northern Japan, are described over a 9-yr period (1982 to 1988, 1992). Annual variations in recruitment success not only caused the highly variable age structure of the population, but also affected its distribution pattern. In heavy recruitment years (1982, 1984 and 1988), location of the densest
T. Noda; S. Nakao
A spatio-temporal analysis was carried out to see how the risk distribution of bovine spongiform encephalopathy (BSE) in France changed depending on the period of birth. The data concerned the 539 BSE cases born in France after the ban (BAB) of meat and bone meal (MBM) in 1990 and detected between July 1, 2001 and December 31, 2003, when the
Christian Ducrot; David Abrial; Didier Calavas; Tim Carpenter
integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC's change. In this study, with the support of GIS, RS technology and based on recent 10 years LULC data, the landscape pattern dynamics and regional spatio-temporal features related with the LULC change of three metropolis in Asian region, Zhangjiagang
Xinglong Zou; Zhen Shang; Inakwu O. A. Odeh; Yizhao Chen; Jianlong Li
A new original method for investigating global spatio-temporal wave properties of meteorological e g ionospheric parameters is offered Its most important application is study of planetary wave influence on ionospheric parameter variations Wave amplitude distributions wave phase propagation velocity and motion directions can be obtained on the basis of interpolation and further analysis of experimental data from world ionospheric database
E. Ryabchenko; O. Sherstyukov
Low birth weight (LBW) defined as infant weight at birth of less than 2500g is a useful health outcome for exploring spatio-temporal variation and the role of covariates. LBW is a key measure of population health used by local, national and international health organizations. Yet its spatio-temporal patterns and their dependence structures are poorly understood. In this study we examine the use of flexible latent structure models for the analysis of spatio-temporal variation in LBW. Beyond the explanatory capabilities of well-known predictors, we observe spatio-temporal effects, which are not directly observable using conventional modeling approaches. Our analysis shows that for county-level counts of LBW in Georgia and South Carolina the proportion of black population is a positive risk factor while high-income is a negative risk factor. Two dominant residual temporal components are also estimated. Finally our proposed method provides a better goodness-of-fit to these data than the conventional space-time models.
Kirby, Russell S.; Liu, Jihong; Lawson, Andrew B.; Choi, Jungsoon; Cai, Bo; Hossain, Md Monir
The majority of the area contaminated by the Fukushima Dai-ichi nuclear power plant accident is covered by forest. To facilitate effective countermeasure strategies to mitigate forest contamination, we simulated the spatio-temporal dynamics of radiocesium deposited into Japanese forest ecosystems in 2011 using a model that was developed after the Chernobyl accident in 1986. The simulation revealed that the radiocesium inventories in tree and soil surface organic layer components drop rapidly during the first two years after the fallout. Over a period of one to two years, the radiocesium is predicted to move from the tree and surface organic soil to the mineral soil, which eventually becomes the largest radiocesium reservoir within forest ecosystems. Although the uncertainty of our simulations should be considered, the results provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident. PMID:23995073
Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji
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.
Mächel, H.; Kapala, A.
Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatio-temporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA approach: spatial complex ICA applied to frequency-domain fMRI data. In several frequency-bands, we identify components pertaining to activity in primary visual cortex (V1) and blood supply vessels. One such component, obtained in the 0.10 Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1.
Anemuller, Jorn; Duann, Jeng-Ren; Sejnowski, Terrence J.; Makeig, Scott
Supersonic jets are important for many experiments in physics, chemistry, and engineering sciences. Characterization of the density profile of the gas released from the nozzle is crucial for many applications and generally requires complicated measurements. A method that uses a common microphone to characterize the spatio-temporal gas profile of the supersonic jet is demonstrated here. Calibrating the microphone signals with the pressure change in the stagnation chamber, it is shown that it is possible to measure the complete density profile of the conical gas emission from the supersonic jet. It is shown that any conical section has a gaussian radial profile and that the peak densities decrease as 1/z'2, where z' is the distance from the nozzle.
Rajeev, R.; Raja, S. V.; Madhu Trivikram, T.; Rishad, K. P. M.; Krishnamurthy, M.
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.
Aksoy, Ece; Panagos, Panos; Montanarella, Luca
The spatial and temporal distribution and the flux of black carbon (BC) concentration in Beijing were continuously investigated over a two-year period at five sites to highlight the relative influence of contributing sources. The results demonstrate firstly that there is significant spatio-temporal variability of BC in Beijing. Highest concentrations occurred during winter primarily due to stagnant meteorological conditions, and seasonal BC sources, such as coal combustion for heating purposes. Biomass burning was identified as a minor seasonal source during the summer months. BC also varied spatially with higher concentrations in the SE of Beijing and lower concentrations in the NW, due to the differing emission intensity of various local BC sources such as traffic and industry. Frequently, overnight BC concentrations were higher due to specific meteorological conditions, such as the lower urban mixing layer height and various anthropogenic activities, such as exclusive night-time heavy duty vehicle traffic in the inner-city. PMID:23978522
Schleicher, Nina; Norra, Stefan; Fricker, Mathieu; Kaminski, Uwe; Chen, Yizhen; Chai, Fahe; Wang, Shulan; Yu, Yang; Cen, Kuang
We propose a spatial version of the neutral community model on a network of interconnected patches. The dynamical equations for the abundances and higher order moments of the abundances are established. Due to the neutrality assumption these equations are autonomous, enabling an exact analysis of spatio-temporal dynamics. We compute local (i.e., inside a patch) and global (i.e., between patches) diversities, and illustrate our results with two examples: (1) a non-spatial community, for which we recover previous results, and (2) a model with a finite number of patches which are all connected to each other with equal migration intensity. We discuss the relevance of this model for experiments in microbial ecology. PMID:19885659
Vanpeteghem, Dimitri; Haegeman, Bart
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.
Weldeab, Syee; Frank, Martin; Stichel, Torben; Haley, Brian; Sangen, Mark
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.
Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji
Our group has developed a system for observing seafloor crustal deformation with a combination of acoustic ranging and kinematic GPS positioning techniques. One of the effective factors to reduce estimation error of submarine benchmark in our system is modeling variation of ocean acoustic velocity. We estimated various 1-dimensional velocity models with depth under some constraints, because it is difficult to estimate 3-dimensional acoustic velocity structure including temporal change due to our simple acquisition procedure of acoustic ranging data. We, then, applied the joint hypocenter determination method in seismology [Kissling et al., 1994] to acoustic ranging data. We assume two conditions as constraints in inversion procedure as follows: 1) fixed acoustic velocity in deeper part because it is usually stable both in space and time, 2) each inverted velocity model should be decreased with depth. The following two remarkable spatio-temporal changes of acoustic velocity 1) variations of travel-time residuals at the same points within short time and 2) larger differences between residuals at the neighboring points, which are one's of travel-time from different benchmarks. The First results cannot be explained only by the effect of atmospheric condition change including heating by sunlight. To verify the residual variations mentioned as the second result, we have performed forward modeling of acoustic ranging data with velocity models added velocity anomalies. We calculate travel time by a pseudo-bending ray tracing method [Um and Thurber, 1987] to examine effects of velocity anomaly on the travel-time differences. Comparison between these residuals and travel-time difference in forward modeling, velocity anomaly bodies in shallower depth can make these anomalous residuals, which may indicate moving water bodies. We need to apply an acoustic velocity structure model with velocity anomaly(s) in acoustic ranging data analysis and/or to develop a new system with a large number of sea surface stations to detect them, which may be able to reduce error of seafloor benchmarker position.
Eto, S.; Nagai, S.; Tadokoro, K.
Lake Tebenquiche is one of the largest saline water bodies in the Salar de Atacama at 2,500 m above sea level in northeastern Chile. Bacteria inhabiting there have to deal with extreme changes in salinity, temperature and UV dose (i.e., high environmental dissimilarity in the physical landscape). We analyzed the bacterioplankton structure of this lake by 16S rRNA gene analyses along a spatio-temporal survey. The bacterial assemblage within the lake was quite heterogeneous both in space and time. Salinity changed both in space and time ranging between 1 and 30% (w/v), and total abundances of planktonic prokaryotes in the different sampling points within the lake ranged between two and nine times 10(6) cells mL(-1). Community composition changed accordingly to the particular salinity of each point as depicted by genetic fingerprinting analyses (denaturing gradient gel electrophoresis), showing a high level of variation in species composition from place to place (beta-diversity). Three selected sites were analyzed in more detail by clone libraries. We observed a predominance of Bacteroidetes (about one third of the clones) and Gammaproteobacteria (another third) with respect to all the other bacterial groups. The diversity of Bacteroidetes sequences was large and showed a remarkable degree of novelty. Bacteroidetes formed at least four clusters with no cultured relatives in databases and rather distantly related to any known 16S rRNA sequence. Within this phylum, a rich and diverse presence of Salinibacter relatives was found in the saltiest part of the lake. Lake Tebenquiche included several novel microorganisms of environmental importance and appeared as a large unexplored reservoir of unknown bacteria. PMID:18347752
Demergasso, Cecilia; Escudero, Lorena; Casamayor, Emilio O; Chong, Guillermo; Balagué, Vanessa; Pedrós-Alió, Carlos
Floodplains have been intensively altered in industrialized countries, but are now increasingly being restored. It is therefore important to assess the effect of these restoration projects on the aquatic and terrestrial components of ecosystems. However, despite being functionally crucial components of terrestrial ecosystems, soils are generally overlooked in floodplain restoration assessments. We studied the spatio-temporal heterogeneity of soil morphology in a restored (riverbed widening) river reach along the River Thur (Switzerland) using three criteria (soil diversity, dynamism and typicality) and their associated indicators. We hypothesized that these criteria would correctly discriminate the post-restoration changes in soil morphology, and that these changes correspond to patterns of vascular plant diversity. Soil diversity and dynamism increased 5 yr after the restoration, but some typical soils of braided rivers were still missing. Soil typicality and dynamism were correlated to vegetation changes. These results suggest a limited success of the project, in agreement with evaluations carried out at the same site using other, more resource-demanding, methods (e.g., soil fauna, fish diversity, ecosystem functioning). Soil morphology provides structural and functional information on floodplain ecosystems. The spatio-temporal heterogeneity of soil morphology represents a cost-efficient ecological indicator that could easily be integrated into rapid assessment protocols of floodplain and river restoration projects. The follow-up assessment after several major floods (? HQ20) should take place to allow for testing the longer-term validity of our conclusion for the River Thur site. More generally, it would be useful to apply the soil morphology indicator approach in different settings to test its broader applicability.
Fournier, B.; Guenat, C.; Bullinger-Weber, G.; Mitchell, E. A. D.
The aim of this study is to estimate the influence of different forcing factors acting on instability phases of a slow alpine earthslide-earthflow, by means of the characteristics of decomposed deformations signals derived by displacement rates measured in its different sectors. In this work we analyze a slow landslide located ESE from Corvara in Badia, a famous tourist area in the Dolomites (NE Italy). Road, infrastructure, ski and other recreational facilities, isolated buildings close to the town of Corvara and finally an artificial reservoir for snow production are threatened and occasionally damaged by this mass movement. It flows from 2000m s.l. to 1500m s.l. where a paleo-landslide deposit is partially covered and re-activated. In the last 10 years the Province of Bolzano carried out discontinuous GPS surveys between 5 and 1 times per year to define the landslide's level of hazard. The landslide volume is resulted to be 30Mm3, extending downslope for approx. 3km, with displacement rates between few centimeters and slightly less than 10m per year. To analyze this area we used data from active radar sensors (SAR - Synthetic Aperture Radar). The SAR-based dataset consists in high resolution X-band SAR data from the Cosmo SkyMed (CSK) mission acquired every 8 days from August 2010 to September 2011. Part of the 38 CSK scenes contain the back-scattering signal from 17 artificial reflectors (AR) installed along the AOI and partially on existing GPS benchmarks for data validation and integration. The ARs back scattering signal has been elaborated in order to track their displacement from August 2010 to September 2011, in the lower zone of the landslide, as well as from March 2011 to September 2011 in the higher part, excluding the period when the snow was covering the surface. The signals have been analyzed with Fourier and wavelet methods to identify the different frequencies and nature of the components. T and Mann-Kendall tests have been used to assess the presence of trends. Fits with exponential functions of the de-trended and de-seasonalized signal have been performed to identify the presence of dissipating deformations. We observed that the signal of velocity and acceleration is characterized by the coexistence of different factors: first, periodic signals associated to seasonal and gravitational kinematic behavior; second, decay effects due to instability events. Moreover, using different points is possible to observe the signal propagation both in time and space. This analysis allow us to determine the spatio-temporal scale of different forcing events and their effect on the total landslide area. Finally, this study represent a new approach for identify the spatio-temporal nature of different factors in the evolution of the landslide for setting-up a system of conscious prediction of maintenance tasks of the exposed structures. The use of the SAR data demonstrated to be an innovative tool for high temporal resolution surveys with a big amount of points that in comparison with GPS surveys results to be economically convenient in wide AOI.
Mulas, M.; Petitta, M.; Brazanti, M.; Benedetti, E.; Corsini, A.; Iasio, C.
In this paper a method for spatio-temporal encoding is presented for synthetic transmit aperture ultrasound imaging (STA). The purpose is to excite several transmitters at the same time in order to transmit more acoustic energy in every single transmission. When increasing the transmitted acoustic energy, the signal to noise ratio will increase. However, to focus the data properly using the STA approach, the transmitters have to be separated from each other. This is done by dividing the available spectrum into several subbands with a small overlap. Separating different transmitters can be done by bandpass filtering. Therefore, the separation can be done instantaneously without the need for further transmissions, unlike spatial encoding relying on Hadamard or Golay coding schemes, where several transmissions have to be made before the decoding can be done. Motion artifacts from the decoding can, thus, be avoided. To further increase the transmitted energy, the excitation waveforms are designed as linear frequency modulated (FM) signals. This makes it possible to maintain the full excitation amplitude during most of the transmission. The design of the separation filters will also be discussed. The method was tested using the experimental ultrasound scanner RASMUS and evaluated using a reference setup with a linear FM excitation waveform and STA beamforming. The point spread function (PSF) was measured on a wire phantom in water. A wire phantom with an attenuating medium was also measured, where the proposed method achieved approximately 2 cm improvement in penetration depth. The signal to noise ratio was also measured, where the gain was approx. 7 dB in comparison to the reference.
Gran, Fredrik; Jensen, Jorgen A.
Background The Comunitat Valenciana (CV) is a tourist region on the Mediterranean coast of Spain with a high rate of retirement migration. Lung cancer in women is the cancer mortality cause that has increased most in the CV during the period 1991 to 2000. Moreover, the geographical distribution of risk from this cause in the CV has been previously described and a non-homogenous pattern was determined. The present paper studies the spatio-temporal distribution of lung cancer mortality for women in the CV during the period 1987–2004, in order to gain some insight into the factors, such as migration, that have had an influence on these changes. Methods A novel methodology, consisting of a Bayesian hierarchical model, is used in this paper. Such a model allows the handling of data with a very high disaggregation, while at the same time taking advantage of its spatial and temporal structure. Results The spatio-temporal pattern which was found points to geographical differences in the time trends of risk. In fact, the southern coastal side of the CV has had a higher increase in risk, coinciding with the settlement of a large foreign community in that area, mainly comprised of elderly people from the European Union. Conclusion Migration has frequently been ignored as a risk factor in the description of the geographical risk of lung cancer and it is suggested that this factor should be considered, especially in tourist regions. The temporal component in disease mapping provides a more accurate depiction of risk factors acting on the population.
Zurriaga, Oscar; Vanaclocha, Hermelinda; Martinez-Beneito, Miguel A; Botella-Rocamora, Paloma
Despite a longstanding universal concern about and intensive research into woody plant encroachment (WPE)---the replacement of grasslands by shrub- and woodlands---our accumulated understanding of the process has either not been translated into sustainable rangeland management strategies or with only limited success. In order to increase our scientific insights into WPE, move us one step closer toward the sustainable management of rangelands affected by or vulnerable to the process, and identify needs for a future global research agenda, this dissertation presents an unprecedented critical, qualitative and quantitative assessment of the existing literature on the topic and evaluates the utility of an integrative remote sensing, GIS, and spatial modeling approach for quantifying the spatio-temporal dynamics of WPE. Findings from this research suggest that gaps in our current understanding of WPE and difficulties in devising sustainable rangeland management strategies are in part due to the complex spatio-temporal web of interactions between geoecological and anthropogenic variables involved in the process as well as limitations of presently available data and techniques. However, an in-depth analysis of the published literature also reveals that aforementioned problems are caused by two further crucial factors: the absence of information acquisition and reporting standards and the relative lack of long-term, large-scale, multi-disciplinary research efforts. The methodological framework proposed in this dissertation yields data that are easily standardized according to various criteria and facilitates the integration of spatially explicit data generated by a variety of studies. This framework may thus provide one common ground for scientists from a diversity of fields. Also, it has utility for both research and management. Specifically, this research demonstrates that the application of cutting-edge remote sensing techniques (Multiple Endmember Spectral Mixture Analysis, fuzzy logic-based change detection) to conventional medium spatial and spectral resolution imagery (Landsat Thematic Mapper, Landsat Enhanced Thematic Mapper Plus, ASTER) can be used to generate spatially explicit estimates of temporal changes in the abundance of woody plants and other surface materials. The research also shows that spatial models (Geographically Weighted Regression, Weights of Evidence, Weighted Logistic Regression) integrating this timely remotely sensed information with readily available GIS data can yield reasonably accurate estimates of an area's relative vulnerability to WPE and of the importance of anthropogenic and geoecological variables influencing the process. Such models may also be used for the testing of existing and generation of new scientific hypotheses about WPE, for evaluating the impact of natural or human-induced modifications of a landscape on the landscape's vulnerability to WPE, and for identifying target areas for conservation, restoration, or other management objectives. In sum, this dissertation demonstrates that integrative remote sensing, GIS, and spatial modeling approaches have enormous potential for addressing questions relevant to both rangelands research and management. However, it also suggests that much work remains to be done before we can translate our understanding of WPE into sustainable rangeland management strategies. In particular, we need to more fully explore the limitations and potentials of currently available data and techniques for quantifying WPE; build structures for data sharing and integration; develop a set of relevant standards; more actively engage in collaborative research efforts; and foster cross-cutting dialogues among researchers, managers, and communities.
Humans, even babies, perceive causality when one shape moves briefly and linearly after another. Motion timing is crucial in this and causal impressions disappear with short delays between motions. However, the role of temporal information is more complex: it is both a cue to causality and a factor that constrains processing. It affects ability to distinguish causality from non-causality, and social from mechanical causality. Here we study both issues with 3- to 7-year-olds and adults who saw two computer-animated squares and chose if a picture of mechanical, social or non-causality fit each event best. Prior work fit with the standard view that early in development, the distinction between the social and physical domains depends mainly on whether or not the agents make contact, and that this reflects concern with domain-specific motion onset, in particular, whether the motion is self-initiated or not. The present experiments challenge both parts of this position. In Experiments 1 and 2, we showed that not just spatial, but also animacy and temporal information affect how children distinguish between physical and social causality. In Experiments 3 and 4 we showed that children do not seem to use spatio-temporal information in perceptual causality to make inferences about self- or other-initiated motion onset. Overall, spatial contact may be developmentally primary in domain-specific perceptual causality in that it is processed easily and is dominant over competing cues, but it is not the only cue used early on and it is not used to infer motion onset. Instead, domain-specific causal impressions may be automatic reactions to specific perceptual configurations, with a complex role for temporal information. PMID:23874308
Schlottmann, Anne; Cole, Katy; Watts, Rhianna; White, Marina
Intestinal absorption of dietary fat is a complex process mediated by enterocytes leading to lipid assembly and secretion of circulating lipoproteins as chylomicrons, vLDL and intestinal HDL (iHDL). Understanding lipid digestion is of importance knowing the correlation between excessive fat absorption and atherosclerosis. By using time-of-flight secondary ion mass spectrometry (TOF-SIMS), we illustrated a spatio-temporal localization of fat in mice duodenum, at different times of digestion after a lipid gavage, for the first time. Fatty acids progressively increased in enterocytes as well as taurocholic acid, secreted by bile and engaged in the entero-hepatic re-absorption cycle. Cytosolic lipid droplets (CLD) from enterocytes were originally purified separating chylomicron-like, intermediate droplets and smaller HDL-like. A lipidomic quantification revealed their contents in triglycerides, free and esterified cholesterol, phosphatidylcholine, sphingomyelin and ceramides but also in free fatty acids, mono- and di-acylglycerols. An acyl-transferase activity was identified and the enzyme monoacylglycerol acyl transferase 2 (MGAT2) was immunodetected in all CLD. The largest droplets was also shown to contain the microsomal triglyceride transfer protein (MTTP), the acyl-coenzyme A-cholesterol acyltransferases (ACAT) 1 and 2, hormone sensitive lipase (HSL) and adipose triglyceride lipase (ATGL). This highlights the fact that during the digestion of fats, enterocyte CLD contain some enzymes involved in the different stages of the metabolism of diet fatty acids and cholesterol, in anticipation of the crucial work of endoplasmic reticulum in the process. The data further underlines the dual role of chylomicrons and iHDL in fat digestion which should help to efficiently complement lipid-lowering therapy. PMID:23560035
Seyer, Alexandre; Cantiello, Michela; Bertrand-Michel, Justine; Roques, Véronique; Nauze, Michel; Bézirard, Valérie; Collet, Xavier; Touboul, David; Brunelle, Alain; Coméra, Christine
Intestinal absorption of dietary fat is a complex process mediated by enterocytes leading to lipid assembly and secretion of circulating lipoproteins as chylomicrons, vLDL and intestinal HDL (iHDL). Understanding lipid digestion is of importance knowing the correlation between excessive fat absorption and atherosclerosis. By using time-of-flight secondary ion mass spectrometry (TOF-SIMS), we illustrated a spatio-temporal localization of fat in mice duodenum, at different times of digestion after a lipid gavage, for the first time. Fatty acids progressively increased in enterocytes as well as taurocholic acid, secreted by bile and engaged in the entero-hepatic re-absorption cycle. Cytosolic lipid droplets (CLD) from enterocytes were originally purified separating chylomicron-like, intermediate droplets and smaller HDL-like. A lipidomic quantification revealed their contents in triglycerides, free and esterified cholesterol, phosphatidylcholine, sphingomyelin and ceramides but also in free fatty acids, mono- and di-acylglycerols. An acyl-transferase activity was identified and the enzyme monoacylglycerol acyl transferase 2 (MGAT2) was immunodetected in all CLD. The largest droplets was also shown to contain the microsomal triglyceride transfer protein (MTTP), the acyl-coenzyme A-cholesterol acyltransferases (ACAT) 1 and 2, hormone sensitive lipase (HSL) and adipose triglyceride lipase (ATGL). This highlights the fact that during the digestion of fats, enterocyte CLD contain some enzymes involved in the different stages of the metabolism of diet fatty acids and cholesterol, in anticipation of the crucial work of endoplasmic reticulum in the process. The data further underlines the dual role of chylomicrons and iHDL in fat digestion which should help to efficiently complement lipid-lowering therapy.
Seyer, Alexandre; Cantiello, Michela; Bertrand-Michel, Justine; Roques, Veronique; Nauze, Michel; Bezirard, Valerie; Touboul, David; Comera, Christine
The sense of touch is initiated by stimulation of peripheral mechanoreceptors, and then the spatio-temporal pattern of the\\u000a receptors’ activation is interpreted by central cortical processing. To explore the tactile central processing, we psychophysically\\u000a studied human judgments of the temporal relationships between two tactile events occurring at different skin locations. We\\u000a examined four types of two-point temporal judgments—simultaneity, temporal order,
Shinobu KurokiJunji; Junji Watanabe; Naoki Kawakami; Susumu Tachi; Shin’ya Nishida
Eddy covariance measurements of methane are becoming more common with different new analyzers available. The resulting near-continuous time series can among others improve our understanding of short-term processes (e.g. ebullition). While time series of chamber measurements allow the analysis of seasonal development, they rarely detect short-term events. However, even in the case of eddy covariance measurements, these events might be due to changes in the source area while the ecological driving parameters do not change significantly. We hypothesize that short-term oscillations in the time series of CH4 emission can indicate an increase or decrease of the distribution of high-emitting microsites in the fetch in addition to ecological influences. To test this hypothesis, we present data from one growing season (7 May - 30 September 2007) from an oligotrophic mire complex in Eastern Finland (62.46°N, 30.58°E). The eddy covariance system was installed in the centre of the peatland, which consists to varying degree of dry sites (hummocks) and sedge-covered wetter sites (lawns). A footprint model and high-resolution aerial pictures were used to estimate the relative contribution of the two sites to the half-hourly eddy covariance flux. Preliminary results show that the emissions from a mire part with predominating lawns are higher than from a part with equally distributed lawns and hummocks. However, these patterns are overlaid by climate driven parameters: Emissions from the lawn-dominated part can be as low as those from the part with equally distributed hummocks and lawns during periods of cold air coming from the North. Multivariate empirical modelling will be applied to analyse in detail the spatio-temporal control of the eddy covariance methane flux time series.
Forbrich, I.; Kutzbach, L.; Wille, C.; Wu, J.; Becker, T.; Wilmking, M.
The recent 7.0 M earthquake that caused severe damage and destruction in parts of Haiti struck close to 5 PM (local time), at a moment when many people were not in their residences, instead being in their workplaces, schools, or churches. Community vulnerability assessment to seismic hazard relying solely on the location and density of resident-based census population, as is commonly the case, would grossly misrepresent the real situation. In particular in the context of global (climate) change, risk analysis is a research field increasingly gaining in importance whereas risk is usually defined as a function of hazard probability and vulnerability. Assessment and mapping of human vulnerability has however generally been lagging behind hazard analysis efforts. Central to the concept of vulnerability is the issue of human exposure. Analysis of exposure is often spatially tied to administrative units or reference objects such as buildings, spanning scales from the regional level to local studies for small areas. Due to human activities and mobility, the spatial distribution of population is time-dependent, especially in metropolitan areas. Accurately estimating population exposure is a key component of catastrophe loss modeling, one element of effective risk analysis and emergency management. Therefore, accounting for the spatio-temporal dynamics of human vulnerability correlates with recent recommendations to improve vulnerability analyses. Earthquakes are the prototype for a major disaster, being low-probability, rapid-onset, high-consequence events. Lisbon, Portugal, is subject to a high risk of earthquake, which can strike at any day and time, as confirmed by modern history (e.g. December 2009). The recently-approved Special Emergency and Civil Protection Plan (PEERS) is based on a Seismic Intensity map, and only contemplates resident population from the census as proxy for human exposure. In the present work we map and analyze the spatio-temporal distribution of population in the daily cycle to re-assess exposure to earthquake hazard in the Lisbon Metropolitan Area, home to almost three million people. New high-resolution (50 m grids) daytime and nighttime population distribution maps are developed using dasymetric mapping. The modeling approach uses areal interpolation to combine best-available census data and statistics with land use and land cover data. Mobility statistics are considered for mapping daytime distribution, and empirical parameters used for interpolation are obtained from a previous effort in high resolution population mapping of part of the study area. Finally, the population distribution maps are combined with the Seismic Hazard Intensity map to: (1) quantify and compare human exposure to seismic intensity levels in the daytime and nighttime periods, and (2) derive nighttime and daytime overall Earthquake Risk maps. This novel approach yields previously unavailable spatio-temporal population distribution information for the study area, enabling refined and more accurate earthquake risk mapping and assessment. Additionally, such population exposure datasets can be combined with different hazard maps to improve spatio-temporal assessment and risk mapping for any type of hazard, natural or man-made. We believe this improved characterization of vulnerability and risk can benefit all phases of the disaster management process where human exposure has to be considered, namely in emergency planning, risk mitigation, preparedness, and response to an event.
Freire, Sérgio; Aubrecht, Christoph
When sampling spatio-temporal random variables, the cost of a measurement may differ according to the setup of the whole sampling design: static measurements, i.e. repeated measurements at the same location, synchronous measurements or clustered measurements may be cheaper per measurement than completely individual sampling. Such "grouped" measurements may however not be as good as individually chosen ones because of redundancy. Often, the overall cost rather than the total number of measurements is fixed. A sampling design with grouped measurements may allow for a larger number of measurements thus outweighing the drawback of redundancy. The focus of this paper is to include the tradeoff between the number of measurements and the freedom of their location in sampling design optimisation. For simple cases, optimal sampling designs may be fully determined. To predict e.g. the mean over a spatio-temporal field having known covariance, the optimal sampling design often is a grid with density determined by the sampling costs [1, Ch. 15]. For arbitrary objective functions sampling designs can be optimised relocating single measurements, e.g. by Spatial Simulated Annealing . However, this does not allow to take advantage of lower costs when using grouped measurements. We introduce a heuristic that optimises an arbitrary objective function of sampling designs, including static, synchronous, or clustered measurements, to obtain better results at a given sampling budget. Given the cost for a measurement, either within a group or individually, the algorithm first computes affordable sampling design configurations. The number of individual measurements as well as kind and number of grouped measurements are determined. Random locations and dates are assigned to the measurements. Spatial Simulated Annealing is used on each of these initial sampling designs (in parallel) to improve them. In grouped measurements either the whole group is moved or single measurements within the group, e.g. static measurements may be moved to another location or the sampling times may be rearranged. After several optimisation steps, the objective functions of the sampling designs are compared. Only for the best ones optimisation is pursued. After several iterations the sampling designs are selected again. Thus more and more of the low performing sampling designs are deleted and computational effort is concentrated on the most promising candidates. The use case is optimisation of a monitoring sampling design for a river. We use a flow model to simulate the spread of a pollutant that enters the system at different locations with known, location-dependent probabilities and at random times. The objective function to be minimised is the amount of pollution that is not detected. Keywords: spatio-temporal sampling design, static sample, synchronous sample, spatial simulated annealing, cost function References  Jaap de Gruijter, Dick Brus, Marc Bierkens, and Martin Knotters. Sampling for Natural Ressource Monitoring. Springer, 2006.  J. W. van Groenigen. Spatial simulated annealing for optimizing sampling, In: GeoENV I Geostatistics for environmental applications, pages 351 - 361, 1997.
Helle, Kristina; Pebesma, Edzer
The dengue virus has a single-stranded positive-sense RNA genome of approximately 10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1-4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in São José do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000-2001. Sixty DENV-3 from São José do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R(0) = 1.53 and values for lineage 2 of R(0) = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area. PMID:19478848
Mondini, Adriano; de Moraes Bronzoni, Roberta Vieira; Nunes, Silvia Helena Pereira; Chiaravalloti Neto, Francisco; Massad, Eduardo; Alonso, Wladimir J; Lázzaro, Eduardo S M; Ferraz, Amena Alcântara; de Andrade Zanotto, Paolo Marinho; Nogueira, Maurício Lacerda
Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.
Fire changes soil properties directly, through temperature, or indirectly with ash deposition and the temporal elimination of vegetal cover. Both influences change soil colour and soil properties. The degree of changes depends on fire severity that has important implications on soil organic matter, texture, mineralogy and hydrological properties and type of ash produced. The ash colour is different according to the temperature of combustion and burned specie and this property will have implications on soil colour. In addition, ash properties have a strong spatial variability. The aim of this work is to study the spatio-temporal effects of a low severity grassland fire on soil colour occurred in Lithuania, near Vilnius city (54° 42' N, 25° 08' E, 158 m.a.s.l.). After the fire it was designed a plot of 20x20m in a burned and unburned flat area. Soil colour was analysed immediately after the fire, and 2, 5, 7 and 9 months after the fire. In each sampling 25 soil samples were collected, carried out to the laboratory, dried at room temperature (20-24° C) and sieved with the <2mm mesh. Soil colour was observed with the Munsell colour chart and the soil chroma value (CV) was observed. Since data did not respected the Gaussian distribution a neperian logarithmic (ln) transformation was applied. Differences among time and between plots were observed with the repeated measures ANOVA test, followed by a Tukey HSD test. Differences were significant at a p<0.05. The spatial variability (SV) was assessed with the coefficient of variation using non transformed data. The results showed differences among time at a p<0.001, treatment at a p<0.01 and time x treatment at a p<0.01. This means that fire during the first 9 months changed significantly soil colour. The CV of the burned plot was lower than the control plot (darker colour), that is attributed to the deposition of charred material and charcoal. This ash produced in this fire was mainly black coloured. With the time the soil of the burned plot became lighter, due the movement of charred material and charcoal in depth through soil profile. After the fire SV was higher in the burned plot (13.27%) than in the unburned plot (7.95%). This major variability might be attributed to ash influence, since this fire did nit had direct effects on soil. Despite the reduced CV, some patches burned at higher severity, and ash was dark and light grey and this might had influences on soil colour SV. In the following measurements SV was very similar, but always slightly higher in the control plot than in the burned plot. Two months, unburned 15.52% and burned, 14.70%. Five months, unburned, 14.78% and burned 14.42%, Seven months, unburned, 15.15% and burned, 14.67%. Nine months, unburned, 18.96% and burned 17.84%. After the fire ash can be (re)distributed uncountable times. In the immediate period after the fire, finner ash produced at higher severities is easily transported by wind and can remix (Pereira et al., 2013a, Pereira et al., 2013b) and change soil colour. In this fire, vegetation recovered very fast, thus this process might occurred only in the first weeks after the fire (Pereira et al., 2013c). Since vegetation recovered fast, soil colour SV depended on carbon and charred material movement in depth soil profile. Further studies are needed on the soil colour evolution after the fire, since can be an indicator of soil properties such as temperature reached with implications in other soil properties. Acknowledgements The authors appreciated the support of the project "Litfire", Fire effects in Lithuanian soils and ecosystems (MIP-048/2011) funded by the Lithuanian Research Council, Spanish Ministry of Science and Innovation for funding through the HYDFIRE project CGL2010-21670-C02-01, FUEGORED (Spanish Network of Forest Fire Effects on Soils http://grupo.us.es/fuegored/) and to Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya. References Pereira, P. Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2013a) Mod
Pereira, Paulo; Cerdà, Artemi; Bolutiene, Violeta; Pranskevicius, Mantas; Úbeda, Xavier; Jordán, Antonio; Zavala, Lorena; Mataix-Solera, Jorge
Inferior olive (IO) neurons project to the cerebellum and contribute to motor control. They can show intriguing spatio-temporal dynamics with rhythmic and synchronized spiking. IO neurons are connected to their neighbors via gap junctions to form an electrically coupled network, and so it is considered that this coupling contributes to the characteristic dynamics of this nucleus. Here, we demonstrate that a gap junction-coupled network composed of simple conductance-based model neurons (a simplified version of a Hodgkin–Huxley type neuron) reproduce important aspects of IO activity. The simplified phenomenological model neuron facilitated the analysis of the single cell and network properties of the IO while still quantitatively reproducing the spiking patterns of complex spike activity observed by simultaneous recording in anesthetized rats. The results imply that both intrinsic bistability of each neuron and gap junction coupling among neurons play key roles in the generation of the spatio-temporal dynamics of IO neurons.
KATORI, YUICHI; LANG, ERIC J.; ONIZUKA, MIHO; KAWATO, MITSUO; AIHARA, KAZUYUKI
Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles.
Nasser, Hassan; Marre, Olivier; Cessac, Bruno
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
We have measured and analyzed the spatio-temporal behavior of the electro-optic (EO) responsivity of LiNbO3 single crystals. While there is no apparent feedback-loop circuit involved in the sensor system, very strong spatio-temporal instabilities appear in the EO responsivity of some LiNbO3 crystals. The temporal instability exhibits an intermittent bursting pattern, which is similar in nature to the results obtained by Grebogi et al (Phys. Rev A 36 , 5365, 1987) from numerical simulations using the Ikeda map. This intermittent bursting in our experiment is due to the interplay between the external fields and the screening fields, and stems from strong nonlinear photorefractive effects. These effects establish an intrinsic feedback-like mechanism in nonlinear LiNbO3 crystals.
Wu, Dong Ho; Wieting, Terence J.
This paper assesses the use of independent component analysis (ICA) as applied to epileptic scalp electroencephalographic (EEG) recordings. In particular we address the newly introduced spatio-temporal ICA algorithm (ST-ICA), which uses both spatial and temporal information derived from multi-channel biomedical signal recordings to inform (or update) the standard ICA algorithm. ICA is a technique well suited to extracting underlying sources
Christopher J. James; Charmaine Demanuele
The combined use of EEG and fMRI allows for the fusion of electrophysiological and hemodynamic information in the study of human cognitive functions. In order to investigate cerebral activity during a visual oddball task, simultaneous EEG\\/fMRI recording from 10 healthy subjects was performed. A devoted data-analysis method based on trial-by-trial coupling of concurrent EEG and fMRI for the high-resolution spatio-temporal
L. Marzetti; D. Mantini; S. Cugini; G. L. Romani; C. Del Gratta
The spatio-temporal distribution of lightning flashes over Israel and the neighboring area and its relation to the regional synoptic systems has been studied, based on data obtained from the Israel Lightning Location System (ILLS) operated by the Israel Electric Corporation (IEC). The system detects cloud-to-ground lightning discharges in a range of ~500 km around central Israel (32.5° N, 35° E).
S. Shalev; H. Saaroni; T. Izsak; Y. Yair; B. Ziv
This paper reports the conceptualization of a remote sensing based technique to map the spatio?temporal change pattern of the coastal landforms of Gahirmatha, India, the world's biggest olive ridley sea turtle rookery. Twenty?seven Indian Remote?sensing Satellite (IRS) multispectral satellite images sampled between the period 1988–2001 are the basic input for the study. While the mapping of temporal change position of
G. Prusty; S. Dash; M. P. Singh
Using secondary data generated from three rounds (31st, 48th and 54th) of the National Sample Survey Organization (NSSO) of\\u000a India, a macro-level estimate of the spread of markets for groundwater supported pump irrigation services in India was derived\\u000a for two periods of time, 1976–1977 and 1997–1998. This estimate is the first of its kind that presents a spatio-temporal analysis\\u000a of
The current paper presents the spatio-temporal stability a nalysis of an instance of laminar separation, with the intention of deter- mining the most appropriate forcing frequency to initiate fl ow reattachment. The flow configuration is a NACA 0015 airfoil at an angle of attack (?) where laminar separation occurs imme- diately downstream of the leading edge. A zero-net-mass-flu x (ZNMF)
V. Kitsios; A. Ooi; J. Soria
The spatio-temporal variations of reference crop evapotranspiration (ETref) reflect the combined effects of meteorological variables, primarily wind speed, relative humidity, net radiation and air temperature. This study investigated the spatial distribution and temporal trends of ETref (calculated by the FAO-56 Penman-Monteith equation), pan evaporation (Epan) and pan coefficient (Kp) in a 140?×?10 km semi-humid to semi-arid area in China. The
Liqiao Liang; Lijuan Li; Qiang Liu
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 efficient for public health response: outbreaks would be detected earlier and reactive vaccination would be better targeted.
Paireau, Juliette; Girond, Florian; Collard, Jean-Marc; Mainassara, Halima B.; Jusot, Jean-Francois
BACKGROUND: On the fringes of endemic zones climate is a major determinant of inter-annual variation in malaria incidence. Quantitative description of the space-time effect of this association has practical implications for the development of operational malaria early warning system (MEWS) and malaria control. We used Bayesian negative binomial models for spatio-temporal analysis of the relationship between annual malaria incidence and
Musawenkoi LH Mabaso; Penelope Vounatsou; Stanely Midzi; Joaquim Da Silva; Thomas Smith
The prosthetic activity monitor (PAM) is an instrument to assess over the long-term the duration and spatio-temporal characteristics of walking of amputees, during normal daily life. In this study, the validity of PAM-derived measurements was investigated. Twelve transtibial amputees performed an activity protocol, consisting of stationary and walking activities, and activities associated with nonlocomotor movements. The protocol also included potential
Johannes B. J. Bussmann; Karen M. Culhane; Herwin L. D. Horemans; Gerard M. Lyons; Henk J. Stam
Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal
Shiliang Su; Junjun Zhi; Liping Lou; Fang Huang; Xia Chen; Jiaping Wu
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. PMID:22997266
Kim, Du Yong; Jeon, Moongu
The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO?-N), silicate (SiO?), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO?-N (P?=?0.008) to 0.79 for S (depth) (P?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
Karakaya, Nusret; Evrendilek, Fatih
Driving by a happened event, entities vary from one state to another. Based on the rule, this paper analyzed the relations between events of entities and its states, and made an improvement on base state with amendments model. The improved model is named as multi base state with amendments model. The key idea of this method is to build more than one historical base state according to the frequency of event happens and the amount of data updates. And for the state between every historical base state, we merely stored the changed part but did not re-store the unchanged part. It overcomes the weakness of snapshot method which leads a great deal of redundant data, and also overcomes the drawback of base state with amendments method which will need a great amount of complex computation when historical state is rebuild. This model has been successfully applied to organize the spatio-temporal data of GIS in campus real estate information system. It is very convenient to rebuild house historical state.
Zhang, Yun; Feng, Xuezhi; Zhao, Shuhe; Xiao, Pengfeng; Le, Xinghua
The spatio-temporal dynamics of the solar photosphere are studied by performing a proper orthogonal decomposition (POD) of line-of-sight velocity fields computed from high-resolution data coming from the SOHO/MDI instrument. Using this technique, we are able to identify and characterize the different dynamical regimes acting in the system. All of the POD modes are characterized by two well-separated peaks in the frequency spectra. In particular, low-frequency oscillations, with frequencies in the range 20 130 ?Hz, dominate the most energetic POD modes (excluding solar rotation) and are characterized by spatial patterns with typical scales of about 3 Mm. Patterns with larger typical scales, of about 10 Mm, are dominated by p-mode oscillations at frequencies of about 3000 ?Hz. The p-mode properties found by POD are in agreement with those obtained with the classical Fourier analysis. The spatial properties of high-energy POD modes suggest the presence of a strong coupling between low-frequency modes and turbulent convection.
Vecchio, A.; Carbone, V.; Lepreti, F.; Primavera, L.; Sorriso-Valvo, L.; Straus, T.; Veltri, P.
In this paper, we address the important problem of feature selection for a P300-based brain computer interface (BCI) speller system in several aspects. Firstly, time segment selection and electroencephalogram channel selection are jointly performed for better discriminability of P300 and background signals. Secondly, in view of the situation that training data with labels are insufficient, we propose an iterative semi-supervised support vector machine for joint spatio-temporal feature selection as well as classification, in which both labeled training data and unlabeled test data are utilized. More importantly, the semi-supervised learning enables the adaptivity of the system. The performance of our algorithm has been evaluated through the analysis of a P300 dataset provided by BCI Competition 2005 and another dataset collected from an in-house P300 speller system. The results show that our algorithm for joint feature selection and classification achieves satisfactory performance, meanwhile it can significantly reduce the training effort of the system. Furthermore, this algorithm is implemented online and the corresponding results demonstrate that our algorithm can improve the adaptiveness of the P300-based BCI speller. PMID:23115595
Long, Jinyi; Gu, Zhenghui; Li, Yuanqing; Yu, Tianyou; Li, Feng; Fu, Ming
Hox genes encode transcription factors that function to pattern regional tissue identities along the anterior-posterior axis during animal embryonic development. Divergent nested Hox gene expression patterns within the posterior pharyngeal arches may play an important role in patterning morphological variation in the pharyngeal jaw apparatus (PJA) between evolutionarily divergent teleost fishes. Recent gene expression studies have shown the expression patterns from all Hox paralog group (PG) 2-6 genes in the posterior pharyngeal arches (PAs) for the Japanese medaka (Oryzias latipes) and from most genes of these PGs for the Nile tilapia (Oreochromis niloticus). While several orthologous Hox genes exhibit divergent spatial and temporal expression patterns between these two teleost species in the posterior PAs, several tilapia Hox gene expression patterns from PG3-6 must be documented for a full comparative study. Here we present the spatio-temporal expression patterns of hoxb3b, c3a, b4a, a5a, b5a, b5b, b6a and b6b in the neural tube and posterior PAs of the Nile tilapia. We show that several of these tilapia Hox genes exhibit divergent expression patterns in the posterior PAs from their medaka orthologs. We also compare these gene expression patterns to orthologs in other gnathostome vertebrates, including the dogfish shark. PMID:23376031
Lyon, R Stewart; Davis, Adam; Scemama, Jean-Luc
In this article, an automatic stereoscopic video conversion scheme which accepts MPEG-encoded videos as input is proposed. Our scheme is depth-based, relying on spatio-temporal analysis of the decoded video data to yield depth perception cues, such as temporal motion and spatial contrast, which reflect the relative depths between the foreground and the background areas. Our scheme is shot-adaptive, demanding that shot change detection and shot classification be performed for tuning of algorithm or parameters that are used for depth cue combination. The above-mentioned depth estimation is initially block-based, followed by a locally adaptive joint trilateral upsampling algorithm to reduce the computing load significantly. A recursive temporal filter is used to reduce the possible depth fluctuations (and also artifacts in the synthesized images) resulting from wrong depth estimations. The traditional Depth-Image-Based-Rendering algorithm is used to synthesize the left- and right-view frames for 3D display. Subjective tests show that videos converted by our scheme provide comparable perceived depth and visual quality with those converted from the depth data calculated by stereo vision techniques. Also, our scheme is shown to outperform the well-known TriDef software in terms of human's perceived 3D depth. Based on the implementation by using "OpenMP" parallel programming model, our scheme is capable of executing in real-time on a multi-core CPU platform.
Lin, Guo-Shiang; Huang, Hsiang-Yun; Chen, Wei-Chih; Yeh, Cheng-Ying; Liu, Kai-Che; Lie, Wen-Nung
Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture–recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control.
Russell, James C.; Ruffino, Lise
We report for the first time the detection of membrane lipid rafts in mouse oocytes and cleaving preimplantation embryos. Cholera toxin ? (CT?), which binds to the raft-enriched ganglioside GM1, was selected to label rafts. In a novel application a Qdot reagent was used to detect CT? labeling. This is the first reported use of nanocrystals in mammalian embryo imaging. Comparative membrane labeling with CT? and lipophilic membrane dyes containing saturated or unsaturated aliphatic tails showed that the detection of GM1 in mouse oocytes and embryo membranes was consistent with the identification of cholesterol- and sphingolipid-enriched rafts in the cell membrane. Distribution of the GM1 was compared with the known distribution of non-raft membrane components, and disruption of membrane rafts with detergents confirmed the cholesterol-dependence of GM1 on lipid raft labeling. Complementary functional studies showed that cholesterol depletion using methyl-?-cyclodextrin inhibited preimplantation development in culture. Our results show that the membranes of the mouse oocyte and zygote are rich in lipid rafts, with heterogeneous and stage-dependent distribution. In dividing embryos, the rafts were clearly associated with the cleavage furrow. At the morula stage, rafts were also apically enriched in each blastomere. In blastocysts, rafts were detectable in the trophectoderm layer, but could not be detected in the inner cell mass without prior fixation and permeabilization of the embryo. Lipid rafts and their associated proteins are, therefore, spatio-temporally positioned to a play a critical role in preimplantation developmental events.
Comiskey, Martina; M.Warner, Carol
Distributed temperature sensing (DTS) allows for simultaneous measurement at many remote locations along an optical fiber probe and is a valuable tool in a broad range of applications, such as downhole oil production, dike structural monitoring or fire protection. The specific requirements on spatial, temporal and temperature resolution and on absolute measurement uncertainty vary with the applications. We investigate the spatio-temporal noise and drift properties of two exemplary Raman backscatter DTS systems and discuss the effect of spatial and temporal data averaging. An Allan deviation analysis provides insight into the optimal degree of averaging for a given distance range along the fiber probe. A temperature calibration procedure is employed to retrieve the temperature sensitivity of the DTS system and to compensate for the systematic spatial slope of recorded DTS temperature measurement traces. In response to small temperature steps of a thermally homogeneous and stable water bath environment, we observe a temperature resolution of approximately 0.05 °C at a chosen 1000 m sampling distance along the fiber probe.
Voigt, Dirk; van Geel, Jan L. W. A.; Kerkhof, Oswin
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
Litvak-Hinenzon, Anna; Stone, Lewi
Enabled by novel molecular markers, fluorescence microscopy enables the monitoring of multiple cellular functions using live cell assays. Automated image analysis is necessary to monitor such model systems in a high-throughput and high-content environment. Here, we demonstrate the ability to simultaneously track cell cycle phase and cell motion at the single cell level. Using a recently introduced cell cycle marker, we present a set of image analysis tools for automated cell phase analysis of live cells over extended time periods. Our model-based approach enables the characterization of the four phases of the cell cycle G1, S, G2, and M, which enables the study of the effect of inhibitor compounds that are designed to block the replication of cancerous cells in any of the phases. We approach the tracking problem as a spatio-temporal volume segmentation task, where the 2D slices are stacked into a volume with time as the z dimension. The segmentation of the G2 and S phases is accomplished using level sets, and we designed a model-based shape/size constraint to control the evolution of the level set. Our main contribution is the design of a speed function coupled with a fast marching path planning approach for tracking cells across the G1 phase based on the appearance change of the nuclei. The viability of our approach is demonstrated by presenting quantitative results on both controls and cases in which cells are treated with a cell cycle inhibitor. PMID:18752984
Padfield, Dirk; Rittscher, Jens; Thomas, Nick; Roysam, Badrinath
Bone multicellular units (BMUs) maintain the viability of the skeletal tissue by coordinating locally the sequence of bone resorption and bone formation performed by cells of the osteoclastic and osteoblastic lineage. Understanding the emergence and the net bone balance of such structured microsystems out of the complex network of biochemical interactions between bone cells is fundamental for many bone-related diseases and the evaluation of fracture risk. Based on current experimental knowledge, we propose a spatio-temporal continuum model describing the interactions of osteoblastic and osteoclastic cells. We show that this model admits travelling-wave-like solutions with well-confined cell profiles upon specifying external conditions mimicking the environment encountered in cortical bone remodelling. The shapes of the various cell concentration profiles within this travelling structure are intrinsically linked to the parameters of the model such as differentiation, proliferation, and apoptosis rates of bone cells. The internal structure of BMUs is reproduced, allowing for experimental calibration. The spatial distribution of the key regulatory factors can also be exhibited, which in diseased states could give hints as to the biochemical agent most accountable for the disorder.
Buenzli, P. R.; Pivonka, P.; Gardiner, B. S.; Smith, D. W.; Dunstan, C. R.; Mundy, G. R.
We study the general properties of stochastic two-species models for predator-prey competition and coexistence with Lotka-Volterra type interactions defined on a d-dimensional lattice. Introducing spatial degrees of freedom and allowing for stochastic fluctuations generically invalidates the classical, deterministic mean-field picture. Already within mean-field theory, however, spatial constraints, modeling locally limited resources, lead to the emergence of a continuous active-to-absorbing state phase transition. Field-theoretic arguments, supported by Monte Carlo simulation results, indicate that this transition, which represents an extinction threshold for the predator population, is governed by the directed percolation universality class. In the active state, where predators and prey coexist, the classical center singularities with associated population cycles are replaced by either nodes or foci. In the vicinity of the stable nodes, the system is characterized by essentially stationary localized clusters of predators in a sea of prey. Near the stable foci, however, the stochastic lattice Lotka-Volterra system displays complex, correlated spatio-temporal patterns of competing activity fronts. Correspondingly, the population densities in our numerical simulations turn out to oscillate irregularly in time, with amplitudes that tend to zero in the thermodynamic limit. Yet in finite systems these oscillatory fluctuations are quite persistent, and their features are determined by the intrinsic interaction rates rather than the initial conditions. We emphasize the robustness of this scenario with respect to various model perturbations.
Mobilia, Mauro; Georgiev, Ivan T.; Täuber, Uwe C.
The main goal of the project supported in this grant is to contribute to the understanding of localized spatial and spatio-temporal structures far from thermodynamic equilibrium. Here we report on our progress in the study of two classes of systems. (1) We have started to investigate localized wave-pulses in binary-mixture convection. This work is based on our recently derived extension of the conventionally used complex Ginzburg-Landau equations. We are considering three regimes: Dispersion-less supercritical waves; strongly dispersive subcritical waves; and localized waves as bound states of fronts between dispersionless subcritical waves and the motionless conductive state. (2) We have completed our investigation of steady domain structures in which domains of structures with different wave numbers alternate, separated by domain walls. In particular, we have studied their regimes of existence and stability within the framework of a Ginzburg-Landau equation and have compared it to previous results. Those were based on a long-wavelength approximation, which misses certain aspects which turn out to be important for the stability of the domain structures in realistic situations. In addition, we give a description of our work on resonantly forced waves in two-dimensional anisotropic systems.
Cell-cell signaling plays a central role in biology, enabling individual cells to coordinate their activities. For example, bacteria show evidence of intercellular signaling through quorum sensing, a regulatory mechanism that launches a coordinated response, depending on the population density. To explore the spatio-temporal development of cell-to-cell signaling, we have created regular, heterotypic microarrays of living cells in hydrogel using time-multiplexed optical traps for submicron positional control of the cell orientation and location without loss of viability. We studied the Lux system for quorum sensing; splitting it into sender and receiver plasmids, which were subsequently introduced into E. Coli. Induced by IPTG, the sender cells express a fluorescent reporter (mRFP1) and the LuxI enzyme that catalyzes the synthesis of a molecular signal AHL that diffuses through the cell membrane and the extra-cellular scaffold. The receiver cells collect the AHL signal that binds to the LuxR regulator and reports it through GFP production. We have measured the time-delay between the onset of mRFP1 and GFP dependence on intercellular spacing in the array.
Mirsaidov, Utkur; Timp, Winston; Timp, Kaethe; Matsudaira, Paul; Timp, Greg
This paper presents a spatio-temporal framework for estimating single-trial response latencies and amplitudes from evoked response MEG/EEG data. Spatial and temporal bases are employed to capture the aspects of the evoked response that are consistent across trials. Trial amplitudes are assumed independent but have the same underlying normal distribution with unknown mean and variance. The trial latency is assumed to be deterministic but unknown. We assume the noise is spatially correlated with unknown covariance matrix. We introduce a generalized expectation-maximization algorithm called TriViAL (Trial Variability in Amplitude and Latency) which computes the maximum likelihood (ML) estimates of the amplitudes, latencies, basis coefficients, and noise covariance matrix. The proposed approach also performs ML source localization by scanning the TriViAL algorithm over spatial bases corresponding to different locations on the cortical surface. Source locations are identified as the locations corresponding to large likelihood values. The effectiveness of the TriViAL algorithm is demonstrated using simulated data and human evoked response experiments. The localization performance is validated using tactile stimulation of the finger. The efficacy of the algorithm in estimating latency variability is shown using the known dependence of the M100 auditory response latency to stimulus tone frequency. We also demonstrate that estimation of response amplitude is improved when latency is included in the signal model.
Limpiti, Tulaya; Van Veen, Barry D.; Wakai, Ronald T.
Indicator molecules for caspase-3 activation have been reported that use fluorescence resonance energy transfer (FRET) between an enhanced cyan fluorescent protein (the donor) and enhanced yellow fluorescent protein (EYFP; the acceptor). Because EYFP is highly sensitive to proton (H+) and chloride ion (Cl-) levels, which can change during apoptosis, this indicator's ability to trace the precise dynamics of caspase activation is limited, especially in vivo. Here, we generated an H+- and Cl--insensitive indicator for caspase activation, SCAT, in which EYFP was replaced with Venus, and monitored the spatio-temporal activation of caspases in living cells. Caspase-3 activation was initiated first in the cytosol and then in the nucleus, and rapidly reached maximum activation in 10 min or less. Furthermore, the nuclear activation of caspase-3 preceded the nuclear apoptotic morphological changes. In contrast, the completion of caspase-9 activation took much longer and its activation was attenuated in the nucleus. However, the time between the initiation of caspase-9 activation and the morphological changes was quite similar to that seen for caspase-3, indicating the activation of both caspases occurred essentially simultaneously during the initiation of apoptosis. PMID:12527749
Takemoto, Kiwamu; Nagai, Takeharu; Miyawaki, Atsushi; Miura, Masayuki
We assessed the performance of two estimators of species richness, the Chao2 and the Coleman 'random placement curve'. Using a dataset of intertidal fish from the Norwegian Skagerrak coast, we found that Chao2 was effective for low sampling intensity, often reaching asymptotic values for few samples, but for higher sampling intensity the performance deteriorated. For large samples, the Coleman random placement curve was more effective than the Chao2 estimates when comparing spatio-temporal patterns of species richness. Spatial patterns were clearly and consistently identified by both methods, whereas the coastal fish communities displayed too much variability in the early summer for any sensible measure of temporal patterns of fish-species richness to be made. To control for spurious results due to systematic differences in mean abundance of the samples the analyses were performed also on data standardised by the number of individuals in the samples, without any significant change in the results. We conclude that modest sampling effort is sufficient to characterise spatial patterns of coastal fish-species richness, while a detailed and high-precision description of seasonal patterns could not be obtained with any reasonable sampling effort. PMID:15800740
Lekve, Kyrre; Ellingsen, Kari E; Lingjaerde, Ole Chr; Gjøsaeter, Jakob; Stenseth, Nils Chr
Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture-recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control. PMID:21775327
Russell, James C; Ruffino, Lise
The artificial neural network (ANN) can reconstruct spatio-temporal neural activities into the corresponding test stimuli. ANN with a simple structure and generalization ability has a potential to reflect a prominent feature of the mechanism of neural computation in the brain. In the present work, we test this hypothesis and propose a novel analysis by investigating input-output relationships of hidden layer neurons. We made ANN with neural activities in the primary auditory cortex serving as the inputs and time-series changes of test frequencies of tones serving as the targets. We then investigated the hidden layer neurons that played important roles in the reconstruction. Neurons that tuned the frequency preference by excitatory inputs had positive contribution from all frequency regions. On the other hand, neurons responsible for inhibitory frequency tuning had negative contribution from a low frequency region. These results suggest that neural activities in the primary auditory cortex form a frequency preference with excitatory inputs from all frequency pathways and inhibitory inputs from a low frequency pathway. This suggestion is consistent with physiological facts that pyramidal cells in the auditory cortex have widely tuned excitatory response area and inhibitory input domains that flank the excitatory areas, supporting our hypothesis and proving the feasibility of the proposed analysis.
Takahashi, Hirokazu; Uchihara, Masanobu; Funamizu, Akihiro; Yokota, Ryo; Kanzaki, Ryohei
In this work, we study the collective behaviour of fish shoals in annular domains. Shoal mates are modelled as self-propelled particles moving on a discrete lattice. Collective decision-making is determined by information exchange among neighbours. Neighbourhoods are specified using the perceptual limit and numerosity of fish. Fish self-propulsion and obedience to group decisions are described through random variables. Spatio-temporal schooling patterns are measured using coarse observables adapted from the literature on coupled oscillator networks and features of the time-varying network describing the fish-to-fish information exchange. Experiments on zebrafish schooling in an annular tank are used to validate the model. Effects of group size and obedience parameter on coarse observables and network features are explored to understand the implications of perceptual numerosity and spatial density on fish schooling. The proposed model is also compared with a more traditional metric model, in which the numerosity constraint is released and fish interactions depend only on physical configurations. Comparison shows that the topological regime on which the proposed model is constructed allows for interpreting characteristic behaviours observed in the experimental study that are not captured by the metric model.
Abaid, Nicole; Porfiri, Maurizio
Woody plant encroachment in dryland ecosystems is an issue of global concern, yet mechanisms related to encroachment are poorly understood. Mechanisms associated with woody plant encroachment likely relate to soil water dynamics, yet few long-term data sets exist to evaluate soil water heterogeneity. Here we highlight how soil water varies both temporally (wet vs. dry years and snow vs. rain dominated months) and spatially (vertically with depth and horizontally beneath vs. between the canopies of woody plants). We measured soil water content using neutron probe over a 15-year period in a pinyon-juniper woodland at the Mesita del Buey Research Site in northern New Mexico. Our objectives included assessing (1) the temporal variability of soil water, both as a function of depth and as a function of cover (canopy patches beneath trees, intercanopy patches between trees, and edges between the two patch types); and (2) implications for the vertical and horizontal distributions of plant-available water. Our results highlight (1) large temporal variations in soil water availability, driven largely by differences in winter precipitation, and (2) the potential importance of considering horizontal as well as vertical heterogeneity in soil moisture. The spatio-temporal variation in soil water that we quantify highlights the potential complexity of changes in the water budget that could be associated with woody plant encroachment and emphasizes the importance of considering horizontal as well as vertical heterogeneity in soil water in improving our understanding of mechanisms associated with woody plant encroachment.
Bresehars, D. D.; Myers, O. B.; Barnes, F. J.
Error concealment at a decoder is an efficient method to reduce the degradation of visual quality caused by channel errors. In this paper, we propose a novel spatio-temporal error concealment algorithm based on the spatial-temporal fading (STF) scheme which has been recently introduced. Although STF achieves good performance for the error concealment, several drawbacks including blurring still remain in the concealed blocks. To alleviate these drawbacks, in the proposed method, hybrid approaches with adaptive weights are proposed. First, the boundary matching algorithm and the decoder motion vector estimation which are well-known temporal error concealment methods are adaptively combined to compensate for the defect of each other. Then, an edge preserved method is utilized to reduce the blurring effects caused by the bilinear interpolation for spatial error concealment. Finally, two concealed results obtained by the hybrid spatial and temporal error concealment are pixelwisely blended with adaptive weights. Experimental results exhibit that the proposed method outperforms conventional methods including STF in terms of the PSNR performance as well as subjective visual quality, and the computational complexity of the proposed method is similar to that of STF.
Hwang, Min-Cheol; Kim, Jun-Hyung; Park, Chun-Su; Ko, Sung-Jea
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. PMID:22246322
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
This paper represents the first step in developing an inertial sensor system that is capable of assessing post-stroke gait in terms of walking speed and temporal gait symmetry. Two inertial sensors were attached at the midpoint of each shank to measure the accelerations and angular velocity during walking. Despite the abnormalities in hemiparetic gait, the angular velocity of most of the testing subjects (12 out of 13) exhibited similar characteristics as those from a healthy population, enabling walking speed estimation and gait event detection based on the pendulum walking model. The results from a standardized 10-meter walk test demonstrated that the IMU-based method has an excellent agreement with the clinically used stopwatch method. The gait symmetry results were comparable with previous studies. The gait segmentation failed when the angular velocity deviates significantly from the healthy groups' profile. With further development and concurrent validations, the inertial sensor-based system may eventually become a useful tool for continually monitoring spatio-temporal gait parameters post stroke in a natural environment. PMID:23000235
Yang, Shuozhi; Zhang, Jun-Tian; Novak, Alison C; Brouwer, Brenda; Li, Qingguo
Meiofauna organisms that play an important role in the trophic ecology of soft bottom benthos, have short life cycles and they respond quickly to disturbance and pollution. The present study shows the spatio-temporal variation ofsubtidal meiofauna (metazoans passing a 500im sieve but retained on meshes of 40-63micro m) in four shallow subtidal stations. Samples were taken in the sandy beach of San Luis, in the Northeastern coast of Venezuela, from October 2005 until September 2006. For this, three replicate sediment core samples (4.91cm2), were collected monthly to a depth of 10cm into the sediment, and preserved in 6% formalin stained with rose Bengal. Specimens of 14 meiofaunal groups (Foraminifera excluded) were collected, being the nematodes, ostracods and harpacticoid copepods the most abundant. Monthly density was comprised between 64 and 503ind./10cm2, and mean density of stations between 173 and 449ind./10cm2. There is a trend of low densities from October to February (end of the rainy season until the middle of the dry season). The San Luis beach control of the meiofaunal community is shared by climatic conditions and by the biology of the species found. The meiofauna mean density in San Luis beach (263ind./10cm2) was low when compared to other studies in tropical areas. PMID:23894963
Arana, Ildefonso Liñero; Ojeda, Sol; Amaro, María Elena
The patterns of acoustic events prior to and after a stick-slip event are transformed to complex networks and the characteristics of the networks are measured. The patterns are the result of acoustic emission monitoring through loading a cylindrical sample of Westerly granite containing a natural fault .Two approaches are implemented in construction of the networks. In the first approach the network is constructed based on nearest neighbour events while the interactions of the main fault with the second and third faults are inspected through analyzing the spatial communities of the networks. The second approach uses a network method on phase space of time series (i.e., constructing a smooth manifold) obtained from the waveforms of over occurrence rank of events . With the later implementation, we characterize the source mechanism of events while we compare the characteristics of the obtained networks (i.e., motif distribution and eigenvector of Laplacian) with the inferred source mechanism from the inverse moment tensor approach. Our results show the correlation of motifs rank evolution with source mechanism. Furthermore, with respect to the shape of triangles (as well as stretching and folding) over spatial complex networks and based on the first approach, the 3 point nodes motif distributions are extended to consider possible statistical geometry of events. Thus, the spatio-temporal complexity and possible coupling of events in time and space in terms of network parameters is inferred. We compare our results with the recent analysis of networks motifs from pure shear rupture associated with sudden variation of contact strings . Keyword:, Stick-sllip; Westerly granite, Acoustic Emission Patterns; Complex Networks, and Motifs Ref.  Thompson, B.D., D.A. Lockner and R.P. Young, Premonitory acoustic emissions and stick slip in natural and smooth faulted Westerly granite,J. Geophysical Research, Vol 114, B02205, doi: 10.1029/2008jb005753, 2009.  J. F. Donges, Y. Zou, N. Marwan and J. Kurths, The backbone of the climate network, EPL, 87 (2009) 48007.  H.O.Ghaffari and R.P.Young, Structural complexity of shear fractures; Physica A 2011 (submitted) ; ArXive-prints (2011) http://arxiv.org/abs/1105.4265.  H.O.Ghaffari and R.P.Young, Motifs of Networks from Shear Fractures ; IJRMMS (Submitted)
Ghaffari, H.; Thompson, B. D.; Young, R.
Spatio-temporal variations of surface ozone are investigated using the KZ-filter considering meteorological factors based on measurement data at 124 air quality monitoring sites and 72 weather stations over South Korea for the time period of 1999-2010. We use hourly data of ozone (O3), nitrogen dioxide (NO2), temperature (°C), dew-point temperature (°C), sea-level pressure (hPa), wind speed (m/s) and direction (16 cardinal directions), relative humidity (%), and solar insolation (W/m²). Over the Korean peninsula, surface O3 levels at the coastal cities are generally high due to the dynamic effects of the sea breeze and short-lived chlorine species from the sea salt, while those at the Seoul metropolitan area and other inland cities are low due to the NOx titration by anthropogenic emissions. The concentrations of surface O3 have generally increased for the analyzed period with the nationwide average linear trend of +0.26 ppbv/yr (+1.15 %/yr). We also examine the meteorological influences on the surface O3 levels over South Korea using a combined analysis of KZ-filter and multiple linear regressions between surface O3 and meteorological variables. Time-series of surface O3 are decomposed into the short-term, seasonal, and long-term components by the KZ-filter and regressed on meteorological variables. Through probability distribution analysis of the decomposed O3 time-series classified by wind direction, the O3 short-term variation at monitoring sites shows transport effects from the source regions. Impacts of surface temperature on the surface O3 levels are found to be significantly high in the highly populated metropolitan area and inland cities. It implies that those regions will be experiencing more frequent high-ozone events in the future climate conditions with the increase of global temperature. Especially in Seoul, the most populated area in South Korea, the probability of high O3 exceeding air quality standard is almost doubled for the temperature increase of about 4°C. Additional SVD analysis between O3 and NO2 shows similar temporal evolution with spatial patterns of the long-term O3 and NO2 components. This study would provide a reference for appropriate ozone control policy and for the performance evaluation of chemistry climate models over East Asia.
Seo, Jihoon; Youn, Daeok; Kim, Jin Young; Choi, Wookap
A minimum-relative-entropy (MRE) based Bayesian inversion framework is applied to monitor spatio-temporal distribution of dielectric permittivity using tomographic radar first arrival time data from a synthetic, transient infiltration experiment in the shallow subsurface. In this experiment, a spatially correlated random saturated hydraulic conductivity field is generated and used as input to the TOUGH2 flow simulator, which provides realistic distributions of water and dielectric permittivity on a fine grid at several temporal snapshots. For each snapshot, a tomographic GPR simulator is utilized to produce first arrival travel times. In this study, we test the performance of our inverse modeling framework by inverting and monitoring dielectric permittivity variations using these traveltime data. The inverse modeling domain is divided into coarse grid blocks compared to flow simulation grid, in order to reduce the dimension of unknowns. Each unknown parameter is first assigned a minimally subjective probability distribution function (pdf) using the MRE method, then pseudorandom dielectric constant parameter sets are drawn from these pdfs using a quasi-Monte Carlo sampling technique. We then compute first arrival GPR travel times for each parameter set and the corresponding weight based upon the misfit between the calculated model responses and observations. This inversion approach can deal with nonlinearity and nonuniqueness between data and model parameters by incorporating a numerical modeling technique and it can quantify uncertainty in the parameter estimates by treating those estimates as probability distributions rather than deterministic estimates. Moreover, the intermediate inversion results can be used as “memory functions” in the form of MRE pdfs for step-wise inversion. Testing results show that this framework is capable of reproducing estimates of saturation at grid blocks throughout the study area, and that accuracy and precision are improved as more data become available. These outcomes spur ongoing efforts to improve upon this framework including implementing a means of parameter reduction (for example, through use of a pilot point method) and validating the approach using field data from the Chromium-contaminated Hanford 100-D biostimulation study site.
Terry, N.; Hou, Z.; Hubbard, S. S.
Background Culicoides imicola KIEFFER, 1913 (Diptera: Ceratopogonidae) is the principal vector of Bluetongue disease in the Mediterranean basin, Africa and Asia. Previous studies have identified a range of eco-climatic variables associated with the distribution of C. imicola, and these relationships have been used to predict the large-scale distribution of the vector. However, these studies are not temporally-explicit and can not be used to predict the seasonality in C. imicola abundances. Between 2001 and 2006, longitudinal entomological surveillance was carried out throughout Italy, and provided a comprehensive spatio-temporal dataset of C. imicola catches in Onderstepoort-type black-light traps, in particular in Sardinia where the species is considered endemic. Methods We built a dynamic model that allows describing the effect of eco-climatic indicators on the monthly abundances of C. imicola in Sardinia. Model precision and accuracy were evaluated according to the influence of process and observation errors. Results A first-order autoregressive cofactor, a digital elevation model and MODIS Land Surface Temperature (LST)/or temperatures acquired from weather stations explained ~77% of the variability encountered in the samplings carried out in 9 sites during 6?years. Incorporating Normalized Difference Vegetation Index (NDVI) or rainfall did not increase the model's predictive capacity. On average, dynamics simulations showed good accuracy (predicted vs. observed r corr?=?0.9). Although the model did not always reproduce the absolute levels of monthly abundances peaks, it succeeded in reproducing the seasonality in population level and allowed identifying the periods of low abundances and with no apparent activity. On that basis, we mapped C. imicola monthly distribution over the entire Sardinian region. Conclusions This study demonstrated prospects for modelling data arising from Culicoides longitudinal entomological surveillance. The framework explicitly incorporates the influence of eco-climatic factors on population growth rates and accounts for observation and process errors. Upon validation, such a model could be used to predict monthly population abundances on the basis of environmental conditions, and hence can potentially reduce the amount of entomological surveillance.
Relatively little information is available on environmental associations and the conservation of Odonata in the Maltese Islands. Aquatic habitats are normally spatio-temporally restricted, often located within predominantly rural landscapes, and are thereby susceptible to farmland water management practices, which may create additional pressure on water resources. This study investigates how odonate assemblage structure and diversity are associated with habitat variables of local breeding habitats and the surrounding agricultural landscapes. Standardized survey methodology for adult Odonata involved periodical counts over selected water-bodies (valley systems, semi-natural ponds, constructed agricultural reservoirs). Habitat variables relating to the type of water body, the floristic and physiognomic characteristics of vegetation, and the composition of the surrounding landscape, were studied and analyzed through a multivariate approach. Overall, odonate diversity was associated with a range of factors across multiple spatial scales, and was found to vary with time. Lentic water-bodies are probably of high conservation value, given that larval stages were mainly associated with this habitat category, and that all species were recorded in the adult stage in this habitat type. Comparatively, lentic and lotic seminatural waterbodies were more diverse than agricultural reservoirs and brackish habitats. Overall, different odonate groups were associated with different vegetation life-forms and height categories. The presence of the great reed, Arundo donax L., an invasive alien species that forms dense stands along several water-bodies within the Islands, seems to influence the abundance and/or occurrence of a number of species. At the landscape scale, roads and other ecologically disturbed ground, surface water-bodies, and landscape diversity were associated with particular components of the odonate assemblages. Findings from this study have several implications for the use of Odonata as biological indicators, and for current trends with respect to odonate diversity conservation within the Maltese Islands.
Balzan, Mario V.
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
Chaudhuri, Sriroop; Ale, Srinivasulu; Delaune, Paul; Rajan, Nithya
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. PMID:21149702
Scacchi, Emanuele; Salinas, Paula; Gujas, Bojan; Santuari, Luca; Krogan, Naden; Ragni, Laura; Berleth, Thomas; Hardtke, Christian S
Relatively little information is available on environmental associations and the conservation of Odonata in the Maltese Islands. Aquatic habitats are normally spatio-temporally restricted, often located within predominantly rural landscapes, and are thereby susceptible to farmland water management practices, which may create additional pressure on water resources. This study investigates how odonate assemblage structure and diversity are associated with habitat variables of local breeding habitats and the surrounding agricultural landscapes. Standardized survey methodology for adult Odonata involved periodical counts over selected water-bodies (valley systems, semi-natural ponds, constructed agricultural reservoirs). Habitat variables relating to the type of water body, the floristic and physiognomic characteristics of vegetation, and the composition of the surrounding landscape, were studied and analyzed through a multivariate approach. Overall, odonate diversity was associated with a range of factors across multiple spatial scales, and was found to vary with time. Lentic water-bodies are probably of high conservation value, given that larval stages were mainly associated with this habitat category, and that all species were recorded in the adult stage in this habitat type. Comparatively, lentic and lotic seminatural waterbodies were more diverse than agricultural reservoirs and brackish habitats. Overall, different odonate groups were associated with different vegetation life-forms and height categories. The presence of the great reed, Arundo donax L., an invasive alien species that forms dense stands along several water-bodies within the Islands, seems to influence the abundance and/or occurrence of a number of species. At the landscape scale, roads and other ecologically disturbed ground, surface water-bodies, and landscape diversity were associated with particular components of the odonate assemblages. Findings from this study have several implications for the use of Odonata as biological indicators, and for current trends with respect to odonate diversity conservation within the Maltese Islands. PMID:23427906
Balzan, Mario V
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.
Thompson, R.; Clark, R. M.
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.
Forests play a leading role in regional and global carbon (C) cycles. Detailed assessment of the temporal and spatial changes in C sinks/sources of China's forests is critical to the estimation of the national C budget and can help to constitute sustainable forest management policies for climate change. In this study, we explored the spatio-temporal changes in forest biomass C stocks in China between 1977 and 2008, using six periods of the national forest inventory data. According to the definition of the forest inventory, China's forest was categorized into three groups: forest stand, economic forest, and bamboo forest. We estimated forest biomass C stocks for each inventory period by using continuous biomass expansion factor (BEF) method for forest stands, and the mean biomass density method for economic and bamboo forests. As a result, China's forests have accumulated biomass C (i.e., biomass C sink) of 1896 Tg (1 Tg=10(12) g) during the study period, with 1710, 108 and 78 Tg C in forest stands, and economic and bamboo forests, respectively. Annual forest biomass C sink was 70.2 Tg C a(-1), offsetting 7.8% of the contemporary fossil CO2 emissions in the country. The results also showed that planted forests have functioned as a persistent C sink, sequestrating 818 Tg C and accounting for 47.8% of total C sink in forest stands, and that the old-, mid- and young-aged forests have sequestrated 930, 391 and 388 Tg C from 1977 to 2008. Our results suggest that China's forests have a big potential as biomass C sink in the future because of its large area of planted forests with young-aged growth and low C density. PMID:23722235
Guo, Zhaodi; Hu, Huifeng; Li, Pin; Li, Nuyun; Fang, Jingyun
Gaits can be defined based upon specific interlimb coordination patterns characteristic of a limited range of speeds, with one or more defining variables changing discontinuously at a transition. With changing speed, horses perform a repertoire of gaits (walk, trot, canter and gallop), with transitions between them. Knowledge of the series of kinematic events necessary to realize a gait is essential for understanding the proximate mechanisms as well as the control underlying gait transitions. We studied the kinematics of the actual transition from trot to canter in miniature horses. The kinematics were characterized at three different levels: the whole-body level, the spatio-temporal level of the foot falls and the level of basic limb kinematics. This concept represents a hierarchy: the horse's center of mass (COM) moves forward by means of the coordinated action of the limbs and changes in the latter are the result of alterations in the basic limb kinematics. Early and short placement of the fore limb was observed before the dissociation of the footfalls of one of the diagonal limb pairs when entering the canter. Dissociation coincided with increased amplitude and wavelength of the oscillations of the trunk in the sagittal plane. The increased amplitude cannot be explained solely by the passive effects of acceleration or by neck and head movements which are inconsistent with the timing of the transition. We propose that the transition is initiated by the fore limb followed by subsequent changes in the hind limbs in a series of kinematic events that take about 2.5 strides to complete. PMID:23810157
Nauwelaerts, Sandra; Aerts, Peter; Clayton, Hilary
Regarding the noise evaluation of image sensor, it is important to establish the objective evaluation method which has high correlation with appearance. It is well known that visual noise standard is a noise evaluation metric using human visual characteristics. The visual noise level can vary depending on the viewing distance, spatial frequency, color and viewing conditions. A method of measuring the visual noise level is provided in ISO 15739. Furthermore it was discovered that visual characteristics depend on contrast and frame rate; however, the ISO method doesn't consider that. For example, since ISO15739 focus the absolute threshold of human visual system for still image, in some case, the correlation between subjective evaluation and objective evaluation was not so high. And in moving image sequences case, the faster frame rate becomes, the lower perception of noise becomes. We propose solutions to solve those problems using visual spatio-temporal frequency characteristics. Firstly, we investigated visual spatial frequency characteristics that depend on contrast and propose a new evaluation method. It shows that the image sensor with large pixel count is effective in noise reduction. Secondly, we investigated visual temporal frequency characteristics and propose a new evaluation method for the moving image sequences. It shows that the image sensor with high frame rate is effective in noise reduction. Finally, by combining two proposed methods, we show the method in which a noise evaluation is possible in both a still image and in moving image sequences. We applied the proposal method to moving image sequences acquired by the image sensor and investigated the validity of the method.
Fujii, Takeyuki; Suzuki, Shoichi; Saito, Shinichiro
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.
Villamizar, S. R.; Pai, H.; Butler, C. A.; Barnes, P. A.; Harmon, T. C.
It is a well known truth that soil moisture plays an essential role within the hydrological cycle and the climate system. Therefore a deeper knowledge and understanding of soil moisture behaviour, changes and pattern is of major interest. This contribution introduces a statistical approach to recognize spatio-temporal patterns within a long-term global soil moisture data set. The great potential of satellites to detect soil moisture on a global and continuous scale is well-known and in particular microwave remote sensing is recognized to work as the most efficient instrument for acquiring soil moisture information. The current study is based on a long-term global soil moisture data set, the ESA CCI soil moisture data set (http://www.esa-soilmoisturee-cci.org). It was developed by combining data derived from active and passive microwave satellite-based sensors, profiting from the advantages of both retrieval techniques. The ESA CCI soil moisture data set provides soil moisture information for more than three decades and can easily be extended with products from current and future satellite missions. Relative dynamics and long term changes of the original satellite derived retrievals are preserved in the CCI product, thus a valuable basis for long-term analysis is given. By applying a cluster algorithm to monthly and seasonal means of the combined CCI data regions with similar temporal soil moisture patterns are created. The plausibility of the resulting groups is verified by comparison with land cover classifications and climate classes. Besides, special care has been taken of the treatment of missing values as their existences causes difficulties when statistical methods are applied. In this study various methods for missing value imputation are discussed to provide as much meaningful data as input for the following cluster analysis as possible. Overall, the described analysis of soil moisture product is expected to improve our knowledge and understanding of soil moisture behaviour and the quality of the used product.
Xaver, Angelika; Dorigo, Wouter A.
The aim of this work is to create a methodology to characterize the dynamics of magnetic clouds (MCs) from signals measured by satellites in the interplanetary medium. We have tested spatio-temporal entropy (STE) technique to study 41 MCs identified by other authors, where the plasma sheath region has been identified. The STE was implemented in Visual Recurrence Analysis software to quantify the order in the recurrence plot. Some tests using synthetic time series were performed to validate the method. In particular, we worked with interplanetary magnetic field (IMF) components Bx, By, Bz of 16 s. Time windows from March 1998 to December 2003 for some MCs were selected. We found higher STE values in the sheaths and 0 STE values in some of the three components in most of the MCs (30 among 41 events). The trend is the principal cause of the lower STE values in the MCs. Also, MCs have magnetic field more structured than sheath and quiet solar wind. We have done a test considering the magnetic components of a cylindrically symmetric force-free field constructed analytically, with the result of 0 STE value. It agrees with the physical assumption of finding 0 STE values when studying experimental data in MC periods. The new feature just examined here adds to the usual features, as described in Burlaga et al. (1981), for the characterization of MCs. The STE calculation can be an auxiliary objective tool to identify flux ropes associated with MCs, mainly during events with no available plasma data but only with IMF.
Ojeda G., A.; Mendes, O.; Calzadilla, M. A.; Domingues, M. O.
The global spread of highly pathogenic avian influenza H5N1 in poultry, wild birds and humans, poses a significant pandemic threat and a serious public health risk. An efficient surveillance and disease control system relies on the understanding of the dispersion patterns and spreading mechanisms of the virus. A space-time cluster analysis of H5N1 outbreaks was used to identify spatio-temporal patterns at a global scale and over an extended period of time. Potential mechanisms explaining the spread of the H5N1 virus, and the role of wild birds, were analyzed. Between December 2003 and December 2006, three global epidemic phases of H5N1 influenza were identified. These H5N1 outbreaks showed a clear seasonal pattern, with a high density of outbreaks in winter and early spring (i.e., October to March). In phase I and II only the East Asia Australian flyway was affected. During phase III, the H5N1 viruses started to appear in four other flyways: the Central Asian flyway, the Black Sea Mediterranean flyway, the East Atlantic flyway and the East Africa West Asian flyway. Six disease cluster patterns along these flyways were found to be associated with the seasonal migration of wild birds. The spread of the H5N1 virus, as demonstrated by the space-time clusters, was associated with the patterns of migration of wild birds. Wild birds may therefore play an important role in the spread of H5N1 over long distances. Disease clusters were also detected at sites where wild birds are known to overwinter and at times when migratory birds were present. This leads to the suggestion that wild birds may also be involved in spreading the H5N1 virus over short distances. PMID:19908191
Si, Yali; Skidmore, Andrew K; Wang, Tiejun; de Boer, Willem F; Debba, Pravesh; Toxopeus, Albert G; Li, Lin; Prins, Herbert H T
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.
Hanasoge, Shravan M.; Gizon, Laurent; Bal, Guillaume
We study acoustic emission (AE) activity caused by cyclic thermal loading due to the backfilling of a cavity in an abandoned salt mine to answer questions regarding the stress memory effect of rock (Kaiser effect), the dependence of AE rates and b-value on the stress state as well as the stress rate and the spatio-temporal evolution of the AE activity. Event rates and b-values of the frequency magnitude relation are calculated for a region well covered by a network of piezo-electric receivers from an event catalog corrected for incomplete recording times. Results are compared and correlated with the output of a 2D thermo-elastic stress modelling performed with an FE program. The high quality of the AE dataset as well as the good control of the input parameters of the FE program allows us to study the in situ activity in the mining environment with exceptionally high precision and temporal resolution. The backfilling period can be subdivided into two AE activity regimes. The first one exhibits a clear and pronounced Kaiser effect as well as an upward migration of the AE event front away from the ceiling of the cavity which correlates with the calculated stress field. This observation of the Kaiser effect implies that no healing effect is observed for these first few loading cycles. The maximum event rate observed during a loading cycle scales with the absolute stress increase of this cycle with respect to the former maximum. This behavior is also observed for later loading cycles which show a deteriorated Kaiser effect with an onset of AE activity well before the former maximum stress and a smaller slope of the relation between maximum event rate and absolute stress increase. During later loading cycles also time periods showing a pronounced anti-correlation between event rate and Coulomb stress with event rate maxima during minima of the Coulomb stress are observed. These time periods are generally characterized by a b-value of the frequency magnitude relation much higher than during times of positive correlation between event rate and Coulomb stress. One possible explanation for this behavior might be a loss of cohesion in the rock salt due to the influence of moisture which is introduced during the backfilling process. The resulting temporal event rate changes might be explained by a Coulomb failure model incorporating the thermal stress changes as well as a time-dependent cohesion coefficient. However, other explanations are also possible and will be discussed. The results of this study indicate that the observation of the AE activity during cyclic loading is able to detect changes in the system and is well suited for monitoring purposes.
Becker, D.; Cailleau, B.; Dahm, T.; Shapiro, S.; Kaiser, D.
The spatio-temporal distribution of lightning flashes over Israel and the neighboring area and its relation to the regional synoptic systems has been studied, based on data obtained from the Israel Lightning Location System (ILLS) operated by the Israel Electric Corporation (IEC). The system detects cloud-to-ground lightning discharges in a range of ~500 km around central Israel (32.5° N, 35° E). The study period was defined for annual activity from August through July, for 5 seasons in the period 2004-2010. The spatial distribution of lightning flash density indicates the highest concentration over the Mediterranean Sea, attributed to the contribution of moisture as well as sensible and latent heat fluxes from the sea surface. Other centers of high density appear along the coastal plain, orographic barriers, especially in northern Israel, and downwind from the metropolitan area of Tel Aviv, Israel. The intra-annual distribution shows an absence of lightning during the summer months (JJA) due to the persistent subsidence over the region. The vast majority of lightning activity occurs during 7 months, October to April. Although over 65 % of the rainfall in Israel is obtained during the winter months (DJF), only 35 % of lightning flashes occur in these months. October is the richest month, with 40 % of total annual flashes. This is attributed both to tropical intrusions, i.e., Red Sea Troughs (RST), which are characterized by intense static instability and convection, and to Cyprus Lows (CLs) arriving from the west. Based on daily study of the spatial distribution of lightning, three patterns have been defined; "land", "maritime" and "hybrid". CLs cause high flash density over the Mediterranean Sea, whereas some of the RST days are typified by flashes over land. The pattern defined "hybrid" is a combination of the other 2 patterns. On CL days, only the maritime pattern was noted, whereas in RST days all 3 patterns were found, including the maritime pattern. It is suggested that atmospheric processes associated with RST produce the land pattern. Hence, the occurrence of a maritime pattern in days identified as RST reflects an "apparent RST". The hybrid pattern was associated with an RST located east of Israel. This synoptic type produced the typical flash maximum over the land, but the upper-level trough together with the onshore winds it induced over the eastern coast of the Mediterranean resulted in lightning activity over the sea as well, similar to that of CLs. It is suggested that the spatial distribution patterns of lightning may better identify the synoptic system responsible, a CL, an "active RST" or an "apparent RST". The electrical activity thus serves as a "fingerprint" for the synoptic situation responsible for its generation.
Shalev, S.; Saaroni, H.; Izsak, T.; Yair, Y.; Ziv, B.
A~method to determine the mean response of upper tropospheric water to localised deep convective (DC) events is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation are composited with respect to local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the above study are the isolation of DC events in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterization of the DC-induced anomalies. The DC events observed in this study propagate westward at ~ 4 m s-1. Both the upper tropospheric relative humidity and outgoing longwave radiation are substantially perturbed over a broad horizontal extent during peak convection and for long periods of time. Cloud fraction anomaly increases throughout the upper troposphere, especially in the 200-250 hPa layer, reaching peak coverage following deep convection. Cloud ice water content anomaly confined to pressures greater than about 250 hPa and peaks near 450 hPa within a few hours of the DC event but remain enhanced following the DC event. Consistent with the large increase in upper tropospheric cloud ice, albedo increases dramatically and persists for sometime following the DC event. Applying the method to the model demonstrates that it is able to capture the large-scale responses to DC events, most notably for outgoing longwave radiation, but there are a number of important differences. For example, the DC signature of upper tropospheric humidity consistently covers a broader horizontal area than what is observed. In addition, the DC events move eastward in the model, but westward in the observations, and exhibit an unrealistic 24 h repeat cycle. Moreover, the modeled upper tropospheric cloud fraction anomalies - despite being of comparable magnitude and exhibiting similar longevity - are confined to a thinner layer that is closer to the tropopause and peak earlier than in observations. Finally, the modeled ice water content anomalies at pressures greater than about 350 hPa are about twice as large as in the observations and do not persist as long after peak convection.
Johnston, M. S.; Eriksson, P.; Eliasson, S.; Zelinka, M. D.; Forbes, R. M.; Wyser, K.
Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C?N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right.
Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jurgen; Schoeman, David S.
This paper presents a temporal, spatial, and spatio-temporal linear stability analysis of the two-layer film flow down a plate tilted at an angle ?. It is based on a zero Reynolds number approximation to the Orr-Sommerfeld equations and a zero surface tension approximation to both surface boundary conditions. The combined effects of density and viscosity stratifications are systematically investigated. The subtle influence of density stratification is first put into light by a temporal analysis for ?=0.2 when increasing/decreasing the density ratio (upper fluid/lower fluid), the two-layer film flow becomes much more unstable/stable with respect to the finite wavelength instability. Moreover, below a critical density ratio this finite wavelength instability even disappears, whatever the viscous ratio. Concerning the long wave instability, it becomes dominant when decreasing the density ratio below 1 and is even triggered in a region which was stable for equal density layers. The spatio-temporal analysis shows that the instability is convective for incline angles that are not too small as ?=0.2. The study of the local growth rates of the spatio-temporal instability as a function of the ray velocity V shows that there is a transition between long wave and short wave instabilities which has been determined by using the Briggs-Bers collision criterion. Accordingly, there exists a jump for the local oscillatory frequency, spatial amplification rate, and spatial wave number due to this transition. Due to the existence of the absolute Rayleigh-Taylor instability for ?=0, the transition from convective to absolute instability can be detected for values of ? smaller than 0.2, and absolute/convective instability boundary curves have been obtained for varying characteristic parameters.
Hu, J.; Millet, S.; Botton, V.; Ben Hadid, H.; Henry, D.
Studies of food webs often employ stable isotopic approaches to infer trophic position and interaction strength without consideration of spatio-temporal variation in resource assimilation by constituent species. Using results from laboratory diet manipulations and monthly sampling of field populations, we illustrate how nitrogen isotopes may be used to quantify spatio-temporal variation in resource assimilation in ants. First, we determined nitrogen enrichment using a controlled laboratory experiment with the invasive Argentine ant (Linepithema humile). After 12 weeks, worker ?15N values from colonies fed an animal-based diet had ?15N values that were 5.51% greater compared to colonies fed a plant-based diet. The shift in ?15N values in response to the experimental diet occurred within 10 weeks. We next reared Argentine ant colonies with or without access to honeydew-producing aphids and found that after 8 weeks workers from colonies without access to aphids had ?15N values that were 6.31% larger compared to colonies with access to honeydew. Second, we sampled field populations over a 1-year period to quantify spatio-temporal variability in isotopic ratios of L. humile and those of a common native ant (Solenopsis xyloni). Samples from free-living colonies revealed that fluctuations in ?15N were 1.6–2.4‰ for L. humile and 1.8–2.9‰ for S. xyloni. Variation was also detected among L. humile castes: time averaged means of ?15N varied from 1.2 to 2.5‰ depending on the site, with ?15N values for queens ? workers > brood. The estimated trophic positions of L. humile and S. xyloni were similar within a site; however, trophic position for each species differed significantly at larger spatial scales. While stable isotopes are clearly useful for examining the trophic ecology of arthropod communities, our results suggest that caution is warranted when making ecological interpretations when stable isotope collections come from single time periods or life stages.
Suarez, Andy V.; Tillberg, Chadwick V.; Chou, Cheng T.; Holway, David A.
We study collective phenomena in nonhomogeneous cardiac cell culture models, including one- and two-dimensional lattices of oscillatory cells and mixtures of oscillatory and excitable cells. Individual cell dynamics is described by a modified Luo-Rudy model with depolarizing current. We focus on the transition from incoherent behavior to global synchronization via cluster synchronization regimes as coupling strength is increased. These regimes are characterized qualitatively by space-time plots and quantitatively by profiles of local frequencies and distributions of cluster sizes in dependence upon coupling strength. We describe spatio-temporal patterns arising during this transition, including pacemakers, spiral waves, and complicated irregular activity.
Kanakov, O. I.; Osipov, G. V.; Chan, C.-K.; Kurths, J.
The spatio-temporal distribution of benthic colonies of Microcystis aeruginosa in Grangent Reservoir (France) in 2000 was not homogeneous and appeared to be controlled by many external factors: lake depth, station morphometry, substratum and hydraulic regime (lacustrine or fluvial). A most important concentration of benthic colonies was found at deep sites with fine sediment or at sites where the sediment was rich in organic matter. In spite of a stable water level and a minimum flow during summer, the number of benthic colonies showed great variation in the lacustrine downstream part of the reservoir. These variations may be explained by the dynamics of planktonic cyanobacteria. PMID:15506524
Latour, Delphine; Giraudet, Hervé
A key challenge to climate change research is understanding how different components in the Earth system influence one another. For example, it is well known that the Earth's climate system exhibits variability at a wide range of time scales. However, the effect of such variability on terrestrial ecosystems is less well understood. In this dissertation, satellite observations of vegetation activity are used in conjunction with climate records to investigate seasonal-scale interactions between the Earth's terrestrial biosphere, atmosphere, and oceans. The results from this research show that interannual variation in the ocean-atmosphere system result in significant and geographically extensive ecosystem responses. To characterize spatio-temporal patterns of biospheric activity, multi-decadal (1981--2003) global satellite observations of plant growth were used. Non-linear variance decomposition methods were employed to remove artifacts unrelated to vegetation dynamics and to identify climate-related signatures in the data. Vegetation growth in arid and semi-arid regions exhibits strong correlation with interannual fluctuations in precipitation, and responds most strongly to time-integrated precipitation anomalies. The climate mechanisms that give rise to observed patterns of precipitation-vegetation covariability are associated with perturbations in ocean-atmosphere circulations. Generally, these perturbations are caused by low frequency fluctuations in global sea surface temperatures, which are propagated to remote locations via changes in atmospheric circulation. The analysis shows that distinct patterns of coupled climate-vegetation activity are linked to well-defined circulation features and illustrates the global extent and sensitivity of ecosystems susceptible to perturbations in precipitation regimes. Observations of ecosystem dynamics derived from recent satellite data reveal unprecedented reductions in vegetation growth for large areas of the Northern Hemisphere during the boreal summer from 1998--2002. These patterns arise from a geographically extensive and intense drought that persisted in much of the Northern Hemisphere during this period, and are linked to a unique confluence of ocean circulation in the Pacific, Atlantic, and Indo-Pacific ocean basins. This condition resulted in rainfall deficits persisting multiple years in much of North America and Eurasia, with 95% of the continental land area showing below-normal precipitation and vegetation greenness. This episode provides evidence of the nature and magnitude of global vegetation responses to future perturbations in the climate system.
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 significant declines at the 95% confidence interval over much of the Sahel, concentrated during the primary crop growing season (June - August). The majority of these declines coincide with increasing trends in surface temperature. The largest of these declines (-45 mm/yr), which occurred on the western edge of the Gulf of Guinea on the other hand, appear to coincide with declines in precipitation. Declines in eastern Madagascar and the Congo basin, which showed no seasonal pattern or correlation with precipitation and temperature appear to be the result of deforestation. Harmonic regression will be used to further assess these trends. Important changes in AET phase could further our understanding of AET trends and their relation to climate change.
Marshall, M. T.; Funk, C. C.; Michaelsen, J.
On August 16, 2005, a M7.2 earthquake occurred along the plate boundary off Miyagi Prefecture, northeastern Japan, where the Pacific plate is subducting beneath the overriding continental plate at a rate of about 80 mm/yr. There are at least three asperities that were ruptured during the 1978 Miyagi-Oki earthquake (M7.4) there, and one or two of them were reruptured during the 2005 earthquake. We estimated spatio-temporal evolution of the postseismic slip associated with the 2005 Miyagi-Oki earthquake using continuous land GPS and campaign ocean bottom GPS/acoustic observation data in order to investigate whether the strain accumulation process at the unruptured asperities are affected by the event in 2005 or not. Daily site coordinates were estimated using a PPP (Precise Point Positioning) strategy of GIPSY-OASISII Software based on the GPS data observed at continuous sites operated by GSI (Geospatial Information Authority of Japan) and Tohoku University. Data from January 2004 to December 2007 have been analyzed. The linear trends with annual and semi-annual variations for the period from January 1, 2004 to August 15, 2005, and co-seismic displacements due to the main shock were estimated by least square modeling and subtracted from the original onshore GPS time series. As to the ocean bottom displacement data, we calculated secular velocities at the offshore site locations from an interplate coupling model based on the linear trends of land GPS sites and subtracted them from the observed time series. We regarded that the detrended time series represented the deformation due to the afterslip of the 2005 earthquake and were inverted them to obtain spatiotemporal slip distribution on the plate boundary by using a time dependent inversion analysis. We applied an inversion method devised by Yagi and Kikuchi (2003) to estimate the evolution of the fault slip in both space and time. We also estimated spatiotemporal evolution of the aseismic slip based on the activities of small repeating earthquakes, and compared the temporal variations of the accumulated slip at various places estimated from the seismological data with those from geodetic data. Results from the geodetic inversion show large afterslip on the trench-ward side of the rupture areas of the 1978 and 2005 events. Temporal pattern of the cumulative slip estimated from the geodetic data conforms well to those obtained from the small repeating earthquake activity in the region that includes the asperities of the 1978 Miyagi-Oki earthquake. Spatial and temporal change in back-slip distribution in NE Japan is also estimated from onshore GPS data, and the results suggest that the afterslip associated with the 2005 event tends to concentrate in the regions with significant activity of the small repeating earthquakes and that the interplate coupling in the unruptured asperities was strong even in the afterslip period. Therefore, the strain in the asperities is thought to have been considerably accumulated.
Iinuma, T.; Miura, S.; Uchida, N.; Sato, M.; Saito, H.; Ishikawa, T.; Hino, R.; Matsuzawa, T.
Road accidents are among the leading causes of death in many world countries, partly as an inherent consequence of the increasing mobility of today society. The World Health Organization estimates that 1.3 million people died in road accidents in 2011, which means 186 deaths per million. The tragic picture is completed by millions of peoples experiencing different physical injuries or by the enormous social and economic costs that these events imply. Romania has one of the most unsafe road networks within the European Union, with annual averages of 9400 accidents, 8300 injuries and almost 2680 fatalities (2007-2012). An average of 141 death per million is more than twice the average fatality rate in European Union (about 60 death per million). Other specific indicators (accidents or fatalities reported to the road length, vehicle fleet size, driving license owners or adult population etc.) are even worst in the same European context. Road accidents are caused by a complex series of factors, some of them being a relatively constant premise, while others act as catalyzing factors or triggering agent: road features and quality, vehicle technical state, weather conditions, human related factors etc. All these lead to a complex equation with too many unknown variables, making almost impossible a probabilistic approach. However, the high concentration of accidents in a region or in some road sectors is caused by the existence of a specific context, created by factors with permanent or repetitive character, and leads to the idea of a spatial autocorrelation between locations of different adjoining accident. In the same way, the increasing frequency of road accidents and of their causes repeatability in different periods of the year would allow to identify those black timeframes with higher incidence of road accidents. Identifying and analyzing the road blackspots (hotspots) and black zones would help to improve road safety by acting against the common causes that create the spatial or temporal clustering of crash accidents. Since the 1990's, Geographical Informational Systems (GIS) became a very important tool for traffic and road safety management, allowing not only the spatial and multifactorial analysis, but also graphical and non-graphical outputs. The current paper presents an accessible GIS methodology to study the spatio-temporal pattern of injury related road accidents, to identify the high density accidents zones, to make a cluster analysis, to create multicriterial typologies, to identify spatial and temporal similarities and to explain them. In this purpose, a Geographical Information System was created, allowing a complex analysis that involves not only the events, but also a large set of interrelated and spatially linked attributes. The GIS includes the accidents as georeferenced point elements with a spatially linked attribute database: identification information (date, location details); accident type; main, secondary and aggravating causes; data about driver; vehicle information; consequences (damages, injured peoples and fatalities). Each attribute has its own number code that allows both the statistical analysis and the spatial interrogation. The database includes those road accidents that led to physical injuries and loss of human lives between 2007 and 2012 and the spatial analysis was realized using TNTmips 7.3 software facilities. Data aggregation and processing allowed creating the spatial pattern of injury related road accidents through Kernel density estimation at three different levels (national - Romania; county level - Iasi County; local level - Iasi town). Spider graphs were used to create the temporal pattern or road accidents at three levels (daily, weekly and monthly) directly related to their causes. Moreover the spatial and temporal database relates the natural hazards (glazed frost, fog, and blizzard) with the human made ones, giving the opportunity to evaluate the nature of uncertainties in risk assessment. At the end, this paper provides a clustering methodology based on several environmenta
Catalin Stanga, Iulian
Spatial short-term memory for objects' locations was investigated in a spatial relocation task. During maintenance, dynamic visual noise or spatial tapping were administered as visual or spatial secondary tasks, respectively. Because memory for location should tap the visual component of working memory, a visual but not a spatial secondary task should impair location memory. In fact, neither of the tasks impaired memory (Experiment 1), although the expected dissociation between visual and spatial components was clearly confirmed for a spatio-temporal main task (Corsi test) (Experiment 2). We then contrasted location memory for pictures of objects and of nonsense figures under visual interference. Real objects were relocated much better than nonsense figures, and visual noise was again ineffective (Experiment 3). When spatial tapping was combined with the same material (Experiment 3a), again no influence on memory for locations of objects was observed and only a small influence on remembering nonsense figures. We suggest that the Corsi and the relocation VSWM-tasks use different memory mechanisms. The configuration of objects is reconstructed from perceptual records in an episodic buffer, provided by the same structures that enable visual memory after longer intervals. Rehearsal is not necessary for the persistence of these traces. In contrast, in the Corsi task remembering, a temporal sequence across homogeneous locations needs spatio-temporal marking and therefore active rehearsal of the locations by shifting spatial attention. A spatially demanding secondary task during retention interrupts this rehearsal. PMID:12927342
Zimmer, Hubert D; Speiser, Harry R; Seidler, Beate
* Plants must cope with environmental variation in space and time. Phenotypic plasticity allows them to adjust their form and function to small-scale variations in habitat quality. Empirical studies have shown that stoloniferous plants can exploit heterogeneous habitats through plastic ramet specialization and internal resource exchange (division of labour). * Here we present a spatially explicit simulation model to explore costs and benefits of plasticity in spatio-temporally heterogeneous environments. We investigated the performance of three plant strategies in pairwise competition. The nonplastic strategy was unable to specialize. The autonomous plastic strategy displayed localized responses to external resource signals. In the coordinated plastic strategy, localized responses could be modified by internal demand signals from connected modules. * Plasticity in resource uptake proved beneficial in a broad range of environments. Modular coordination was beneficial under virtually all realistic conditions, especially if resource supplies did not closely match resource needs. * The benefits of division of labour extend considerably beyond the parameter combination covered by empirical studies. Our model provides a general framework for evaluating the benefits, costs and limits of plasticity in spatio-temporally heterogeneous habitats. PMID:17335508
Magyar, Gabriella; Kun, Adám; Oborny, Beáta; Stuefer, Josef F
We engaged in cooperative research with fishers and stakeholders to characterize the fine-scale, spatio-temporal characteristics of spawning behavior in an aggregating marine fish (Cynoscion othonopterus: Sciaenidae) and coincident activities of its commercial fishery in the Upper Gulf of California. Approximately 1.5–1.8 million fish are harvested annually from spawning aggregations of C. othonopterus during 21–25 days of fishing and within an area of 1,149?km2 of a biosphere reserve. Spawning and fishing are synchronized on a semi-lunar cycle, with peaks in both occurring 5 to 2 days before the new and full moon, and fishing intensity and catch are highest at the spawning grounds within a no-take reserve. Results of this study demonstrate the benefits of combining GPS data loggers, fisheries data, biological surveys, and cooperative research with fishers to produce spatio-temporally explicit information relevant to the science and management of fish spawning aggregations and the spatial planning of marine reserves.
Erisman, Brad; Aburto-Oropeza, Octavio; Gonzalez-Abraham, Charlotte; Mascarenas-Osorio, Ismael; Moreno-Baez, Marcia; Hastings, Philip A.
A spatio-temporal framework for estimating trial-to-trial variability in evoked response data is presented. Spatial and temporal bases capture the aspects of the response that are consistent across trials, while the basis expansion coefficients represent the variable components of the response. We focus on the simplest case of constant spatio-temporal response shape and varying amplitude across trials. Two different constraints on the amplitude evolution are employed to effectively integrate the individual responses and improve robustness at low SNR. The linear dynamical system response (LDSR) constraint estimates the current trial amplitude as an unknown constant scaling of the estimate in the previous trial plus zero-mean Gaussian noise with unknown variance. The independent response (IR) constraint estimates response amplitudes across trials as independent Gaussian random variables having unknown mean and variance. We develop a generalized expectation-maximization algorithm to obtain the maximum likelihood estimates of the signal waveform, noise covariance matrix, and unknown constraint parameters. Maximum likelihood source localization is achieved by scanning the likelihood over different sets of spatial bases. We demonstrate the variability estimation and source localization effectiveness of the proposed algorithms using both real and simulated evoked response data.
Limpiti, Tulaya; Van Veen, Barry D.; Attias, Hagai T.; Nagarajan, Srikantan S.
We engaged in cooperative research with fishers and stakeholders to characterize the fine-scale, spatio-temporal characteristics of spawning behavior in an aggregating marine fish (Cynoscion othonopterus: Sciaenidae) and coincident activities of its commercial fishery in the Upper Gulf of California. Approximately 1.5-1.8 million fish are harvested annually from spawning aggregations of C. othonopterus during 21-25 days of fishing and within an area of 1,149?km(2) of a biosphere reserve. Spawning and fishing are synchronized on a semi-lunar cycle, with peaks in both occurring 5 to 2 days before the new and full moon, and fishing intensity and catch are highest at the spawning grounds within a no-take reserve. Results of this study demonstrate the benefits of combining GPS data loggers, fisheries data, biological surveys, and cooperative research with fishers to produce spatio-temporally explicit information relevant to the science and management of fish spawning aggregations and the spatial planning of marine reserves. PMID:22359736
Erisman, Brad; Aburto-Oropeza, Octavio; Gonzalez-Abraham, Charlotte; Mascareñas-Osorio, Ismael; Moreno-Báez, Marcia; Hastings, Philip A
Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR). PMID:22558222
Pitzalis, Sabrina; Strappini, Francesca; De Gasperis, Marco; Bultrini, Alessandro; Di Russo, Francesco
Spatio-temporal variability of recharge (R) and groundwater evapotranspiration (ETg) fluxes in a granite Sardon catchment in Spain (˜80 km2) have been assessed based on integration of various data sources and methods within the numerical groundwater MODFLOW model. The data sources and methods included: remote sensing solution of surface energy balance using satellite data, sap flow measurements, chloride mass balance, automated monitoring of climate, depth to groundwater table and river discharges, 1D reservoir modeling, GIS modeling, field cartography and aerial photo interpretation, slug and pumping tests, resistivity, electromagnetic and magnetic resonance soundings. The presented study case provides not only detailed evaluation of the complexity of spatio-temporal variable fluxes, but also a complete and generic methodology of modern data acquisition and data integration in transient groundwater modeling for spatio-temporal groundwater balancing. The calibrated numerical model showed spatially variable patterns of R and ETg fluxes despite a uniform rainfall pattern. The seasonal variability of fluxes indicated: (1) R in the range of 0.3 0.5 mm/d within ˜8 months of the wet season with exceptional peaks as high as 0.9 mm/d in January and February and no recharge in July and August; (2) a year round stable lateral groundwater outflow (Qg) in the range of 0.08 0.24 mm/d; (3) ETg=0.64, 0.80, 0.55 mm/d in the dry seasons of 1997, 1998, 1999, respectively, and <0.05 mm/d in wet seasons; (4) temporally variable aquifer storage, which gains water in wet seasons shortly after rain showers and looses water in dry seasons mainly due to groundwater evapotranspiration. The dry season sap flow measurements of tree transpiration performed in the homogenous stands of Quercus ilex and Quercus pyrenaica indicated flux rates of 0.40 and 0.15 mm/d, respectively. The dry season tree transpiration for the entire catchment was ˜0.16 mm/d. The availability of dry season transpiration measurements considered as root groundwater uptake (Tg), allowed estimation of dry season catchment groundwater evaporation (Eg) as 0.48, 0.64, 0.39 mm/d for 1997, 1998 and 1999, respectively.
W. Lubczynski, Maciek; Gurwin, Jacek
Intensive crop production in the Chippewa River Watershed (CRW) in West Central Minnesota has altered the dynamics and nature of water, sediments, and nutrients and resulted in biophysical changes within and beyond the watershed. Opportunities to improve the ecological functioning of managed and nat...
SUMMARY A high speed 3D shape reconstruction method with multiple video cameras and multiple computers on LAN is presented. The video cameras are set to surround the real 3D space where people exist. Reconstructed 3D space is displayed in voxel format and users can see the space from any viewpoint with a VR viewer. We implemented a prototype system that
Yoshinari KAMEDA; Takeo TAODA; Michihiko MINOH
\\u000a Integrating spatial operators in commercial data streaming engines has gained tremendous interest in recent years. Whether\\u000a to support such operators natively or to enable the operator through an extensibility framework is a challenging and interesting\\u000a debate. In this paper we leverage the Microsoft StreamInsightTM extensibility framework to support spatial operators enabling developers to integrate their domain expertise within the query
Jeremiah Miller; Miles Raymond; Josh Archer; Seid Adem; Leo Hansel; Sushma Konda; Malik Luti; Yao Zhao; Ankur Teredesai; Mohamed Ali
|The tip-of-the-tongue state (TOT) in face naming is a transient state of difficulty in access to a person's name along with the conviction that the name is known. The aim of the present study was to characterize the spatio-temporal course of brain activation in the successful naming and TOT states, by means of magnetoencephalography, during a…
Lindin, Monica; Diaz, Fernando; Capilla, Almudena; Ortiz, Tomas; Maestu, Fernando
Spatio-temporal gait characteristics (step and stride length, stride frequency, duty factor) were determined for the hind-limb cycles of nine bonobos (Pan paniscus) walking quadrupedally and bipedally at a range of speeds. The data were recalculated to dimensionless quantities according to the principle of dynamic similarity. Lower leg length was used as the reference length. Interindividual variability in speed modulation strategy
Peter Aerts; Raoul Van Damme; Linda Van Elsacker; Vicky Duchêne
In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects. PMID:22255854
Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal
Spatio-temporal variability and predictability in Ebro river basin is investigated. Basque-Cantabrian, Pyrenees and Southern Mediterranean regions are differentiated. At decadal time scales SST anomalies are a significant source of predictability for the streamflow. At interannual time scales ARMA modelling provides potential skill in forecasting. Basin-specific hydroclimatic predictions are provided for the Ebro River.
Gámiz-Fortis, S. R.; Hidalgo-Muñoz, J. M.; Argüeso, D.; Esteban-Parra, M. J.; Castro-Díez, Y.
The intense Coherent Synchrotron Radiation emitted in the Terahertz range by relativistic electron bunches circulating in a storage ring is an attractive source for spectroscopy. Its stability is related to the electron bunch dynamics, and can exhibit a bursting behavior resulting from the irregular presence of micro-structures in the bunch. We evidence here the existence of two thresholds in the electron bunch spatio-temporal dynamics, associated with different levels of Terahertz signal fluctuations, with increasing number of electrons. The first threshold indicates the presence of micro-structures drifting in the bunch profile, and the second one appears when those micro-structures are strong enough to persist after about half a revolution period of the electron-bunch in the phase-space. Their prediction thanks to numerical simulations are confirmed by experiments at the synchrotron SOLEIL.
Evain, C.; Barros, J.; Loulergue, A.; Tordeux, M. A.; Nagaoka, R.; Labat, M.; Cassinari, L.; Creff, G.; Manceron, L.; Brubach, J. B.; Roy, P.; Couprie, M. E.
In this paper we discuss the SIMID tool for simulation of the spread of infectious disease, enabling spatio-temporal visualization of the dynamics of influenza outbreaks. SIMID is based on modern random network methodology and implemented within the R and GIS frameworks. The key advantage of SIMID is that it allows not only for the construction of a possible scenario for the spread of an infectious disease but also for the assessment of mitigation strategies, variation and uncertainty in disease parameters and randomness in the progression of an outbreak. We illustrate SIMID by application to an influenza epidemic simulation in a population constructed to resemble the Region of Peel, Ontario, Canada. PMID:23566710
Ramírez-Ramírez, Lilia L; Gel, Yulia R; Thompson, Mary; de Villa, Eileen; McPherson, Matt
As the supplement of spaceborne and airborne imaging spectrometer system, field Imaging spectrometer system spans a very broad range of applications. Imaging spectrometer system of this new kind could provide vital information especially for which spaceborne or airborne remote sensing could not be competent, such as proximal detection of plant population, individual plant or plant organs for site-specific management in precision agriculture. A new self-developed imaging spectrometer system was utilized to monitor spatio-temporal dynamics of spectral changes of plant leaves in response to dehydration. lThe phenomenon of blue shift of red edge of plant leaves was successfully detected and visualized in the form of image series. The patterns of photochemical reflectance index (PRI) of leaves during dehydration were compared and confirmed by fluorescence parameter quantum yield. Our results show that FISS has good spectral and radiometric properties and could be used in quantitative researches and precise information mapping. PMID:22870619
Liu, Bo; Tong, Qing-Xi; Zhang, Li-Fu; Zhang, Xia; Yue, Yue-Min; Zhang, Bing
Acousto-optic deflectors (AOD) are promising ultrafast scanners for non-linear microscopy. Their use has been limited until now by their small scanning range and by the spatial and temporal dispersions of the laser beam going through the deflectors. We show that the use of AOD of large aperture (13mm) compared to standard deflectors allows accessing much larger field of view while minimizing spatio-temporal distortions. An acousto-optic modulator (AOM) placed at distance of the AOD is used to compensate spatial and temporal dispersions. Fine tuning of the AOM-AOD setup using a frequency-resolved optical gating (GRENOUILLE) allows elimination of pulse front tilt whereas spatial chirp is minimized thanks to the large aperture AOD. PMID:18607414
Kremer, Y; Léger, J-F; Lapole, R; Honnorat, N; Candela, Y; Dieudonné, S; Bourdieu, L
This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.
Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam
Background Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. Methodology/Principal Findings We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA), from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the ‘true’ prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. Conclusion/Significance Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken into consideration when making risk prediction at small scales.
Wang, Xian-Hong; Zhou, Xiao-Nong; Vounatsou, Penelope; Chen, Zhao; Utzinger, Jurg; Yang, Kun; Steinmann, Peter; Wu, Xiao-Hua
In Miyagi-Oki region, the area of large coseismic slip of the 2011 off the pacific coast of Tohoku Earthquake (M 9.0), it has been thought that interplate earthquakes with magnitude of ~7.5 occur repeatedly, with an interval of about 37 years. We started a seismic observation in the region, using 5 ocean bottom seismometers (OBSs) in 2002, so as to assist in making long-term forecasting of a forthcoming M-7.5 earthquake by monitoring small earthquake activity in the region. This OBS observation was followed by a series of repeated deployment of OBSs, in which OBSs are recovered and deployed at the same locations to allow long-term continuous data acquisition. In the repeated observation, we also increased the number of OBSs: When the 2005 Miyagi-Oki earthquake (M 7.2) occurred, 15 OBSs were in place and the Tohoku earthquake on March 11 was observed by 23 OBSs. In this research, we built a waveform database by integrating the records obtained from OBS with the data from routine observation points on land as well as another database of completely continuous OBS waveform data. The former database has been used for hypocenter relocations by combining use of on- and offshore seismic data to provide an earthquake catalogue for Miyagi-Oki region with reliable hypocenter locations. In this paper, we examine the continuous waveform records of OBSs to understand spatio-temporal variation of the microseismicity. The continuous records contain many small earthquakes, which do not appear in the catalogue due to the limitation of the detectability of the onshore seismic network. By including these small earthquakes, it is expected that we can examine if the seismicity shows any changes before the occurrence of major earthquakes such as that in 2005 and the Tohoku earthquake, much more in detail than the previous attempt using the available catalogue.
Suzuki, S.; Hino, R.; Ito, Y.; Suzuki, K.; Shinohara, M.; Yamada, T.; Kanazawa, T.; Kaneda, Y.
The small size of the billions of migrating songbirds commuting between temperate breeding sites and the tropics has long prevented the study of the largest part of their annual cycle outside the breeding grounds. Using light-level loggers (geolocators), we recorded the entire annual migratory cycle of the red-backed shrike Lanius collurio, a trans-equatorial Eurasian-African passerine migrant. We tested differences between autumn and spring migration for nine individuals. Duration of migration between breeding and winter sites was significantly longer in autumn (average 96 days) when compared with spring (63 days). This difference was explained by much longer staging periods during autumn (71 days) than spring (9 days). Between staging periods, the birds travelled faster during autumn (356 km d(-1)) than during spring (233 km d(-1)). All birds made a protracted stop (53 days) in Sahelian sub-Sahara on southbound migration. The birds performed a distinct loop migration (22 000 km) where spring distance, including a detour across the Arabian Peninsula, exceeded the autumn distance by 22 per cent. Geographical scatter between routes was particularly narrow in spring, with navigational convergence towards the crossing point from Africa to the Arabian Peninsula. Temporal variation between individuals was relatively constant, while different individuals tended to be consistently early or late at different departure/arrival occasions during the annual cycle. These results demonstrate the existence of fundamentally different spatio-temporal migration strategies used by the birds during autumn and spring migration, and that songbirds may rely on distinct staging areas for completion of their annual cycle, suggesting more sophisticated endogenous control mechanisms than merely clock-and-compass guidance among terrestrial solitary migrants. After a century with metal-ringing, year-round tracking of long-distance migratory songbirds promises further insights into bird migration. PMID:21900322
Tøttrup, Anders P; Klaassen, Raymond H G; Strandberg, Roine; Thorup, Kasper; Kristensen, Mikkel Willemoes; Jørgensen, Peter Søgaard; Fox, James; Afanasyev, Vsevolod; Rahbek, Carsten; Alerstam, Thomas
Video applications on handheld devices such as smart phones pose a significant challenge to achieve high quality user experience. Recent advances in processor and wireless networking technology are producing a new class of multimedia applications (e.g. video streaming) for mobile handheld devices. These devices are light weight and have modest sizes, and therefore very limited resources - lower processing power, smaller display resolution, lesser memory, and limited battery life as compared to desktop and laptop systems. Multimedia applications on the other hand have extensive processing requirements which make the mobile devices extremely resource hungry. In addition, the device specific properties (e.g. display screen) significantly influence the human perception of multimedia quality. In this paper we propose a saliency based framework that exploits the structure in content creation as well as the human vision system to find the salient points in the incoming bitstream and adapt it according to the target device, thus improving the quality of new adapted area around salient points. Our experimental results indicate that the adaptation process that is cognizant of video content and user preferences can produce better perceptual quality video for mobile devices. Furthermore, we demonstrated how such a framework can affect user experience on a handheld device.
Jillani, Rashad; Kalva, Hari
Light use efficiency of photosynthesis dynamically adapts to environmental factors, which lead to complex