WorldWideScience

Sample records for temporal dynamics model

  1. Analysing the temporal dynamics of model performance for hydrological models

    NARCIS (Netherlands)

    Reusser, D.E.; Blume, T.; Schaefli, B.; Zehe, E.

    2009-01-01

    The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or

  2. A dynamic neural field model of temporal order judgments.

    Science.gov (United States)

    Hecht, Lauren N; Spencer, John P; Vecera, Shaun P

    2015-12-01

    Temporal ordering of events is biased, or influenced, by perceptual organization-figure-ground organization-and by spatial attention. For example, within a region assigned figural status or at an attended location, onset events are processed earlier (Lester, Hecht, & Vecera, 2009; Shore, Spence, & Klein, 2001), and offset events are processed for longer durations (Hecht & Vecera, 2011; Rolke, Ulrich, & Bausenhart, 2006). Here, we present an extension of a dynamic field model of change detection (Johnson, Spencer, Luck, & Schöner, 2009; Johnson, Spencer, & Schöner, 2009) that accounts for both the onset and offset performance for figural and attended regions. The model posits that neural populations processing the figure are more active, resulting in a peak of activation that quickly builds toward a detection threshold when the onset of a target is presented. This same enhanced activation for some neural populations is maintained when a present target is removed, creating delays in the perception of the target's offset. We discuss the broader implications of this model, including insights regarding how neural activation can be generated in response to the disappearance of information. (c) 2015 APA, all rights reserved).

  3. Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

    Energy Technology Data Exchange (ETDEWEB)

    Rossi, R; Gallagher, B; Neville, J; Henderson, K

    2011-11-11

    Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.

  4. A dynamic texture based approach to recognition of facial actions and their temporal models

    NARCIS (Netherlands)

    Koelstra, Sander; Pantic, Maja; Patras, Ioannis (Yannis)

    2010-01-01

    In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the

  5. A Model of the Temporal Dynamics of Knowledge Brokerage in Sustainable Development

    Science.gov (United States)

    Hukkinen, Janne I.

    2016-01-01

    I develop a conceptual model of the temporal dynamics of knowledge brokerage for sustainable development. Brokerage refers to efforts to make research and policymaking more accessible to each other. The model enables unbiased and systematic consideration of knowledge brokerage as part of policy evolution. The model is theoretically grounded in…

  6. A dynamic appearance descriptor approach to facial actions temporal modeling

    NARCIS (Netherlands)

    Jiang, Bihan; Valstar, Michel; Martinez, Brais; Pantic, Maja

    Both the configuration and the dynamics of facial expressions are crucial for the interpretation of human facial behavior. Yet to date, the vast majority of reported efforts in the field either do not take the dynamics of facial expressions into account, or focus only on prototypic facial

  7. A dynamic texture-based approach to recognition of facial actions and their temporal models.

    Science.gov (United States)

    Koelstra, Sander; Pantic, Maja; Patras, Ioannis

    2010-11-01

    In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the dynamics and the appearance in the face region of an input video are compared: an extended version of Motion History Images and a novel method based on Nonrigid Registration using Free-Form Deformations (FFDs). The extracted motion representation is used to derive motion orientation histogram descriptors in both the spatial and temporal domain. Per AU, a combination of discriminative, frame-based GentleBoost ensemble learners and dynamic, generative Hidden Markov Models detects the presence of the AU in question and its temporal segments in an input image sequence. When tested for recognition of all 27 lower and upper face AUs, occurring alone or in combination in 264 sequences from the MMI facial expression database, the proposed method achieved an average event recognition accuracy of 89.2 percent for the MHI method and 94.3 percent for the FFD method. The generalization performance of the FFD method has been tested using the Cohn-Kanade database. Finally, we also explored the performance on spontaneous expressions in the Sensitive Artificial Listener data set.

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

    Science.gov (United States)

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

    2010-01-01

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

  9. Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.

    Science.gov (United States)

    Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano

    2016-11-15

    Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.

  10. A comprehensive model of audiovisual perception: both percept and temporal dynamics.

    Directory of Open Access Journals (Sweden)

    Patricia Besson

    Full Text Available The sparse information captured by the sensory systems is used by the brain to apprehend the environment, for example, to spatially locate the source of audiovisual stimuli. This is an ill-posed inverse problem whose inherent uncertainty can be solved by jointly processing the information, as well as introducing constraints during this process, on the way this multisensory information is handled. This process and its result--the percept--depend on the contextual conditions perception takes place in. To date, perception has been investigated and modeled on the basis of either one of two of its dimensions: the percept or the temporal dynamics of the process. Here, we extend our previously proposed audiovisual perception model to predict both these dimensions to capture the phenomenon as a whole. Starting from a behavioral analysis, we use a data-driven approach to elicit a bayesian network which infers the different percepts and dynamics of the process. Context-specific independence analyses enable us to use the model's structure to directly explore how different contexts affect the way subjects handle the same available information. Hence, we establish that, while the percepts yielded by a unisensory stimulus or by the non-fusion of multisensory stimuli may be similar, they result from different processes, as shown by their differing temporal dynamics. Moreover, our model predicts the impact of bottom-up (stimulus driven factors as well as of top-down factors (induced by instruction manipulation on both the perception process and the percept itself.

  11. A Markov model for the temporal dynamics of balanced random networks of finite size

    Science.gov (United States)

    Lagzi, Fereshteh; Rotter, Stefan

    2014-01-01

    The balanced state of recurrent networks of excitatory and inhibitory spiking neurons is characterized by fluctuations of population activity about an attractive fixed point. Numerical simulations show that these dynamics are essentially nonlinear, and the intrinsic noise (self-generated fluctuations) in networks of finite size is state-dependent. Therefore, stochastic differential equations with additive noise of fixed amplitude cannot provide an adequate description of the stochastic dynamics. The noise model should, rather, result from a self-consistent description of the network dynamics. Here, we consider a two-state Markovian neuron model, where spikes correspond to transitions from the active state to the refractory state. Excitatory and inhibitory input to this neuron affects the transition rates between the two states. The corresponding nonlinear dependencies can be identified directly from numerical simulations of networks of leaky integrate-and-fire neurons, discretized at a time resolution in the sub-millisecond range. Deterministic mean-field equations, and a noise component that depends on the dynamic state of the network, are obtained from this model. The resulting stochastic model reflects the behavior observed in numerical simulations quite well, irrespective of the size of the network. In particular, a strong temporal correlation between the two populations, a hallmark of the balanced state in random recurrent networks, are well represented by our model. Numerical simulations of such networks show that a log-normal distribution of short-term spike counts is a property of balanced random networks with fixed in-degree that has not been considered before, and our model shares this statistical property. Furthermore, the reconstruction of the flow from simulated time series suggests that the mean-field dynamics of finite-size networks are essentially of Wilson-Cowan type. We expect that this novel nonlinear stochastic model of the interaction between

  12. Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

    Science.gov (United States)

    Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

    2014-09-10

    Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3

  13. Modelling temporal and spatial dynamics of benthic fauna in North-West-European shelf seas

    Science.gov (United States)

    Lessin, Gennadi; Bruggeman, Jorn; Artioli, Yuri; Butenschön, Momme; Blackford, Jerry

    2017-04-01

    Benthic zones of shallow shelf seas receive high amounts of organic material. Physical processes such as resuspension, as well as complex transformations mediated by diverse faunal and microbial communities, define fate of this material, which can be returned to the water column, reworked within sediments or ultimately buried. In recent years, numerical models of various complexity and serving different goals have been developed and applied in order to better understand and predict dynamics of benthic processes. ERSEM includes explicit parameterisations of several groups of benthic biota, which makes it particularly applicable for studies of benthic biodiversity, biological interactions within sediments and benthic-pelagic coupling. To assess model skill in reproducing temporal (inter-annual and seasonal) dynamics of major benthic macrofaunal groups, 1D model simulation results were compared with data from the Western Channel Observatory (WCO) benthic survey. The benthic model was forced with organic matter deposition rates inferred from observed phytoplankton abundance and model parameters were subsequently recalibrated. Based on model results and WCO data comparison, deposit-feeders exert clear seasonal variability, while for suspension-feeders inter-annual variability is more pronounced. Spatial distribution of benthic fauna was investigated using results of a full-scale NEMO-ERSEM hindcast simulation of the North-West European Shelf Seas area, covering the period of 1981-2014. Results suggest close relationship between spatial distribution of biomass of benthic faunal functional groups in relation to bathymetry, hydrodynamic conditions and organic matter supply. Our work highlights that it is feasible to construct, implement and validate models that explicitly include functional groups of benthic macrofauna. Moreover, the modelling approach delivers detailed information on benthic biogeochemistry and food-web at spatial and temporal scales that are unavailable

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

    Directory of Open Access Journals (Sweden)

    Matthias Rieckher

    Full Text Available We describe a customizable and cost-effective light sheet microscopy (LSM platform for rapid three-dimensional imaging of protein dynamics in small model organisms. The system is designed for high acquisition speeds and enables extended time-lapse in vivo experiments when using fluorescently labeled specimens. We demonstrate the capability of the setup to monitor gene expression and protein localization during ageing and upon starvation stress in longitudinal studies in individual or small groups of adult Caenorhabditis elegans nematodes. The system is equipped to readily perform fluorescence recovery after photobleaching (FRAP, which allows monitoring protein recovery and distribution under low photobleaching conditions. Our imaging platform is designed to easily switch between light sheet microscopy and optical projection tomography (OPT modalities. The setup permits monitoring of spatio-temporal expression and localization of ageing biomarkers of subcellular size and can be conveniently adapted to image a wide range of small model organisms and tissue samples.

  15. Measuring and modeling the temporal dynamics of nitrogen balance in an experimental-scale paddy field

    Science.gov (United States)

    Tseng, C.; Lin, Y.

    2013-12-01

    Nitrogen balance involves many mechanisms and plays an important role to maintain the function of nature. Fertilizer application in agriculture activity is usually seen as a common and significant nitrogen input to environment. Improper fertilizer application on paddy field can result in great amount of various types of nitrogen losses. Hence, it is essential to understand and quantify the nitrogen dynamics in paddy field for fertilizer management and pollution control. In this study, we develop a model which considers major transformation processes of nitrogen (e.g. volatilization, nitrification, denitrification and plant uptake). In addition, we measured different types of nitrogen in plants, soil and water at plant growth stages in an experimental-scale paddy field in Taiwan. The measurement includes total nitrogen in plants and soil, and ammonium-N (NH4+-N), nitrate-N (NO3--N) and organic nitrogen in water. The measured data were used to calibrate the model parameters and validate the model for nitrogen balance simulation. The results showed that the model can accurately estimate the temporal dynamics of nitrogen balance in paddy field during the whole growth stage. This model might be helpful and useful for future fertilizer management and pollution control in paddy field.

  16. Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

    Science.gov (United States)

    Tranmer, Mark; Marcum, Christopher Steven; Morton, F Blake; Croft, Darren P; de Kort, Selvino R

    2015-03-01

    Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula , in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

  17. Predicting seizures in untreated temporal lobe epilepsy using point-process nonlinear models of heartbeat dynamics.

    Science.gov (United States)

    Valenza, G; Romigi, A; Citi, L; Placidi, F; Izzi, F; Albanese, M; Scilingo, E P; Marciani, M G; Duggento, A; Guerrisi, M; Toschi, N; Barbieri, R

    2016-08-01

    Symptoms of temporal lobe epilepsy (TLE) are frequently associated with autonomic dysregulation, whose underlying biological processes are thought to strongly contribute to sudden unexpected death in epilepsy (SUDEP). While abnormal cardiovascular patterns commonly occur during ictal events, putative patterns of autonomic cardiac effects during pre-ictal (PRE) periods (i.e. periods preceding seizures) are still unknown. In this study, we investigated TLE-related heart rate variability (HRV) through instantaneous, nonlinear estimates of cardiovascular oscillations during inter-ictal (INT) and PRE periods. ECG recordings from 12 patients with TLE were processed to extract standard HRV indices, as well as indices of instantaneous HRV complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra) obtained through definition of inhomogeneous point-process nonlinear models, employing Volterra-Laguerre expansions of linear, quadratic, and cubic kernels. Experimental results demonstrate that the best INT vs. PRE classification performance (balanced accuracy: 73.91%) was achieved only when retaining the time-varying, nonlinear, and non-stationary structure of heartbeat dynamical features. The proposed approach opens novel important avenues in predicting ictal events using information gathered from cardiovascular signals exclusively.

  18. Temporal structures in shell models

    DEFF Research Database (Denmark)

    Okkels, F.

    2001-01-01

    The intermittent dynamics of the turbulent Gledzer, Ohkitani, and Yamada shell-model is completely characterized by a single type of burstlike structure, which moves through the shells like a front. This temporal structure is described by the dynamics of the instantaneous configuration of the shell...

  19. Using dynamic Brownian bridge movement modelling to measure temporal patterns of habitat selection.

    Science.gov (United States)

    Byrne, Michael E; Clint McCoy, J; Hinton, Joseph W; Chamberlain, Michael J; Collier, Bret A

    2014-09-01

    Accurately describing animal space use is vital to understanding how wildlife use habitat. Improvements in GPS technology continue to facilitate collection of telemetry data at high spatial and temporal resolutions. Application of the recently introduced dynamic Brownian bridge movement model (dBBMM) to such data is promising as the method explicitly incorporates the behavioural heterogeneity of a movement path into the estimated utilization distribution (UD). Utilization distributions defining space use are normally estimated for time-scales ranging from weeks to months, obscuring much of the fine-scale information available from high-volume GPS data sets. By accounting for movement heterogeneity, the dBBMM provides a rigorous, behaviourally based estimate of space use between each set of relocations. Focusing on UDs generated between individual sets of locations allows us to quantify fine-scale circadian variation in habitat use. We used the dBBMM to estimate UDs bounding individual time steps for three terrestrial species with different life histories to illustrate how the method can be used to identify fine-scale variations in habitat use. We also demonstrate how dBBMMs can be used to characterize circadian patterns of habitat selection and link fine-scale patterns of habitat use to behaviour. We observed circadian patterns of habitat use that varied seasonally for a white-tailed deer (Odocoileus virginianus) and coyote (Canis latrans). We found seasonal patterns in selection by the white-tailed deer and were able to link use of conifer forests and agricultural fields to behavioural state of the coyote. Additionally, we were able to quantify the date in which a Rio Grande wild turkey (Meleagris gallopavo intermedia) initiated laying as well as when during the day, she was most likely to visit the nest site to deposit eggs. The ability to quantify circadian patterns of habitat use may have important implications for research and management of wildlife

  20. An Agent Model of Temporal Dynamics in Relapse and Recurrence in Depression

    NARCIS (Netherlands)

    Aziz, A.A.; Klein, M.C.A.; Treur, J.

    2009-01-01

    This paper presents a dynamic agent model of recurrences of a depression for an individual. Based on several personal characteristics and a representation of events (i.e. life events or daily hassles) the agent model can simulate whether a human agent that recovered from a depression will fall into

  1. A neural model of the temporal dynamics of figure-ground segregation in motion perception.

    Science.gov (United States)

    Raudies, Florian; Neumann, Heiko

    2010-03-01

    How does the visual system manage to segment a visual scene into surfaces and objects and manage to attend to a target object? Based on psychological and physiological investigations, it has been proposed that the perceptual organization and segmentation of a scene is achieved by the processing at different levels of the visual cortical hierarchy. According to this, motion onset detection, motion-defined shape segregation, and target selection are accomplished by processes which bind together simple features into fragments of increasingly complex configurations at different levels in the processing hierarchy. As an alternative to this hierarchical processing hypothesis, it has been proposed that the processing stages for feature detection and segregation are reflected in different temporal episodes in the response patterns of individual neurons. Such temporal epochs have been observed in the activation pattern of neurons as low as in area V1. Here, we present a neural network model of motion detection, figure-ground segregation and attentive selection which explains these response patterns in an unifying framework. Based on known principles of functional architecture of the visual cortex, we propose that initial motion and motion boundaries are detected at different and hierarchically organized stages in the dorsal pathway. Visual shapes that are defined by boundaries, which were generated from juxtaposed opponent motions, are represented at different stages in the ventral pathway. Model areas in the different pathways interact through feedforward and modulating feedback, while mutual interactions enable the communication between motion and form representations. Selective attention is devoted to shape representations by sending modulating feedback signals from higher levels (working memory) to intermediate levels to enhance their responses. Areas in the motion and form pathway are coupled through top-down feedback with V1 cells at the bottom end of the hierarchy

  2. Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations

    Science.gov (United States)

    Schall, Megan K.; Blazer, Vicki S.; Lorantas, Robert M.; Smith, Geoffrey; Mullican, John E.; Keplinger, Brandon J.; Wagner, Tyler

    2018-01-01

    Detecting temporal changes in fish abundance is an essential component of fisheries management. Because of the need to understand short‐term and nonlinear changes in fish abundance, traditional linear models may not provide adequate information for management decisions. This study highlights the utility of Bayesian dynamic linear models (DLMs) as a tool for quantifying temporal dynamics in fish abundance. To achieve this goal, we quantified temporal trends of Smallmouth Bass Micropterus dolomieu catch per effort (CPE) from rivers in the mid‐Atlantic states, and we calculated annual probabilities of decline from the posterior distributions of annual rates of change in CPE. We were interested in annual declines because of recent concerns about fish health in portions of the study area. In general, periods of decline were greatest within the Susquehanna River basin, Pennsylvania. The declines in CPE began in the late 1990s—prior to observations of fish health problems—and began to stabilize toward the end of the time series (2011). In contrast, many of the other rivers investigated did not have the same magnitude or duration of decline in CPE. Bayesian DLMs provide information about annual changes in abundance that can inform management and are easily communicated with managers and stakeholders.

  3. Spatio-temporal pattern formation, fractals, and chaos in conceptual ecological models as applied to coupled plankton-fish dynamics

    International Nuclear Information System (INIS)

    Medvinskii, Aleksandr B; Tikhonova, Irina A; Tikhonov, D A; Ivanitskii, Genrikh R; Petrovskii, Sergei V; Li, B.-L.; Venturino, E; Malchow, H

    2002-01-01

    The current turn-of-the-century period witnesses the intensive use of the bioproducts of the World Ocean while at the same time calling for precautions to preserve its ecological stability. This requires that biophysical processes in aquatic systems be comprehensively explored and new methods for monitoring their dynamics be developed. While aquatic and terrestrial ecosystems have much in common in terms of their mathematical description, there are essential differences between them. For example, the mobility of oceanic plankton is mainly controlled by diffusion processes, whereas terrestrial organisms naturally enough obey totally different laws. This paper is focused on the processes underlying the dynamics of spatially inhomogeneous plankton communities. We demonstrate that conceptual reaction-diffusion mathematical models are an appropriate tool for investigating both complex spatio-temporal plankton dynamics and the fractal properties of planktivorous fish school walks. (reviews of topical problems)

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

    Science.gov (United States)

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

    2016-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Patrick Fried

    2016-09-01

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

  6. An advanced analysis and modelling the air pollutant concentration temporal dynamics in atmosphere of the industrial cities: Odessa city

    Science.gov (United States)

    Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Ternovsky, V. B.; Serga, I. N.; Bykowszczenko, N.

    2017-10-01

    Results of analysis and modelling the air pollutant (dioxide of nitrogen) concentration temporal dynamics in atmosphere of the industrial city Odessa are presented for the first time and based on computing by nonlinear methods of the chaos and dynamical systems theories. A chaotic behaviour is discovered and investigated. To reconstruct the corresponding strange chaotic attractor, the time delay and embedding dimension are computed. The former is determined by the methods of autocorrelation function and average mutual information, and the latter is calculated by means of correlation dimension method and algorithm of false nearest neighbours. It is shown that low-dimensional chaos exists in the nitrogen dioxide concentration time series under investigation. Further, the Lyapunov’s exponents spectrum, Kaplan-Yorke dimension and Kolmogorov entropy are computed.

  7. Temporal dynamics of online petitions.

    Science.gov (United States)

    Böttcher, Lucas; Woolley-Meza, Olivia; Brockmann, Dirk

    2017-01-01

    Online petitions are an important avenue for direct political action, yet the dynamics that determine when a petition will be successful are not well understood. Here we analyze the temporal characteristics of online-petition signing behavior in order to identify systematic differences between popular petitions, which receive a high volume of signatures, and unpopular ones. We find that, in line with other temporal characterizations of human activity, the signing process is typically non-Poissonian and non-homogeneous in time. However, this process exhibits anomalously high memory for human activity, possibly indicating that synchronized external influence or contagion play and important role. More interestingly, we find clear differences in the characteristics of the inter-event time distributions depending on the total number of signatures that petitions receive, independently of the total duration of the petitions. Specifically, popular petitions that attract a large volume of signatures exhibit more variance in the distribution of inter-event times than unpopular petitions with only a few signatures, which could be considered an indication that the former are more bursty. However, petitions with large signature volume are less bursty according to measures that consider the time ordering of inter-event times. Our results, therefore, emphasize the importance of accounting for time ordering to characterize human activity.

  8. Internal cycling, not external loading, decides the nutrient limitation in eutrophic lake: A dynamic model with temporal Bayesian hierarchical inference.

    Science.gov (United States)

    Wu, Zhen; Liu, Yong; Liang, Zhongyao; Wu, Sifeng; Guo, Huaicheng

    2017-06-01

    Lake eutrophication is associated with excessive anthropogenic nutrients (mainly nitrogen (N) and phosphorus (P)) and unobserved internal nutrient cycling. Despite the advances in understanding the role of external loadings, the contribution of internal nutrient cycling is still an open question. A dynamic mass-balance model was developed to simulate and measure the contributions of internal cycling and external loading. It was based on the temporal Bayesian Hierarchical Framework (BHM), where we explored the seasonal patterns in the dynamics of nutrient cycling processes and the limitation of N and P on phytoplankton growth in hyper-eutrophic Lake Dianchi, China. The dynamic patterns of the five state variables (Chla, TP, ammonia, nitrate and organic N) were simulated based on the model. Five parameters (algae growth rate, sediment exchange rate of N and P, nitrification rate and denitrification rate) were estimated based on BHM. The model provided a good fit to observations. Our model results highlighted the role of internal cycling of N and P in Lake Dianchi. The internal cycling processes contributed more than external loading to the N and P changes in the water column. Further insights into the nutrient limitation analysis indicated that the sediment exchange of P determined the P limitation. Allowing for the contribution of denitrification to N removal, N was the more limiting nutrient in most of the time, however, P was the more important nutrient for eutrophication management. For Lake Dianchi, it would not be possible to recover solely by reducing the external watershed nutrient load; the mechanisms of internal cycling should also be considered as an approach to inhibit the release of sediments and to enhance denitrification. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Modelling estimation and analysis of dynamic processes from image sequences using temporal random closed sets and point processes with application to the cell exocytosis and endocytosis

    OpenAIRE

    Díaz Fernández, Ester

    2010-01-01

    In this thesis, new models and methodologies are introduced for the analysis of dynamic processes characterized by image sequences with spatial temporal overlapping. The spatial temporal overlapping exists in many natural phenomena and should be addressed properly in several Science disciplines such as Microscopy, Material Sciences, Biology, Geostatistics or Communication Networks. This work is related to the Point Process and Random Closed Set theories, within Stochastic Ge...

  10. GIS and dynamic phenomena modeling

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana

    2006-01-01

    Roč. 4, č. 4 (2006), s. 11-15 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : dynamic modelling * temporal analysis * dynamics evaluation * temporal space Subject RIV: BC - Control Systems Theory

  11. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  12. Computational cognitive modeling of the temporal dynamics of fatigue from sleep loss.

    Science.gov (United States)

    Walsh, Matthew M; Gunzelmann, Glenn; Van Dongen, Hans P A

    2017-12-01

    Computational models have become common tools in psychology. They provide quantitative instantiations of theories that seek to explain the functioning of the human mind. In this paper, we focus on identifying deep theoretical similarities between two very different models. Both models are concerned with how fatigue from sleep loss impacts cognitive processing. The first is based on the diffusion model and posits that fatigue decreases the drift rate of the diffusion process. The second is based on the Adaptive Control of Thought - Rational (ACT-R) cognitive architecture and posits that fatigue decreases the utility of candidate actions leading to microlapses in cognitive processing. A biomathematical model of fatigue is used to control drift rate in the first account and utility in the second. We investigated the predicted response time distributions of these two integrated computational cognitive models for performance on a psychomotor vigilance test under conditions of total sleep deprivation, simulated shift work, and sustained sleep restriction. The models generated equivalent predictions of response time distributions with excellent goodness-of-fit to the human data. More importantly, although the accounts involve different modeling approaches and levels of abstraction, they represent the effects of fatigue in a functionally equivalent way: in both, fatigue decreases the signal-to-noise ratio in decision processes and decreases response inhibition. This convergence suggests that sleep loss impairs psychomotor vigilance performance through degradation of the quality of cognitive processing, which provides a foundation for systematic investigation of the effects of sleep loss on other aspects of cognition. Our findings illustrate the value of treating different modeling formalisms as vehicles for discovery.

  13. Modeling the temporal dynamics of nonstructural carbohydrate pools in forest trees

    Energy Technology Data Exchange (ETDEWEB)

    Richardson, Andrew [Northern Arizona Univ., Flagstaff, AZ (United States); Harvard Univ., Cambridge, MA (United States)

    2017-11-09

    Trees store carbohydrates, in the form of sugars and starch, as reserves to be used to power both future growth as well as to support day-to-day metabolic functions. These reserves are particularly important in the context of how trees cope with disturbance and stress—for example, as related to pest outbreaks, wind or ice damage, and extreme climate events. In this project, we measured the size of carbon reserves in forest trees, and determined how quickly these reserves are used and replaced—i.e., their “turnover time”. Our work was conducted at Harvard Forest, a temperate deciduous forest in central Massachusetts. Through field sampling, laboratory-based chemical analyses, and allometric modeling, we scaled these measurements up to whole-tree NSC budgets. We used these data to test and improve computer simulation models of carbon flow through forest ecosystems. Our modeling focused on the mathematical representation of these stored carbon reserves, and we examined the sensitivity of model performance to different model structures. This project contributes to DOE’s goal to improve next-generation models of the earth system, and to understand the impacts of climate change on terrestrial ecosystems.

  14. Coalescent models for developmental biology and the spatio-temporal dynamics of growing tissues.

    Science.gov (United States)

    Smadbeck, Patrick; Stumpf, Michael P H

    2016-04-01

    Development is a process that needs to be tightly coordinated in both space and time. Cell tracking and lineage tracing have become important experimental techniques in developmental biology and allow us to map the fate of cells and their progeny. A generic feature of developing and homeostatic tissues that these analyses have revealed is that relatively few cells give rise to the bulk of the cells in a tissue; the lineages of most cells come to an end quickly. Computational and theoretical biologists/physicists have, in response, developed a range of modelling approaches, most notably agent-based modelling. These models seem to capture features observed in experiments, but can also become computationally expensive. Here, we develop complementary genealogical models of tissue development that trace the ancestry of cells in a tissue back to their most recent common ancestors. We show that with both bounded and unbounded growth simple, but universal scaling relationships allow us to connect coalescent theory with the fractal growth models extensively used in developmental biology. Using our genealogical perspective, it is possible to study bulk statistical properties of the processes that give rise to tissues of cells, without the need for large-scale simulations. © 2016 The Authors.

  15. A Computational Model of the Temporal Dynamics of Plasticity in Procedural Learning: Sensitivity to Feedback Timing

    Directory of Open Access Journals (Sweden)

    Vivian V. Valentin

    2014-07-01

    Full Text Available The evidence is now good that different memory systems mediate the learning of different types of category structures. In particular, declarative memory dominates rule-based (RB category learning and procedural memory dominates information-integration (II category learning. For example, several studies have reported that feedback timing is critical for II category learning, but not for RB category learning – results that have broad support within the memory systems literature. Specifically, II category learning has been shown to be best with feedback delays of 500ms compared to delays of 0 and 1000ms, and highly impaired with delays of 2.5 seconds or longer. In contrast, RB learning is unaffected by any feedback delay up to 10 seconds. We propose a neurobiologically detailed theory of procedural learning that is sensitive to different feedback delays. The theory assumes that procedural learning is mediated by plasticity at cortical-striatal synapses that are modified by dopamine-mediated reinforcement learning. The model captures the time-course of the biochemical events in the striatum that cause synaptic plasticity, and thereby accounts for the empirical effects of various feedback delays on II category learning.

  16. Dynamic spatio-temporal imaging of early reflow in a neonatal rat stroke model.

    Science.gov (United States)

    Leger, Pierre-Louis; Bonnin, Philippe; Lacombe, Pierre; Couture-Lepetit, Elisabeth; Fau, Sebastien; Renolleau, Sylvain; Gharib, Abdallah; Baud, Olivier; Charriaut-Marlangue, Christiane

    2013-01-01

    The aim of the study was to better understand blood-flow changes in large arteries and microvessels during the first 15 minutes of reflow in a P7 rat model of arterial occlusion. Blood-flow changes were monitored by using ultrasound imaging with sequential Doppler recordings in internal carotid arteries (ICAs) and basilar trunk. Relative cerebral blood flow (rCBF) changes were obtained by using laser speckle Doppler monitoring. Tissue perfusion was measured with [(14)C]-iodoantipyrine autoradiography. Cerebral energy metabolism was evaluated by mitochondrial oxygen consumption. Gradual increase in mean blood-flow velocities illustrated a gradual perfusion during early reflow in both ICAs. On ischemia, the middle cerebral artery (MCA) territory presented a residual perfusion, whereas the caudal territory remained normally perfused. On reflow, speckle images showed a caudorostral propagation of reperfusion through anastomotic connections, and a reduced perfusion in the MCA territory. Autoradiography highlighted the caudorostral gradient, and persistent perfusion in ventral and medial regions. These blood-flow changes were accompanied by mitochondrial respiration impairment in the ipsilateral cortex. Collectively, these data indicate the presence of a primary collateral pathway through the circle of Willis, providing an immediate diversion of blood flow toward ischemic regions, and secondary efficient cortical anastomoses in the immature rat brain.

  17. Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

    Science.gov (United States)

    Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

    2011-11-01

    In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

  18. A Hybrid Approach Combining the Multi-Temporal Scale Spatio-Temporal Network with the Continuous Triangular Model for Exploring Dynamic Interactions in Movement Data: A Case Study of Football

    Directory of Open Access Journals (Sweden)

    Pengdong Zhang

    2018-01-01

    Full Text Available Benefiting from recent advantages in location-aware technologies, movement data are becoming ubiquitous. Hence, numerous research topics with respect to movement data have been undertaken. Yet, the research of dynamic interactions in movement data is still in its infancy. In this paper, we propose a hybrid approach combining the multi-temporal scale spatio-temporal network (MTSSTN and the continuous triangular model (CTM for exploring dynamic interactions in movement data. The approach mainly includes four steps: first, the relative trajectory calculus (RTC is used to derive three types of interaction patterns; second, for each interaction pattern, a corresponding MTSSTN is generated; third, for each MTSSTN, the interaction intensity measures and three centrality measures (i.e., degree, betweenness and closeness are calculated; finally, the results are visualized at multiple temporal scales using the CTM and analyzed based on the generated CTM diagrams. Based on the proposed approach, three distinctive aims can be achieved for each interaction pattern at multiple temporal scales: (1 exploring the interaction intensities between any two individuals; (2 exploring the interaction intensities among multiple individuals, and (3 exploring the importance of each individual and identifying the most important individuals. The movement data obtained from a real football match are used as a case study to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach is useful in exploring dynamic interactions in football movement data and discovering insightful information.

  19. The temporal dynamics of speeded decision making

    NARCIS (Netherlands)

    Dutilh, G.

    2012-01-01

    This dissertation sheds light on the temporal dynamics of behavior in speeded decision making. Participants on reaction time (RT) tasks learn, get distracted, speed up, slow down, get confused, get bored, and eventually may start guessing. One can safely say that participants' behavior is dynamic.

  20. Temporal fidelity in dynamic social networks

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Sapiezynski, Piotr; Pentland, Alex ‘Sandy’

    2015-01-01

    of the network dynamics can be used to inform the process of measuring social networks. The details of measurement are of particular importance when considering dynamic processes where minute-to-minute details are important, because collection of physical proximity interactions with high temporal resolution...

  1. Model Checking Discounted Temporal Properties

    NARCIS (Netherlands)

    de Alfaro, Luca; Faella, Marco; Henzinger, Thomas A.; Majumdar, Rupak; Stoelinga, Mariëlle Ida Antoinette

    2005-01-01

    Temporal logic is two-valued: a property is either true or false. When applied to the analysis of stochastic systems, or systems with imprecise formal models, temporal logic is therefore fragile: even small changes in the model can lead to opposite truth values for a specification. We present a

  2. Model Checking Discounted Temporal Properties

    NARCIS (Netherlands)

    de Alfaro, Luca; Faella, Marco; Henzinger, Thomas A.; Majumdar, Rupak; Stoelinga, Mariëlle Ida Antoinette; Jensen, K; Podelski, A.

    2004-01-01

    Temporal logic is two-valued: a property is either true or false. When applied to the analysis of stochastic systems, or systems with imprecise formal models, temporal logic is therefore fragile: even small changes in the model can lead to opposite truth values for a specification. We present a

  3. Temporal information encoding in dynamic memristive devices

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Wen; Chen, Lin; Du, Chao; Lu, Wei D., E-mail: wluee@eecs.umich.edu [Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109 (United States)

    2015-11-09

    We show temporal and frequency information can be effectively encoded in memristive devices with inherent short-term dynamics. Ag/Ag{sub 2}S/Pd based memristive devices with low programming voltage (∼100 mV) were fabricated and tested. At weak programming conditions, the devices exhibit inherent decay due to spontaneous diffusion of the Ag atoms. When the devices were subjected to pulse train inputs emulating different spiking patterns, the switching probability distribution function diverges from the standard Poisson distribution and evolves according to the input pattern. The experimentally observed switching probability distributions and the associated cumulative probability functions can be well-explained using a model accounting for the short-term decay effects. Such devices offer an intriguing opportunity to directly encode neural signals for neural information storage and analysis.

  4. Memory for temporally dynamic scenes.

    Science.gov (United States)

    Ferguson, Ryan; Homa, Donald; Ellis, Derek

    2017-07-01

    Recognition memory was investigated for individual frames extracted from temporally continuous, visually rich film segments of 5-15 min. Participants viewed a short clip from a film in either a coherent or a jumbled order, followed by a recognition test of studied frames. Foils came either from an earlier or a later part of the film (Experiment 1) or from deleted segments selected from random cuts of varying duration (0.5 to 30 s) within the film itself (Experiment 2). When the foils came from an earlier or later part of the film (Experiment 1), recognition was excellent, with the hit rate far exceeding the false-alarm rate (.78 vs. 18). In Experiment 2, recognition was far worse, with the hit rate (.76) exceeding the false-alarm rate only for foils drawn from the longest cuts (15 and 30 s) and matching the false-alarm rate for the 5 s segments. When the foils were drawn from the briefest cuts (0.5 and 1.0 s), the false-alarm rate exceeded the hit rate. Unexpectedly, jumbling had no effect on recognition in either experiment. These results are consistent with the view that memory for complex visually temporal events is excellent, with the integrity unperturbed by disruption of the global structure of the visual stream. Disruption of memory was observed only when foils were drawn from embedded segments of duration less than 5 s, an outcome consistent with the view that memory at these shortest durations are consolidated with expectations drawn from the previous stream.

  5. Modeling the spatial-temporal dynamics of net primary production in Yangtze River Basin using IBIS model

    Science.gov (United States)

    Zhang, Z.; Jiang, H.; Liu, J.; Zhu, Q.; Wei, X.; Jiang, Z.; Zhou, G.; Zhang, X.; Han, J.

    2011-01-01

    The climate change has significantly affected the carbon cycling in Yangtze River Basin. To better understand the alternation pattern for the relationship between carbon cycling and climate change, the net primary production (NPP) were simulated in the study area from 1956 to 2006 by using the Integrated Biosphere Simulator (IBIS). The results showed that the average annual NPP per square meter was about 0.518 kg C in Yangtze River Basin. The high NPP levels were mainly distributed in the southeast area of Sichuan, and the highest value reached 1.05 kg C/m2. The NPP increased based on the simulated temporal trends. The spatiotemporal variability of the NPP in the vegetation types was obvious, and it was depended on the climate and soil condition. We found the drought climate was one of critical factor that impacts the alterations of the NPP in the area by the simulation. ?? 2011 IEEE.

  6. Dynamic perfusion patterns in temporal lobe epilepsy

    International Nuclear Information System (INIS)

    Dupont, Patrick; Paesschen, Wim van; Zaknun, John J.; Maes, Alex; Tepmongkol, Supatporn; Locharernkul, Chaichon; Vasquez, Silvia; Carpintiero, Silvina; Bal, C.S.; Dondi, Maurizio

    2009-01-01

    To investigate dynamic ictal perfusion changes during temporal lobe epilepsy (TLE). We investigated 37 patients with TLE by ictal and interictal SPECT. All ictal injections were performed within 60 s of seizure onset. Statistical parametric mapping was used to analyse brain perfusion changes and temporal relationships with injection time and seizure duration as covariates. The analysis revealed significant ictal hyperperfusion in the ipsilateral temporal lobe extending to subcortical regions. Hypoperfusion was observed in large extratemporal areas. There were also significant dynamic changes in several extratemporal regions: ipsilateral orbitofrontal and bilateral superior frontal gyri and the contralateral cerebellum and ipsilateral striatum. The study demonstrated early dynamic perfusion changes in extratemporal regions probably involved in both propagation of epileptic activity and initiation of inhibitory mechanisms. (orig.)

  7. Dynamic perfusion patterns in temporal lobe epilepsy

    Energy Technology Data Exchange (ETDEWEB)

    Dupont, Patrick; Paesschen, Wim van [KU Leuven/UZ Gasthuisberg, Nuclear Medicine, Medical Imaging Center and Neurology, Leuven (Belgium); Zaknun, John J. [International Atomic Energy Agency (IAEA), Nuclear Medicine Section, Division of Human Health, Wagramer Strasse 5, PO BOX 200, Vienna (Austria); University Hospital of Innsbruck, Department of Nuclear Medicine, Innsbruck (Austria); Maes, Alex [KU Leuven/UZ Gasthuisberg, Nuclear Medicine, Medical Imaging Center and Neurology, Leuven (Belgium); AZ Groeninge, Nuclear Medicine, Kortrijk (Belgium); Tepmongkol, Supatporn; Locharernkul, Chaichon [Chulalongkorn University, Nuclear Medicine and Neurology, Bangkok (Thailand); Vasquez, Silvia; Carpintiero, Silvina [Fleni Instituto de Investigaciones Neurologicas, Nuclear Medicine, Buenos Aires (Argentina); Bal, C.S. [All India Institute of Medical Sciences, Nuclear Medicine, New Delhi (India); Dondi, Maurizio [International Atomic Energy Agency (IAEA), Nuclear Medicine Section, Division of Human Health, Wagramer Strasse 5, PO BOX 200, Vienna (Austria); Ospedale Maggiore, Nuclear Medicine, Bologna (Italy)

    2009-05-15

    To investigate dynamic ictal perfusion changes during temporal lobe epilepsy (TLE). We investigated 37 patients with TLE by ictal and interictal SPECT. All ictal injections were performed within 60 s of seizure onset. Statistical parametric mapping was used to analyse brain perfusion changes and temporal relationships with injection time and seizure duration as covariates. The analysis revealed significant ictal hyperperfusion in the ipsilateral temporal lobe extending to subcortical regions. Hypoperfusion was observed in large extratemporal areas. There were also significant dynamic changes in several extratemporal regions: ipsilateral orbitofrontal and bilateral superior frontal gyri and the contralateral cerebellum and ipsilateral striatum. The study demonstrated early dynamic perfusion changes in extratemporal regions probably involved in both propagation of epileptic activity and initiation of inhibitory mechanisms. (orig.)

  8. Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

    Science.gov (United States)

    Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

    2016-01-01

    Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly

  9. Temporal dimension in cognitive models

    International Nuclear Information System (INIS)

    Decortis, F.; Cacciabue, P.C.

    1988-01-01

    Increased attention has been given to the role of humans in nuclear power plant safety, but one aspect seldom considered is the temporal dimension of human reasoning. Time is recognized as crucial in human reasoning and has been the subject of empirical studies where cognitive mechanisms and strategies to face the temporal dimension have been studied. The present study shows why temporal reasoning is essential in Human Reliability Analysis and how it could be introduced in a human model. Accounting for the time dimension in human behaviour is discussed first, with reference to proven field studies. Then, theoretical modelling of the temporal dimension in human reasoning and its relevance in simulation of cognitive activities of plant operator is discussed. Finally a Time Experience Model is presented

  10. Identify Dynamic Network Modules with Temporal and Spatial Constraints

    Energy Technology Data Exchange (ETDEWEB)

    Jin, R; McCallen, S; Liu, C; Almaas, E; Zhou, X J

    2007-09-24

    Despite the rapid accumulation of systems-level biological data, understanding the dynamic nature of cellular activity remains a difficult task. The reason is that most biological data are static, or only correspond to snapshots of cellular activity. In this study, we explicitly attempt to detangle the temporal complexity of biological networks by using compilations of time-series gene expression profiling data.We define a dynamic network module to be a set of proteins satisfying two conditions: (1) they form a connected component in the protein-protein interaction (PPI) network; and (2) their expression profiles form certain structures in the temporal domain. We develop the first efficient mining algorithm to discover dynamic modules in a temporal network, as well as frequently occurring dynamic modules across many temporal networks. Using yeast as a model system, we demonstrate that the majority of the identified dynamic modules are functionally homogeneous. Additionally, many of them provide insight into the sequential ordering of molecular events in cellular systems. We further demonstrate that identifying frequent dynamic network modules can significantly increase the signal to noise separation, despite the fact that most dynamic network modules are highly condition-specific. Finally, we note that the applicability of our algorithm is not limited to the study of PPI systems, instead it is generally applicable to the combination of any type of network and time-series data.

  11. Temporal languages for simulation and analysis of the dynamics within an organisation.

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

    2002-01-01

    In this paper a modelling approach to the dynamics within a multi- agent organisation is presented. A declarative, executable temporal modelling language for organisation dynamics is proposed as a basis for simulation. Moreover, to be able to specify and analyse dynamic properties, another temporal

  12. A million-plus neuron model of the hippocampal dentate gyrus: Dependency of spatio-temporal network dynamics on topography.

    Science.gov (United States)

    Hendrickson, Phillip J; Yu, Gene J; Song, Dong; Berger, Theodore W

    2015-01-01

    This paper describes a million-plus granule cell compartmental model of the rat hippocampal dentate gyrus, including excitatory, perforant path input from the entorhinal cortex, and feedforward and feedback inhibitory input from dentate interneurons. The model includes experimentally determined morphological and biophysical properties of granule cells, together with glutamatergic AMPA-like EPSP and GABAergic GABAA-like IPSP synaptic excitatory and inhibitory inputs, respectively. Each granule cell was composed of approximately 200 compartments having passive and active conductances distributed throughout the somatic and dendritic regions. Modeling excitatory input from the entorhinal cortex was guided by axonal transport studies documenting the topographical organization of projections from subregions of the medial and lateral entorhinal cortex, plus other important details of the distribution of glutamatergic inputs to the dentate gyrus. Results showed that when medial and lateral entorhinal cortical neurons maintained Poisson random firing, dentate granule cells expressed, throughout the million-cell network, a robust, non-random pattern of spiking best described as spatiotemporal "clustering". To identify the network property or properties responsible for generating such firing "clusters", we progressively eliminated from the model key mechanisms such as feedforward and feedback inhibition, intrinsic membrane properties underlying rhythmic burst firing, and/or topographical organization of entorhinal afferents. Findings conclusively identified topographical organization of inputs as the key element responsible for generating a spatio-temporal distribution of clustered firing. These results uncover a functional organization of perforant path afferents to the dentate gyrus not previously recognized: topography-dependent clusters of granule cell activity as "functional units" that organize the processing of entorhinal signals.

  13. Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

    Science.gov (United States)

    Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...

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

    Science.gov (United States)

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

    2014-05-01

    In the context of proactive disaster risk as well as immediate situational crisis management knowledge of locational social aspects in terms of spatio-temporal population distribution dynamics is considered among the most important factors for disaster impact minimization (Aubrecht et al., 2013a). This applies to both the pre-event stage for designing appropriate preparedness measures and to acute crisis situations when an event chain actually unfolds for efficient situation-aware response. The presented DynaPop population dynamics model is developed at the interface of those interlinked crisis stages and aims at providing basic input for social impact evaluation and decision support in crisis management. The model provides the starting point for assessing population exposure dynamics - thus here labeled as DynaPop-X - which can either be applied in a sense of illustrating the changing locations and numbers of affected people at different stages during an event or as ex-ante estimations of probable and maximum expected clusters of affected population (Aubrecht et al., 2013b; Freire & Aubrecht, 2012). DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation (Ahola et al., 2007; Bhaduri, 2008; Cockings et al., 2010). We will present ongoing developments particularly focusing on the implementation logic of the model using the emikat software tool, a data management system initially designed for inventorying and analysis of spatially resolved regional air pollutant emission scenarios. This study was performed in the framework of the EU CRISMA project. CRISMA is funded from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552. REFERENCES Ahola, T., Virrantaus, K., Krisp, J

  15. A Computational Model Based on Multi-Regional Calcium Imaging Represents the Spatio-Temporal Dynamics in a Caenorhabditis elegans Sensory Neuron.

    Directory of Open Access Journals (Sweden)

    Masahiro Kuramochi

    Full Text Available Due to the huge number of neuronal cells in the brain and their complex circuit formation, computer simulation of neuronal activity is indispensable to understanding whole brain dynamics. Recently, various computational models have been developed based on whole-brain calcium imaging data. However, these analyses monitor only the activity of neuronal cell bodies and treat the cells as point unit. This point-neuron model is inexpensive in computational costs, but the model is unrealistically simplistic at representing intact neural activities in the brain. Here, we describe a novel three-unit Ordinary Differential Equation (ODE model based on the neuronal responses derived from a Caenorhabditis elegans salt-sensing neuron. We recorded calcium responses in three regions of the ASER neuron using a simple downstep of NaCl concentration. Our simple ODE model generated from a single recording can adequately reproduce and predict the temporal responses of each part of the neuron to various types of NaCl concentration changes. Our strategy which combines a simple recording data and an ODE mathematical model may be extended to realistically understand whole brain dynamics by computational simulation.

  16. Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

    Science.gov (United States)

    Amirpour Haredasht, Sara; Polson, Dale; Main, Rodger; Lee, Kyuyoung; Holtkamp, Derald; Martínez-López, Beatriz

    2017-06-07

    Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight. The model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124). The result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

  17. Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks.

    Science.gov (United States)

    Onaga, Tomokatsu; Gleeson, James P; Masuda, Naoki

    2017-09-08

    Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

  18. Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks

    Science.gov (United States)

    Onaga, Tomokatsu; Gleeson, James P.; Masuda, Naoki

    2017-09-01

    Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

  19. The Models of Inter-temporal Consume

    Directory of Open Access Journals (Sweden)

    Nora Mihail

    2007-10-01

    Full Text Available The articol presents a category of consumption models which shows the manner how theexpenses of consume in an economy are related to the available income achieved by this economy and theinterest rate from the financial market. Since the income as well as the expenses of consume are realizedin time, such dynamic models of consume are also referred to as models of inter-temporal consume,emphasizing therefore the fact that the available income achieved at a certain moment may be used forconsume at a future moment, whereas the decision of consume taken at a current moment may consider theincome that is to be achieved in the future.

  20. Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh.

    Science.gov (United States)

    Rahman, M Tauhid Ur; Tabassum, Faheemah; Rasheduzzaman, Md; Saba, Humayra; Sarkar, Lina; Ferdous, Jannatul; Uddin, Syed Zia; Zahedul Islam, A Z M

    2017-10-17

    Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. "Bare lands" decreased by 21% being occupied by other land uses, especially by "shrimp farms." Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in "settlement" area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy

  1. Temporal dynamics of divided spatial attention.

    Science.gov (United States)

    Itthipuripat, Sirawaj; Garcia, Javier O; Serences, John T

    2013-05-01

    In naturalistic settings, observers often have to monitor multiple objects dispersed throughout the visual scene. However, the degree to which spatial attention can be divided across spatially noncontiguous objects has long been debated, particularly when those objects are in close proximity. Moreover, the temporal dynamics of divided attention are unclear: is the process of dividing spatial attention gradual and continuous, or does it onset in a discrete manner? To address these issues, we recorded steady-state visual evoked potentials (SSVEPs) as subjects covertly monitored two flickering targets while ignoring an intervening distractor that flickered at a different frequency. All three stimuli were clustered within either the lower left or the lower right quadrant, and our dependent measure was SSVEP power at the target and distractor frequencies measured over time. In two experiments, we observed a temporally discrete increase in power for target- vs. distractor-evoked SSVEPs extending from ∼350 to 150 ms prior to correct (but not incorrect) responses. The divergence in SSVEP power immediately prior to a correct response suggests that spatial attention can be divided across noncontiguous locations, even when the targets are closely spaced within a single quadrant. In addition, the division of spatial attention appears to be relatively discrete, as opposed to slow and continuous. Finally, the predictive relationship between SSVEP power and behavior demonstrates that these neurophysiological measures of divided attention are meaningfully related to cognitive function.

  2. Estimating spatio-temporal dynamics of size-structured populations

    DEFF Research Database (Denmark)

    Kristensen, Kasper; Thygesen, Uffe Høgsbro; Andersen, Ken Haste

    2014-01-01

    with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between size classes within each trawl haul due to clustering...... of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort...

  3. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    Science.gov (United States)

    Schöll, Eckehard

    2005-08-01

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

  4. Effective Connectivity between Ventral Occipito-Temporal and Ventral Inferior Frontal Cortex during Lexico-Semantic Processing. A Dynamic Causal Modeling Study

    Directory of Open Access Journals (Sweden)

    Marcela Perrone-Bertolotti

    2017-06-01

    Full Text Available It has been suggested that dorsal and ventral pathways support distinct aspects of language processing. Yet, the full extent of their involvement and their inter-regional connectivity in visual word recognition is still unknown. Studies suggest that they might reflect the dual-route model of reading, with the dorsal pathway more involved in grapho-phonological conversion during phonological tasks, and the ventral pathway performing lexico-semantic access during semantic tasks. Furthermore, this subdivision is also suggested at the level of the inferior frontal cortex, involving ventral and dorsal parts for lexico-semantic and phonological processing, respectively. In the present study, we assessed inter-regional brain connectivity and task-induced modulations of brain activity during a phoneme detection and semantic categorization tasks, using fMRI in healthy subject. We used a dynamic causal modeling approach to assess inter-regional connectivity and task demand modulation within the dorsal and ventral pathways, including the following network components: the ventral occipito-temporal cortex (vOTC; dorsal and ventral, the superior temporal gyrus (STG; dorsal, the dorsal inferior frontal gyrus (dIFG; dorsal, and the ventral IFG (vIFG; ventral. We report three distinct inter-regional interactions supporting orthographic information transfer from vOTC to other language regions (vOTC -> STG, vOTC -> vIFG and vOTC -> dIFG regardless of task demands. Moreover, we found that (a during semantic processing (direct ventral pathway the vOTC -> vIFG connection strength specifically increased and (b a lack of modulation of the vOTC -> dIFG connection strength by the task that could suggest a more general involvement of the dorsal pathway during visual word recognition. Results are discussed in terms of anatomo-functional connectivity of visual word recognition network.

  5. Interstitial diffusion and the relationship between compartment modelling and multi-scale spatial-temporal modelling of (18)F-FLT tumour uptake dynamics.

    Science.gov (United States)

    Liu, Dan; Chalkidou, Anastasia; Landau, David B; Marsden, Paul K; Fenwick, John D

    2014-09-07

    Tumour cell proliferation can be imaged via positron emission tomography of the radiotracer 3'-deoxy-3'-18F-fluorothymidine (18F-FLT). Conceptually, the number of proliferating cells might be expected to correlate more closely with the kinetics of 18F-FLT uptake than with uptake at a fixed time. Radiotracer uptake kinetics are standardly visualized using parametric maps of compartment model fits to time-activity-curves (TACs) of individual voxels. However the relationship between the underlying spatiotemporal accumulation of FLT and the kinetics described by compartment models has not yet been explored. In this work tumour tracer uptake is simulated using a mechanistic spatial-temporal model based on a convection-diffusion-reaction equation solved via the finite difference method. The model describes a chain of processes: the flow of FLT between the spatially heterogeneous tumour vasculature and interstitium; diffusion and convection of FLT within the interstitium; transport of FLT into cells; and intracellular phosphorylation. Using values of model parameters estimated from the biological literature, simulated FLT TACs are generated with shapes and magnitudes similar to those seen clinically. Results show that the kinetics of the spatial-temporal model can be recovered accurately by fitting a 3-tissue compartment model to FLT TACs simulated for those tumours or tumour sub-volumes that can be viewed as approximately closed, for which tracer diffusion throughout the interstitium makes only a small fractional change to the quantity of FLT they contain. For a single PET voxel of width 2.5-5 mm we show that this condition is roughly equivalent to requiring that the relative difference in tracer uptake between the voxel and its neighbours is much less than one.

  6. Semantics of Temporal Models with Multiple Temporal Dimensions

    DEFF Research Database (Denmark)

    Kraft, Peter; Sørensen, Jens Otto

    ending up with lexical data models. In particular we look upon the representations by sets of normalised tables, by sets of 1NF tables and by sets of N1NF/nested tables. At each translation step we focus on how the temporal semantic is consistently maintained. In this way we recognise the requirements...... for representation of temporal properties in different models and the correspondence between the models. The results rely on the assumptions that the temporal dimensions are interdependent and ordered. Thus for example the valid periods of existences of a property in a mini world are dependent on the transaction...... periods in which the corresponding recordings are valid. This is not the normal way of looking at temporal dimensions and we give arguments supporting our assumption....

  7. Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition.

    Science.gov (United States)

    van Niftrik, Christiaan Hendrik Bas; Piccirelli, Marco; Bozinov, Oliver; Pangalu, Athina; Fisher, Joseph A; Valavanis, Antonios; Luft, Andreas R; Weller, Michael; Regli, Luca; Fierstra, Jorn

    2017-09-01

    To improve quantitative cerebrovascular reactivity (CVR) measurements and CO 2 arrival times, we present an iterative analysis capable of decomposing different temporal components of the dynamic carbon dioxide- Blood Oxygen-Level Dependent (CO 2 -BOLD) relationship. Decomposition of the dynamic parameters included a redefinition of the voxel-wise CO 2 arrival time, and a separation from the vascular response to a stepwise increase in CO 2 (Delay to signal Plateau - DTP) and a decrease in CO 2 (Delay to signal Baseline -DTB). Twenty-five (normal) datasets, obtained from BOLD MRI combined with a standardized pseudo-square wave CO 2 change, were co-registered to generate reference atlases for the aforementioned dynamic processes to score the voxel-by-voxel deviation probability from normal range. This analysis is further illustrated in two subjects with unilateral carotid artery occlusion using these reference atlases. We have found that our redefined CO 2 arrival time resulted in the best data fit. Additionally, excluding both dynamic BOLD phases (DTP and DTB) resulted in a static CVR, that is maximal response, defined as CVR calculated only over a normocapnic and hypercapnic calibrated plateau. Decomposition and novel iterative modeling of different temporal components of the dynamic CO 2 -BOLD relationship improves quantitative CVR measurements.

  8. Spatial and temporal diversification of crops dynamics in soil erosion modelling. A case study in the arable land of the upper Enziwigger River, Switzerland.

    Science.gov (United States)

    Borrelli, Pasquale; Meusburger, Katrin; Panagos, Panos; Ballabio, Cristiano; Alewell, Christine

    2017-04-01

    Accelerated soil erosion by water is a widespread phenomenon that affects several Mediterranean and Alpine landscapes causing on-site and off-site environmental impacts. Recognized in the EU Thematic Strategy for Soil Protection as one of the major threats to European soils (COM(2006)231), accelerated soil erosion is a major concern in landscape management and conservation planning (UN SDG 2.4). Agriculture and associated land-use change is the primary cause of accelerated soil erosion. This, because the soil displacement by water erosion mainly occurs when bare-sloped soil surfaces are exposed to the effect of rainfall and overland flow. The Revised Universal Soil Loss Equation (RUSLE) and other RUSLE-based models (which account for more than 90% of current worldwide modelling applications) describe the effect of the vegetation in the so called cover and management factor (C). The C-factor is generally the most challenging modelling component to compute over large study sites. To run a GIS-based RUSLE modelling for a study site greater than few hectares, the use of a simplified approach to assess the C-factor is inevitably necessary. In most of the cases, the C-factor values are assigned to the different land-use classes according to i) the C-values proposed in the literature, and ii) through land-use classifications based on vegetation indices (VI). In previous national (Land Use Policy, 50, 408-421, 2016) and pan-European (Environmental Science & Policy, 54, 438-447, 2015) studies, we computed regional C-values through weighted average operations combining crop statistics with remote sensing and GIS modelling techniques. Here, we present the preliminary results of an object-oriented change detection approach that we are testing to acquire spatial as well temporal crops dynamics at field-scale level in complex agricultural systems.

  9. Characterization of the Temporal Trends in the Rate of Cattle Carcass Condemnations in the US and Dynamic Modeling of the Condemnation Reasons in California With a Seasonal Component

    Directory of Open Access Journals (Sweden)

    Sara Amirpour Haredasht

    2018-06-01

    Full Text Available Based on the 2016 National Cattlemen's Beef Association statistics, the cattle inventory in the US reached 93.5 million head, from which 30.5 million were commercial slaughter in 2016. California ranked fourth among all the US states that raise cattle and calves, with 5.15 million head and approximately 1.18 million slaughtered animals per year. Approximately 0.5% of cattle carcasses in the US are condemned each year, which has an important economic impact on cattle producers.In this study, we first described and compared the temporal trends of cattle carcass condemnations in all the US states from Jan-2005 to Dec-2014. Then, we focused on the condemnation reasons with a seasonal component in California and used dynamic harmonic regression (DHR models both to model (from Jan-2005 to Dec-2011 and predict (from Jan-2012 to Dec-2014 the carcass condemnations rate in different time horizons (3 to 12 months.Data consisted of daily reports of 35 condemnation reasons per cattle type reported in 684 federally inspected slaughterhouses in the US from Jan-2005 to Dec-2014 and the monthly slaughtered animals per cattle type per states. Almost 1.5 million carcasses were condemned in the US during the 10 year study period (Jan 2005-Dec 2014, and around 40% were associated with three condemnation reasons: malignant lymphoma, septicemia and pneumonia. In California, emaciation, eosinophilic myositis and malignant lymphoma were the only condemnation reasons presenting seasonality and, therefore, the only ones selected to be modeled using DHRs. The DHR models for Jan-2005 to Dec-2011 were able to correctly model the dynamics of the emaciation, malignant lymphoma and eosinophilic myositis condemnation rates with coefficient of determination (Rt2 of 0.98, 0.87 and 0.78, respectively. The DHR models for Jan-2012 to Dec-2014 were able to predict the rate of condemned carcasses 3 month ahead of time with mean relative prediction error of 33, 11, and 38

  10. Temporal dynamics of soil organic carbon after land-use change in the temperate zone – carbon response functions as a model approach

    DEFF Research Database (Denmark)

    Poeplau, Christopher; Don, Axel; Vesterdal, Lars

    2011-01-01

    Land-use change (LUC) is a major driving factor for the balance of soil organic carbon (SOC) stocks and the global carbon cycle. The temporal dynamic of SOC after LUC is especially important in temperate systems with a long reaction time. On the basis of 95 compiled studies covering 322 sites...... approach, the developed CRFs provide an easily applicable tool to estimate SOC stock changes after LUC to improve greenhouse gas reporting in the framework of UNFCCC....

  11. Developing Baltic cod recruitment models I : Resolving spatial and temporal dynamics of spawning stock and recruitment for cod, herring, and sprat

    DEFF Research Database (Denmark)

    Köster, Fritz; Möllmann, C.; Neuenfeldt, Stefan

    2001-01-01

    The Baltic Sea comprises a heterogeneous oceanographic environment influencing the spatial and temporal potential for reproductive success of cod (Gadus morhua) and sprat (Sprattus sprattus) in the different spawning basins. Hence, to quantify stock and recruitment dynamics, it is necessary......-disaggregated multispecies virtual population analyses (MSVPA) were performed for interacting species cod, herring (Clupea harengus), and sprat in the different subdivisions of the Central Baltic. The MSVPA runs revealed distinct spatial trends in population abundance, spawning biomass, recruitment, and predation...

  12. Spatio-temporal diffusion of dynamic PET images

    International Nuclear Information System (INIS)

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

    2011-01-01

    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.

  13. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

  14. Spatio-temporal dynamics of the tropical rain forest

    Energy Technology Data Exchange (ETDEWEB)

    Chave, J. [CEN Saclay, Gif-sur-Yvette (France). Service de Physique de l' Etat Condense

    2000-07-01

    Mechanisms which drive the dynamics of forest ecosystems are complex, from seedling establishment to pollination, and seed dispersal by animals, running water or wind. These processes are more complex when the ecosystem shelters a large number of species and of vegetative forms, as it is the case in the tropical rainforest. To take them into account, we must develop and use models. I present a review of the fundamental mechanisms for the of a natural forest dynamics - photosynthesis, tree growth, recruitment and mortality - as well as a description of the past and of the present of tropical rainforests. This information is used to develop a spatially-explicit and individual-based forest model. Simplified models are deduced from it, and they serve to address more specific issues, such as the resilience of the forest to climate disturbances, or savanna-forest dynamics. The last topic is related to the spatio-temporal description of tropical plant biodiversity. A detailed introduction to the problem is provided, and models accounting for the maintenance of diversity are compared. These models include non spatial as well a spatial approaches (branching anihilating random walks and voter model with mutation). (orig.)

  15. An investigation of temporal regularization techniques for dynamic PET reconstructions using temporal splines

    International Nuclear Information System (INIS)

    Verhaeghe, Jeroen; D'Asseler, Yves; Vandenberghe, Stefaan; Staelens, Steven; Lemahieu, Ignace

    2007-01-01

    The use of a temporal B-spline basis for the reconstruction of dynamic positron emission tomography data was investigated. Maximum likelihood (ML) reconstructions using an expectation maximization framework and maximum A-posteriori (MAP) reconstructions using the generalized expectation maximization framework were evaluated. Different parameters of the B-spline basis of such as order, number of basis functions and knot placing were investigated in a reconstruction task using simulated dynamic list-mode data. We found that a higher order basis reduced both the bias and variance. Using a higher number of basis functions in the modeling of the time activity curves (TACs) allowed the algorithm to model faster changes of the TACs, however, the TACs became noisier. We have compared ML, Gaussian postsmoothed ML and MAP reconstructions. The noise level in the ML reconstructions was controlled by varying the number of basis functions. The MAP algorithm penalized the integrated squared curvature of the reconstructed TAC. The postsmoothed ML was always outperformed in terms of bias and variance properties by the MAP and ML reconstructions. A simple adaptive knot placing strategy was also developed and evaluated. It is based on an arc length redistribution scheme during the reconstruction. The free knot reconstruction allowed a more accurate reconstruction while reducing the noise level especially for fast changing TACs such as blood input functions. Limiting the number of temporal basis functions combined with the adaptive knot placing strategy is in this case advantageous for regularization purposes when compared to the other regularization techniques

  16. Noise-induced temporal dynamics in Turing systems

    KAUST Repository

    Schumacher, Linus J.; Woolley, Thomas E.; Baker, Ruth E.

    2013-01-01

    We examine the ability of intrinsic noise to produce complex temporal dynamics in Turing pattern formation systems, with particular emphasis on the Schnakenberg kinetics. Using power spectral methods, we characterize the behavior of the system using

  17. A Temporal Ratio Model of Memory

    Science.gov (United States)

    Brown, Gordon D. A.; Neath, Ian; Chater, Nick

    2007-01-01

    A model of memory retrieval is described. The model embodies four main claims: (a) temporal memory--traces of items are represented in memory partly in terms of their temporal distance from the present; (b) scale-similarity--similar mechanisms govern retrieval from memory over many different timescales; (c) local distinctiveness--performance on a…

  18. Models, Entropy and Information of Temporal Social Networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Márton; Bianconi, Ginestra

    Temporal social networks are characterized by heterogeneous duration of contacts, which can either follow a power-law distribution, such as in face-to-face interactions, or a Weibull distribution, such as in mobile-phone communication. Here we model the dynamics of face-to-face interaction and mobile phone communication by a reinforcement dynamics, which explains the data observed in these different types of social interactions. We quantify the information encoded in the dynamics of these networks by the entropy of temporal networks. Finally, we show evidence that human dynamics is able to modulate the information present in social network dynamics when it follows circadian rhythms and when it is interfacing with a new technology such as the mobile-phone communication technology.

  19. UTP and Temporal Logic Model Checking

    Science.gov (United States)

    Anderson, Hugh; Ciobanu, Gabriel; Freitas, Leo

    In this paper we give an additional perspective to the formal verification of programs through temporal logic model checking, which uses Hoare and He Unifying Theories of Programming (UTP). Our perspective emphasizes the use of UTP designs, an alphabetised relational calculus expressed as a pre/post condition pair of relations, to verify state or temporal assertions about programs. The temporal model checking relation is derived from a satisfaction relation between the model and its properties. The contribution of this paper is that it shows a UTP perspective to temporal logic model checking. The approach includes the notion of efficiency found in traditional model checkers, which reduced a state explosion problem through the use of efficient data structures

  20. Dynamic CRM occupancy reflects a temporal map of developmental progression.

    Science.gov (United States)

    Wilczyński, Bartek; Furlong, Eileen E M

    2010-06-22

    Development is driven by tightly coordinated spatio-temporal patterns of gene expression, which are initiated through the action of transcription factors (TFs) binding to cis-regulatory modules (CRMs). Although many studies have investigated how spatial patterns arise, precise temporal control of gene expression is less well understood. Here, we show that dynamic changes in the timing of CRM occupancy is a prevalent feature common to all TFs examined in a developmental ChIP time course to date. CRMs exhibit complex binding patterns that cannot be explained by the sequence motifs or expression of the TFs themselves. The temporal changes in TF binding are highly correlated with dynamic patterns of target gene expression, which in turn reflect transitions in cellular function during different stages of development. Thus, it is not only the timing of a TF's expression, but also its temporal occupancy in refined time windows, which determines temporal gene expression. Systematic measurement of dynamic CRM occupancy may therefore serve as a powerful method to decode dynamic changes in gene expression driving developmental progression.

  1. Temporal dynamics of Bose-condensed gases

    Energy Technology Data Exchange (ETDEWEB)

    Trujillo Martinez, Mauricio

    2014-03-19

    We perform a detailed quantum dynamical study of non-equilibrium trapped, interacting Bose-condensed gases. We investigate Josephson oscillations between interacting Bose-Einstein condensates confined in a finite size double-well trap and the non-trivial time evolution of a coherent state placed at the center of a two dimensional optical lattice. For the Josephson oscillations three time scales appear. We find that Josephson junction can sustain multiple undamped oscillations up to a characteristic time scale τ{sub c} without exciting atoms out of the condensates. Beyond the characteristic time scale τ{sub c} the dynamics of the junction are governed by fast, non-condensed particles assisted Josephson tunnelling as well as the collisions between non-condensed particles. In the non-condensed particles dominated regime we observe strong damping of the oscillations due to inelastic collisions, equilibrating the system leading to an effective loss of details of the initial conditions. In addition, we predict that an initially self-trapped BEC state will be destroyed by these fast dynamics. The time evolution of a coherent state released at the center of a two dimensional optical lattice shows a ballistic expansion with a decreasing expansion velocity for increasing two-body interactions strength and particle number. Additionally, we predict that if the two-body interactions strength exceeds a certain value, a forerunner splits up from the expanding coherent state. We also observe that this system, which is prepared far from equilibrium, can evolve to a quasistationary non-equilibrium state.

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

    Science.gov (United States)

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

    2016-04-01

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

  3. The temporal dynamics of the stress response

    NARCIS (Netherlands)

    Koolhaas, J.M.; Meerlo, P; de Boer, S.F.; Strubbe, J.H.; Bohus, B.G J

    1997-01-01

    This paper summarises the available evidence that failure of defense mechanisms in (semi)-natural social groups of animals may lead to serious forms of stress pathology. Hence the study of social stress may provide animal models with a high face validity. However, most of the animal models of human

  4. Forecasting Temporal Dynamics of Cutaneous Leishmaniasis in Northeast Brazil

    Science.gov (United States)

    Lewnard, Joseph A.; Jirmanus, Lara; Júnior, Nivison Nery; Machado, Paulo R.; Glesby, Marshall J.; Ko, Albert I.; Carvalho, Edgar M.; Schriefer, Albert; Weinberger, Daniel M.

    2014-01-01

    Introduction Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions. Methodology/Principal Findings We fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation. Significance These outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets. PMID:25356734

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

    Science.gov (United States)

    Böhringer, Klaus; Hess, Ortwin

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

  6. 3D City Models with Different Temporal Characteristica

    DEFF Research Database (Denmark)

    Bodum, Lars

    2005-01-01

    traditional static city models and those models that are built for realtime applications. The difference between the city models applies both to the spatial modelling and also when using the phenomenon time in the models. If the city models are used in visualizations without any variation in time or when......-built dynamic or a model suitable for visualization in realtime, it is required that modelling is done with level-of-detail and simplification of both the aesthetics and the geometry. If a temporal characteristic is combined with a visual characteristic, the situation can easily be seen as a t/v matrix where t...... is the temporal characteristic or representation and v is the visual characteristic or representation....

  7. Effects of dynamic-range compression on temporal acuity

    DEFF Research Database (Denmark)

    Wiinberg, Alan; Jepsen, Morten Løve; Epp, Bastian

    2016-01-01

    Some of the challenges that hearing-aid listeners experience with speech perception in complex acoustic environments may originate from limitations in the temporal processing of sounds. To systematically investigate the influence of hearing impairment and hearing-aid signal processing on temporal...... processing, temporal modulation transfer functions (TMTFs) and “supra-threshold” modulation-depth discrimination (MDD) thresholds were obtained in normal-hearing (NH) and hearing-impaired (HI) listeners with and without wide-dynamic range compression (WDRC). The TMTFs were obtained using tonal carriers of 1...... with the physical compression of the modulation depth due to the WDRC. Indications of reduced temporal resolution in the HI listeners were observed in the TMTF patterns for the 5 kHz carrier. Significantly higher MDD thresholds were found for the HI group relative to the NH group. No relationship was found between...

  8. Temporal nonlinear beam dynamics in infiltrated photonic crystal fibers

    DEFF Research Database (Denmark)

    Bennet, Francis; Rosberg, Christian Romer; Neshev, Dragomir N.

    Liquid-infiltrated photonic crystal fibers (PCFs) offer a new way of studying light propagation in periodic and discrete systems. A wide range of available fiber structures combined with the ease of infiltration opens up a range of novel experimental opportunities for optical detection and bio...... the evolution of the fiber output beam in the few micro or milliseconds after the beam is turned on. The characterization of the temporal behavior of the thermal nonlinear response provides important information about the nonlocality associated with heat diffusion inside the fiber, thus enabling studies of long...... and technological potential of liquid-infiltrated PCFs it is important to understand the temporal dynamics of nonlinear beam propagation in such structures. In this work we consider thermally induced spatial nonlinear effects in infiltrated photonic crystal fibers. We experimentally study the temporal dynamics...

  9. The Temporal Dynamics Model of Emotional Memory Processing: A Synthesis on the Neurobiological Basis of Stress-Induced Amnesia, Flashbulb and Traumatic Memories, and the Yerkes-Dodson Law

    OpenAIRE

    Diamond, David M.; Campbell, Adam M.; Park, Collin R.; Halonen, Joshua; Zoladz, Phillip R.

    2007-01-01

    We have reviewed research on the effects of stress on LTP in the hippocampus, amygdala and prefrontal cortex (PFC) and present new findings which provide insight into how the attention and memory-related functions of these structures are influenced by strong emotionality. We have incorporated the stress-LTP findings into our “temporal dynamics†model, which provides a framework for understanding the neurobiological basis of flashbulb and traumatic memories, as well as stress-induced ...

  10. Spatial and temporal dynamics of land use pattern response to ...

    African Journals Online (AJOL)

    Urban settlements account for only two percent of the Earth's land surface. However, over half of the world's population resides in cities (United Nations, 2001). The quantitative evidences presented here showed that there were drastic changes in the temporal and spatial dynamics of land use/land cover. As an overall ...

  11. Temporal dynamics of top predators interactions in the Barents Sea.

    Science.gov (United States)

    Durant, Joël M; Skern-Mauritzen, Mette; Krasnov, Yuri V; Nikolaeva, Natalia G; Lindstrøm, Ulf; Dolgov, Andrey

    2014-01-01

    The Barents Sea system is often depicted as a simple food web in terms of number of dominant feeding links. The most conspicuous feeding link is between the Northeast Arctic cod Gadus morhua, the world's largest cod stock which is presently at a historical high level, and capelin Mallotus villosus. The system also holds diverse seabird and marine mammal communities. Previous diet studies may suggest that these top predators (cod, bird and sea mammals) compete for food particularly with respect to pelagic fish such as capelin and juvenile herring (Clupea harengus), and krill. In this paper we explored the diet of some Barents Sea top predators (cod, Black-legged kittiwake Rissa tridactyla, Common guillemot Uria aalge, and Minke whale Balaenoptera acutorostrata). We developed a GAM modelling approach to analyse the temporal variation diet composition within and between predators, to explore intra- and inter-specific interactions. The GAM models demonstrated that the seabird diet is temperature dependent while the diet of Minke whale and cod is prey dependent; Minke whale and cod diets depend on the abundance of herring and capelin, respectively. There was significant diet overlap between cod and Minke whale, and between kittiwake and guillemot. In general, the diet overlap between predators increased with changes in herring and krill abundances. The diet overlap models developed in this study may help to identify inter-specific interactions and their dynamics that potentially affect the stocks targeted by fisheries.

  12. Modelling spatial and temporal dynamics of gross primary production in the Sahel from earth-observation-based photosynthetic capacity and quantum efficiency

    DEFF Research Database (Denmark)

    Tagesson, Håkan Torbern; Ardoe, Jonas; Cappelaere, Bernard

    2017-01-01

    based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled Fopt and α for GPP modelling purposes...... impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001-2014 was 736 ± 39 gCm-2yr-1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, Fopt and α incorporating EO-based Fopt and α in dynamic global vegetation models could improve estimates...

  13. Temporal dynamics of the Saccharopolyspora erythraea phosphoproteome.

    Science.gov (United States)

    Licona-Cassani, Cuauhtemoc; Lim, Sooa; Marcellin, Esteban; Nielsen, Lars K

    2014-05-01

    Actinomycetes undergo a dramatic reorganization of metabolic and cellular machinery during a brief period of growth arrest ("metabolic switch") preceding mycelia differentiation and the onset of secondary metabolite biosynthesis. This study explores the role of phosphorylation in coordinating the metabolic switch in the industrial actinomycete Saccharopolyspora erythraea. A total of 109 phosphopeptides from 88 proteins were detected across a 150-h fermentation using open-profile two-dimensional LC-MS proteomics and TiO(2) enrichment. Quantitative analysis of the phosphopeptides and their unphosphorylated cognates was possible for 20 pairs that also displayed constant total protein expression. Enzymes from central carbon metabolism such as putative acetyl-coenzyme A carboxylase, isocitrate lyase, and 2-oxoglutarate dehydrogenase changed dramatically in the degree of phosphorylation during the stationary phase, suggesting metabolic rearrangement for the reutilization of substrates and the production of polyketide precursors. In addition, an enzyme involved in cellular response to environmental stress, trypsin-like serine protease (SACE_6340/NC_009142_6216), decreased in phosphorylation during the growth arrest stage. More important, enzymes related to the regulation of protein synthesis underwent rapid phosphorylation changes during this stage. Whereas the degree of phosphorylation of ribonuclease Rne/Rng (SACE_1406/NC_009142_1388) increased during the metabolic switch, that of two ribosomal proteins, S6 (SACE_7351/NC_009142_7233) and S32 (SACE_6101/NC_009142_5981), dramatically decreased during this stage of the fermentation, supporting the hypothesis that ribosome subpopulations differentially regulate translation before and after the metabolic switch. Overall, we show the great potential of phosphoproteomic studies to explain microbial physiology and specifically provide evidence of dynamic protein phosphorylation events across the developmental cycle of

  14. Temporal Dynamics of the Saccharopolyspora erythraea Phosphoproteome*

    Science.gov (United States)

    Licona-Cassani, Cuauhtemoc; Lim, SooA; Marcellin, Esteban; Nielsen, Lars K.

    2014-01-01

    Actinomycetes undergo a dramatic reorganization of metabolic and cellular machinery during a brief period of growth arrest (“metabolic switch”) preceding mycelia differentiation and the onset of secondary metabolite biosynthesis. This study explores the role of phosphorylation in coordinating the metabolic switch in the industrial actinomycete Saccharopolyspora erythraea. A total of 109 phosphopeptides from 88 proteins were detected across a 150-h fermentation using open-profile two-dimensional LC-MS proteomics and TiO2 enrichment. Quantitative analysis of the phosphopeptides and their unphosphorylated cognates was possible for 20 pairs that also displayed constant total protein expression. Enzymes from central carbon metabolism such as putative acetyl-coenzyme A carboxylase, isocitrate lyase, and 2-oxoglutarate dehydrogenase changed dramatically in the degree of phosphorylation during the stationary phase, suggesting metabolic rearrangement for the reutilization of substrates and the production of polyketide precursors. In addition, an enzyme involved in cellular response to environmental stress, trypsin-like serine protease (SACE_6340/NC_009142_6216), decreased in phosphorylation during the growth arrest stage. More important, enzymes related to the regulation of protein synthesis underwent rapid phosphorylation changes during this stage. Whereas the degree of phosphorylation of ribonuclease Rne/Rng (SACE_1406/NC_009142_1388) increased during the metabolic switch, that of two ribosomal proteins, S6 (SACE_7351/NC_009142_7233) and S32 (SACE_6101/NC_009142_5981), dramatically decreased during this stage of the fermentation, supporting the hypothesis that ribosome subpopulations differentially regulate translation before and after the metabolic switch. Overall, we show the great potential of phosphoproteomic studies to explain microbial physiology and specifically provide evidence of dynamic protein phosphorylation events across the developmental cycle of

  15. Temporal dynamics of hippocampal neurogenesis in chronic neurodegeneration

    Science.gov (United States)

    Suzzi, Stefano; Vargas-Caballero, Mariana; Fransen, Nina L.; Al-Malki, Hussain; Cebrian-Silla, Arantxa; Garcia-Verdugo, Jose Manuel; Riecken, Kristoffer; Fehse, Boris; Perry, V. Hugh

    2014-01-01

    The study of neurogenesis during chronic neurodegeneration is crucial in order to understand the intrinsic repair mechanisms of the brain, and key to designing therapeutic strategies. In this study, using an experimental model of progressive chronic neurodegeneration, murine prion disease, we define the temporal dynamics of the generation, maturation and integration of new neurons in the hippocampal dentate gyrus, using dual pulse-chase, multicolour γ-retroviral tracing, transmission electron microscopy and patch-clamp. We found increased neurogenesis during the progression of prion disease, which partially counteracts the effects of chronic neurodegeneration, as evidenced by blocking neurogenesis with cytosine arabinoside, and helps to preserve the hippocampal function. Evidence obtained from human post-mortem samples, of both variant Creutzfeldt-Jakob disease and Alzheimer’s disease patients, also suggests increased neurogenic activity. These results open a new avenue into the exploration of the effects and regulation of neurogenesis during chronic neurodegeneration, and offer a new model to reproduce the changes observed in human neurodegenerative diseases. PMID:24941947

  16. Temporal dynamics of visual working memory.

    Science.gov (United States)

    Sobczak-Edmans, M; Ng, T H B; Chan, Y C; Chew, E; Chuang, K H; Chen, S H A

    2016-01-01

    The involvement of the human cerebellum in working memory has been well established in the last decade. However, the cerebro-cerebellar network for visual working memory is not as well defined. Our previous fMRI study showed superior and inferior cerebellar activations during a block design visual working memory task, but specific cerebellar contributions to cognitive processes in encoding, maintenance and retrieval have not yet been established. The current study examined cerebellar contributions to each of the components of visual working memory and presence of cerebellar hemispheric laterality was investigated. 40 young adults performed a Sternberg visual working memory task during fMRI scanning using a parametric paradigm. The contrast between high and low memory load during each phase was examined. We found that the most prominent activation was observed in vermal lobule VIIIb and bilateral lobule VI during encoding. Using a quantitative laterality index, we found that left-lateralized activation of lobule VIIIa was present in the encoding phase. In the maintenance phase, there was bilateral lobule VI and right-lateralized lobule VIIb activity. Changes in activation in right lobule VIIIa were present during the retrieval phase. The current results provide evidence that superior and inferior cerebellum contributes to visual working memory, with a tendency for left-lateralized activations in the inferior cerebellum during encoding and right-lateralized lobule VIIb activations during maintenance. The results of the study are in agreement with Baddeley's multi-component working memory model, but also suggest that stored visual representations are additionally supported by maintenance mechanisms that may employ verbal coding. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Temporal rainfall estimation using input data reduction and model inversion

    Science.gov (United States)

    Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

    2016-12-01

    Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a

  18. Spatio-temporal modeling for residential burglary

    NARCIS (Netherlands)

    Mahfoud, M.; Bhulai, Sandjai; van der Mei, R.D.; Bhulai, Sandjai; Kardaras, Dimitris

    2017-01-01

    Spatio-temporal modeling is widely recognized as a promising means for predicting crime patterns. Despite their enormous potential, the available methods are still in their infancy. A lot of research focuses on crime hotspot detection and geographic crime clusters, while a systematic approach to

  19. A temporal interpolation approach for dynamic reconstruction in perfusion CT

    International Nuclear Information System (INIS)

    Montes, Pau; Lauritsch, Guenter

    2007-01-01

    This article presents a dynamic CT reconstruction algorithm for objects with time dependent attenuation coefficient. Projection data acquired over several rotations are interpreted as samples of a continuous signal. Based on this idea, a temporal interpolation approach is proposed which provides the maximum temporal resolution for a given rotational speed of the CT scanner. Interpolation is performed using polynomial splines. The algorithm can be adapted to slow signals, reducing the amount of data acquired and the computational cost. A theoretical analysis of the approximations made by the algorithm is provided. In simulation studies, the temporal interpolation approach is compared with three other dynamic reconstruction algorithms based on linear regression, linear interpolation, and generalized Parker weighting. The presented algorithm exhibits the highest temporal resolution for a given sampling interval. Hence, our approach needs less input data to achieve a certain quality in the reconstruction than the other algorithms discussed or, equivalently, less x-ray exposure and computational complexity. The proposed algorithm additionally allows the possibility of using slow rotating scanners for perfusion imaging purposes

  20. Temporal dynamics of ikaite in experimental sea ice

    Science.gov (United States)

    Rysgaard, S.; Wang, F.; Galley, R. J.; Grimm, R.; Notz, D.; Lemes, M.; Geilfus, N.-X.; Chaulk, A.; Hare, A. A.; Crabeck, O.; Else, B. G. T.; Campbell, K.; Sørensen, L. L.; Sievers, J.; Papakyriakou, T.

    2014-08-01

    Ikaite (CaCO3 · 6H2O) is a metastable phase of calcium carbonate that normally forms in a cold environment and/or under high pressure. Recently, ikaite crystals have been found in sea ice, and it has been suggested that their precipitation may play an important role in air-sea CO2 exchange in ice-covered seas. Little is known, however, of the spatial and temporal dynamics of ikaite in sea ice. Here we present evidence for highly dynamic ikaite precipitation and dissolution in sea ice grown at an outdoor pool of the Sea-ice Environmental Research Facility (SERF) in Manitoba, Canada. During the experiment, ikaite precipitated in sea ice when temperatures were below -4 °C, creating three distinct zones of ikaite concentrations: (1) a millimeter-to-centimeter-thin surface layer containing frost flowers and brine skim with bulk ikaite concentrations of >2000 μmol kg-1, (2) an internal layer with ikaite concentrations of 200-400 μmol kg-1, and (3) a bottom layer with ikaite concentrations of ikaite crystals to dissolve. Manual removal of the snow cover allowed the sea ice to cool and brine salinities to increase, resulting in rapid ikaite precipitation. The observed ikaite concentrations were on the same order of magnitude as modeled by FREZCHEM, which further supports the notion that ikaite concentration in sea ice increases with decreasing temperature. Thus, varying snow conditions may play a key role in ikaite precipitation and dissolution in sea ice. This could have a major implication for CO2 exchange with the atmosphere and ocean that has not been accounted for previously.

  1. Temporal dynamics of ikaite in experimental sea ice

    OpenAIRE

    S. Rysgaard; F. Wang; R. J. Galley; R. Grimm; D. Notz; M. Lemes; N.-X. Geilfus; A. Chaulk; A. A. Hare; O. Crabeck; B. G. T. Else; K. Campbell; L. L. Sørensen; J. Sievers; T. Papakyriakou

    2014-01-01

    Ikaite (CaCO3 · 6H2O) is a metastable phase of calcium carbonate that normally forms in a cold environment and/or under high pressure. Recently, ikaite crystals have been found in sea ice, and it has been suggested that their precipitation may play an important role in air–sea CO2 exchange in ice-covered seas. Little is known, however, of the spatial and temporal dynamics of ikaite in sea ice. Here we present evidence for highly dynamic ikaite precipitation and dissolution i...

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

    International Nuclear Information System (INIS)

    Wikle, C.K.

    1996-01-01

    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

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

    Science.gov (United States)

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

    2016-08-15

    This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Simulating temporal variations of nitrogen losses in river networks with a dynamic transport model unravels the coupled effects of hydrological and biogeochemical processes

    Energy Technology Data Exchange (ETDEWEB)

    Mulholland, Patrick J [ORNL; Alexander, Richard [U.S. Geological Survey; Bohlke, John [U.S. Geological Survey; Boyer, Elizabeth [Pennsylvania State University; Harvey, Judson [U.S. Geological Survey; Seitzinger, Sybil [Rutgers University; Tobias, Craig [University of North Carolina, Wilmington; Tonitto, Christina [Cornell University; Wollheim, Wilfred [University of New Hampshire

    2009-01-01

    The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly

  5. Representation of spatial and temporal variability of daily wind speed and of intense wind events over the Mediterranean Sea using dynamical downscaling: impact of the regional climate model configuration

    Directory of Open Access Journals (Sweden)

    M. Herrmann

    2011-07-01

    Full Text Available Atmospheric datasets coming from long term reanalyzes of low spatial resolution are used for different purposes. Wind over the sea is, for example, a major ingredient of oceanic simulations. However, the shortcomings of those datasets prevent them from being used without an adequate corrective preliminary treatment. Using a regional climate model (RCM to perform a dynamical downscaling of those large scale reanalyzes is one of the methods used in order to produce fields that realistically reproduce atmospheric chronology and where those shortcomings are corrected. Here we assess the influence of the configuration of the RCM used in this framework on the representation of wind speed spatial and temporal variability and intense wind events on a daily timescale. Our RCM is ALADIN-Climate, the reanalysis is ERA-40, and the studied area is the Mediterranean Sea.

    First, the dynamical downscaling significantly reduces the underestimation of daily wind speed, in average by 9 % over the whole Mediterranean. This underestimation has been corrected both globally and locally, and for the whole wind speed spectrum. The correction is the strongest for periods and regions of strong winds. The representation of spatial variability has also been significantly improved. On the other hand, the temporal correlation between the downscaled field and the observations decreases all the more that one moves eastwards, i.e. further from the atmospheric flux entry. Nonetheless, it remains ~0.7, the downscaled dataset reproduces therefore satisfactorily the real chronology.

    Second, the influence of the choice of the RCM configuration has an influence one order of magnitude smaller than the improvement induced by the initial downscaling. The use of spectral nudging or of a smaller domain helps to improve the realism of the temporal chronology. Increasing the resolution very locally (both spatially and temporally improves the representation of spatial

  6. Spatio-temporal patterns in simple models of marine systems

    Science.gov (United States)

    Feudel, U.; Baurmann, M.; Gross, T.

    2009-04-01

    Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

  7. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard; Ahuja, Narendra

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal

  8. Human Plague Risk: Spatial-Temporal Models

    Science.gov (United States)

    Pinzon, Jorge E.

    2010-01-01

    This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

  9. A Temporal Domain Decomposition Algorithmic Scheme for Large-Scale Dynamic Traffic Assignment

    Directory of Open Access Journals (Sweden)

    Eric J. Nava

    2012-03-01

    This paper presents a temporal decomposition scheme for large spatial- and temporal-scale dynamic traffic assignment, in which the entire analysis period is divided into Epochs. Vehicle assignment is performed sequentially in each Epoch, thus improving the model scalability and confining the peak run-time memory requirement regardless of the total analysis period. A proposed self-turning scheme adaptively searches for the run-time-optimal Epoch setting during iterations regardless of the characteristics of the modeled network. Extensive numerical experiments confirm the promising performance of the proposed algorithmic schemes.

  10. Learning large-scale dynamic discrete choice models of spatio-temporal preferences with application to migratory pastoralism in East Africa

    Science.gov (United States)

    Understanding spatio-temporal resource preferences is paramount in the design of policies for sustainable development. Unfortunately, resource preferences are often unknown to policy-makers and have to be inferred from data. In this paper we consider the problem of inferring agents’ preferences fro...

  11. Ananke: temporal clustering reveals ecological dynamics of microbial communities

    Directory of Open Access Journals (Sweden)

    Michael W. Hall

    2017-09-01

    Full Text Available Taxonomic markers such as the 16S ribosomal RNA gene are widely used in microbial community analysis. A common first step in marker-gene analysis is grouping genes into clusters to reduce data sets to a more manageable size and potentially mitigate the effects of sequencing error. Instead of clustering based on sequence identity, marker-gene data sets collected over time can be clustered based on temporal correlation to reveal ecologically meaningful associations. We present Ananke, a free and open-source algorithm and software package that complements existing sequence-identity-based clustering approaches by clustering marker-gene data based on time-series profiles and provides interactive visualization of clusters, including highlighting of internal OTU inconsistencies. Ananke is able to cluster distinct temporal patterns from simulations of multiple ecological patterns, such as periodic seasonal dynamics and organism appearances/disappearances. We apply our algorithm to two longitudinal marker gene data sets: faecal communities from the human gut of an individual sampled over one year, and communities from a freshwater lake sampled over eleven years. Within the gut, the segregation of the bacterial community around a food-poisoning event was immediately clear. In the freshwater lake, we found that high sequence identity between marker genes does not guarantee similar temporal dynamics, and Ananke time-series clusters revealed patterns obscured by clustering based on sequence identity or taxonomy. Ananke is free and open-source software available at https://github.com/beiko-lab/ananke.

  12. Spatial Temporal Modelling of Particulate Matter for Health Effects Studies

    Science.gov (United States)

    Hamm, N. A. S.

    2016-10-01

    Epidemiological studies of the health effects of air pollution require estimation of individual exposure. It is not possible to obtain measurements at all relevant locations so it is necessary to predict at these space-time locations, either on the basis of dispersion from emission sources or by interpolating observations. This study used data obtained from a low-cost sensor network of 32 air quality monitoring stations in the Dutch city of Eindhoven, which make up the ILM (innovative air (quality) measurement system). These stations currently provide PM10 and PM2.5 (particulate matter less than 10 and 2.5 m in diameter), aggregated to hourly means. The data provide an unprecedented level of spatial and temporal detail for a city of this size. Despite these benefits the time series of measurements is characterized by missing values and noisy values. In this paper a space-time analysis is presented that is based on a dynamic model for the temporal component and a Gaussian process geostatistical for the spatial component. Spatial-temporal variability was dominated by the temporal component, although the spatial variability was also substantial. The model delivered accurate predictions for both isolated missing values and 24-hour periods of missing values (RMSE = 1.4 μg m-3 and 1.8 μg m-3 respectively). Outliers could be detected by comparison to the 95% prediction interval. The model shows promise for predicting missing values, outlier detection and for mapping to support health impact studies.

  13. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  14. Equivalent Dynamic Models.

    Science.gov (United States)

    Molenaar, Peter C M

    2017-01-01

    Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

  15. Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

    Science.gov (United States)

    Sonter, Laura J; Watson, Keri B; Wood, Spencer A; Ricketts, Taylor H

    2016-01-01

    Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

  16. Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae

    Science.gov (United States)

    Rosu, Grigore; Havelund, Klaus

    2001-01-01

    The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.

  17. Temporal dynamics of ikaite in experimental sea ice

    DEFF Research Database (Denmark)

    Rysgaard, Søren; Wang, F.; Galley, R.J.

    2014-01-01

    Ikaite (CaCO3·6H2O) is a metastable phase of calcium carbonate that normally forms in a cold environment and/or under high pressure. Recently, ikaite crystals have been found in sea ice, and it has been suggested that their precipitation may play an important role in air–sea CO2 exchange in ice......-covered seas. Little is known, however, of the spatial and temporal dynamics of ikaite in sea ice. Here we present evidence for highly dynamic ikaite precipitation and dissolution in sea ice grown at an outdoor pool of the Sea-ice Environmental Research Facility (SERF) in Manitoba, Canada. During...... the experiment, ikaite precipitated in sea ice when temperatures were below −4 C, creating three distinct zones of ikaite concentrations: (1) a millimeter-to-centimeter-thin surface layer containing frost flowers and brine skim with bulk ikaite concentrations of > 2000 μmol kg−1, (2) an internal layer...

  18. The Temporal Dynamics of Arc Expression Regulate Cognitive Flexibility.

    Science.gov (United States)

    Wall, Mark J; Collins, Dawn R; Chery, Samantha L; Allen, Zachary D; Pastuzyn, Elissa D; George, Arlene J; Nikolova, Viktoriya D; Moy, Sheryl S; Philpot, Benjamin D; Shepherd, Jason D; Müller, Jürgen; Ehlers, Michael D; Mabb, Angela M; Corrêa, Sonia A L

    2018-05-24

    Neuronal activity regulates the transcription and translation of the immediate-early gene Arc/Arg3.1, a key mediator of synaptic plasticity. Proteasome-dependent degradation of Arc tightly limits its temporal expression, yet the significance of this regulation remains unknown. We disrupted the temporal control of Arc degradation by creating an Arc knockin mouse (ArcKR) where the predominant Arc ubiquitination sites were mutated. ArcKR mice had intact spatial learning but showed specific deficits in selecting an optimal strategy during reversal learning. This cognitive inflexibility was coupled to changes in Arc mRNA and protein expression resulting in a reduced threshold to induce mGluR-LTD and enhanced mGluR-LTD amplitude. These findings show that the abnormal persistence of Arc protein limits the dynamic range of Arc signaling pathways specifically during reversal learning. Our work illuminates how the precise temporal control of activity-dependent molecules, such as Arc, regulates synaptic plasticity and is crucial for cognition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

    Science.gov (United States)

    Dias, Daniela; Tchepel, Oxana

    2018-01-01

    Analyzing individual exposure in urban areas offers several challenges where both the individual’s activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals’ activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual’s time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives. PMID:29558426

  20. Lateralization for dynamic facial expressions in human superior temporal sulcus.

    Science.gov (United States)

    De Winter, François-Laurent; Zhu, Qi; Van den Stock, Jan; Nelissen, Koen; Peeters, Ronald; de Gelder, Beatrice; Vanduffel, Wim; Vandenbulcke, Mathieu

    2015-02-01

    Most face processing studies in humans show stronger activation in the right compared to the left hemisphere. Evidence is largely based on studies with static stimuli focusing on the fusiform face area (FFA). Hence, the pattern of lateralization for dynamic faces is less clear. Furthermore, it is unclear whether this property is common to human and non-human primates due to predisposing processing strategies in the right hemisphere or that alternatively left sided specialization for language in humans could be the driving force behind this phenomenon. We aimed to address both issues by studying lateralization for dynamic facial expressions in monkeys and humans. Therefore, we conducted an event-related fMRI experiment in three macaques and twenty right handed humans. We presented human and monkey dynamic facial expressions (chewing and fear) as well as scrambled versions to both species. We studied lateralization in independently defined face-responsive and face-selective regions by calculating a weighted lateralization index (LIwm) using a bootstrapping method. In order to examine if lateralization in humans is related to language, we performed a separate fMRI experiment in ten human volunteers including a 'speech' expression (one syllable non-word) and its scrambled version. Both within face-responsive and selective regions, we found consistent lateralization for dynamic faces (chewing and fear) versus scrambled versions in the right human posterior superior temporal sulcus (pSTS), but not in FFA nor in ventral temporal cortex. Conversely, in monkeys no consistent pattern of lateralization for dynamic facial expressions was observed. Finally, LIwms based on the contrast between different types of dynamic facial expressions (relative to scrambled versions) revealed left-sided lateralization in human pSTS for speech-related expressions compared to chewing and emotional expressions. To conclude, we found consistent laterality effects in human posterior STS but not

  1. Spatio-temporal cell dynamics in tumour spheroid irradiation

    International Nuclear Information System (INIS)

    Kempf, H.; Bleicher, M.; Meyer-Hermann, M.; Kempf, H.; Bleicher, M.; Kempf, H.; Meyer-Hermann, M.

    2010-01-01

    Multicellular tumour spheroids are realistic in vitro systems in radiation research that integrate cell-cell interaction and cell cycle control by factors in the medium. The dynamic reaction inside a tumour spheroid triggered by radiation is not well understood. Of special interest is the amount of cell cycle synchronization which could be triggered by irradiation, since this would allow follow-up irradiations to exploit the increased sensitivity of certain cell cycle phases. In order to investigate these questions we need to support irradiation experiments with mathematical models. In this article a new model is introduced combining the dynamics of tumour growth and irradiation treatments. The tumour spheroid growth is modelled using an agent-based Delaunay/Voronoi hybrid model in which the cells are represented by weighted dynamic vertices. Cell properties like full cell cycle dynamics are included. In order to be able to distinguish between different cell reactions in response to irradiation quality we introduce a probabilistic model for damage dynamics. The overall cell survival from this model is in agreement with predictions from the linear-quadratic model. Our model can describe the growth of avascular tumour spheroids in agreement to experimental results. Using the probabilistic model for irradiation damage dynamics the classic 'four Rs' of radiotherapy can be studied in silico. We found a pronounced reactivation of the tumour spheroid in response to irradiation. A majority of the surviving cells is synchronized in their cell cycle progression after irradiation. The cell synchronization could be actively triggered and should be exploited in an advanced fractionation scheme. Thus it has been demonstrated that our model could be used to understand the dynamics of tumour growth after irradiation and to propose optimized fractionation schemes in cooperation with experimental investigations. (authors)

  2. The temporal-relevance temporal-uncertainty model of prospective duration judgment.

    Science.gov (United States)

    Zakay, Dan

    2015-12-15

    A model aimed at explaining prospective duration judgments in real life settings (as well as in the laboratory) is presented. The model is based on the assumption that situational meaning is continuously being extracted by humans' perceptual and cognitive information processing systems. Time is one of the important dimensions of situational meaning. Based on the situational meaning, a value for Temporal Relevance is set. Temporal Relevance reflects the importance of temporal aspects for enabling adaptive behavior in a specific moment in time. When Temporal Relevance is above a certain threshold a prospective duration judgment process is evoked automatically. In addition, a search for relevant temporal information is taking place and its outcomes determine the level of Temporal Uncertainty which reflects the degree of knowledge one has regarding temporal aspects of the task to be performed. The levels of Temporal Relevance and Temporal Uncertainty determine the amount of attentional resources allocated for timing by the executive system. The merit of the model is in connecting timing processes with the ongoing general information processing stream. The model rests on findings in various domains which indicate that cognitive-relevance and self-relevance are powerful determinants of resource allocation policy. The feasibility of the model is demonstrated by analyzing various temporal phenomena. Suggestions for further empirical validation of the model are presented. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Research on Process-oriented Spatio-temporal Data Model

    Directory of Open Access Journals (Sweden)

    XUE Cunjin

    2016-02-01

    Full Text Available According to the analysis of the present status and existing problems of spatio-temporal data models developed in last 20 years,this paper proposes a process-oriented spatio-temporal data model (POSTDM,aiming at representing,organizing and storing continuity and gradual geographical entities. The dynamic geographical entities are graded and abstracted into process objects series from their intrinsic characteristics,which are process objects,process stage objects,process sequence objects and process state objects. The logical relationships among process entities are further studied and the structure of UML models and storage are also designed. In addition,through the mechanisms of continuity and gradual changes impliedly recorded by process objects,and the modes of their procedure interfaces offered by the customized ObjcetStorageTable,the POSTDM can carry out process representation,storage and dynamic analysis of continuity and gradual geographic entities. Taking a process organization and storage of marine data as an example,a prototype system (consisting of an object-relational database and a functional analysis platform is developed for validating and evaluating the model's practicability.

  4. 3D Printed Pediatric Temporal Bone: A Novel Training Model.

    Science.gov (United States)

    Longfield, Evan A; Brickman, Todd M; Jeyakumar, Anita

    2015-06-01

    Temporal bone dissection is a fundamental element of otologic training. Cadaveric temporal bones (CTB) are the gold standard surgical training model; however, many institutions do not have ready access to them and their cost can be significant: $300 to $500. Furthermore, pediatric cadaveric temporal bones are not readily available. Our objective is to develop a pediatric temporal bone model. Temporal bone model. Tertiary Children's Hospital. Pediatric patient model. We describe the novel use of a 3D printer for the generation of a plaster training model from a pediatric high- resolution CT temporal bone scan of a normal pediatric temporal bone. Three models were produced and were evaluated. The models utilized multiple colors (white for bone, yellow for the facial nerve) and were of high quality. Two models were drilled as a proof of concept and found to be an acceptable facsimile of the patient's anatomy, rendering all necessary surgical landmarks accurately. The only negative comments pertaining to the 3D printed temporal bone as a training model were the lack of variation in hardness between cortical and cancellous bone, noting a tactile variation from cadaveric temporal bones. Our novel pediatric 3D temporal bone training model is a viable, low-cost training option for previously inaccessible pediatric temporal bone training. Our hope is that, as 3D printers become commonplace, these models could be rapidly reproduced, allowing for trainees to print models of patients before performing surgery on the living patient.

  5. Models for Dynamic Applications

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Morales Rodriguez, Ricardo; Heitzig, Martina

    2011-01-01

    This chapter covers aspects of the dynamic modelling and simulation of several complex operations that include a controlled blending tank, a direct methanol fuel cell that incorporates a multiscale model, a fluidised bed reactor, a standard chemical reactor and finally a polymerisation reactor...... be applied to formulate, analyse and solve these dynamic problems and how in the case of the fuel cell problem the model consists of coupledmeso and micro scale models. It is shown how data flows are handled between the models and how the solution is obtained within the modelling environment....

  6. Theoretical aspects of spatial-temporal modeling

    CERN Document Server

    Matsui, Tomoko

    2015-01-01

    This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter provides up-to-date coverage of particle association measures that underpin the theoretical properties of recently developed random set methods in space and time otherwise known as the class of probability hypothesis density framework (PHD filters). The second chapter gives an overview of recent advances in Monte Carlo methods for Bayesian filtering in high-dimensional spaces. In particular, the chapter explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data applications. The third chapter presents an overview of generalized families of processes that extend the class of Gaussian process models to heavy-tailed families known as alph...

  7. Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

    Science.gov (United States)

    Jung, Minju; Hwang, Jungsik; Tani, Jun

    2015-01-01

    It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

  8. Temporal dynamics of glyoxalase 1 in secondary neuronal injury.

    Directory of Open Access Journals (Sweden)

    Philipp Pieroh

    Full Text Available BACKGROUND: Enhanced glycolysis leads to elevated levels of the toxic metabolite methylglyoxal which contributes to loss of protein-function, metabolic imbalance and cell death. Neurons were shown being highly susceptible to methylglyoxal toxicity. Glyoxalase 1 as an ubiquitous enzyme reflects the main detoxifying enzyme of methylglyoxal and underlies changes during aging and neurodegeneration. However, little is known about dynamics of Glyoxalase 1 following neuronal lesions so far. METHODS: To determine a possible involvement of Glyoxalase 1 in acute brain injury, we analysed the temporal dynamics of Glyoxalase 1 distribution and expression by immunohistochemistry and Western Blot analysis. Organotypic hippocampal slice cultures were excitotoxically (N-methyl-D-aspartate, 50 µM for 4 hours lesioned in vitro (5 minutes to 72 hours. Additionally, permanent middle cerebral artery occlusion was performed (75 minutes to 60 days. RESULTS: We found (i a predominant localisation of Glyoxalase 1 in endothelial cells in non-lesioned brains (ii a time-dependent up-regulation and re-distribution of Glyoxalase 1 in neurons and astrocytes and (iii a strong increase in Glyoxalase 1 dimers after neuronal injury (24 hours to 72 hours when compared to monomers of the protein. CONCLUSIONS: The high dynamics of Glyoxalase 1 expression and distribution following neuronal injury may indicate a novel role of Glyoxalase 1.

  9. MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

    Science.gov (United States)

    Novosad, Philip; Reader, Andrew J.

    2016-06-01

    Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral

  10. Temporal dynamics of biogeochemical processes at the Norman Landfill site

    Science.gov (United States)

    Arora, Bhavna; Mohanty, Binayak P.; McGuire, Jennifer T.; Cozzarelli, Isabelle M.

    2013-01-01

    The temporal variability observed in redox sensitive species in groundwater can be attributed to coupled hydrological, geochemical, and microbial processes. These controlling processes are typically nonstationary, and distributed across various time scales. Therefore, the purpose of this study is to investigate biogeochemical data sets from a municipal landfill site to identify the dominant modes of variation and determine the physical controls that become significant at different time scales. Data on hydraulic head, specific conductance, δ2H, chloride, sulfate, nitrate, and nonvolatile dissolved organic carbon were collected between 1998 and 2000 at three wells at the Norman Landfill site in Norman, OK. Wavelet analysis on this geochemical data set indicates that variations in concentrations of reactive and conservative solutes are strongly coupled to hydrologic variability (water table elevation and precipitation) at 8 month scales, and to individual eco-hydrogeologic framework (such as seasonality of vegetation, surface-groundwater dynamics) at 16 month scales. Apart from hydrologic variations, temporal variability in sulfate concentrations can be associated with different sources (FeS cycling, recharge events) and sinks (uptake by vegetation) depending on the well location and proximity to the leachate plume. Results suggest that nitrate concentrations show multiscale behavior across temporal scales for different well locations, and dominant variability in dissolved organic carbon for a closed municipal landfill can be larger than 2 years due to its decomposition and changing content. A conceptual framework that explains the variability in chemical concentrations at different time scales as a function of hydrologic processes, site-specific interactions, and/or coupled biogeochemical effects is also presented.

  11. Dynamic term structure models

    DEFF Research Database (Denmark)

    Andreasen, Martin Møller; Meldrum, Andrew

    This paper studies whether dynamic term structure models for US nominal bond yields should enforce the zero lower bound by a quadratic policy rate or a shadow rate specification. We address the question by estimating quadratic term structure models (QTSMs) and shadow rate models with at most four...

  12. Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics.

    Science.gov (United States)

    Reinl, Maren; Bartels, Andreas

    2014-11-15

    Facial movement conveys important information for social interactions, yet its neural processing is poorly understood. Computational models propose that shape- and temporal sequence sensitive mechanisms interact in processing dynamic faces. While face processing regions are known to respond to facial movement, their sensitivity to particular temporal sequences has barely been studied. Here we used fMRI to examine the sensitivity of human face-processing regions to two aspects of directionality in facial movement trajectories. We presented genuine movie recordings of increasing and decreasing fear expressions, each of which were played in natural or reversed frame order. This two-by-two factorial design matched low-level visual properties, static content and motion energy within each factor, emotion-direction (increasing or decreasing emotion) and timeline (natural versus artificial). The results showed sensitivity for emotion-direction in FFA, which was timeline-dependent as it only occurred within the natural frame order, and sensitivity to timeline in the STS, which was emotion-direction-dependent as it only occurred for decreased fear. The occipital face area (OFA) was sensitive to the factor timeline. These findings reveal interacting temporal sequence sensitive mechanisms that are responsive to both ecological meaning and to prototypical unfolding of facial dynamics. These mechanisms are temporally directional, provide socially relevant information regarding emotional state or naturalness of behavior, and agree with predictions from modeling and predictive coding theory. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Noise-induced temporal dynamics in Turing systems

    KAUST Repository

    Schumacher, Linus J.

    2013-04-25

    We examine the ability of intrinsic noise to produce complex temporal dynamics in Turing pattern formation systems, with particular emphasis on the Schnakenberg kinetics. Using power spectral methods, we characterize the behavior of the system using stochastic simulations at a wide range of points in parameter space and compare with analytical approximations. Specifically, we investigate whether polarity switching of stochastic patterns occurs at a defined frequency. We find that it can do so in individual realizations of a stochastic simulation, but that the frequency is not defined consistently across realizations in our samples of parameter space. Further, we examine the effect of noise on deterministically predicted traveling waves and find them increased in amplitude and decreased in speed. © 2013 American Physical Society.

  14. The temporal dynamics model of emotional memory processing: a synthesis on the neurobiological basis of stress-induced amnesia, flashbulb and traumatic memories, and the Yerkes-Dodson law.

    Science.gov (United States)

    Diamond, David M; Campbell, Adam M; Park, Collin R; Halonen, Joshua; Zoladz, Phillip R

    2007-01-01

    We have reviewed research on the effects of stress on LTP in the hippocampus, amygdala and prefrontal cortex (PFC) and present new findings which provide insight into how the attention and memory-related functions of these structures are influenced by strong emotionality. We have incorporated the stress-LTP findings into our "temporal dynamics" model, which provides a framework for understanding the neurobiological basis of flashbulb and traumatic memories, as well as stress-induced amnesia. An important feature of the model is the idea that endogenous mechanisms of plasticity in the hippocampus and amygdala are rapidly activated for a relatively short period of time by a strong emotional learning experience. Following this activational period, both structures undergo a state in which the induction of new plasticity is suppressed, which facilitates the memory consolidation process. We further propose that with the onset of strong emotionality, the hippocampus rapidly shifts from a "configural/cognitive map" mode to a "flashbulb memory" mode, which underlies the long-lasting, but fragmented, nature of traumatic memories. Finally, we have speculated on the significance of stress-LTP interactions in the context of the Yerkes-Dodson Law, a well-cited, but misunderstood, century-old principle which states that the relationship between arousal and behavioral performance can be linear or curvilinear, depending on the difficulty of the task.

  15. The Financial Accounting Model from a System Dynamics' Perspective

    OpenAIRE

    Melse, Eric

    2006-01-01

    This paper explores the foundation of the financial accounting model. We examine the properties of the accounting equation as the principal algorithm for the design and the development of a System Dynamics model. Key to the perspective is the foundational requirement that resolves the temporal conflict that resides in a stock and flow model. Through formal analysis the accounting equation is redefined as a cybernetic model by expressing the temporal and dynamic properties of its terms. Articu...

  16. Temporal networks

    CERN Document Server

    Saramäki, Jari

    2013-01-01

    The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach  the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and concept...

  17. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    OpenAIRE

    David Ebert

    2006-01-01

    One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

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

    Science.gov (United States)

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

    2012-10-01

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

  19. Spatio-Temporal Modeling of Neuron Fields

    DEFF Research Database (Denmark)

    Lund, Adam

    The starting point and focal point for this thesis was stochastic dynamical modelling of neuronal imaging data with the declared objective of drawing inference, within this model framework, in a large-scale (high-dimensional) data setting. Implicitly this objective entails carrying out three...... be achieved if the scale of the data is taken into consideration throughout i) - iii). The strategy in this project was, relying on a space and time continuous stochastic modelling approach, to obtain a stochastic functional differential equation on a Hilbert space. By decomposing the drift operator...... of this SFDE such that each component is essentially represented by a smooth function of time and space and expanding these component functions in a tensor product basis we implicitly reduce the number of model parameters. In addition, the component-wise tensor representation induce a corresponding component...

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

    OpenAIRE

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

    2013-01-01

    The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implem...

  1. Dynamic Raman imaging system with high spatial and temporal resolution

    Science.gov (United States)

    Wang, Lei; Dai, Yinzhen; He, Hao; Lv, Ruiqi; Zong, Cheng; Ren, Bin

    2017-09-01

    There is an increasing need to study dynamic changing systems with significantly high spatial and temporal resolutions. In this work, we integrated point-scanning, line-scanning, and wide-field Raman imaging techniques into a single system. By using an Electron Multiplying CCD (EMCCD) with a high gain and high frame rate, we significantly reduced the time required for wide-field imaging, making it possible to monitor the electrochemical reactions in situ. The highest frame rate of EMCDD was ˜50 fps, and the Raman images for a specific Raman peak can be obtained by passing the signal from the sample through the Liquid Crystal Tunable Filter. The spatial resolutions of scanning imaging and wide-field imaging with a 100× objective (NA = 0.9) are 0.5 × 0.5 μm2 and 0.36 × 0.36 μm2, respectively. The system was used to study the surface plasmon resonance of Au nanorods, the surface-enhanced Raman scattering signal distribution for Au Nanoparticle aggregates, and dynamic Raman imaging of an electrochemical reacting system.

  2. Learning predictive statistics from temporal sequences: Dynamics and strategies.

    Science.gov (United States)

    Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

    2017-10-01

    Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

  3. Dynamic accelerator modeling

    International Nuclear Information System (INIS)

    Nishimura, Hiroshi.

    1993-05-01

    Object-Oriented Programming has been used extensively to model the LBL Advanced Light Source 1.5 GeV electron storage ring. This paper is on the present status of the class library construction with emphasis on a dynamic modeling

  4. Dynamic panel data models

    NARCIS (Netherlands)

    Bun, M.J.G.; Sarafidis, V.

    2013-01-01

    This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.

  5. Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media

    Science.gov (United States)

    Watson, Keri B.; Wood, Spencer A.; Ricketts, Taylor H.

    2016-01-01

    Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making. PMID:27611325

  6. Quality of a fished resource: Assessing spatial and temporal dynamics.

    Directory of Open Access Journals (Sweden)

    Sarah J Teck

    Full Text Available Understanding spatio-temporal variability in the demography of harvested species is essential to improve sustainability, especially if there is large geographic variation in demography. Reproductive patterns commonly vary spatially, which is particularly important for management of "roe"-based fisheries, since profits depend on both the number and reproductive condition of individuals. The red sea urchin, Mesocentrotus franciscanus, is harvested in California for its roe (gonad, which is sold to domestic and international sushi markets. The primary driver of price within this multi-million-dollar industry is gonad quality. A relatively simple measure of the fraction of the body mass that is gonad, the gonadosomatic index (GSI, provides important insight into the ecological and environmental factors associated with variability in reproductive quality, and hence value within the industry. We identified the seasonality of the reproductive cycle and determined whether it varied within a heavily fished region. We found that fishermen were predictable both temporally and spatially in collecting urchins according to the reproductive dynamics of urchins. We demonstrated the use of red sea urchin GSI as a simple, quantitative tool to predict quality, effort, landings, price, and value of the fishery. We found that current management is not effectively realizing some objectives for the southern California fishery, since the reproductive cycle does not match the cycle in northern California, where these management guidelines were originally shaped. Although regulations may not be meeting initial management goals, the scheme may in fact provide conservation benefits by curtailing effort during part of the high-quality fishing season right before spawning.

  7. Modeling Temporal Evolution and Multiscale Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2013-01-01

    Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...

  8. Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.

    Science.gov (United States)

    Kasabov, Nikola; Dhoble, Kshitij; Nuntalid, Nuttapod; Indiveri, Giacomo

    2013-05-01

    On-line learning and recognition of spatio- and spectro-temporal data (SSTD) is a very challenging task and an important one for the future development of autonomous machine learning systems with broad applications. Models based on spiking neural networks (SNN) have already proved their potential in capturing spatial and temporal data. One class of them, the evolving SNN (eSNN), uses a one-pass rank-order learning mechanism and a strategy to evolve a new spiking neuron and new connections to learn new patterns from incoming data. So far these networks have been mainly used for fast image and speech frame-based recognition. Alternative spike-time learning methods, such as Spike-Timing Dependent Plasticity (STDP) and its variant Spike Driven Synaptic Plasticity (SDSP), can also be used to learn spatio-temporal representations, but they usually require many iterations in an unsupervised or semi-supervised mode of learning. This paper introduces a new class of eSNN, dynamic eSNN, that utilise both rank-order learning and dynamic synapses to learn SSTD in a fast, on-line mode. The paper also introduces a new model called deSNN, that utilises rank-order learning and SDSP spike-time learning in unsupervised, supervised, or semi-supervised modes. The SDSP learning is used to evolve dynamically the network changing connection weights that capture spatio-temporal spike data clusters both during training and during recall. The new deSNN model is first illustrated on simple examples and then applied on two case study applications: (1) moving object recognition using address-event representation (AER) with data collected using a silicon retina device; (2) EEG SSTD recognition for brain-computer interfaces. The deSNN models resulted in a superior performance in terms of accuracy and speed when compared with other SNN models that use either rank-order or STDP learning. The reason is that the deSNN makes use of both the information contained in the order of the first input spikes

  9. Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology

    Science.gov (United States)

    Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

    2018-02-01

    Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a

  10. Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security

    Directory of Open Access Journals (Sweden)

    Yi Lu

    2016-11-01

    Full Text Available Urban ecological security is the basic principle of national ecological security. However, analyses of the spatial and temporal dynamics of ecological security remain limited, especially those that consider different scenarios of urban development. In this study, an integrated method is proposed that combines the Conversion of Land Use and its Effects (CLUE-S model with the Pressure–State–Response (P-S-R framework to assess landscape ecological security (LES in Huangshan City, China under two scenarios. Our results suggest the following conclusions: (1 the spatial and temporal dynamics of ecological security are closely related to the urbanization process; (2 although the average values of landscape ecological security are similar under different scenarios, the areas of relatively high security levels vary considerably; and (3 spatial heterogeneity in ecological security exists between different districts and counties, and the city center and its vicinity may face relatively serious declines in ecological security in the future. Overall, the proposed method not only illustrates the spatio-temporal dynamics of landscape ecological security under different scenarios but also reveals the anthropogenic effects on ecosystems by differentiating between causes, effects, and human responses at the landscape scale. This information is of great significance to decision-makers for future urban planning and management.

  11. Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.

    Directory of Open Access Journals (Sweden)

    Kanghoon Jung

    2014-08-01

    Full Text Available A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a a highly biased choice distribution; and (b preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.

  12. Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions

    Science.gov (United States)

    Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D.; Jeong, Jaeseung

    2014-01-01

    A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices. PMID:25122498

  13. Temporal variability in phosphorus transfers: classifying concentration–discharge event dynamics

    Directory of Open Access Journals (Sweden)

    P. Haygarth

    2004-01-01

    Full Text Available The importance of temporal variability in relationships between phosphorus (P concentration (Cp and discharge (Q is linked to a simple means of classifying the circumstances of Cp–Q relationships in terms of functional types of response. New experimental data at the upstream interface of grassland soil and catchment systems at a range of scales (lysimeters to headwaters in England and Australia are used to demonstrate the potential of such an approach. Three types of event are defined as Types 1–3, depending on whether the relative change in Q exceeds the relative change in Cp (Type 1, whether Cp and Q are positively inter-related (Type 2 and whether Cp varies yet Q is unchanged (Type 3. The classification helps to characterise circumstances that can be explained mechanistically in relation to (i the scale of the study (with a tendency towards Type 1 in small scale lysimeters, (ii the form of P with a tendency for Type 1 for soluble (i.e., p–Q relationships that can be developed further to contribute to future models of P transfer and delivery from slope to stream. Studies that evaluate the temporal dynamics of the transfer of P are currently grossly under-represented in comparison with models based on static/spatial factors. Keywords: phosphorus, concentration, discharge, lysimeters, temporal dynamics, overland flow

  14. Spatio-temporal Dynamics of Land-use and Land-cover Change: A Multi-agent Simulation Model and Its Application to an Upland Watershed in Central Vietnam

    Science.gov (United States)

    Le, Q.; Vlek, P. L.; Park, S.

    2005-12-01

    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 socio-economic dynamics emerging from the complex socio-ecological interactions at micro levels resulting from land-use policy interventions. The model provides land-use scenarios under alternative policy to support decisions on land management for improved rural livelihoods while protecting the environment. In the multi-agent simulation model, the human community is represented by household agents (heterogeneous farming households) with their profiles and decision-making mechanisms about land use. The household profile defines the five asset dimensions of household livelihood (e.g., social, human, financial, natural and physical assets). The land-use decision-making program works by taking inputs from the household profile, perceived spatial environmental attributes, and introduced policies. The decision-making program is a logical procedure that combines a land-use choice model (multi-nominal logistic choices) and anthropological rules. The landscape environment is represented by landscape agents (congruent land patches of 30mx30m) with their state variables and ecological response mechanisms to environmental changes and human interventions. State variables of landscape agents correspond to spatial GIS-raster layers of biophysical, economic, and institutional variables. Ecological mechanisms of landscape agents are represented by internal sub-models of agricultural and forest productivity dynamics, which work in response to the current state, history, and spatial neighbourhood of the landscape agents. A multi-agent based protocol coordinates the

  15. Spatial-temporal dynamics of broadband terahertz Bessel beam propagation

    International Nuclear Information System (INIS)

    Semenova, V A; Kulya, M S; Bespalov, V G

    2016-01-01

    The unique properties of narrowband and broadband terahertz Bessel beams have led to a number of their applications in different fields, for example, for the depth of focusing and resolution enhancement in terahertz imaging. However, broadband terahertz Bessel beams can probably be also used for the diffraction minimization in the short-range broadband terahertz communications. For this purpose, the study of spatial-temporal dynamics of the broadband terahertz Bessel beams is needed. Here we present a simulation-based study of the propagating in non-dispersive medium broadband Bessel beams generated by a conical axicon lens. The algorithm based on scalar diffraction theory was used to obtain the spatial amplitude and phase distributions of the Bessel beam in the frequency range from 0.1 to 3 THz at the distances 10-200 mm from the axicon. Bessel beam field is studied for the different spectral components of the initial pulse. The simulation results show that for the given parameters of the axicon lens one can obtain the Gauss-Bessel beam generation in the spectral range from 0.1 to 3 THz. The length of non-diffraction propagation for a different spectral components was measured, and it was shown that for all spectral components of the initial pulse this length is about 130 mm. (paper)

  16. Temporal dynamics of access to consciousness in the attentional blink.

    Science.gov (United States)

    Kranczioch, Cornelia; Debener, Stefan; Maye, Alexander; Engel, Andreas K

    2007-09-01

    Presentation of two targets in close temporal succession often results in an impairment of conscious perception for the second stimulus. Previous studies have identified several electrophysiological correlates for this so-called 'attentional blink'. Components of the event-related potential (ERP) such as the N2 and the P3, but also oscillatory brain signals have been shown to distinguish between detected and missed stimuli, and thus, conscious perception. Here we investigate oscillatory responses that specifically relate to conscious stimulus processing together with potential ERP predictors. Our results show that successful target detection is associated with enhanced coherence in the low beta frequency range, but a decrease in alpha coherence before and during target presentation. In addition, we find an inverse relation between the P3 amplitudes associated with the first and second target. We conclude that the resources allocated to first and second target processing are directly mirrored by the P3 component and, moreover, that brain states before and during stimulus presentation, as reflected by oscillatory brain activity, strongly determine the access to consciousness. Thus, becoming aware of a stimulus seems to depend on the dynamic interaction between a number of widely distributed neural processes, rather than on the modulation of one single process or component.

  17. Corruption dynamics model

    Science.gov (United States)

    Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

    2017-07-01

    The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

  18. The Temporal Dynamics Model of Emotional Memory Processing: A Synthesis on the Neurobiological Basis of Stress-Induced Amnesia, Flashbulb and Traumatic Memories, and the Yerkes-Dodson Law

    Directory of Open Access Journals (Sweden)

    Phillip R. Zoladz

    2007-03-01

    Full Text Available We have reviewed research on the effects of stress on LTP in the hippocampus, amygdala and prefrontal cortex (PFC and present new findings which provide insight into how the attention and memory-related functions of these structures are influenced by strong emotionality. We have incorporated the stress-LTP findings into our “temporal dynamics” model, which provides a framework for understanding the neurobiological basis of flashbulb and traumatic memories, as well as stress-induced amnesia. An important feature of the model is the idea that endogenous mechanisms of plasticity in the hippocampus and amygdala are rapidly activated for a relatively short period of time by a strong emotional learning experience. Following this activational period, both structures undergo a state in which the induction of new plasticity is suppressed, which facilitates the memory consolidation process. We further propose that with the onset of strong emotionality, the hippocampus rapidly shifts from a “configural/cognitive map” mode to a “flashbulb memory” mode, which underlies the long-lasting, but fragmented, nature of traumatic memories. Finally, we have speculated on the significance of stress-LTP interactions in the context of the Yerkes-Dodson Law, a well-cited, but misunderstood, century-old principle which states that the relationship between arousal and behavioral performance can be linear or curvilinear, depending on the difficulty of the task.

  19. Dynamics of temporally localized states in passively mode-locked semiconductor lasers

    Science.gov (United States)

    Schelte, C.; Javaloyes, J.; Gurevich, S. V.

    2018-05-01

    We study the emergence and the stability of temporally localized structures in the output of a semiconductor laser passively mode locked by a saturable absorber in the long-cavity regime. For large yet realistic values of the linewidth enhancement factor, we disclose the existence of secondary dynamical instabilities where the pulses develop regular and subsequent irregular temporal oscillations. By a detailed bifurcation analysis we show that additional solution branches that consist of multipulse (molecules) solutions exist. We demonstrate that the various solution curves for the single and multipeak pulses can splice and intersect each other via transcritical bifurcations, leading to a complex web of solutions. Our analysis is based on a generic model of mode locking that consists of a time-delayed dynamical system, but also on a much more numerically efficient, yet approximate, partial differential equation. We compare the results of the bifurcation analysis of both models in order to assess up to which point the two approaches are equivalent. We conclude our analysis by the study of the influence of group velocity dispersion, which is only possible in the framework of the partial differential equation model, and we show that it may have a profound impact on the dynamics of the localized states.

  20. The Temporal Dynamics of Visual Search: Evidence for Parallel Processing in Feature and Conjunction Searches

    Science.gov (United States)

    McElree, Brian; Carrasco, Marisa

    2012-01-01

    Feature and conjunction searches have been argued to delineate parallel and serial operations in visual processing. The authors evaluated this claim by examining the temporal dynamics of the detection of features and conjunctions. The 1st experiment used a reaction time (RT) task to replicate standard mean RT patterns and to examine the shapes of the RT distributions. The 2nd experiment used the response-signal speed–accuracy trade-off (SAT) procedure to measure discrimination (asymptotic detection accuracy) and detection speed (processing dynamics). Set size affected discrimination in both feature and conjunction searches but affected detection speed only in the latter. Fits of models to the SAT data that included a serial component overpredicted the magnitude of the observed dynamics differences. The authors concluded that both features and conjunctions are detected in parallel. Implications for the role of attention in visual processing are discussed. PMID:10641310

  1. Temporal diagnostic analysis of the SWAT model to detect dominant periods of poor model performance

    Science.gov (United States)

    Guse, Björn; Reusser, Dominik E.; Fohrer, Nicola

    2013-04-01

    Hydrological models generally include thresholds and non-linearities, such as snow-rain-temperature thresholds, non-linear reservoirs, infiltration thresholds and the like. When relating observed variables to modelling results, formal methods often calculate performance metrics over long periods, reporting model performance with only few numbers. Such approaches are not well suited to compare dominating processes between reality and model and to better understand when thresholds and non-linearities are driving model results. We present a combination of two temporally resolved model diagnostic tools to answer when a model is performing (not so) well and what the dominant processes are during these periods. We look at the temporal dynamics of parameter sensitivities and model performance to answer this question. For this, the eco-hydrological SWAT model is applied in the Treene lowland catchment in Northern Germany. As a first step, temporal dynamics of parameter sensitivities are analyzed using the Fourier Amplitude Sensitivity test (FAST). The sensitivities of the eight model parameters investigated show strong temporal variations. High sensitivities were detected for two groundwater (GW_DELAY, ALPHA_BF) and one evaporation parameters (ESCO) most of the time. The periods of high parameter sensitivity can be related to different phases of the hydrograph with dominances of the groundwater parameters in the recession phases and of ESCO in baseflow and resaturation periods. Surface runoff parameters show high parameter sensitivities in phases of a precipitation event in combination with high soil water contents. The dominant parameters give indication for the controlling processes during a given period for the hydrological catchment. The second step included the temporal analysis of model performance. For each time step, model performance was characterized with a "finger print" consisting of a large set of performance measures. These finger prints were clustered into

  2. A Temporal-Causal Modelling Approach to Integrated Contagion and Network Change in Social Networks

    NARCIS (Netherlands)

    Blankendaal, Romy; Parinussa, Sarah; Treur, Jan

    2016-01-01

    This paper introduces an integrated temporal-causal model for dynamics in social networks addressing the contagion principle by which states are affected mutually, and both the homophily principle and the more-becomes-more principle by which connections are adapted over time. The integrated model

  3. DYNAMIC LOAD DAMPER MODELING

    Directory of Open Access Journals (Sweden)

    Loktev Aleksey Alekseevich

    2013-01-01

    Full Text Available The authors present their findings associated with their modeling of a dynamic load damper. According to the authors, the damper is to be installed onto a structure or its element that may be exposed to impact, vibration or any other dynamic loading. The damper is composed of paralleled or consecutively connected viscous and elastic elements. The authors study the influence of viscosity and elasticity parameters of the damper produced onto the regular displacement of points of the structure to be protected and onto the regular acceleration transmitted immediately from the damper to the elements positioned below it.

  4. Near equilibrium dynamics and one-dimensional spatial—temporal structures of polar active liquid crystals

    International Nuclear Information System (INIS)

    Yang Xiao-Gang; Wang Qi; Forest, M. Gregory

    2014-01-01

    We systematically explore near equilibrium, flow-driven, and flow-activity coupled dynamics of polar active liquid crystals using a continuum model. Firstly, we re-derive the hydrodynamic model to ensure the thermodynamic laws are obeyed and elastic stresses and forces are consistently accounted. We then carry out a linear stability analysis about constant steady states to study near equilibrium dynamics around the steady states, revealing long-wave instability inherent in this model system and how active parameters in the model affect the instability. We then study model predictions for one-dimensional (1D) spatial—temporal structures of active liquid crystals in a channel subject to physical boundary conditions. We discuss the model prediction in two selected regimes, one is the viscous stress dominated regime, also known as the flow-driven regime, while the other is the full regime, in which all active mechanisms are included. In the viscous stress dominated regime, the polarity vector is driven by the prescribed flow field. Dynamics depend sensitively on the physical boundary condition and the type of the driven flow field. Bulk-dominated temporal periodic states and spatially homogeneous states are possible under weak anchoring conditions while spatially inhomogeneous states exist under strong anchoring conditions. In the full model, flow-orientation interaction generates a host of planar as well as out-of-plane spatial—temporal structures related to the spontaneous flows due to the molecular self-propelled motion. These results provide contact with the recent literature on active nematic suspensions. In addition, symmetry breaking patterns emerge as the additional active viscous stress due to the polarity vector is included in the force balance. The inertia effect is found to limit the long-time survival of spatial structures to those with small wave numbers, i.e., an asymptotic coarsening to long wave structures. A rich set of mechanisms for generating

  5. Spatio-temporal Dynamics and Mechanisms of Stress Granule Assembly.

    Directory of Open Access Journals (Sweden)

    Daisuke Ohshima

    2015-06-01

    Full Text Available Stress granules (SGs are non-membranous cytoplasmic aggregates of mRNAs and related proteins, assembled in response to environmental stresses such as heat shock, hypoxia, endoplasmic reticulum (ER stress, chemicals (e.g. arsenite, and viral infections. SGs are hypothesized as a loci of mRNA triage and/or maintenance of proper translation capacity ratio to the pool of mRNAs. In brain ischemia, hippocampal CA3 neurons, which are resilient to ischemia, assemble SGs. In contrast, CA1 neurons, which are vulnerable to ischemia, do not assemble SGs. These results suggest a critical role SG plays in regards to cell fate decisions. Thus SG assembly along with its dynamics should determine the cell fate. However, the process that exactly determines the SG assembly dynamics is largely unknown. In this paper, analyses of experimental data and computer simulations were used to approach this problem. SGs were assembled as a result of applying arsenite to HeLa cells. The number of SGs increased after a short latent period, reached a maximum, then decreased during the application of arsenite. At the same time, the size of SGs grew larger and became localized at the perinuclear region. A minimal mathematical model was constructed, and stochastic simulations were run to test the modeling. Since SGs are discrete entities as there are only several tens of them in a cell, commonly used deterministic simulations could not be employed. The stochastic simulations replicated observed dynamics of SG assembly. In addition, these stochastic simulations predicted a gamma distribution relative to the size of SGs. This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly. Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics. Thus our experiments and stochastic simulations presented a possible mechanism regulating SG assembly.

  6. Temporal dynamics in microbial soil communities at anthrax carcass sites.

    Science.gov (United States)

    Valseth, Karoline; Nesbø, Camilla L; Easterday, W Ryan; Turner, Wendy C; Olsen, Jaran S; Stenseth, Nils Chr; Haverkamp, Thomas H A

    2017-09-26

    Anthrax is a globally distributed disease affecting primarily herbivorous mammals. It is caused by the soil-dwelling and spore-forming bacterium Bacillus anthracis. The dormant B. anthracis spores become vegetative after ingestion by grazing mammals. After killing the host, B. anthracis cells return to the soil where they sporulate, completing the lifecycle of the bacterium. Here we present the first study describing temporal microbial soil community changes in Etosha National Park, Namibia, after decomposition of two plains zebra (Equus quagga) anthrax carcasses. To circumvent state-associated-challenges (i.e. vegetative cells/spores) we monitored B. anthracis throughout the period using cultivation, qPCR and shotgun metagenomic sequencing. The combined results suggest that abundance estimation of spore-forming bacteria in their natural habitat by DNA-based approaches alone is insufficient due to poor recovery of DNA from spores. However, our combined approached allowed us to follow B. anthracis population dynamics (vegetative cells and spores) in the soil, along with closely related organisms from the B. cereus group, despite their high sequence similarity. Vegetative B. anthracis abundance peaked early in the time-series and then dropped when cells either sporulated or died. The time-series revealed that after carcass deposition, the typical semi-arid soil community (e.g. Frankiales and Rhizobiales species) becomes temporarily dominated by the orders Bacillales and Pseudomonadales, known to contain plant growth-promoting species. Our work indicates that complementing DNA based approaches with cultivation may give a more complete picture of the ecology of spore forming pathogens. Furthermore, the results suggests that the increased vegetation biomass production found at carcass sites is due to both added nutrients and the proliferation of microbial taxa that can be beneficial for plant growth. Thus, future B. anthracis transmission events at carcass sites may be

  7. Dynamic encoding of speech sequence probability in human temporal cortex.

    Science.gov (United States)

    Leonard, Matthew K; Bouchard, Kristofer E; Tang, Claire; Chang, Edward F

    2015-05-06

    Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. Copyright © 2015 the authors 0270-6474/15/357203-12$15.00/0.

  8. Temporal dynamics of blue and green virtual water trade networks

    Science.gov (United States)

    Konar, M.; Dalin, C.; Hanasaki, N.; Rinaldo, A.; Rodriguez-Iturbe, I.

    2012-12-01

    Global food security increasingly relies on the trade of food commodities. Freshwater resources are essential to agricultural production and are thus embodied in the trade of food commodities, referred to as "virtual water trade." Agricultural production predominantly relies on rainwater (i.e., "green water"), though irrigation (i.e., "blue water") does play an important role. These different sources of water have distinctly different opportunity costs, which may be reflected in the way these resources are traded. Thus, the temporal dynamics of the virtual water trade networks from these distinct water sources require characterization. We find that 42 × 109 m3 blue and 310 × 109 m3 green water was traded in 1986, growing to 78 × 109 m3 blue and 594 × 109 m3 green water traded in 2008. Three nations dominate the export of green water resources: the USA, Argentina, and Brazil. As a country increases its export trade partners it tends to export relatively more blue water. However, as a country increases its import trade partners it does not preferentially import water from a specific source. The amount of virtual water that a country imports by increasing its import trade partners has been decreasing over time, with the exception of the soy trade. Both blue and green virtual water networks are efficient: 119 × 109 m3 blue and 105 × 109 m3 green water were saved in 2008. Importantly, trade has been increasingly saving water over time, due to the intensification of crop trade on more water-efficient links.

  9. Dynamic wake meandering modeling

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Gunner C.; Aagaard Madsen, H.; Bingoel, F. (and others)

    2007-06-15

    We present a consistent, physically based theory for the wake meandering phenomenon, which we consider of crucial importance for the overall description of wind turbine loadings in wind farms. In its present version the model is confined to single wake situations. The model philosophy does, however, have the potential to include also mutual wake interaction phenomenons. The basic conjecture behind the dynamic wake meandering model is that wake transportation in the atmospheric boundary layer is driven by the large scale lateral- and vertical turbulence components. Based on this conjecture a stochastic model of the downstream wake meandering is formulated. In addition to the kinematic formulation of the dynamics of the 'meandering frame of reference', models characterizing the mean wake deficit as well as the added wake turbulence, described in the meandering frame of reference, are an integrated part the model complex. For design applications, the computational efficiency of wake deficit prediction is a key issue. Two computationally low cost models are developed for this purpose. The character of the added wake turbulence, generated by the up-stream turbine in the form of shed and trailed vorticity, has been approached by analytical as well as by numerical studies. The dynamic wake meandering philosophy has been verified by comparing model predictions with extensive full-scale measurements. These comparisons have demonstrated good agreement, both qualitatively and quantitatively, concerning both flow characteristics and turbine load characteristics. Contrary to previous attempts to model wake loading, the dynamic wake meandering approach opens for a unifying description in the sense that turbine power and load aspects can be treated simultaneously. This capability is a direct and attractive consequence of the model being based on the underlying physical process, and it potentially opens for optimization of wind farm topology, of wind farm operation as

  10. Dynamical chiral bag model

    International Nuclear Information System (INIS)

    Colanero, K.; Chu, M.-C.

    2002-01-01

    We study a dynamical chiral bag model, in which massless fermions are confined within an impenetrable but movable bag coupled to meson fields. The self-consistent motion of the bag is obtained by solving the equations of motion exactly assuming spherical symmetry. When the bag interacts with an external meson wave we find three different kinds of resonances: fermionic, geometric, and σ resonances. We discuss the phenomenological implications of our results

  11. Model for macroevolutionary dynamics.

    Science.gov (United States)

    Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E

    2013-07-02

    The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.

  12. Multiresolution Network Temporal and Spatial Scheduling Model of Scenic Spot

    Directory of Open Access Journals (Sweden)

    Peng Ge

    2013-01-01

    Full Text Available Tourism is one of pillar industries of the world economy. Low-carbon tourism will be the mainstream direction of the scenic spots' development, and the ω path of low-carbon tourism development is to develop economy and protect environment simultaneously. However, as the tourists' quantity is increasing, the loads of scenic spots are out of control. And the instantaneous overload in some spots caused the image phenomenon of full capacity of the whole scenic spot. Therefore, realizing the real-time schedule becomes the primary purpose of scenic spot’s management. This paper divides the tourism distribution system into several logically related subsystems and constructs a temporal and spatial multiresolution network scheduling model according to the regularity of scenic spots’ overload phenomenon in time and space. It also defines dynamic distribution probability and equivalent dynamic demand to realize the real-time prediction. We define gravitational function between fields and takes it as the utility of schedule, after resolving the transportation model of each resolution, it achieves hierarchical balance between demand and capacity of the system. The last part of the paper analyzes the time complexity of constructing a multiresolution distribution system.

  13. RETRAN dynamic slip model

    International Nuclear Information System (INIS)

    McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

    1981-01-01

    Thermal-hydraulic codes in general use for system calculations are based on extensive analyses of loss-of-coolant accidents following the postulated rupture of a large coolant pipe. In this study, time-dependent equation for the slip velocity in a two-phase flow condition has been incorporated into the RETRAN-02 computer code. This model addition was undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. The dynamic slip equation was derived from a set of two-fluid conservation equations. 18 refs

  14. A model relating Eulerian spatial and temporal velocity correlations

    Science.gov (United States)

    Cholemari, Murali R.; Arakeri, Jaywant H.

    2006-03-01

    In this paper we propose a model to relate Eulerian spatial and temporal velocity autocorrelations in homogeneous, isotropic and stationary turbulence. We model the decorrelation as the eddies of various scales becoming decorrelated. This enables us to connect the spatial and temporal separations required for a certain decorrelation through the ‘eddy scale’. Given either the spatial or the temporal velocity correlation, we obtain the ‘eddy scale’ and the rate at which the decorrelation proceeds. This leads to a spatial separation from the temporal correlation and a temporal separation from the spatial correlation, at any given value of the correlation relating the two correlations. We test the model using experimental data from a stationary axisymmetric turbulent flow with homogeneity along the axis.

  15. An assessment of the temporal dynamics of moral decisions

    Directory of Open Access Journals (Sweden)

    Gregory J. Koop

    2013-09-01

    Full Text Available In the domain of moral decision making, models in which emotion and deliberation constitute competing dual-systems have become increasingly popular. Currently, the favored explanation of this interaction is what Evans (2008 termed a ``default-interventionist'' (DI process where moral decisions are the result of a prepotent emotional response, which can be overridden with substantial deliberative effort. Although this ``emotion-then-deliberation'' sequence is often assumed, existing methods have lacked the requisite process resolution to clearly depict the nature of this interaction. The present work utilized continuous mouse tracking, or response dynamics, to develop and test predictions of these DI models of moral decision making. Study 1 utilized previously published moral dilemmas to validate the method for use with such complex stimuli. Although the data replicated typical choice and RT patterns, the process metrics provided by the response trajectories did not demonstrate the online preference reversals predicted by DI models. Study 2 utilized more rigorously constructed stimuli and an alternative presentation format to provide the strongest possible test of DI predictions, but again failed to show the predicted reversals. In summary, neither experiment provided data in accordance with the predictions of popular DI dual-systems models, which suggests that researchers should consider models allowing for concurrent activation of deliberative and emotional systems, or reconceptualize moral decisions within the typical multiattribute decision framework.

  16. A model of nematode dynamics in the Westerschelde estuary

    NARCIS (Netherlands)

    Li, J.; Vincx, M.; Herman, P.M.J.

    1996-01-01

    We developed a time dynamic model to investigate the temporal dynamics of nematode community in the brackish zone of the Westerschelde Estuary. The biomass of four nematode feeding groups observed from March 1991 to February 1992 is used to calibrate the model. Using environmental data as the input,

  17. Contact dynamics math model

    Science.gov (United States)

    Glaese, John R.; Tobbe, Patrick A.

    1986-01-01

    The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.

  18. How Well Do Students in Secondary School Understand Temporal Development of Dynamical Systems?

    Science.gov (United States)

    Forjan, Matej; Grubelnik, Vladimir

    2015-01-01

    Despite difficulties understanding the dynamics of complex systems only simple dynamical systems without feedback connections have been taught in secondary school physics. Consequently, students do not have opportunities to develop intuition of temporal development of systems, whose dynamics are conditioned by the influence of feedback processes.…

  19. Temporally Dynamic, Spatially Static, Cobble Bedforms In Reversing Subtidal Currents

    Science.gov (United States)

    Abdulkade, Akirat; Carling, Paul; Zong, Quanli; Leyland, Julian; Thompson, Charlie

    2016-04-01

    Cobble bedforms, transverse to the reversing tidal currents, are exposed at extreme low-water Spring tides on an inter-tidal bedrock shelf in the macro-tidal Severn Estuary, UK. Near-bed flow velocities during Spring tides can exceed 1.5m/s, with water depths varying from zero to in excess of 10m. During neap tides the bedforms are not exposed, and sediment is expected to be of limited mobility. When exposed, the bedform geometry tends to be asymmetric; orientated down estuary with the ebb current. During Spring tides, vigorous bedload transport of gravel (including large cobbles) occurs during both flood and ebb over the crests and yet, despite this temporal dynamism, the bedforms remain spatially static over long time periods or show weak down-estuary migration. Stasis implies that the tidal bedload transport vectors are essentially in balance. Near-bed shear stress and bed roughness values vary systematically with the Spring-tide current speeds and the predicted grain-size of the bed load using the Shields criterion is in accord with observed coarser grain-sizes in transport. These hydrodynamic data, delimited by estimates of the threshold of motion, and integrated over either flood or ebb tides are being used to explain the apparent stability of the bedforms. The bulk hydraulic data are supplemented by particle tracer studies and laser-scanning of bed configurations between tides. The high-energy environment results in two forms of armouring. Pronounced steep imbrication of platy-cobbles visible on the exposed up-estuary side of dunes is probably disrupted during flood tides leading to rapid reworking of the toe deposits facing up-estuary. In contrast, some crest and leeside locations have been stable for prolonged periods such that closely-fitted fabrics result; these portions of the bedforms are static and effectively are 'armour-plated'. Ebb-tide deposits of finer, ephemeral sandy-units occur on the down estuary side of the bedforms. Sandy-units (although

  20. Modelling temporal networks of human face-to-face contacts with public activity and individual reachability

    Science.gov (United States)

    Zhang, Yi-Qing; Cui, Jing; Zhang, Shu-Min; Zhang, Qi; Li, Xiang

    2016-02-01

    Modelling temporal networks of human face-to-face contacts is vital both for understanding the spread of airborne pathogens and word-of-mouth spreading of information. Although many efforts have been devoted to model these temporal networks, there are still two important social features, public activity and individual reachability, have been ignored in these models. Here we present a simple model that captures these two features and other typical properties of empirical face-to-face contact networks. The model describes agents which are characterized by an attractiveness to slow down the motion of nearby people, have event-triggered active probability and perform an activity-dependent biased random walk in a square box with periodic boundary. The model quantitatively reproduces two empirical temporal networks of human face-to-face contacts which are testified by their network properties and the epidemic spread dynamics on them.

  1. Erythrocyte orientation and lung conductivity analysis with a high temporal resolution FEM model for bioimpedance measurements

    NARCIS (Netherlands)

    Ulbrich, M.; Paluchowski, P.; Muehlsteff, J.; Leonhardt, S.

    2012-01-01

    Impedance cardiography (ICG) is a simple and cheap method to acquirehemodynamic parameters. In this work, the influence of three dynamic physiological sources has been analyzed using a model of the humanthorax with a high temporal resolution. Therefore, simulations havebeen conducted using the

  2. Kronecker-ARX models in identifying (2D) spatial-temporal systems

    NARCIS (Netherlands)

    Sinquin, B.; Verhaegen, M.H.G.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    In this paper we address the identification of (2D) spatial-temporal dynamical systems governed by the Vector Auto-Regressive (VAR) form. The coefficient-matrices of the VAR model are parametrized as sums of Kronecker products. When the number of terms in the sum is small compared to the size of

  3. Temporal and spatial dynamics of mineral levels of forage, soil and ...

    African Journals Online (AJOL)

    Temporal and spatial dynamics of mineral levels of forage, soil and cattle blood ... In the plain lands, local variations occurred for soil phosphorus and magnesium. ... Rangeland improvement and supplementation strategies are suggested to ...

  4. Brazilian Amazon Roads and Parks: Temporal & Spatial Deforestation Dynamics

    Science.gov (United States)

    Pfaff, A.; Robalino, J.

    2011-12-01

    Heterogeneous Forest Impacts of Transport Infrastructure: spatial frontier dynamics & impacts of Brazilian Amazon road changes Prior research on road impacts has almost completely ignored heterogeneity of impacts and as a result both empirically understated potential impact and missed policy potential. We note von Thunen's model suggests not only heterogeneity with distance from market but also specifically road impacts rising then falling with distance ('non-monoThunicity') Endogenous development and partial adjustment dynamics support this for the short run. Causal effects result from studying Brazilian Amazon deforestation (1976-87, 2000-04) using matching for short-run responses to lagged new roads changes (1968-75, 1985-00). We show the critical role of prior development, proxied by 1968 and 1985 road distances, for which exact matching addresses development trends and transforms impact estimates. Splitting the sample on this measure finds confirmation of the nonmonotonic predictions: new road impacts are relatively low if a prior road was close, such that prior transport access and endogenous development dynamics compete with the new road for influence, but also if a prior road was far, since first-decade adjustment in pristine areas is limited; yet in between these bounds, investments immediately raise deforestation significantly. This pattern helps to explain lower estimates within research on a single average impact. It suggests potential for REDD if a country chooses to shift its spatial transport networks. Protected Areas & Brazilian Amazon Deforestation: modeling and testing the impacts of varied PA strategies We model and then estimate the impacts of multiple types of protected areas upon 2000 - 2004 deforestation in the Brazilian Amazon. Our modeling starts with federal versus state objectives and predicts differences in both choice and implementation of each PA strategy that we examine. Our empirical examination brings not only breakdowns sufficient

  5. The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics.

    Science.gov (United States)

    McKenna, Erin; Bray, Laurence C Jayet; Zhou, Weiwei; Joiner, Wilsaan M

    2017-10-01

    Delays in transmitting and processing sensory information require correctly associating delayed feedback to issued motor commands for accurate error compensation. The flexibility of this alignment between motor signals and feedback has been demonstrated for movement recalibration to visual manipulations, but the alignment dependence for adapting movement dynamics is largely unknown. Here we examined the effect of visual feedback manipulations on force-field adaptation. Three subject groups used a manipulandum while experiencing a lag in the corresponding cursor motion (0, 75, or 150 ms). When the offset was applied at the start of the session (continuous condition), adaptation was not significantly different between groups. However, these similarities may be due to acclimation to the offset before motor adaptation. We tested additional subjects who experienced the same delays concurrent with the introduction of the perturbation (abrupt condition). In this case adaptation was statistically indistinguishable from the continuous condition, indicating that acclimation to feedback delay was not a factor. In addition, end-point errors were not significantly different across the delay or onset conditions, but end-point correction (e.g., deceleration duration) was influenced by the temporal offset. As an additional control, we tested a group of subjects who performed without visual feedback and found comparable movement adaptation results. These results suggest that visual feedback manipulation (absence or temporal misalignment) does not affect adaptation to novel dynamics, independent of both acclimation and perceptual awareness. These findings could have implications for modeling how the motor system adjusts to errors despite concurrent delays in sensory feedback information. NEW & NOTEWORTHY A temporal offset between movement and distorted visual feedback (e.g., visuomotor rotation) influences the subsequent motor recalibration, but the effects of this offset for

  6. The general dynamic model

    DEFF Research Database (Denmark)

    Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James

    2016-01-01

    Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...

  7. Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

    Science.gov (United States)

    Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

    2017-09-01

    Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

  8. Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

    DEFF Research Database (Denmark)

    Frelat, Romain; Lindegren, Martin; Dencker, Tim Spaanheden

    2017-01-01

    it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered...... by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii...

  9. Temporal dynamics of categorization: Forgetting as the basis of abstraction and generalization

    Directory of Open Access Journals (Sweden)

    Haley eVlach

    2014-09-01

    Full Text Available Historically, models of categorization have focused on how learners track frequencies and co-occurrence information to abstract relevant category features for generalization. The current study takes a different approach by examining how the temporal dynamics of categorization affect abstraction and generalization. In the learning phase of the experiment, all relevant category features were presented an equal number of times across category exemplars. However, the relevant features were presented on one of two learning schedules: massed or interleaved. At a series of immediate and delayed tests, learners were asked to generalize to novel exemplars that contained massed features, interleaved features, or all novel features. The results of this experiment revealed that, at an immediate test, learners more readily generalized based upon features presented on a massed schedule. Conversely, at a delayed test, learners more readily generalized based upon features presented on an interleaved schedule, until information was no longer readily retrievable from memory. These findings suggest that forgetting and retrieval processes engendered by the temporal dynamics of learning are used as a basis of abstraction, implicating forgetting as a central mechanism of generalization.

  10. Spatial and temporal dynamics of the genetic organization of small mammal populations

    International Nuclear Information System (INIS)

    Smith, M.H.; Manlove, M.N.; Joule, J.

    1978-01-01

    A functional population is a group of organisms and their offspring that contributes to a common gene pool within a certain area and time period. It is also the unit of evolution and should be viewed both in quantitative and qualitative terms. Selection, drift, dispersal, and mutation can alter the composition of populations. Spatial heterogeneity in allele frequencies argues for a conceptual model that has a series of relatively small populations semi-isolated from one another. Because of the relatively high levels of genetic variability characteristic of most mammalian species, significant amounts of gene flow between these spatially subdivided populations must occur when longer time periods are considered. Fluctuations in the genetic structure of populations seem to be important in altering the fitness of the individuals within the populations. The interaction of populations through gene flow is important in changing the levels of intrapopulational genetic variability. Populations can be characterized as existing on a continuum from relatively stable to unstable numbers and by other associated changes in their characteristics. Temporal changes in allele frequency occur in a variety of mammals. Conceptually, a species can be viewed as a series of dynamic populations that vary in numbers and quality in both a spatial and temporal context even over short distances and time periods. Short term changes in the quality of individuals in a population can be important in altering the short term dynamics of a population

  11. Spatial and Temporal Self-Calibration of a Hydroeconomic Model

    Science.gov (United States)

    Howitt, R. E.; Hansen, K. M.

    2008-12-01

    across key nodes on the network and to annual carryover storage at ground and surface water storage facilities. To our knowledge, this is the first hydroeconomic model to perform spatial and temporal calibration simultaneously. The base for the LFN model is CALVIN, a hydroeconomic optimization model of the California water system developed at the University of California, Davis (Draper, et al. 2003). The LFN model, programmed in GAMS, is nonlinear, which permits incorporation of dynamic groundwater pumping costs that reflect head elevation. Hydropower production, also nonlinear in storage levels, could be added in the future. In this paper, we describe model implementation and performance over a sequence of water years drawn from the historical hydrologic record in California. Preliminary findings indicate that calibration occurs within acceptable limits and simulations replicate base case results well. Cai, X., and Wang, D. 2006. "Calibrating Holistic Water Resources-Economic Models." Journal of Water Resources Planning and Management November-December. Draper, A.J., M.W. Jenkins, K.W. Kirby, J.R. Lund, and R.E. Howitt. 2003. "Economic-Engineering Optimization for California Water Management." Journal of Water Resources Planning and Management 129(3):155-164. Howitt, R.E. 1995. "Positive Mathematical Programming." American Journal of Agricultural Economics 77:329-342. Howitt, R.E. 1998. "Self-Calibrating Network Flow Models." Working Paper, Department of Agricultural and Resource Economics, University of California, Davis. October 1998. class="ab'>

  12. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  13. Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

    Science.gov (United States)

    Ma, Xiaoke; Sun, Penggang; Wang, Yu

    2018-04-01

    Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

  14. Dynamic Linear Models with R

    CERN Document Server

    Campagnoli, Patrizia; Petris, Giovanni

    2009-01-01

    State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.

  15. Large scale stochastic spatio-temporal modelling with PCRaster

    NARCIS (Netherlands)

    Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.

    2013-01-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model

  16. Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Vikas, E-mail: vikas.kumar@urv.cat [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Barros, Felipe P.J. de [Sonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles 90089, CA (United States); Schuhmacher, Marta [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier [Hydrogeology Group, Department of Geotechnical Engineering and Geosciences, University Politècnica de Catalunya-BarcelonaTech, Barcelona 08034 (Spain)

    2013-12-15

    Highlights: • Dynamic parametric interaction in daily dose prediction under uncertainty. • Importance of temporal dynamics associated with the dose. • Different dose experienced by different population cohorts as a function of time. • Relevance of uncertainty reduction in the input parameters shows temporal dynamism. -- Abstract: We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty.

  17. Spatio-temporal modeling of nonlinear distributed parameter systems

    CERN Document Server

    Li, Han-Xiong

    2011-01-01

    The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

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

    Science.gov (United States)

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

    2016-01-01

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

  19. Temporal dynamics of figure-ground segregation in human vision.

    Science.gov (United States)

    Neri, Peter; Levi, Dennis M

    2007-01-01

    The segregation of figure from ground is arguably one of the most fundamental operations in human vision. Neural signals reflecting this operation appear in cortex as early as 50 ms and as late as 300 ms after presentation of a visual stimulus, but it is not known when these signals are used by the brain to construct the percepts of figure and ground. We used psychophysical reverse correlation to identify the temporal window for figure-ground signals in human perception and found it to lie within the range of 100-160 ms. Figure enhancement within this narrow temporal window was transient rather than sustained as may be expected from measurements in single neurons. These psychophysical results prompt and guide further electrophysiological studies.

  20. Temporal dynamics of a subtropical urban forest in San Juan, Puerto Rico, 2001-2010

    Science.gov (United States)

    J. M. Tucker Lima; C. L. Staudhammer; T. J. Brandeis; F. J. Escobedo; W. Zipperer

    2013-01-01

    Several studies report urban tree growth and mortality rates as well as species composition, structural dynamics, and other characteristics of urban forests in mostly temperate, inland urban areas. Temporal dynamics of urban forests in subtropical and tropical forest regions are, until now, little explored and represent a new and important direction for study and...

  1. Dynamic models in research and management of biological invasions.

    Science.gov (United States)

    Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

    2017-07-01

    Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Integrated Spatio-Temporal Ecological Modeling System

    Science.gov (United States)

    1998-07-01

    models that we hold in our conscious (and subconscious ) minds. Chapter 3 explores how this approach is being augmented with the more formal capture...This approach makes it possible to add new simulation model components to I- STEMS without having to reprogram existing components. The steps required

  3. The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses.

    Directory of Open Access Journals (Sweden)

    Yotam Luz

    Full Text Available Spike-Timing Dependent Plasticity (STDP is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.

  4. Modelling dynamic roughness during floods

    NARCIS (Netherlands)

    Paarlberg, Andries; Dohmen-Janssen, Catarine M.; Hulscher, Suzanne J.M.H.; Termes, A.P.P.

    2007-01-01

    In this paper, we present a dynamic roughness model to predict water levels during floods. Hysteresis effects of dune development are explicitly included. It is shown that differences between the new dynamic roughness model, and models where the roughness coefficient is calibrated, are most

  5. Modeling the Temporal Nature of Human Behavior for Demographics Prediction

    DEFF Research Database (Denmark)

    Felbo, Bjarke; Sundsøy, Pål; Pentland, Alex

    2017-01-01

    Mobile phone metadata is increasingly used for humanitarian purposes in developing countries as traditional data is scarce. Basic demographic information is however often absent from mobile phone datasets, limiting the operational impact of the datasets. For these reasons, there has been a growing...... interest in predicting demographic information from mobile phone metadata. Previous work focused on creating increasingly advanced features to be modeled with standard machine learning algorithms. We here instead model the raw mobile phone metadata directly using deep learning, exploiting the temporal...... on both age and gender prediction using only the temporal modality in mobile metadata. We finally validate our method on low activity users and evaluate the modeling assumptions....

  6. Retinal Vascular and Oxygen Temporal Dynamic Responses to Light Flicker in Humans.

    Science.gov (United States)

    Felder, Anthony E; Wanek, Justin; Blair, Norman P; Shahidi, Mahnaz

    2017-11-01

    To mathematically model the temporal dynamic responses of retinal vessel diameter (D), oxygen saturation (SO2), and inner retinal oxygen extraction fraction (OEF) to light flicker and to describe their responses to its cessation in humans. In 16 healthy subjects (age: 60 ± 12 years), retinal oximetry was performed before, during, and after light flicker stimulation. At each time point, five metrics were measured: retinal arterial and venous D (DA, DV) and SO2 (SO2A, SO2V), and OEF. Intra- and intersubject variability of metrics was assessed by coefficient of variation of measurements before flicker within and among subjects, respectively. Metrics during flicker were modeled by exponential functions to determine the flicker-induced steady state metric values and the time constants of changes. Metrics after the cessation of flicker were compared to those before flicker. Intra- and intersubject variability for all metrics were less than 6% and 16%, respectively. At the flicker-induced steady state, DA and DV increased by 5%, SO2V increased by 7%, and OEF decreased by 13%. The time constants of DA and DV (14, 15 seconds) were twofold smaller than those of SO2V and OEF (39, 34 seconds). Within 26 seconds after the cessation of flicker, all metrics were not significantly different from before flicker values (P ≥ 0.07). Mathematical modeling revealed considerable differences in the time courses of changes among metrics during flicker, indicating flicker duration should be considered separately for each metric. Future application of this method may be useful to elucidate alterations in temporal dynamic responses to light flicker due to retinal diseases.

  7. Temporal variability in phosphorus transfers: classifying concentration-discharge event dynamics

    Science.gov (United States)

    Haygarth, P.; Turner, B. L.; Fraser, A.; Jarvis, S.; Harrod, T.; Nash, D.; Halliwell, D.; Page, T.; Beven, K.

    The importance of temporal variability in relationships between phosphorus (P) concentration (Cp) and discharge (Q) is linked to a simple means of classifying the circumstances of Cp-Q relationships in terms of functional types of response. New experimental data at the upstream interface of grassland soil and catchment systems at a range of scales (lysimeters to headwaters) in England and Australia are used to demonstrate the potential of such an approach. Three types of event are defined as Types 1-3, depending on whether the relative change in Q exceeds the relative change in Cp (Type 1), whether Cp and Q are positively inter-related (Type 2) and whether Cp varies yet Q is unchanged (Type 3). The classification helps to characterise circumstances that can be explained mechanistically in relation to (i) the scale of the study (with a tendency towards Type 1 in small scale lysimeters), (ii) the form of P with a tendency for Type 1 for soluble (i.e., <0.45 μm P forms) and (iii) the sources of P with Type 3 dominant where P availability overrides transport controls. This simple framework provides a basis for development of a more complex and quantitative classification of Cp-Q relationships that can be developed further to contribute to future models of P transfer and delivery from slope to stream. Studies that evaluate the temporal dynamics of the transfer of P are currently grossly under-represented in comparison with models based on static/spatial factors.

  8. Using temporal information to construct, update, and retrieve situation models of narratives

    NARCIS (Netherlands)

    Rinck, M.; Hähnel, A.; Becker, G.

    2001-01-01

    Four experiments explored how readers use temporal information to construct and update situation models and retrieve them from memory. In Experiment 1, readers spontaneously constructed temporal and spatial situation models of single sentences. In Experiment 2, temporal inconsistencies caused

  9. Bi-temporal 3D Active Appearance Modelling

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2005-01-01

    in fourdimensional MRI. The theoretical foundation of our work is the generative two-dimensional Active Appearance Models by Cootes et al., here extended to bi-temporal, three-dimensional models. Further issues treated include correction of respiratory induced slice displacements, systole detection, and a texture...

  10. Temporal-pattern learning in neural models

    CERN Document Server

    Genís, Carme Torras

    1985-01-01

    While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi­ mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica­ tion of the pacemaker neuron model proposed together with its valida­ tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve­ ral factors r...

  11. Demand-supply dynamics in tourism systems: A spatio-temporal GIS analysis. The Alberta ski industry case study

    Science.gov (United States)

    Bertazzon, Stefania

    The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new

  12. Dynamic Circuit Model for Spintronic Devices

    KAUST Repository

    Alawein, Meshal

    2017-01-09

    In this work we propose a finite-difference scheme based circuit model of a general spintronic device and benchmark it with other models proposed for spintronic switching devices. Our model is based on the four-component spin circuit theory and utilizes the widely used coupled stochastic magnetization dynamics/spin transport framework. In addition to the steady-state analysis, this work offers a transient analysis of carrier transport. By discretizing the temporal and spatial derivatives to generate a linear system of equations, we derive new and simple finite-difference conductance matrices that can, to the first order, capture both static and dynamic behaviors of a spintronic device. We also discuss an extension of the spin modified nodal analysis (SMNA) for time-dependent situations based on the proposed scheme.

  13. Dynamic Circuit Model for Spintronic Devices

    KAUST Repository

    Alawein, Meshal; Fariborzi, Hossein

    2017-01-01

    In this work we propose a finite-difference scheme based circuit model of a general spintronic device and benchmark it with other models proposed for spintronic switching devices. Our model is based on the four-component spin circuit theory and utilizes the widely used coupled stochastic magnetization dynamics/spin transport framework. In addition to the steady-state analysis, this work offers a transient analysis of carrier transport. By discretizing the temporal and spatial derivatives to generate a linear system of equations, we derive new and simple finite-difference conductance matrices that can, to the first order, capture both static and dynamic behaviors of a spintronic device. We also discuss an extension of the spin modified nodal analysis (SMNA) for time-dependent situations based on the proposed scheme.

  14. Population responses to environmental change in a tropical ant: the interaction of spatial and temporal dynamics.

    Science.gov (United States)

    Jackson, Doug; Vandermeer, John; Perfecto, Ivette; Philpott, Stacy M

    2014-01-01

    Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants' dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution - a signal of spatial self organization - but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations.

  15. Population responses to environmental change in a tropical ant: the interaction of spatial and temporal dynamics.

    Directory of Open Access Journals (Sweden)

    Doug Jackson

    Full Text Available Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants' dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution - a signal of spatial self organization - but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations.

  16. Threshold model of cascades in empirical temporal networks

    Science.gov (United States)

    Karimi, Fariba; Holme, Petter

    2013-08-01

    Threshold models try to explain the consequences of social influence like the spread of fads and opinions. Along with models of epidemics, they constitute a major theoretical framework of social spreading processes. In threshold models on static networks, an individual changes her state if a certain fraction of her neighbors has done the same. When there are strong correlations in the temporal aspects of contact patterns, it is useful to represent the system as a temporal network. In such a system, not only contacts but also the time of the contacts are represented explicitly. In many cases, bursty temporal patterns slow down disease spreading. However, as we will see, this is not a universal truth for threshold models. In this work we propose an extension of Watts’s classic threshold model to temporal networks. We do this by assuming that an agent is influenced by contacts which lie a certain time into the past. I.e., the individuals are affected by contacts within a time window. In addition to thresholds in the fraction of contacts, we also investigate the number of contacts within the time window as a basis for influence. To elucidate the model’s behavior, we run the model on real and randomized empirical contact datasets.

  17. Spatial and temporal infiltration dynamics during managed aquifer recharge.

    Science.gov (United States)

    Racz, Andrew J; Fisher, Andrew T; Schmidt, Calla M; Lockwood, Brian S; Los Huertos, Marc

    2012-01-01

    Natural groundwater recharge is inherently difficult to quantify and predict, largely because it comprises a series of processes that are spatially distributed and temporally variable. Infiltration ponds used for managed aquifer recharge (MAR) provide an opportunity to quantify recharge processes across multiple scales under semi-controlled conditions. We instrumented a 3-ha MAR infiltration pond to measure and compare infiltration patterns determined using whole-pond and point-specific methods. Whole-pond infiltration was determined by closing a transient water budget (accounting for inputs, outputs, and changes in storage), whereas point-specific infiltration rates were determined using heat as a tracer and time series analysis at eight locations in the base of the pond. Whole-pond infiltration, normalized for wetted area, rose rapidly to more than 1.0 m/d at the start of MAR operations (increasing as pond stage rose), was sustained at high rates for the next 40 d, and then decreased to less than 0.1 m/d by the end of the recharge season. Point-specific infiltration rates indicated high spatial and temporal variability, with the mean of measured values generally being lower than rates indicated by whole-pond calculations. Colocated measurements of head gradients within saturated soils below the pond were combined with infiltration rates to calculate soil hydraulic conductivity. Observations indicate a brief period of increasing saturated hydraulic conductivity, followed by a decrease of one to two orders of magnitude during the next 50 to 75 d. Locations indicating the most rapid infiltration shifted laterally during MAR operation, and we suggest that infiltration may function as a "variable source area" processes, conceptually similar to catchment runoff. © 2011, The Author(s). Ground Water © 2011, National Ground Water Association.

  18. Dynamic imaging in mild traumatic brain injury: support for the theory of medial temporal vulnerability.

    Science.gov (United States)

    Umile, Eric M; Sandel, M Elizabeth; Alavi, Abass; Terry, Charles M; Plotkin, Rosette C

    2002-11-01

    To determine whether patients with mild traumatic brain injury (TBI) and persistent postconcussive symptoms have evidence of temporal lobe injury on dynamic imaging. Case series. An academic medical center. Twenty patients with a clinical diagnosis of mild TBI and persistent postconcussive symptoms were referred for neuropsychologic evaluation and dynamic imaging. Fifteen (75%) had normal magnetic resonance imaging (MRI) and/or computed tomography (CT) scans at the time of injury. Neuropsychologic testing, positron-emission tomography (PET), and single-photon emission-computed tomography (SPECT). Temporal lobe findings on static imaging (MRI, CT) and dynamic imaging (PET, SPECT); neuropsychologic test findings on measures of verbal and visual memory. Testing documented neurobehavioral deficits in 19 patients (95%). Dynamic imaging documented abnormal findings in 18 patients (90%). Fifteen patients (75%) had temporal lobe abnormalities on PET and SPECT (primarily in medial temporal regions); abnormal findings were bilateral in 10 patients (50%) and unilateral in 5 (25%). Six patients (30%) had frontal abnormalities, and 8 (40%) had nonfrontotemporal abnormalities. Correlations between neuropsychologic testing and dynamic imaging could be established but not consistently across the whole group. Patients with mild TBI and persistent postconcussive symptoms have a high incidence of temporal lobe injury (presumably involving the hippocampus and related structures), which may explain the frequent finding of memory disorders in this population. The abnormal temporal lobe findings on PET and SPECT in humans may be analogous to the neuropathologic evidence of medial temporal injury provided by animal studies after mild TBI. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

  19. Spatio-temporal dynamics of a pulsed microwave argon plasma: ignition and afterglow

    International Nuclear Information System (INIS)

    Carbone, Emile; Sadeghi, Nader; Vos, Erik; Hübner, Simon; Van Veldhuizen, Eddie; Van Dijk, Jan; Nijdam, Sander; Kroesen, Gerrit

    2015-01-01

    In this paper, a detailed investigation of the spatio-temporal dynamics of a pulsed microwave plasma is presented. The plasma is ignited inside a dielectric tube in a repetitively pulsed regime at pressures ranging from 1 up to 100 mbar with pulse repetition frequencies from 200 Hz up to 500 kHz. Various diagnostic techniques are employed to obtain the main plasma parameters both spatially and with high temporal resolution. Thomson scattering is used to obtain the electron density and mean electron energy at fixed positions in the dielectric tube. The temporal evolution of the two resonant and two metastable argon 4s states are measured by laser diode absorption spectroscopy. Nanosecond time-resolved imaging of the discharge allows us to follow the spatio-temporal evolution of the discharge with high temporal and spatial resolution. Finally, the temporal evolution of argon 4p and higher states is measured by optical emission spectroscopy. The combination of these various diagnostics techniques gives deeper insight on the plasma dynamics during pulsed microwave plasma operation from low to high pressure regimes. The effects of the pulse repetition frequency on the plasma ignition dynamics are discussed and the plasma-off time is found to be the relevant parameter for the observed ignition modes. Depending on the delay between two plasma pulses, the dynamics of the ionization front are found to be changing dramatically. This is also reflected in the dynamics of the electron density and temperature and argon line emission from the plasma. On the other hand, the (quasi) steady state properties of the plasma are found to depend only weakly on the pulse repetition frequency and the afterglow kinetics present an uniform spatio-temporal behavior. However, compared to continuous operation, the time-averaged metastable and resonant state 4s densities are found to be significantly larger around a few kHz pulsing frequency. (paper)

  20. Evaluation of spatio-temporal Bayesian models for the spread of infectious diseases in oil palm.

    Science.gov (United States)

    Denis, Marie; Cochard, Benoît; Syahputra, Indra; de Franqueville, Hubert; Tisné, Sébastien

    2018-02-01

    In the field of epidemiology, studies are often focused on mapping diseases in relation to time and space. Hierarchical modeling is a common flexible and effective tool for modeling problems related to disease spread. In the context of oil palm plantations infected by the fungal pathogen Ganoderma boninense, we propose and compare two spatio-temporal hierarchical Bayesian models addressing the lack of information on propagation modes and transmission vectors. We investigate two alternative process models to study the unobserved mechanism driving the infection process. The models help gain insight into the spatio-temporal dynamic of the infection by identifying a genetic component in the disease spread and by highlighting a spatial component acting at the end of the experiment. In this challenging context, we propose models that provide assumptions on the unobserved mechanism driving the infection process while making short-term predictions using ready-to-use software. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Subliminal semantic priming changes the dynamic causal influence between the left frontal and temporal cortex.

    Science.gov (United States)

    Matsumoto, Atsushi; Kakigi, Ryusuke

    2014-01-01

    Recent neuroimaging experiments have revealed that subliminal priming of a target stimulus leads to the reduction of neural activity in specific regions concerned with processing the target. Such findings lead to questions about the degree to which the subliminal priming effect is based only on decreased activity in specific local brain regions, as opposed to the influence of neural mechanisms that regulate communication between brain regions. To address this question, this study recorded EEG during performance of a subliminal semantic priming task. We adopted an information-based approach that used independent component analysis and multivariate autoregressive modeling. Results indicated that subliminal semantic priming caused significant modulation of alpha band activity in the left inferior frontal cortex and modulation of gamma band activity in the left inferior temporal regions. The multivariate autoregressive approach confirmed significant increases in information flow from the inferior frontal cortex to inferior temporal regions in the early time window that was induced by subliminal priming. In the later time window, significant enhancement of bidirectional causal flow between these two regions underlying subliminal priming was observed. Results suggest that unconscious processing of words influences not only local activity of individual brain regions but also the dynamics of neural communication between those regions.

  2. Dynamics of Disagreement: Large-Scale Temporal Network Analysis Reveals Negative Interactions in Online Collaboration

    Science.gov (United States)

    Tsvetkova, Milena; García-Gavilanes, Ruth; Yasseri, Taha

    2016-11-01

    Disagreement and conflict are a fact of social life. However, negative interactions are rarely explicitly declared and recorded and this makes them hard for scientists to study. In an attempt to understand the structural and temporal features of negative interactions in the community, we use complex network methods to analyze patterns in the timing and configuration of reverts of article edits to Wikipedia. We investigate how often and how fast pairs of reverts occur compared to a null model in order to control for patterns that are natural to the content production or are due to the internal rules of Wikipedia. Our results suggest that Wikipedia editors systematically revert the same person, revert back their reverter, and come to defend a reverted editor. We further relate these interactions to the status of the involved editors. Even though the individual reverts might not necessarily be negative social interactions, our analysis points to the existence of certain patterns of negative social dynamics within the community of editors. Some of these patterns have not been previously explored and carry implications for the knowledge collection practice conducted on Wikipedia. Our method can be applied to other large-scale temporal collaboration networks to identify the existence of negative social interactions and other social processes.

  3. MODELING SPECTRAL AND TEMPORAL MASKING IN THE HUMAN AUDITORY SYSTEM

    DEFF Research Database (Denmark)

    Dau, Torsten; Jepsen, Morten Løve; Ewert, Stephan D.

    2007-01-01

    An auditory signal processing model is presented that simulates psychoacoustical data from a large variety of experimental conditions related to spectral and temporal masking. The model is based on the modulation filterbank model by Dau et al. [J. Acoust. Soc. Am. 102, 2892-2905 (1997)] but inclu......An auditory signal processing model is presented that simulates psychoacoustical data from a large variety of experimental conditions related to spectral and temporal masking. The model is based on the modulation filterbank model by Dau et al. [J. Acoust. Soc. Am. 102, 2892-2905 (1997...... was tested in conditions of tone-in-noise masking, intensity discrimination, spectral masking with tones and narrowband noises, forward masking with (on- and off-frequency) noise- and pure-tone maskers, and amplitude modulation detection using different noise carrier bandwidths. One of the key properties...

  4. Hybrid dynamics for currency modeling

    OpenAIRE

    Theodosopoulos, Ted; Trifunovic, Alex

    2006-01-01

    We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. im...

  5. Model Checking Temporal Logic Formulas Using Sticker Automata

    Science.gov (United States)

    Feng, Changwei; Wu, Huanmei

    2017-01-01

    As an important complex problem, the temporal logic model checking problem is still far from being fully resolved under the circumstance of DNA computing, especially Computation Tree Logic (CTL), Interval Temporal Logic (ITL), and Projection Temporal Logic (PTL), because there is still a lack of approaches for DNA model checking. To address this challenge, a model checking method is proposed for checking the basic formulas in the above three temporal logic types with DNA molecules. First, one-type single-stranded DNA molecules are employed to encode the Finite State Automaton (FSA) model of the given basic formula so that a sticker automaton is obtained. On the other hand, other single-stranded DNA molecules are employed to encode the given system model so that the input strings of the sticker automaton are obtained. Next, a series of biochemical reactions are conducted between the above two types of single-stranded DNA molecules. It can then be decided whether the system satisfies the formula or not. As a result, we have developed a DNA-based approach for checking all the basic formulas of CTL, ITL, and PTL. The simulated results demonstrate the effectiveness of the new method. PMID:29119114

  6. Urbanization Changes the Temporal Dynamics of Nutrients and Water Chemistry

    Science.gov (United States)

    Steele, M.; Badgley, B.

    2017-12-01

    Recent studies find that urban development alters the seasonal dynamics of nutrient concentrations, where the highest concentrations of nitrogen occurred during the winter in urban watersheds, rather than the summer. However, the effects of urbanization on the seasonal concentrations of other nutrients and chemical components is unknown. Therefore, to determine how urbanization changes the seasonal dynamics, once a week we measured concentrations of dissolved organic carbon (DOC), nutrients (NO3, DON, TN, PO4), base cations (Ca, Mg, Na, K), anions (F, Cl, SO4), pH, sediment, temperature, conductivity, and dissolved oxygen (DO) of nine urban, agricultural, and minimally developed watersheds in southwest Virginia, USA. We found that urbanization disrupted the seasonal dynamics of all metrics, except DON, PO4, Ca, sediment, and DO, where some shifted to high concentrations during the winter (Cl, conductivity), highs during late winter or spring (DOC, Na), a season low (TN, SO4, NO3) or high (NH4) during the summer, or remained more constant throughout the year compared to the reference watersheds (Mg, K, pH). The complex changes in seasonal dynamics coincide with a decoupling of common correlations between constituents; for example, DO and NO3 are negatively correlated in reference watersheds (NO3 increases, DO decreases), but positively correlated in urban watersheds. These results suggest that as watersheds become more intensely developed, the influence of natural drivers like temperature and vegetation become steadily overcome by the influence of urban drivers like deicing salts and wastewater leakage, which exert increasing control of seasonal water quality and aquatic habitat.

  7. Temporal dynamics and leaf trait variability in Neotropical dry forests

    Science.gov (United States)

    Hesketh, Michael Sean

    This thesis explores the variability of leaf traits resulting from changes in season, ecosystem successional stage, and site characteristics. In chapter two, I present a review of the use of remote sensing analysis for the evaluation of Neotropical dry forests. Here, I stress the conclusion, drawn from studies on land cover characterization, biodiversity assessment, and evaluation of forest structural characteristics, that addressing temporal variability in spectral properties is an essential element in the monitoring of these ecosystems. Chapter three describes the effect of wet-dry seasonality on spectral classification of tree and liana species. Highly accurate classification (> 80%) was possible using data from either the wet or dry season. However, this accuracy decreased by a factor of ten when data from the wet season was classified using an algorithm trained on the dry, or vice versa. I also address the potential creation of a spectral taxonomy of species, but found that any clustering based on spectral properties resulted in markedly different arrangements in the wet and dry seasons. In chapter 4, I address the variation present in both physical and spectral leaf traits according to changes in forest successional stage at dry forest sites in Mexico and Costa Rica. I found significant differences in leaf traits between successional stages, but more strongly so in Costa Rica. This variability deceased the accuracy of spectral classification of tree species by a factor of four when classifying data using an algorithm trained on a different successional stage. Chapter 5 shows the influence of seasonality and succession on trait variability in Mexico. Differences in leaf traits between successional stages were found to be greater during the dry season, but were sufficient in both seasons to negatively influence spectral classification of tree species. Throughout this thesis, I show clear and unambiguous evidence of the variability of key physical and spectral

  8. Annual and diurnal african biomass burning temporal dynamics

    Directory of Open Access Journals (Sweden)

    G. Roberts

    2009-05-01

    Full Text Available Africa is the single largest continental source of biomass burning emissions. Here we conduct the first analysis of one full year of geostationary active fire detections and fire radiative power data recorded over Africa at 15-min temporal interval and a 3 km sub-satellite spatial resolution by the Spinning Enhanced Visible and Infrared Imager (SEVIRI imaging radiometer onboard the Meteosat-8 satellite. We use these data to provide new insights into the rates and totals of open biomass burning over Africa, particularly into the extremely strong seasonal and diurnal cycles that exist across the continent. We estimate peak daily biomass combustion totals to be 9 and 6 million tonnes of fuel per day in the northern and southern hemispheres respectively, and total fuel consumption between February 2004 and January 2005 is estimated to be at least 855 million tonnes. Analysis is carried out with regard to fire pixel temporal persistence, and we note that the majority of African fires are detected only once in consecutive 15 min imaging slots. An investigation of the variability of the diurnal fire cycle is carried out with respect to 20 different land cover types, and whilst differences are noted between land covers, the fire diurnal cycle characteristics for most land cover type are very similar in both African hemispheres. We compare the Fire Radiative Power (FRP derived biomass combustion estimates to burned-areas, both at the scale of individual fires and over the entire continent at a 1-degree scale. Fuel consumption estimates are found to be less than 2 kg/m2 for all land cover types noted to be subject to significant fire activity, and for savanna grasslands where literature values are commonly reported the FRP-derived median fuel consumption estimate of 300 g/m2 is well within commonly quoted values. Meteosat-derived FRP data of the type presented here is now available freely to interested users continuously and in near

  9. Temporal dynamics of all-optical switching in Photonic Crystal Cavity

    DEFF Research Database (Denmark)

    Colman, Pierre; Heuck, Mikkel; Yu, Yi

    2014-01-01

    The temporal dynamics of all-optical switching has been investigated in a Photonic Crystal Cavity with a 150fs-40aJ/pulse resolution. This allowed observing for the first time effects like pulse reshaping, pulse delay and intra-cavity Four-Wave-Mixing.......The temporal dynamics of all-optical switching has been investigated in a Photonic Crystal Cavity with a 150fs-40aJ/pulse resolution. This allowed observing for the first time effects like pulse reshaping, pulse delay and intra-cavity Four-Wave-Mixing....

  10. Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

    Science.gov (United States)

    Juchem Neto, J. P.; Claeyssen, J. C. R.; Pôrto Júnior, S. S.

    2018-03-01

    In this paper we introduce capital transport cost in a unidimensional spatial Solow-Swan model of economic growth with capital-induced labor migration, considered in an unbounded domain. Proceeding with a stability analysis, we show that there is a critical value for the capital transport cost where the dynamic behavior of the economy changes, provided that the intensity of capital-induced labor migration is strong enough. On the one hand, if the capital transport cost is higher than this critical value, the spatially homogeneous equilibrium of coexistence of the model is stable, and the economy converges to this spatially homogeneous state in the long run; on the other hand, if transport cost is lower than this critical value, the equilibrium is unstable, and the economy may develop different spatio-temporal dynamics, including the formation of stable economic agglomerations and spatio-temporal economic cycles, depending on the other parameters in the model. Finally, numerical simulations support the results of the stability analysis, and illustrate the spatio-temporal dynamics generated by the model, suggesting that the economy as a whole benefits from the formation of economic agglomerations and cycles, with a higher capital transport cost reducing this gain.

  11. The financial accounting model from a system dynamics' perspective

    NARCIS (Netherlands)

    Melse, E.

    2006-01-01

    This paper explores the foundation of the financial accounting model. We examine the properties of the accounting equation as the principal algorithm for the design and the development of a System Dynamics model. Key to the perspective is the foundational requirement that resolves the temporal

  12. STABILITY AND DYNAMICS OF SPATIO-TEMPORAL STRUCTURES

    Energy Technology Data Exchange (ETDEWEB)

    Hermann Riecke

    2005-10-21

    This document constitutes the final report for the grant. It provides a complete list of publications and presentations that arose from the project as well as a brief description of the highlights of the research results. The research funded by this grant has provided insights into the spontaneous formation of structures of increasing complexity in systems driven far from thermodynamic equilibrium. A classic example of such a system is thermally driven convection in a horizontal fluid layer. Highlights of the research are: (1) explanation of the localized traveling wave pulses observed in binary-mixture convection, (2) explanation of the localized waves in electroconvection, (3) introduction of a new diagnostics for spatially and temporally chaotic states, which is based on the statistics of defect trajectories, (4) prediction of complex states in thermally driven convection in rotating systems. Additional contributions provided insight into the localization mechanism for oscillons, the prediction of a new localization mechanism for traveling waves based on a resonant periodic forcing, and an analysis of the stability of quasi-periodic patterns.

  13. Temporal validation for landsat-based volume estimation model

    Science.gov (United States)

    Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan

    2015-01-01

    Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

  14. Theoretical foundations: Formalized temporal models for hyperlinked multimedia documents

    NARCIS (Netherlands)

    B. Meixner (Britta)

    2018-01-01

    textabstractConsistent linking and accurate synchronization of multimedia elements in hypervideos or multimedia documents are essential to provide a good quality of experience to viewers. Temporal models are needed to define relationships and constraints between multimedia elements and create an

  15. The gamma model : a new neural network for temporal processing

    NARCIS (Netherlands)

    Vries, de B.

    1992-01-01

    In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.

  16. Encoding model of temporal processing in human visual cortex.

    Science.gov (United States)

    Stigliani, Anthony; Jeska, Brianna; Grill-Spector, Kalanit

    2017-12-19

    How is temporal information processed in human visual cortex? Visual input is relayed to V1 through segregated transient and sustained channels in the retina and lateral geniculate nucleus (LGN). However, there is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. The prevailing view associates transient processing predominately with motion-sensitive regions and sustained processing with ventral stream regions, while the opposing view suggests that both temporal channels contribute to neural processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli and then implemented a two temporal channel-encoding model to evaluate the contributions of each channel. Different from the general linear model of fMRI that predicts responses directly from the stimulus, the encoding approach first models neural responses to the stimulus from which fMRI responses are derived. This encoding approach not only predicts cortical responses to time-varying stimuli from milliseconds to seconds but also, reveals differential contributions of temporal channels across visual cortex. Consistent with the prevailing view, motion-sensitive regions and adjacent lateral occipitotemporal regions are dominated by transient responses. However, ventral occipitotemporal regions are driven by both sustained and transient channels, with transient responses exceeding the sustained. These findings propose a rethinking of temporal processing in the ventral stream and suggest that transient processing may contribute to rapid extraction of the content of the visual input. Importantly, our encoding approach has vast implications, because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain. Copyright © 2017 the Author(s). Published by PNAS.

  17. Computer Modelling of Dynamic Processes

    Directory of Open Access Journals (Sweden)

    B. Rybakin

    2000-10-01

    Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.

  18. Practical considerations for high spatial and temporal resolution dynamic transmission electron microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, Michael R. [Materials Science and Technology Division, Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-356, Livermore, CA 94550 (United States)], E-mail: armstrong30@llnl.gov; Boyden, Ken [Materials Science and Technology Division, Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-356, Livermore, CA 94550 (United States); Browning, Nigel D. [Materials Science and Technology Division, Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-356, Livermore, CA 94550 (United States); Department of Chemical Engineering and Materials Science, University of California-Davis, One Shields Avenue, Davis, CA 95616 (United States); Campbell, Geoffrey H.; Colvin, Jeffrey D.; De Hope, William J.; Frank, Alan M. [Materials Science and Technology Division, Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-356, Livermore, CA 94550 (United States); Gibson, David J.; Hartemann, Fred [N Division, Physics and Advanced Technologies Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-280, Livermore, CA 94550 (United States); Kim, Judy S. [Materials Science and Technology Division, Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-356, Livermore, CA 94550 (United States); Department of Chemical Engineering and Materials Science, University of California-Davis, One Shields Avenue, Davis, CA 95616 (United States); King, Wayne E.; La Grange, Thomas B.; Pyke, Ben J.; Reed, Bryan W.; Shuttlesworth, Richard M.; Stuart, Brent C.; Torralva, Ben R. [Materials Science and Technology Division, Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, P.O. Box 808, L-356, Livermore, CA 94550 (United States)

    2007-04-15

    Although recent years have seen significant advances in the spatial resolution possible in the transmission electron microscope (TEM), the temporal resolution of most microscopes is limited to video rate at best. This lack of temporal resolution means that our understanding of dynamic processes in materials is extremely limited. High temporal resolution in the TEM can be achieved, however, by replacing the normal thermionic or field emission source with a photoemission source. In this case the temporal resolution is limited only by the ability to create a short pulse of photoexcited electrons in the source, and this can be as short as a few femtoseconds. The operation of the photo-emission source and the control of the subsequent pulse of electrons (containing as many as 5x10{sup 7} electrons) create significant challenges for a standard microscope column that is designed to operate with a single electron in the column at any one time. In this paper, the generation and control of electron pulses in the TEM to obtain a temporal resolution <10{sup -6} s will be described and the effect of the pulse duration and current density on the spatial resolution of the instrument will be examined. The potential of these levels of temporal and spatial resolution for the study of dynamic materials processes will also be discussed.

  19. Practical considerations for high spatial and temporal resolution dynamic transmission electron microscopy

    International Nuclear Information System (INIS)

    Armstrong, Michael R.; Boyden, Ken; Browning, Nigel D.; Campbell, Geoffrey H.; Colvin, Jeffrey D.; De Hope, William J.; Frank, Alan M.; Gibson, David J.; Hartemann, Fred; Kim, Judy S.; King, Wayne E.; La Grange, Thomas B.; Pyke, Ben J.; Reed, Bryan W.; Shuttlesworth, Richard M.; Stuart, Brent C.; Torralva, Ben R.

    2007-01-01

    Although recent years have seen significant advances in the spatial resolution possible in the transmission electron microscope (TEM), the temporal resolution of most microscopes is limited to video rate at best. This lack of temporal resolution means that our understanding of dynamic processes in materials is extremely limited. High temporal resolution in the TEM can be achieved, however, by replacing the normal thermionic or field emission source with a photoemission source. In this case the temporal resolution is limited only by the ability to create a short pulse of photoexcited electrons in the source, and this can be as short as a few femtoseconds. The operation of the photo-emission source and the control of the subsequent pulse of electrons (containing as many as 5x10 7 electrons) create significant challenges for a standard microscope column that is designed to operate with a single electron in the column at any one time. In this paper, the generation and control of electron pulses in the TEM to obtain a temporal resolution -6 s will be described and the effect of the pulse duration and current density on the spatial resolution of the instrument will be examined. The potential of these levels of temporal and spatial resolution for the study of dynamic materials processes will also be discussed

  20. Temporal Expectations Guide Dynamic Prioritization in Visual Working Memory through Attenuated α Oscillations.

    Science.gov (United States)

    van Ede, Freek; Niklaus, Marcel; Nobre, Anna C

    2017-01-11

    Although working memory is generally considered a highly dynamic mnemonic store, popular laboratory tasks used to understand its psychological and neural mechanisms (such as change detection and continuous reproduction) often remain relatively "static," involving the retention of a set number of items throughout a shared delay interval. In the current study, we investigated visual working memory in a more dynamic setting, and assessed the following: (1) whether internally guided temporal expectations can dynamically and reversibly prioritize individual mnemonic items at specific times at which they are deemed most relevant; and (2) the neural substrates that support such dynamic prioritization. Participants encoded two differently colored oriented bars into visual working memory to retrieve the orientation of one bar with a precision judgment when subsequently probed. To test for the flexible temporal control to access and retrieve remembered items, we manipulated the probability for each of the two bars to be probed over time, and recorded EEG in healthy human volunteers. Temporal expectations had a profound influence on working memory performance, leading to faster access times as well as more accurate orientation reproductions for items that were probed at expected times. Furthermore, this dynamic prioritization was associated with the temporally specific attenuation of contralateral α (8-14 Hz) oscillations that, moreover, predicted working memory access times on a trial-by-trial basis. We conclude that attentional prioritization in working memory can be dynamically steered by internally guided temporal expectations, and is supported by the attenuation of α oscillations in task-relevant sensory brain areas. In dynamic, everyday-like, environments, flexible goal-directed behavior requires that mental representations that are kept in an active (working memory) store are dynamic, too. We investigated working memory in a more dynamic setting than is conventional

  1. The interplay between perceptual organization and object recognition: Temporal dynamics and neuropsychology

    OpenAIRE

    Torfs, Katrien

    2012-01-01

    The ease and efficiency with which we perceive objects in daily life masks the complexity of the processes involved. The main goal of my doctoral research was to enhance our understanding of the complex interplay between perceptual organization and object recognition. To this end, we investigated the dynamic interplay between different component processes of object recognition, and their temporal dynamics. In the first part of this thesis, I present three behavioral studies focusing on the ro...

  2. Bioluminescence in a complex coastal environment: 1. Temporal dynamics of nighttime water-leaving radiance

    Science.gov (United States)

    Moline, Mark A.; Oliver, Matthew J.; Mobley, Curtis D.; Sundman, Lydia; Bensky, Thomas; Bergmann, Trisha; Bissett, W. Paul; Case, James; Raymond, Erika H.; Schofield, Oscar M. E.

    2007-11-01

    Nighttime water-leaving radiance is a function of the depth-dependent distribution of both the in situ bioluminescence emissions and the absorption and scattering properties of the water. The vertical distributions of these parameters were used as inputs for a modified one-dimensional radiative transfer model to solve for spectral bioluminescence water-leaving radiance from prescribed depths of the water column. Variation in the water-leaving radiance was consistent with local episodic physical forcing events, with tidal forcing, terrestrial runoff, particulate accumulation, and biological responses influencing the shorter timescale dynamics. There was a >90 nm shift in the peak water-leaving radiance from blue (˜474 nm) to green as light propagated to the surface. In addition to clues in ecosystem responses to physical forcing, the temporal dynamics in intensity and spectral quality of water-leaving radiance provide suitable ranges for assessing detection. This may provide the information needed to estimate the depth of internal light sources in the ocean, which is discussed in part 2 of this paper.

  3. The Temporal Signature of Memories: Identification of a General Mechanism for Dynamic Memory Replay in Humans

    Science.gov (United States)

    Michelmann, Sebastian; Bowman, Howard; Hanslmayr, Simon

    2016-01-01

    Reinstatement of dynamic memories requires the replay of neural patterns that unfold over time in a similar manner as during perception. However, little is known about the mechanisms that guide such a temporally structured replay in humans, because previous studies used either unsuitable methods or paradigms to address this question. Here, we overcome these limitations by developing a new analysis method to detect the replay of temporal patterns in a paradigm that requires participants to mentally replay short sound or video clips. We show that memory reinstatement is accompanied by a decrease of low-frequency (8 Hz) power, which carries a temporal phase signature of the replayed stimulus. These replay effects were evident in the visual as well as in the auditory domain and were localized to sensory-specific regions. These results suggest low-frequency phase to be a domain-general mechanism that orchestrates dynamic memory replay in humans. PMID:27494601

  4. The Temporal Signature of Memories: Identification of a General Mechanism for Dynamic Memory Replay in Humans.

    Directory of Open Access Journals (Sweden)

    Sebastian Michelmann

    2016-08-01

    Full Text Available Reinstatement of dynamic memories requires the replay of neural patterns that unfold over time in a similar manner as during perception. However, little is known about the mechanisms that guide such a temporally structured replay in humans, because previous studies used either unsuitable methods or paradigms to address this question. Here, we overcome these limitations by developing a new analysis method to detect the replay of temporal patterns in a paradigm that requires participants to mentally replay short sound or video clips. We show that memory reinstatement is accompanied by a decrease of low-frequency (8 Hz power, which carries a temporal phase signature of the replayed stimulus. These replay effects were evident in the visual as well as in the auditory domain and were localized to sensory-specific regions. These results suggest low-frequency phase to be a domain-general mechanism that orchestrates dynamic memory replay in humans.

  5. Models of neural dynamics in brain information processing - the developments of 'the decade'

    International Nuclear Information System (INIS)

    Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B; Ivanitskii, Genrikh R

    2002-01-01

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

  6. Longitudinal structure in temperate stream fish communities: evaluating conceptual models with temporal data

    Science.gov (United States)

    Roberts, James H.; Hitt, Nathaniel P.

    2010-01-01

    Five conceptual models of longitudinal fish community organization in streams were examined: (1) niche diversity model (NDM), (2) stream continuum model (SCM), (3) immigrant accessibility model (IAM), (4) environmental stability model (ESM), and (5) adventitious stream model (ASM). We used differences among models in their predictions about temporal species turnover, along with five spatiotemporal fish community data sets, to evaluate model applicability. Models were similar in predicting a positive species richness–stream size relationship and longitudinal species nestedness, but differed in predicting either similar temporal species turnover throughout the stream continuum (NDM, SCM), higher turnover upstream (IAM, ESM), or higher turnover downstream (ASM). We calculated measures of spatial and temporal variation from spatiotemporal fish data in five wadeable streams in central and eastern North America spanning 34–68 years (French Creek [New York], Piasa Creek [Illinois], Spruce Run [Virginia], Little Stony Creek [Virginia], and Sinking Creek [Virginia]). All streams exhibited substantial species turnover (i.e., at least 27% turnover in stream-scale species pools), in contrast to the predictions of the SCM. Furthermore, community change was greater in downstream than upstream reaches in four of five streams. This result is most consistent with the ASM and suggests that downstream communities are strongly influenced by migrants to and from species pools outside the focal stream. In Sinking Creek, which is isolated from external species pools, temporal species turnover (via increased richness) was higher upstream than downstream, which is a pattern most consistent with the IAM or ESM. These results corroborate the hypothesis that temperate stream habitats and fish communities are temporally dynamic and that fish migration and environmental disturbances play fundamental roles in stream fish community organization.

  7. Temporal dynamics of motor cortex excitability during perception of natural emotional scenes

    NARCIS (Netherlands)

    Borgomaneri, Sara; Gazzola, Valeria; Avenanti, Alessio

    2014-01-01

    Although it is widely assumed that emotions prime the body for action, the effects of visual perception of natural emotional scenes on the temporal dynamics of the human motor system have scarcely been investigated. Here, we used single-pulse transcranial magnetic stimulation (TMS) to assess motor

  8. The Temporal Dynamics of Spoken Word Recognition in Adverse Listening Conditions

    Science.gov (United States)

    Brouwer, Susanne; Bradlow, Ann R.

    2016-01-01

    This study examined the temporal dynamics of spoken word recognition in noise and background speech. In two visual-world experiments, English participants listened to target words while looking at four pictures on the screen: a target (e.g. "candle"), an onset competitor (e.g. "candy"), a rhyme competitor (e.g.…

  9. Temporal dynamics of reward anticipation in the human brain.

    Science.gov (United States)

    Zhang, Yuanyuan; Li, Qi; Wang, Zhao; Liu, Xun; Zheng, Ya

    2017-09-01

    Reward anticipation is a complex process including cue evaluation, motor preparation, and feedback anticipation. The present study investigated whether these psychological processes were dissociable on neural dynamics in terms of incentive valence and approach motivation. We recorded EEG when participants were performing a monetary incentive delay task, and found a cue-P3 during the cue-evaluation stage, a contingent negative variation (CNV) during the motor-preparation stage, and a stimulus-preceding negativity (SPN) during the feedback-anticipation stage. Critically, both the cue-P3 and SPN exhibited an enhanced sensitivity to gain versus loss anticipation, which was not observed for the CNV. Moreover, both the cue-P3 and SPN, instead of the CNV, for gain anticipation selectively predicted the participants' approach motivation as measured in a following effort expenditure for rewards task, particularly when reward uncertainty was maximal. Together, these results indicate that reward anticipation consists of several sub-stages, each with distinct functional significance, thus providing implications for neuropsychiatric diseases characterized by dysfunction in anticipatory reward processing. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. An American termite in Paris: temporal colony dynamics.

    Science.gov (United States)

    Baudouin, Guillaume; Dedeine, Franck; Bech, Nicolas; Bankhead-Dronnet, Stéphanie; Dupont, Simon; Bagnères, Anne-Geneviève

    2017-12-01

    Termites of the genus Reticulitermes are widespread invaders, particularly in urban habitats. Their cryptic and subterranean lifestyle makes them difficult to detect, and we know little about their colony dynamics over time. In this study we examined the persistence of Reticulitermes flavipes (Kollar) colonies in the city of Paris over a period of 15 years. The aim was (1) to define the boundaries of colonies sampled within the same four areas over two sampling periods, (2) to determine whether the colonies identified during the first sampling period persisted to the second sampling period, and (3) to compare the results obtained when colonies were delineated using a standard population genetic approach versus a Bayesian clustering method that combined both spatial and genetic information. Herein, colony delineations were inferred from genetic differences at nine microsatellite loci and one mitochondrial locus. Four of the 18 identified colonies did not show significant differences in their genotype distributions between the two sampling periods. While allelic richness was low, making it hard to reliably distinguish colony family type, most colonies appeared to retain the same breeding structure over time. These large and expansive colonies showed an important ability to fuse (39% were mixed-family colonies), contained hundreds of reproductives and displayed evidence of isolation-by-distance, suggesting budding dispersal. These traits, which favor colony persistence over time, present a challenge for pest control efforts, which apply treatment locally. The other colonies showed significant differences, but we cannot exclude the possibility that their genotype distributions simply changed over time.

  11. A Spatio-Temporal Enhanced Metadata Model for Interdisciplinary Instant Point Observations in Smart Cities

    Directory of Open Access Journals (Sweden)

    Nengcheng Chen

    2017-02-01

    Full Text Available Due to the incomprehensive and inconsistent description of spatial and temporal information for city data observed by sensors in various fields, it is a great challenge to share the massive, multi-source and heterogeneous interdisciplinary instant point observation data resources. In this paper, a spatio-temporal enhanced metadata model for point observation data sharing was proposed. The proposed Data Meta-Model (DMM focused on the spatio-temporal characteristics and formulated a ten-tuple information description structure to provide a unified and spatio-temporal enhanced description of the point observation data. To verify the feasibility of the point observation data sharing based on DMM, a prototype system was established, and the performance improvement of Sensor Observation Service (SOS for the instant access and insertion of point observation data was realized through the proposed MongoSOS, which is a Not Only SQL (NoSQL SOS based on the MongoDB database and has the capability of distributed storage. For example, the response time of the access and insertion for navigation and positioning data can be realized at the millisecond level. Case studies were conducted, including the gas concentrations monitoring for the gas leak emergency response and the smart city public vehicle monitoring based on BeiDou Navigation Satellite System (BDS used for recording the dynamic observation information. The results demonstrated the versatility and extensibility of the DMM, and the spatio-temporal enhanced sharing for interdisciplinary instant point observations in smart cities.

  12. Amnesia, rehearsal, and temporal distinctiveness models of recall.

    Science.gov (United States)

    Brown, Gordon D A; Della Sala, Sergio; Foster, Jonathan K; Vousden, Janet I

    2007-04-01

    Classical amnesia involves selective memory impairment for temporally distant items in free recall (impaired primacy) together with relative preservation of memory for recency items. This abnormal serial position curve is traditionally taken as evidence for a distinction between different memory processes, with amnesia being associated with selectively impaired long-term memory. However recent accounts of normal serial position curves have emphasized the importance of rehearsal processes in giving rise to primacy effects and have suggested that a single temporal distinctiveness mechanism can account for both primacy and recency effects when rehearsal is considered. Here we explore the pattern of strategic rehearsal in a patient with very severe amnesia. When the patient's rehearsal pattern is taken into account, a temporal distinctiveness model can account for the serial position curve in both amnesic and control free recall. The results are taken as consistent with temporal distinctiveness models of free recall, and they motivate an emphasis on rehearsal patterns in understanding amnesic deficits in free recall.

  13. Structural dynamic modifications via models

    Indian Academy of Sciences (India)

    The study shows that as many as half of the matrix ... the dynamicist's analytical modelling skill which would appear both in the numerator as. Figure 2. ..... Brandon J A 1990 Strategies for structural dynamic modification (New York: John Wiley).

  14. Dynamic programming models and applications

    CERN Document Server

    Denardo, Eric V

    2003-01-01

    Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.

  15. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel

    2017-10-13

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  16. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2017-01-01

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  17. EEG Based Inference of Spatio-Temporal Brain Dynamics

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese

    Electroencephalography (EEG) provides a measure of brain activity and has improved our understanding of the brain immensely. However, there is still much to be learned and the full potential of EEG is yet to be realized. In this thesis we suggest to improve the information gain of EEG using three...... different approaches; 1) by recovery of the EEG sources, 2) by representing and inferring the propagation path of EEG sources, and 3) by combining EEG with functional magnetic resonance imaging (fMRI). The common goal of the methods, and thus of this thesis, is to improve the spatial dimension of EEG...... recovery ability. The forward problem describes the propagation of neuronal activity in the brain to the EEG electrodes on the scalp. The geometry and conductivity of the head layers are normally required to model this path. We propose a framework for inferring forward models which is based on the EEG...

  18. An assessment of the temporal dynamics of moral decisions

    OpenAIRE

    Gregory J. Koop

    2013-01-01

    In the domain of moral decision making, models in which emotion and deliberation constitute competing dual-systems have become increasingly popular. Currently, the favored explanation of this interaction is what Evans (2008) termed a ``default-interventionist'' (DI) process where moral decisions are the result of a prepotent emotional response, which can be overridden with substantial deliberative effort. Although this ``emotion-then-deliberation'' sequence is often assumed, existing methods ...

  19. Dynamical models of the Galaxy

    Directory of Open Access Journals (Sweden)

    McMillan P.J.

    2012-02-01

    Full Text Available I discuss the importance of dynamical models for exploiting survey data, focusing on the advantages of “torus” models. I summarize a number of applications of these models to the study of the Milky Way, including the determination of the peculiar Solar velocity and investigation of the Hyades moving group.

  20. Evolution of predator dispersal in relation to spatio-temporal prey dynamics: how not to get stuck in the wrong place!

    Directory of Open Access Journals (Sweden)

    Justin M J Travis

    Full Text Available The eco-evolutionary dynamics of dispersal are recognised as key in determining the responses of populations to environmental changes. Here, by developing a novel modelling approach, we show that predators are likely to have evolved to emigrate more often and become more selective over their destination patch when their prey species exhibit spatio-temporally complex dynamics. We additionally demonstrate that the cost of dispersal can vary substantially across space and time. Perhaps as a consequence of current environmental change, many key prey species are currently exhibiting major shifts in their spatio-temporal dynamics. By exploring similar shifts in silico, we predict that predator populations will be most vulnerable when prey dynamics shift from stable to complex. The more sophisticated dispersal rules, and greater variance therein, that evolve under complex dynamics will enable persistence across a broader range of prey dynamics than the rules which evolve under relatively stable prey conditions.

  1. Attention increases the temporal precision of conscious perception: verifying the Neural-ST Model.

    Directory of Open Access Journals (Sweden)

    Srivas Chennu

    2009-11-01

    Full Text Available What role does attention play in ensuring the temporal precision of visual perception? Behavioural studies have investigated feature selection and binding in time using fleeting sequences of stimuli in the Rapid Serial Visual Presentation (RSVP paradigm, and found that temporal accuracy is reduced when attentional control is diminished. To reduce the efficacy of attentional deployment, these studies have employed the Attentional Blink (AB phenomenon. In this article, we use electroencephalography (EEG to directly investigate the temporal dynamics of conscious perception. Specifically, employing a combination of experimental analysis and neural network modelling, we test the hypothesis that the availability of attention reduces temporal jitter in the latency between a target's visual onset and its consolidation into working memory. We perform time-frequency analysis on data from an AB study to compare the EEG trials underlying the P3 ERPs (Event-related Potential evoked by targets seen outside vs. inside the AB time window. We find visual differences in phase-sorted ERPimages and statistical differences in the variance of the P3 phase distributions. These results argue for increased variation in the latency of conscious perception during the AB. This experimental analysis is complemented by a theoretical exploration of temporal attention and target processing. Using activation traces from the Neural-ST(2 model, we generate virtual ERPs and virtual ERPimages. These are compared to their human counterparts to propose an explanation of how target consolidation in the context of the AB influences the temporal variability of selective attention. The AB provides us with a suitable phenomenon with which to investigate the interplay between attention and perception. The combination of experimental and theoretical elucidation in this article contributes to converging evidence for the notion that the AB reflects a reduction in the temporal acuity of

  2. Exploring the isotopic niche: isotopic variance, physiological incorporation, and the temporal dynamics of foraging

    Directory of Open Access Journals (Sweden)

    Justin Douglas Yeakel

    2016-01-01

    Full Text Available Consumer foraging behaviors are dynamic, changing in response to prey availability, seasonality, competition, and even the consumer's physiological state. The isotopic composition of a consumer is a product of these factors as well as the isotopic `landscape' of its prey, i.e. the isotopic mixing space. Stable isotope mixing models are used to back-calculate the most likely proportional contribution of a set of prey to a consumer's diet based on their respective isotopic distributions, however they are disconnected from ecological process. Here we build a mechanistic framework that links the ecological and physiological processes of an individual consumer to the isotopic distribution that describes its diet, and ultimately to the isotopic composition of its own tissues, defined as its `isotopic niche’. By coupling these processes, we systematically investigate under what conditions the isotopic niche of a consumer changes as a function of both the geometric properties of its mixing space and foraging strategies that may be static or dynamic over time. Results of our derivations reveal general insight into the conditions impacting isotopic niche width as a function of consumer specialization on prey, as well as the consumer's ability to transition between diets over time. We show analytically that moderate specialization on isotopically unique prey can serve to maximize a consumer's isotopic niche width, while temporally dynamic diets will tend to result in peak isotopic variance during dietary transitions. We demonstrate the relevance of our theoretical findings by examining a marine system composed of nine invertebrate species commonly consumed by sea otters. In general, our analytical framework highlights the complex interplay of mixing space geometry and consumer dietary behavior in driving expansion and contraction of the isotopic niche. Because this approach is established on ecological mechanism, it is well-suited for enhancing the

  3. Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hansen, Lars Kai

    2016-01-01

    the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging......Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding...

  4. Spatial-temporal modeling of malware propagation in networks.

    Science.gov (United States)

    Chen, Zesheng; Ji, Chuanyi

    2005-09-01

    Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.

  5. Reconstruction of tissue dynamics in the compressed breast using multiplexed measurements and temporal basis functions

    Science.gov (United States)

    Boverman, Gregory; Miller, Eric L.; Brooks, Dana H.; Fang, Qianqian; Carp, S. A.; Selb, J. J.; Boas, David A.

    2007-02-01

    In the course of our experiments imaging the compressed breast in conjunction with digital tomosynthesis, we have noted that significant changes in tissue optical properties, on the order of 5%, occur during our imaging protocol. These changes seem to consistent with changes both in total Hemoglobin concentration as well as in oxygen saturation, as was the case for our standalone breast compression study, which made use of reflectance measurements. Simulation experiments show the importance of taking into account the temporal dynamics in the image reconstruction, and demonstrate the possibility of imaging the spatio-temporal dynamics of oxygen saturation and total Hemoglobin in the breast. In the image reconstruction, we make use of spatio-temporal basis functions, specifically a voxel basis for spatial imaging, and a cubic spline basis in time, and we reconstruct the spatio-temporal images using the entire data set simultaneously, making use of both absolute and relative measurements in the cost function. We have modified the sequence of sources used in our imaging acquisition protocol to improve our temporal resolution, and preliminary results are shown for normal subjects.

  6. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  7. Portraying Temporal Dynamics of Urban Spatial Divisions with Mobile Phone Positioning Data: A Complex Network Approach

    Directory of Open Access Journals (Sweden)

    Meng Zhou

    2016-12-01

    Full Text Available Spatial structure is a fundamental characteristic of cities that influences the urban functioning to a large extent. While administrative partitioning is generally done in the form of static spatial division, understanding a more temporally dynamic structure of the urban space would benefit urban planning and management immensely. This study makes use of a large-scale mobile phone positioning dataset to characterize the diurnal dynamics of the interaction-based urban spatial structure. To extract the temporally vibrant structure, spatial interaction networks at different times are constructed based on the movement connections of individuals between geographical units. Complex network community detection technique is applied to identify the spatial divisions as well as to quantify their temporal dynamics. Empirical analysis is conducted using data containing all user positions on a typical weekday in Shenzhen, China. Results are compared with official zoning and planned structure and indicate a certain degree of expansion in urban central areas and fragmentation in industrial suburban areas. A high level of variability in spatial divisions at different times of day is detected with some distinct temporal features. Peak and pre-/post-peak hours witness the most prominent fluctuation in spatial division indicating significant change in the characteristics of movements and activities during these periods of time. Findings of this study demonstrate great potential of large-scale mobility data in supporting intelligent spatial decision making and providing valuable knowledge to the urban planning sectors.

  8. Temporal dynamics of selective attention and conflict resolution during cross-dimensional go-nogo decisions

    Directory of Open Access Journals (Sweden)

    Moschner Carsten

    2007-08-01

    Full Text Available Abstract Background Decision-making is a fundamental capacity which is crucial to many higher-order psychological functions. We recorded event-related potentials (ERPs during a visual target-identification task that required go-nogo choices. Targets were identified on the basis of cross-dimensional conjunctions of particular colors and forms. Color discriminability was manipulated in three conditions to determine the effects of color distinctiveness on component processes of decision-making. Results Target identification was accompanied by the emergence of prefrontal P2a and P3b. Selection negativity (SN revealed that target-compatible features captured attention more than target-incompatible features, suggesting that intra-dimensional attentional capture was goal-contingent. No changes of cross-dimensional selection priorities were measurable when color discriminability was altered. Peak latencies of the color-related SN provided a chronometric measure of the duration of attention-related neural processing. ERPs recorded over the frontocentral scalp (N2c, P3a revealed that color-overlap distractors, more than form-overlap distractors, required additional late selection. The need for additional response selection induced by color-overlap distractors was severely reduced when color discriminability decreased. Conclusion We propose a simple model of cross-dimensional perceptual decision-making. The temporal synchrony of separate color-related and form-related choices determines whether or not distractor processing includes post-perceptual stages. ERP measures contribute to a comprehensive explanation of the temporal dynamics of component processes of perceptual decision-making.

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

    Science.gov (United States)

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

    2016-10-15

    Understanding of the distribution patterns of sediment erosion, concentration and transport in river basins is critically important as sediment plays a major role in river basin hydrophysical and ecological processes. In this study, we proposed an integrated framework for the assessment of sediment dynamics, including soil erosion (SE), suspended sediment load (SSL) and suspended sediment concentration (SSC), and applied this framework to the Mekong River Basin. The Revised Universal Soil Loss Equation (RUSLE) model was adopted with a geographic information system to assess SE and was coupled with a sediment accumulation and a routing scheme to simulate SSL. This framework also analyzed Landsat imagery captured between 1987 and 2000 together with ground observations to interpolate spatio-temporal patterns of SSC. The simulated SSL results from 1987 to 2000 showed the relative root mean square error of 41% and coefficient of determination (R(2)) of 0.89. The polynomial relationship of the near infrared exoatmospheric reflectance and the band 4 wavelength (760-900nm) to the observed SSC at 9 sites demonstrated the good agreement (overall relative RMSE=5.2%, R(2)=0.87). The result found that the severe SE occurs in the upper (China and Lao PDR) and lower (western part of Vietnam) regions. The SSC in the rainy season (June-November) showed increasing and decreasing trends longitudinally in the upper (China and Lao PDR) and lower regions (Cambodia), respectively, while the longitudinal profile of SSL showed a fluctuating trend along the river in the early rainy season. Overall, the results described the unique spatio-temporal patterns of SE, SSL and SSC in the Mekong River Basin. Thus, the proposed integrated framework is useful for elucidating complex process of sediment generation and transport in the land and river systems of large river basins. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Graphics Processing Unit-Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks.

    Science.gov (United States)

    García-Calvo, Raúl; Guisado, J L; Diaz-Del-Rio, Fernando; Córdoba, Antonio; Jiménez-Morales, Francisco

    2018-01-01

    Understanding the regulation of gene expression is one of the key problems in current biology. A promising method for that purpose is the determination of the temporal dynamics between known initial and ending network states, by using simple acting rules. The huge amount of rule combinations and the nonlinear inherent nature of the problem make genetic algorithms an excellent candidate for finding optimal solutions. As this is a computationally intensive problem that needs long runtimes in conventional architectures for realistic network sizes, it is fundamental to accelerate this task. In this article, we study how to develop efficient parallel implementations of this method for the fine-grained parallel architecture of graphics processing units (GPUs) using the compute unified device architecture (CUDA) platform. An exhaustive and methodical study of various parallel genetic algorithm schemes-master-slave, island, cellular, and hybrid models, and various individual selection methods (roulette, elitist)-is carried out for this problem. Several procedures that optimize the use of the GPU's resources are presented. We conclude that the implementation that produces better results (both from the performance and the genetic algorithm fitness perspectives) is simulating a few thousands of individuals grouped in a few islands using elitist selection. This model comprises 2 mighty factors for discovering the best solutions: finding good individuals in a short number of generations, and introducing genetic diversity via a relatively frequent and numerous migration. As a result, we have even found the optimal solution for the analyzed gene regulatory network (GRN). In addition, a comparative study of the performance obtained by the different parallel implementations on GPU versus a sequential application on CPU is carried out. In our tests, a multifold speedup was obtained for our optimized parallel implementation of the method on medium class GPU over an equivalent

  11. Graphics Processing Unit–Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks

    Science.gov (United States)

    García-Calvo, Raúl; Guisado, JL; Diaz-del-Rio, Fernando; Córdoba, Antonio; Jiménez-Morales, Francisco

    2018-01-01

    Understanding the regulation of gene expression is one of the key problems in current biology. A promising method for that purpose is the determination of the temporal dynamics between known initial and ending network states, by using simple acting rules. The huge amount of rule combinations and the nonlinear inherent nature of the problem make genetic algorithms an excellent candidate for finding optimal solutions. As this is a computationally intensive problem that needs long runtimes in conventional architectures for realistic network sizes, it is fundamental to accelerate this task. In this article, we study how to develop efficient parallel implementations of this method for the fine-grained parallel architecture of graphics processing units (GPUs) using the compute unified device architecture (CUDA) platform. An exhaustive and methodical study of various parallel genetic algorithm schemes—master-slave, island, cellular, and hybrid models, and various individual selection methods (roulette, elitist)—is carried out for this problem. Several procedures that optimize the use of the GPU’s resources are presented. We conclude that the implementation that produces better results (both from the performance and the genetic algorithm fitness perspectives) is simulating a few thousands of individuals grouped in a few islands using elitist selection. This model comprises 2 mighty factors for discovering the best solutions: finding good individuals in a short number of generations, and introducing genetic diversity via a relatively frequent and numerous migration. As a result, we have even found the optimal solution for the analyzed gene regulatory network (GRN). In addition, a comparative study of the performance obtained by the different parallel implementations on GPU versus a sequential application on CPU is carried out. In our tests, a multifold speedup was obtained for our optimized parallel implementation of the method on medium class GPU over an equivalent

  12. RETRAN dynamic slip model

    International Nuclear Information System (INIS)

    McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

    1981-01-01

    A time dependent equation for the slip velocity in a two-phase flow condition has been incorporated into a developmental version of the RETRAN computer code. This model addition has been undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. In this paper, the development of the slip model is summarized and the corresponding constitutive equations are discussed. Comparisons of RETRAN analyses with steady-state void fraction data and data from the Semiscale S-02-6 small break test are also presented

  13. Modeling Propellant Tank Dynamics

    Data.gov (United States)

    National Aeronautics and Space Administration — The main objective of my work will be to develop accurate models of self-pressurizing propellant tanks for use in designing hybrid rockets. The first key goal is to...

  14. Spatio-temporal dynamics of pneumonia in bighorn sheep.

    Science.gov (United States)

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

    2013-05-01

    apparent fade-out events may be the key to managing this disease. Our data and modelling indicate that pneumonia can have greater impacts on bighorn sheep populations than previously reported, and we present hypotheses about processes involved for testing in future investigations and management. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

  15. Spatio-temporal dynamics of pneumonia in bighorn sheep

    Science.gov (United States)

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

    2013-01-01

    apparent fade-out events may be the key to managing this disease. Our data and modelling indicate that pneumonia can have greater impacts on bighorn sheep populations than previously reported, and we present hypotheses about processes involved for testing in future investigations and management.

  16. Spatial-temporal data model and fractal analysis of transportation network in GIS environment

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua; Li, Yangdong

    2008-10-01

    How to organize transportation data characterized by multi-time, multi-scale, multi-resolution and multi-source is one of the fundamental problems of GIS-T development. A spatial-temporal data model for GIS-T is proposed based on Spatial-temporal- Object Model. Transportation network data is systemically managed using dynamic segmentation technologies. And then a spatial-temporal database is built to integrally store geographical data of multi-time for transportation. Based on the spatial-temporal database, functions of spatial analysis of GIS-T are substantively extended. Fractal module is developed to improve the analyzing in intensity, density, structure and connectivity of transportation network based on the validation and evaluation of topologic relation. Integrated fractal with GIS-T strengthens the functions of spatial analysis and enriches the approaches of data mining and knowledge discovery of transportation network. Finally, the feasibility of the model and methods are tested thorough Guangdong Geographical Information Platform for Highway Project.

  17. Modelling group dynamic animal movement

    DEFF Research Database (Denmark)

    Langrock, Roland; Hopcraft, J. Grant C.; Blackwell, Paul G.

    2014-01-01

    makes its movement decisions relative to the group centroid. The basic idea is framed within the flexible class of hidden Markov models, extending previous work on modelling animal movement by means of multi-state random walks. While in simulation experiments parameter estimators exhibit some bias......, to date, practical statistical methods which can include group dynamics in animal movement models have been lacking. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement of the group's centre, and an individual-level model, such that each individual......Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, particularly in order to differentiate the role of social forces in individual movement from environmental factors. However...

  18. Temporal dynamics of attentional selection in adult male carriers of the fragile X premutation allele and adult controls

    Directory of Open Access Journals (Sweden)

    Ling Mei Wong

    2015-02-01

    Full Text Available Carriers of the fragile X premutation allele (fXPCs have an expanded CGG trinucleotide repeat size within the emph{FMR1} gene and are at increased risk of developing Fragile X-associated Tremor Ataxia Syndrome (FXTAS. Previous research has shown that male fXPCs with FXTAS exhibit cognitive decline, predominantly in executive functions such as inhibitory control and working memory. Recent evidence suggests fXPCs may also exhibit impairments in processing temporal information. The attentional blink (AB task is often used to examine the dynamics of attentional selection, but disagreements exist as to whether the AB is due to excessive or insufficient attentional control. In this study, we used a variant of the AB task and neuropsychological testing to explore the dynamics of attentional selection, relate AB performance to attentional control, and determine whether fXPCs exhibited temporal and/or attentional control impairments. Participants were adult male fXPCs, aged 18--48 years and asymptomatic for FXTAS (emph{n} = 19 and age-matched male controls (emph{n} = 20. We found that fXPCs did not differ from controls in the AB task, indicating that the temporal dynamics of attentional selection were intact. However, they were impaired in the letter-number sequencing task, a test of attentional control. In the combined fXPC and control group, letter-number sequencing performance correlated positively with AB magnitude. This finding supports models that posit the AB is due to excess attentional control. In our two-pronged analysis approach, we contribute to the theoretical literature in controls by extending the AB literature, and we enhance our understanding of fXPCs by demonstrating that at least some aspects of temporal processing may be spared.

  19. Modeling Internet Topology Dynamics

    NARCIS (Netherlands)

    Haddadi, H.; Uhlig, S.; Moore, A.; Mortier, R.; Rio, M.

    Despite the large number of papers on network topology modeling and inference, there still exists ambiguity about the real nature of the Internet AS and router level topology. While recent findings have illustrated the inaccuracies in maps inferred from BGP peering and traceroute measurements,

  20. Generative Models of Conformational Dynamics

    OpenAIRE

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a...

  1. Generative Temporal Modelling of Neuroimaging - Decomposition and Nonparametric Testing

    DEFF Research Database (Denmark)

    Hald, Ditte Høvenhoff

    The goal of this thesis is to explore two improvements for functional magnetic resonance imaging (fMRI) analysis; namely our proposed decomposition method and an extension to the non-parametric testing framework. Analysis of fMRI allows researchers to investigate the functional processes...... of the brain, and provides insight into neuronal coupling during mental processes or tasks. The decomposition method is a Gaussian process-based independent components analysis (GPICA), which incorporates a temporal dependency in the sources. A hierarchical model specification is used, featuring both...... instantaneous and convolutive mixing, and the inferred temporal patterns. Spatial maps are seen to capture smooth and localized stimuli-related components, and often identifiable noise components. The implementation is freely available as a GUI/SPM plugin, and we recommend using GPICA as an additional tool when...

  2. Spatial and spatio-temporal bayesian models with R - INLA

    CERN Document Server

    Blangiardo, Marta

    2015-01-01

    Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr

  3. Spatio-temporal dynamics of a fish predator: Density-dependent and hydrographic effects on Baltic Sea cod population.

    Directory of Open Access Journals (Sweden)

    Valerio Bartolino

    Full Text Available Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes.

  4. Conceptual Model of Dynamic Geographic Environment

    Directory of Open Access Journals (Sweden)

    Martínez-Rosales Miguel Alejandro

    2014-04-01

    Full Text Available In geographic environments, there are many and different types of geographic entities such as automobiles, trees, persons, buildings, storms, hurricanes, etc. These entities can be classified into two groups: geographic objects and geographic phenomena. By its nature, a geographic environment is dynamic, thus, it’s static modeling is not sufficient. Considering the dynamics of geographic environment, a new type of geographic entity called event is introduced. The primary target is a modeling of geographic environment as an event sequence, because in this case the semantic relations are much richer than in the case of static modeling. In this work, the conceptualization of this model is proposed. It is based on the idea to process each entity apart instead of processing the environment as a whole. After that, the so called history of each entity and its spatial relations to other entities are defined to describe the whole environment. The main goal is to model systems at a conceptual level that make use of spatial and temporal information, so that later it can serve as the semantic engine for such systems.

  5. Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

    Directory of Open Access Journals (Sweden)

    Shi Chen

    Full Text Available Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density, subgroup clustering (modularity, triadic property (transitivity, and dyadic interactions (correlation coefficient from a quadratic assignment procedure at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level or temporal (aggregated at daily level resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc. also changed substantially at different time and locations. There were certain time (feeding and location (hay that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect disease transmission pathways.

  6. Mesoscopic model of temporal and spatial heterogeneity in aging colloids

    DEFF Research Database (Denmark)

    Becker, Nikolaj; Sibani, Paolo; Boettcher, Stefan

    2014-01-01

    We develop a simple and effective description of the dynamics of dense hard sphere colloids in the aging regime deep in the glassy phase. Our description complements the many efforts to understand the onset of jamming in low density colloids, whose dynamics is still time-homogeneous. Based...... scattering function and particle mean-square displacements for jammed colloidal systems, and we predict a growth for the peak of the χ4 mobility correlation function that is logarithmic in waiting-time. At the same time, our model suggests a novel unified description for the irreversible aging dynamics...

  7. Vehicle dynamics modeling and simulation

    CERN Document Server

    Schramm, Dieter; Bardini, Roberto

    2014-01-01

    The authors examine in detail the fundamentals and mathematical descriptions of the dynamics of automobiles. In this context different levels of complexity will be presented, starting with basic single-track models up to complex three-dimensional multi-body models. A particular focus is on the process of establishing mathematical models on the basis of real cars and the validation of simulation results. The methods presented are explained in detail by means of selected application scenarios.

  8. Transition Dynamics of a Dentate Gyrus-CA3 Neuronal Network during Temporal Lobe Epilepsy

    Directory of Open Access Journals (Sweden)

    Liyuan Zhang

    2017-07-01

    Full Text Available In temporal lobe epilepsy (TLE, the variation of chemical receptor expression underlies the basis of neural network activity shifts, resulting in neuronal hyperexcitability and epileptiform discharges. However, dynamical mechanisms involved in the transitions of TLE are not fully understood, because of the neuronal diversity and the indeterminacy of network connection. Hence, based on Hodgkin–Huxley (HH type neurons and Pinsky–Rinzel (PR type neurons coupling with glutamatergic and GABAergic synaptic connections respectively, we propose a computational framework which contains dentate gyrus (DG region and CA3 region. By regulating the concentration range of N-methyl-D-aspartate-type glutamate receptor (NMDAR, we demonstrate the pyramidal neuron can generate transitions from interictal to seizure discharges. This suggests that enhanced endogenous activity of NMDAR contributes to excitability in pyramidal neuron. Moreover, we conclude that excitatory discharges in CA3 region vary considerably on account of the excitatory currents produced by the excitatory pyramidal neuron. Interestingly, by changing the backprojection connection, we find that glutamatergic type backprojection can promote the dominant frequency of firings and further motivate excitatory counterpropagation from CA3 region to DG region. However, GABAergic type backprojection can reduce firing rate and block morbid counterpropagation, which may be factored into the terminations of TLE. In addition, neuronal diversity dominated network shows weak correlation with different backprojections. Our modeling and simulation studies provide new insights into the mechanisms of seizures generation and connectionism in local hippocampus, along with the synaptic mechanisms of this disease.

  9. Interplay between the temporal dynamics of the vaginal microbiota and human papillomavirus detection.

    Science.gov (United States)

    Brotman, Rebecca M; Shardell, Michelle D; Gajer, Pawel; Tracy, J Kathleen; Zenilman, Jonathan M; Ravel, Jacques; Gravitt, Patti E

    2014-12-01

    We sought to describe the temporal relationship between vaginal microbiota and human papillomavirus (HPV) detection. Thirty-two reproductive-age women self-collected midvaginal swabs twice weekly for 16 weeks (937 samples). Vaginal bacterial communities were characterized by pyrosequencing of barcoded 16S rRNA genes and clustered into 6 community state types (CSTs). Each swab was tested for 37 HPV types. The effects of CSTs on the rate of transition between HPV-negative and HPV-positive states were assessed using continuous-time Markov models. Participants had an average of 29 samples, with HPV point prevalence between 58%-77%. CST was associated with changes in HPV status (PVaginal microbiota dominated by L. gasseri was associated with increased clearance of detectable HPV. Frequent longitudinal sampling is necessary for evaluation of the association between HPV detection and dynamic microbiota. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Temporal dynamics of physical activity and affect in depressed and nondepressed individuals.

    Science.gov (United States)

    Stavrakakis, Nikolaos; Booij, Sanne H; Roest, Annelieke M; de Jonge, Peter; Oldehinkel, Albertine J; Bos, Elisabeth H

    2015-12-01

    The association between physical activity and affect found in longitudinal observational studies is generally small to moderate. It is unknown how this association generalizes to individuals. The aim of the present study was to investigate interindividual differences in the bidirectional dynamic relationship between physical activity and affect, in depressed and nondepressed individuals, using time-series analysis. A pair-matched sample of 10 depressed and 10 nondepressed participants (mean age = 36.6, SD = 8.9, 30% males) wore accelerometers and completed electronic questionnaires 3 times a day for 30 days. Physical activity was operationalized as the total energy expenditure (EE) per day segment (i.e., 6 hr). The multivariate time series (T = 90) of every individual were analyzed using vector autoregressive modeling (VAR), with the aim to assess direct as well as lagged (i.e., over 1 day) effects of EE on positive and negative affect, and vice versa. Large interindividual differences in the strength, direction and temporal aspects of the relationship between physical activity and positive and negative affect were observed. An exception was the direct (but not the lagged) effect of physical activity on positive affect, which was positive in nearly all individuals. This study showed that the association between physical activity and affect varied considerably across individuals. Thus, while at the group level the effect of physical activity on affect may be small, in some individuals the effect may be clinically relevant. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  11. Transition Dynamics of a Dentate Gyrus-CA3 Neuronal Network during Temporal Lobe Epilepsy.

    Science.gov (United States)

    Zhang, Liyuan; Fan, Denggui; Wang, Qingyun

    2017-01-01

    In temporal lobe epilepsy (TLE), the variation of chemical receptor expression underlies the basis of neural network activity shifts, resulting in neuronal hyperexcitability and epileptiform discharges. However, dynamical mechanisms involved in the transitions of TLE are not fully understood, because of the neuronal diversity and the indeterminacy of network connection. Hence, based on Hodgkin-Huxley (HH) type neurons and Pinsky-Rinzel (PR) type neurons coupling with glutamatergic and GABAergic synaptic connections respectively, we propose a computational framework which contains dentate gyrus (DG) region and CA3 region. By regulating the concentration range of N-methyl-D-aspartate-type glutamate receptor (NMDAR), we demonstrate the pyramidal neuron can generate transitions from interictal to seizure discharges. This suggests that enhanced endogenous activity of NMDAR contributes to excitability in pyramidal neuron. Moreover, we conclude that excitatory discharges in CA3 region vary considerably on account of the excitatory currents produced by the excitatory pyramidal neuron. Interestingly, by changing the backprojection connection, we find that glutamatergic type backprojection can promote the dominant frequency of firings and further motivate excitatory counterpropagation from CA3 region to DG region. However, GABAergic type backprojection can reduce firing rate and block morbid counterpropagation, which may be factored into the terminations of TLE. In addition, neuronal diversity dominated network shows weak correlation with different backprojections. Our modeling and simulation studies provide new insights into the mechanisms of seizures generation and connectionism in local hippocampus, along with the synaptic mechanisms of this disease.

  12. Bio-Inspired Neural Model for Learning Dynamic Models

    Science.gov (United States)

    Duong, Tuan; Duong, Vu; Suri, Ronald

    2009-01-01

    A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

  13. Laminar and Temporal Expression Dynamics of Coding and Noncoding RNAs in the Mouse Neocortex

    Directory of Open Access Journals (Sweden)

    Sofia Fertuzinhos

    2014-03-01

    Full Text Available The hallmark of the cerebral neocortex is its organization into six layers, each containing a characteristic set of cell types and synaptic connections. The transcriptional events involved in laminar development and function still remain elusive. Here, we employed deep sequencing of mRNA and small RNA species to gain insights into transcriptional differences among layers and their temporal dynamics during postnatal development of the mouse primary somatosensory neocortex. We identify a number of coding and noncoding transcripts with specific spatiotemporal expression and splicing patterns. We also identify signature trajectories and gene coexpression networks associated with distinct biological processes and transcriptional overlap between these processes. Finally, we provide data that allow the study of potential miRNA and mRNA interactions. Overall, this study provides an integrated view of the laminar and temporal expression dynamics of coding and noncoding transcripts in the mouse neocortex and a resource for studies of neurodevelopment and transcriptome.

  14. Containing Terrorism: A Dynamic Model

    Directory of Open Access Journals (Sweden)

    Giti Zahedzadeh

    2017-06-01

    Full Text Available The strategic interplay between counterterror measures and terror activity is complex. Herein, we propose a dynamic model to depict this interaction. The model generates stylized prognoses: (i under conditions of inefficient counterterror measures, terror groups enjoy longer period of activity but only if recruitment into terror groups remains low; high recruitment shortens the period of terror activity (ii highly efficient counterterror measures effectively contain terror activity, but only if recruitment remains low. Thus, highly efficient counterterror measures can effectively contain terrorism if recruitment remains restrained. We conclude that the trajectory of the dynamics between counterterror measures and terror activity is heavily altered by recruitment.

  15. Time-resolved PIV technique for high temporal resolution measurement of mechanical prosthetic aortic valve fluid dynamics.

    Science.gov (United States)

    Kaminsky, R; Morbiducci, U; Rossi, M; Scalise, L; Verdonck, P; Grigioni, M

    2007-02-01

    Prosthetic heart valves (PHVs) have been used to replace diseased native valves for more than five decades. Among these, mechanical PHVs are the most frequently implanted. Unfortunately, these devices still do not achieve ideal behavior and lead to many complications, many of which are related to fluid mechanics. The fluid dynamics of mechanical PHVs are particularly complex and the fine-scale characteristics of such flows call for very accurate experimental techniques. Adequate temporal resolution can be reached by applying time-resolved PIV, a high-resolution dynamic technique which is able to capture detailed chronological changes in the velocity field. The aim of this experimental study is to investigate the evolution of the flow field in a detailed time domain of a commercial bileaflet PHV in a mock-loop mimicking unsteady conditions, by means of time-resolved 2D Particle Image Velocimetry (PIV). The investigated flow field corresponded to the region immediately downstream of the valve plane. Spatial resolution as in "standard" PIV analysis of prosthetic valve fluid dynamics was used. The combination of a Nd:YLF high-repetition-rate double-cavity laser with a high frame rate CMOS camera allowed a detailed, highly temporally resolved acquisition (up to 10000 fps depending on the resolution) of the flow downstream of the PHV. Features that were observed include the non-homogeneity and unsteadiness of the phenomenon and the presence of large-scale vortices within the field, especially in the wake of the valve leaflets. Furthermore, we observed that highly temporally cycle-resolved analysis allowed the different behaviors exhibited by the bileaflet valve at closure to be captured in different acquired cardiac cycles. By accurately capturing hemodynamically relevant time scales of motion, time-resolved PIV characterization can realistically be expected to help designers in improving PHV performance and in furnishing comprehensive validation with experimental data

  16. Spatial and temporal dynamics of the microbial community in the Hanford unconfined aquifer

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Xueju; McKinley, James P.; Resch, Charles T.; Kaluzny, Rachael M.; Lauber, C.; Fredrickson, Jim K.; Knight, Robbie C.; Konopka, Allan

    2012-03-29

    Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater Bacteria and Archaea over 10 months within 3 well clusters separated by ~30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained 3 wells screened at different depths ranging from 10 to 17 m that differed in hydraulic conductivities. Representative samples were selected for analyses of prokaryotic 16S and eukaryotic 18S rRNA gene copy numbers. Temporal changes in community composition occurred in all 9 wells over the 10 month sampling period. However, there were particularly strong effects near the top of the water table when the seasonal rise in the Columbia River caused river water intrusion at the top of the aquifer. The occurrence and disappearance of some microbial assemblages (such as Actinobacteria ACK-M1) were correlated to river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (e.g.methane oxidizers and metal reducers) suggests dynamic changes in fluxes of electron donors and acceptors over an annual cycle. In addition, temporal dynamics in eukaryotic 18S rRNA gene copies and the dominance of protozoa in 18S clone libraries suggest that bacterial community dynamics could be affected not only by the physical and chemical environment, but also by top-down biological control.

  17. Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

    Science.gov (United States)

    Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

    2017-12-01

    The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

  18. A dynamical model of terrorism

    Directory of Open Access Journals (Sweden)

    Firdaus Udwadia

    2006-01-01

    Full Text Available This paper develops a dynamical model of terrorism. We consider the population in a given region as being made up of three primary components: terrorists, those susceptible to both terrorist and pacifist propaganda, and nonsusceptibles, or pacifists. The dynamical behavior of these three populations is studied using a model that incorporates the effects of both direct military/police intervention to reduce the terrorist population, and nonviolent, persuasive intervention to influence the susceptibles to become pacifists. The paper proposes a new paradigm for studying terrorism, and looks at the long-term dynamical evolution in time of these three population components when such interventions are carried out. Many important features—some intuitive, others not nearly so—of the nature of terrorism emerge from the dynamical model proposed, and they lead to several important policy implications for the management of terrorism. The different circumstances in which nonviolent intervention and/or military/police intervention may be beneficial, and the specific conditions under which each mode of intervention, or a combination of both, may be useful, are obtained. The novelty of the model presented herein is that it deals with the time evolution of terrorist activity. It appears to be one of the few models that can be tested, evaluated, and improved upon, through the use of actual field data.

  19. Modern methodology and applications in spatial-temporal modeling

    CERN Document Server

    Matsui, Tomoko

    2015-01-01

    This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component an...

  20. A Novel Temporal Bone Simulation Model Using 3D Printing Techniques.

    Science.gov (United States)

    Mowry, Sarah E; Jammal, Hachem; Myer, Charles; Solares, Clementino Arturo; Weinberger, Paul

    2015-09-01

    An inexpensive temporal bone model for use in a temporal bone dissection laboratory setting can be made using a commercially available, consumer-grade 3D printer. Several models for a simulated temporal bone have been described but use commercial-grade printers and materials to produce these models. The goal of this project was to produce a plastic simulated temporal bone on an inexpensive 3D printer that recreates the visual and haptic experience associated with drilling a human temporal bone. Images from a high-resolution CT of a normal temporal bone were converted into stereolithography files via commercially available software, with image conversion and print settings adjusted to achieve optimal print quality. The temporal bone model was printed using acrylonitrile butadiene styrene (ABS) plastic filament on a MakerBot 2x 3D printer. Simulated temporal bones were drilled by seven expert temporal bone surgeons, assessing the fidelity of the model as compared with a human cadaveric temporal bone. Using a four-point scale, the simulated bones were assessed for haptic experience and recreation of the temporal bone anatomy. The created model was felt to be an accurate representation of a human temporal bone. All raters felt strongly this would be a good training model for junior residents or to simulate difficult surgical anatomy. Material cost for each model was $1.92. A realistic, inexpensive, and easily reproducible temporal bone model can be created on a consumer-grade desktop 3D printer.

  1. Innovations in individual feature history management - The significance of feature-based temporal model

    Science.gov (United States)

    Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

    2008-01-01

    A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

  2. Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease.

    Science.gov (United States)

    Jie, Biao; Liu, Mingxia; Shen, Dinggang

    2018-07-01

    Functional connectivity networks (FCNs) using resting-state functional magnetic resonance imaging (rs-fMRI) have been applied to the analysis and diagnosis of brain disease, such as Alzheimer's disease (AD) and its prodrome, i.e., mild cognitive impairment (MCI). Different from conventional studies focusing on static descriptions on functional connectivity (FC) between brain regions in rs-fMRI, recent studies have resorted to dynamic connectivity networks (DCNs) to characterize the dynamic changes of FC, since dynamic changes of FC may indicate changes in macroscopic neural activity patterns in cognitive and behavioral aspects. However, most of the existing studies only investigate the temporal properties of DCNs (e.g., temporal variability of FC between specific brain regions), ignoring the important spatial properties of the network (e.g., spatial variability of FC associated with a specific brain region). Also, emerging evidence on FCNs has suggested that, besides temporal variability, there is significant spatial variability of activity foci over time. Hence, integrating both temporal and spatial properties of DCNs can intuitively promote the performance of connectivity-network-based learning methods. In this paper, we first define a new measure to characterize the spatial variability of DCNs, and then propose a novel learning framework to integrate both temporal and spatial variabilities of DCNs for automatic brain disease diagnosis. Specifically, we first construct DCNs from the rs-fMRI time series at successive non-overlapping time windows. Then, we characterize the spatial variability of a specific brain region by computing the correlation of functional sequences (i.e., the changing profile of FC between a pair of brain regions within all time windows) associated with this region. Furthermore, we extract both temporal variabilities and spatial variabilities from DCNs as features, and integrate them for classification by using manifold regularized multi

  3. Generative Models of Conformational Dynamics

    Science.gov (United States)

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358

  4. Mapping and spatial-temporal modeling of Bromus tectorum invasion in central Utah

    Science.gov (United States)

    Jin, Zhenyu

    Cheatgrass, or Downy Brome, is an exotic winter annual weed native to the Mediterranean region. Since its introduction to the U.S., it has become a significant weed and aggressive invader of sagebrush, pinion-juniper, and other shrub communities, where it can completely out-compete native grasses and shrubs. In this research, remotely sensed data combined with field collected data are used to investigate the distribution of the cheatgrass in Central Utah, to characterize the trend of the NDVI time-series of cheatgrass, and to construct a spatially explicit population-based model to simulate the spatial-temporal dynamics of the cheatgrass. This research proposes a method for mapping the canopy closure of invasive species using remotely sensed data acquired at different dates. Different invasive species have their own distinguished phenologies and the satellite images in different dates could be used to capture the phenology. The results of cheatgrass abundance prediction have a good fit with the field data for both linear regression and regression tree models, although the regression tree model has better performance than the linear regression model. To characterize the trend of NDVI time-series of cheatgrass, a novel smoothing algorithm named RMMEH is presented in this research to overcome some drawbacks of many other algorithms. By comparing the performance of RMMEH in smoothing a 16-day composite of the MODIS NDVI time-series with that of two other methods, which are the 4253EH, twice and the MVI, we have found that RMMEH not only keeps the original valid NDVI points, but also effectively removes the spurious spikes. The reconstructed NDVI time-series of different land covers are of higher quality and have smoother temporal trend. To simulate the spatial-temporal dynamics of cheatgrass, a spatially explicit population-based model is built applying remotely sensed data. The comparison between the model output and the ground truth of cheatgrass closure demonstrates

  5. Experimental Modeling of Dynamic Systems

    DEFF Research Database (Denmark)

    Knudsen, Morten Haack

    2006-01-01

    An engineering course, Simulation and Experimental Modeling, has been developed that is based on a method for direct estimation of physical parameters in dynamic systems. Compared with classical system identification, the method appears to be easier to understand, apply, and combine with physical...

  6. Approximate Entropy as a measure of complexity in sap flow temporal dynamics of two tropical tree species under water deficit

    Directory of Open Access Journals (Sweden)

    Gustavo M. Souza

    2004-09-01

    Full Text Available Approximate Entropy (ApEn, a model-independent statistics to quantify serial irregularities, was used to evaluate changes in sap flow temporal dynamics of two tropical species of trees subjected to water deficit. Water deficit induced a decrease in sap flow of G. ulmifolia, whereas C. legalis held stable their sap flow levels. Slight increases in time series complexity were observed in both species under drought condition. This study showed that ApEn could be used as a helpful tool to assess slight changes in temporal dynamics of physiological data, and to uncover some patterns of plant physiological responses to environmental stimuli.Entropia Aproximada (ApEn, um modelo estatístico independente para quantificar irregularidade em séries temporais, foi utilizada para avaliar alterações na dinâmica temporal do fluxo de seiva em duas espécies arbóreas tropicais submetidas à deficiência hídrica. A deficiência hídrica induziu uma grande redução no fluxo de seiva em G. ulmifolia, enquanto que na espécie C. legalis manteve-se estável. A complexidade das séries temporais foi levemente aumentada sob deficiência hídrica. O estudo mostrou que ApEn pode ser usada como um método para detectar pequenas alterações na dinâmica temporal de dados fisiológicos, e revelar alguns padrões de respostas fisiológicas a estímulos ambientais.

  7. Temporal dynamics of spectral bioindicators evidence biological and ecological differences among functional types in a cork oak open woodland

    Science.gov (United States)

    Cerasoli, Sofia; Costa e Silva, Filipe; Silva, João M. N.

    2016-06-01

    The application of spectral vegetation indices for the purpose of vegetation monitoring and modeling increased largely in recent years. Nonetheless, the interpretation of biophysical properties of vegetation through their spectral signature is still a challenging task. This is particularly true in Mediterranean oak forest characterized by a high spatial and temporal heterogeneity. In this study, the temporal dynamics of vegetation indices expected to be related with green biomass and photosynthetic efficiency were compared for the canopy of trees, the herbaceous layer, and two shrub species: cistus ( Cistus salviifolius) and ulex ( Ulex airensis). coexisting in a cork oak woodland. All indices were calculated from in situ measurements with a FieldSpec3 spectroradiometer (ASD Inc., Boulder, USA). Large differences emerged in the temporal trends and in the correlation between climate and vegetation indices. The relationship between spectral indices and temperature, radiation, and vapor pressure deficit for cork oak was opposite to that observed for the herbaceous layer and cistus. No correlation was observed between rainfall and vegetation indices in cork oak and ulex, but in the herbaceous layer and in the cistus, significant correlations were found. The analysis of spectral vegetation indices with fraction of absorbed PAR (fPAR) and quantum yield of chlorophyll fluorescence ( ΔF/ Fm') evidenced strongest relationships with the indices Normalized Difference Water Index (NDWI) and Photochemical Reflectance Index (PRI)512, respectively. Our results, while confirms the ability of spectral vegetation indices to represent temporal dynamics of biophysical properties of vegetation, evidence the importance to consider ecosystem composition for a correct ecological interpretation of results when the spatial resolution of observations includes different plant functional types.

  8. Model-based control of the temporal patterns of intracellular signaling in silico

    Science.gov (United States)

    Murakami, Yohei; Koyama, Masanori; Oba, Shigeyuki; Kuroda, Shinya; Ishii, Shin

    2017-01-01

    The functions of intracellular signal transduction systems are determined by the temporal behavior of intracellular molecules and their interactions. Of the many dynamical properties of the system, the relationship between the dynamics of upstream molecules and downstream molecules is particularly important. A useful tool in understanding this relationship is a methodology to control the dynamics of intracellular molecules with an extracellular stimulus. However, this is a difficult task because the relationship between the levels of upstream molecules and those of downstream molecules is often not only stochastic, but also time-inhomogeneous, nonlinear, and not one-to-one. In this paper, we present an easy-to-implement model-based control method that makes the target downstream molecule to trace a desired time course by changing the concentration of a controllable upstream molecule. Our method uses predictions from Monte Carlo simulations of the model to decide the strength of the stimulus, while using a particle-based approach to make inferences regarding unobservable states. We applied our method to in silico control problems of insulin-dependent AKT pathway model and EGF-dependent Akt pathway model with system noise. We show that our method can robustly control the dynamics of the intracellular molecules against unknown system noise of various strengths, even in the absence of complete knowledge of the true model of the target system. PMID:28275530

  9. Temporal networks

    Science.gov (United States)

    Holme, Petter; Saramäki, Jari

    2012-10-01

    A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered

  10. Spatio-temporal dynamics of cod nursery areas in the Baltic Sea

    Science.gov (United States)

    Hinrichsen, H.-H.; von Dewitz, B.; Lehmann, A.; Bergström, U.; Hüssy, K.

    2017-06-01

    In this study the drift of eastern Baltic cod larvae and juveniles spawned within the historical eastern Baltic cod spawning grounds was investigated by detailed drift model simulations for the years 1971-2010, to examine the spatio-temporal dynamics of environmental suitability in the nursery areas of juvenile cod settlement. The results of the long-term model scenario runs, where juvenile cod were treated as simulated passively drifting particles, enabled us to find strong indications for long-term variations of settlement and potentially the reproduction success of the historically important eastern Baltic cod nursery grounds. Only low proportions of juveniles hatched in the Arkona Basin and in the Gotland Basin were able to settle in their respective spawning ground. Ocean currents were either unfavorable for the juveniles to reach suitable habitats or transported the juveniles to nursery grounds of neighboring subdivisions. Juveniles which hatched in the Bornholm Basin were most widely dispersed and showed the highest settlement probability, while the second highest settlement probability and horizontal dispersal was observed for juveniles originating from the Gdansk Deep. In a long-term perspective, wind-driven transport of larvae/juveniles positively affected the settlement success predominately in the Bornholm Basin and in the Bay of Gdansk. The Bornholm Basin has the potential to contribute on average 54% and the Bay of Gdansk 11% to the production of juveniles in the Baltic Sea. Furthermore, transport of juveniles surviving to the age of settlement with origin in the Bornholm Basin contributed on average 13 and 11% to the total settlement in the Arkona Basin and in the Gdansk Deep, respectively. The time-series of the simulated occupied juvenile cod habitat in the Bornholm Basin and in the Gdansk Deep showed a similar declining trend as the Fulton's K condition factor of demersal 1-group cod, which may confirm the importance of oxygen-dependent habitat

  11. The Temporal Derivative of Expected Utility: A Neural Mechanism for Dynamic Decision-making

    Science.gov (United States)

    Zhang, Xian; Hirsch, Joy

    2012-01-01

    Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, those neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. PMID:22963852

  12. The temporal derivative of expected utility: a neural mechanism for dynamic decision-making.

    Science.gov (United States)

    Zhang, Xian; Hirsch, Joy

    2013-01-15

    Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, the neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. Copyright © 2012 Elsevier Inc. All rights reserved.

  13. Models for inference in dynamic metacommunity systems

    Science.gov (United States)

    Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.

  14. Temporal and spatial variation in recent vehicular emission inventories in China based on dynamic emission factors.

    Science.gov (United States)

    Cai, Hao; Xie, Shaodong

    2013-03-01

    The vehicular emission trend in China was tracked for the recent period 2006-2009 based on a database of dynamic emission factors of CO, nonmethane volatile organic compounds (NMVOC), NOx, PM10, CO2, CH4, and N2O for all categories of on-road motor vehicles in China, which was developed at the provincial level using the COPERT 4 model, to account for the effects of rapid advances in engine technologies, implementation of improved emission standards, emission deterioration due to mileage, and fuel quality improvement. Results show that growth rates of CO and NMVOC emissions slowed down, but NOx and PM10 emissions continued rising rapidly for the period 2006-2009. Moreover CO2, CH4, and N2O emissions in 2009 almost doubled compared to those in 2005. Characteristics of recent spatial distribution of emissions and emission contributions by vehicle category revealed that priority of vehicular emission control should be put on the eastern and southeastern coastal provinces and northern regions, and passenger cars and motorcycles require stricter control for the reduction of CO and NMVOC emissions, while effective reduction of NOx and PM10 emissions can be achieved by better control of heavy-duty vehicles, buses and coaches, and passenger cars. Explicit provincial-level Monte Carlo uncertainty analysis, which quantified for the first time the Chinese vehicular emission uncertainties associated with both COPERT-derived and domestically measured emission factors by vehicle technology, showed that CO, NMVOC, and NOx emissions for the period 2006-2009 were calculated with the least uncertainty, followed by PM10 and CO2, despite relatively larger uncertainties in N2O and CH4 emissions. The quantified low uncertainties of emissions revealed a necessity of applying vehicle technology- and vehicle age-specific dynamic emission factors for vehicular emission estimation, and these improved methodologies are applicable for routine update and forecast of China's on-road motor vehicle

  15. Dynamic spatial organization of the occipito-temporal word form area for second language processing.

    Science.gov (United States)

    Gao, Yue; Sun, Yafeng; Lu, Chunming; Ding, Guosheng; Guo, Taomei; Malins, Jeffrey G; Booth, James R; Peng, Danling; Liu, Li

    2017-08-01

    Despite the left occipito-temporal region having shown consistent activation in visual word form processing across numerous studies in different languages, the mechanisms by which word forms of second languages are processed in this region remain unclear. To examine this more closely, 16 Chinese-English and 14 English-Chinese late bilinguals were recruited to perform lexical decision tasks to visually presented words in both their native and second languages (L1 and L2) during functional magnetic resonance imaging scanning. Here we demonstrate that visual word form processing for L1 versus L2 engaged different spatial areas of the left occipito-temporal region. Namely, the spatial organization of the visual word form processing in the left occipito-temporal region is more medial and posterior for L2 than L1 processing in Chinese-English bilinguals, whereas activation is more lateral and anterior for L2 in English-Chinese bilinguals. In addition, for Chinese-English bilinguals, more lateral recruitment of the occipito-temporal region was correlated with higher L2 proficiency, suggesting higher L2 proficiency is associated with greater involvement of L1-preferred mechanisms. For English-Chinese bilinguals, higher L2 proficiency was correlated with more lateral and anterior activation of the occipito-temporal region, suggesting higher L2 proficiency is associated with greater involvement of L2-preferred mechanisms. Taken together, our results indicate that L1 and L2 recruit spatially different areas of the occipito-temporal region in visual word processing when the two scripts belong to different writing systems, and that the spatial organization of this region for L2 visual word processing is dynamically modulated by L2 proficiency. Specifically, proficiency in L2 in Chinese-English is associated with assimilation to the native language mechanisms, whereas L2 in English-Chinese is associated with accommodation to second language mechanisms. Copyright © 2017

  16. INFORMATION MINING OF SPATIO-TEMPORAL EVOLUTION OF LAKES BASED ON MULTIPLE DYNAMIC MEASUREMENTS

    Directory of Open Access Journals (Sweden)

    W. Feng

    2017-09-01

    Full Text Available Lakes are important water resources and integral parts of the natural ecosystem, and it is of great significance to study the evolution of lakes. The area of each lake increased and decreased at the same time in natural condition, only but the net change of lakes’ area is the result of the bidirectional evolution of lakes. In this paper, considering the effects of net fragmentation, net attenuation, swap change and spatial invariant part in lake evolution, a comprehensive evaluation indexes of lake dynamic evolution were defined,. Such degree contains three levels of measurement: 1 the swap dynamic degree (SDD reflects the space activity of lakes in the study period. 2 the attenuation dynamic degree (ADD reflects the net attenuation of lakes into non-lake areas. 3 the fragmentation dynamic degree (FDD reflects the trend of lakes to be divided and broken into smaller lakes. Three levels of dynamic measurement constitute the three-dimensional "Swap - attenuation – fragmentation" dynamic evolution measurement system of lakes. To show its effectiveness, the dynamic measurement was applied to lakes in Jianghan Plain, the middle Yangtze region of China for a more detailed analysis of lakes from 1984 to 2014. In combination with spatial-temporal location characteristics of lakes, the hidden information in lake evolution in the past 30 years can be revealed.

  17. Spatio-temporal dynamics and laterality effects of face inversion, feature presence and configuration, and face outline

    Directory of Open Access Journals (Sweden)

    Ksenija eMarinkovic

    2014-11-01

    Full Text Available Although a crucial role of the fusiform gyrus in face processing has been demonstrated with a variety of methods, converging evidence suggests that face processing involves an interactive and overlapping processing cascade in distributed brain areas. Here we examine the spatio-temporal stages and their functional tuning to face inversion, presence and configuration of inner features, and face contour in healthy subjects during passive viewing. Anatomically-constrained magnetoencephalography (aMEG combines high-density whole-head MEG recordings and distributed source modeling with high-resolution structural MRI. Each person's reconstructed cortical surface served to constrain noise-normalized minimum norm inverse source estimates. The earliest activity was estimated to the occipital cortex at ~100 ms after stimulus onset and was sensitive to an initial coarse level visual analysis. Activity in the right-lateralized ventral temporal area (inclusive of the fusiform gyrus peaked at ~160ms and was largest to inverted faces. Images containing facial features in the veridical and rearranged configuration irrespective of the facial outline elicited intermediate level activity. The M160 stage may provide structural representations necessary for downstream distributed areas to process identity and emotional expression. However, inverted faces additionally engaged the left ventral temporal area at ~180 ms and were uniquely subserved by bilateral processing. This observation is consistent with the dual route model and spared processing of inverted faces in prosopagnosia. The subsequent deflection, peaking at ~240ms in the anterior temporal areas bilaterally, was largest to normal, upright faces. It may reflect initial engagement of the distributed network subserving individuation and familiarity. These results support dynamic models suggesting that processing of unfamiliar faces in the absence of a cognitive task is subserved by a distributed and

  18. A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Kamronn, Simon Due; Paquet, Ulrich

    2017-01-01

    This paper takes a step towards temporal reasoning in a dynamically changing video, not in the pixel space that constitutes its frames, but in a latent space that describes the non-linear dynamics of the objects in its world. We introduce the Kalman variational auto-encoder, a framework...... for unsupervised learning of sequential data that disentangles two latent representations: an object’s representation, coming from a recognition model, and a latent state describing its dynamics. As a result, the evolution of the world can be imagined and missing data imputed, both without the need to generate...

  19. Model-Based Speech Signal Coding Using Optimized Temporal Decomposition for Storage and Broadcasting Applications

    Science.gov (United States)

    Athaudage, Chandranath R. N.; Bradley, Alan B.; Lech, Margaret

    2003-12-01

    A dynamic programming-based optimization strategy for a temporal decomposition (TD) model of speech and its application to low-rate speech coding in storage and broadcasting is presented. In previous work with the spectral stability-based event localizing (SBEL) TD algorithm, the event localization was performed based on a spectral stability criterion. Although this approach gave reasonably good results, there was no assurance on the optimality of the event locations. In the present work, we have optimized the event localizing task using a dynamic programming-based optimization strategy. Simulation results show that an improved TD model accuracy can be achieved. A methodology of incorporating the optimized TD algorithm within the standard MELP speech coder for the efficient compression of speech spectral information is also presented. The performance evaluation results revealed that the proposed speech coding scheme achieves 50%-60% compression of speech spectral information with negligible degradation in the decoded speech quality.

  20. Temporal carbon dynamics of forests in Washington, US: implications for ecological theory and carbon management

    Science.gov (United States)

    Crystal L. Raymond; Donald. McKenzie

    2014-01-01

    We quantified carbon (C) dynamics of forests in Washington, US using theoretical models of C dynamics as a function of forest age. We fit empirical models to chronosequences of forest inventory data at two scales: a coarse-scale ecosystem classification (ecosections) and forest types (potential vegetation) within ecosections. We hypothesized that analysis at the finer...

  1. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  2. Temporal dynamics and transcriptional control using single-cell gene expression analysis.

    Science.gov (United States)

    Kouno, Tsukasa; de Hoon, Michiel; Mar, Jessica C; Tomaru, Yasuhiro; Kawano, Mitsuoki; Carninci, Piero; Suzuki, Harukazu; Hayashizaki, Yoshihide; Shin, Jay W

    2013-01-01

    Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous regulatory network is distributed and utilized by cells transitioning through a key developmental event. Here we investigate the temporal dynamics of a single-cell transcriptional network of 45 transcription factors in THP-1 human myeloid monocytic leukemia cells undergoing differentiation to macrophages. We systematically measure temporal regulation of expression and variation by profiling 120 single cells at eight distinct time points, and infer highly controlled regulatory modules through which signaling operates with stochastic effects. This reveals dynamic and specific rewiring as a cellular strategy for differentiation. The integration of both positive and negative co-expression networks further identifies the proto-oncogene MYB as a network hinge to modulate both the pro- and anti-differentiation pathways. Compared to averaged cell populations, temporal single-cell expression profiling provides a much more powerful technique to probe for mechanistic insights underlying cellular differentiation. We believe that our approach will form the basis of novel strategies to study the regulation of transcription at a single-cell level.

  3. Towards understanding temporal and spatial dynamics of seagrass landscapes using time-series remote sensing

    Science.gov (United States)

    Lyons, Mitchell B.; Roelfsema, Chris M.; Phinn, Stuart R.

    2013-03-01

    The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (≈200 km2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and

  4. Insights into soil carbon dynamics across climatic and geologic gradients from temporally-resolved radiocarbon measurements

    Science.gov (United States)

    van der Voort, T. S.; Hagedorn, F.; Mannu, U.; Walthert, L.; McIntyre, C.; Eglinton, T. I.

    2016-12-01

    Soil carbon constitutes the largest terrestrial reservoir of organic carbon, and therefore quantifying soil organic matter dynamics (carbon turnover, stocks and fluxes) across spatial gradients is essential for an understanding of the carbon cycle and the impacts of global change. In particular, links between soil carbon dynamics and different climatic and compositional factors remains poorly understood. Radiocarbon constitutes a powerful tool for unraveling soil carbon dynamics. Temporally-resolved radiocarbon measurements, which take advantage of "bomb-radiocarbon"-driven changes in atmospheric 14C, enable further constraints to be placed on C turnover times. These in turn can yield more precise flux estimates for both upper and deeper soil horizons. This project combines bulk radiocarbon measurements on a suite of soil profiles spanning strong climatic (MAT 1.3-9.2°C, MAP 600 to 2100 mm m-2y-1) and geologic gradients with a more in-depth approach for a subset of locations. For this subset, temporal and carbon-fraction specific radiocarbon data has been acquired for both topsoil and deeper soils. These well-studied sites are part of the Long-Term Forest Ecosystem Research (LWF) program of the Swiss Federal Institute for Forest, Snow and Landscape research (WSL). Resulting temporally-resolved turnover estimates are coupled to carbon stocks, fluxes across this wide range of forest ecosystems and are examined in the context of environmental drivers (temperature, precipitation, primary production and soil moisture) as well as composition (sand, silt and clay content). Statistical analysis on the region-scale - correlating radiocarbon signature with climatic variables such as temperature, precipitation, primary production and elevation - indicates that composition rather than climate is a key driver of ­­Δ14C signatures. Estimates of carbon turnover, stocks and fluxes derived from temporally-resolved measurements highlight the pivotal role of soil moisture as a

  5. An investigation into the effects of temporal resolution on hepatic dynamic contrast-enhanced MRI in volunteers and in patients with hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Gill, Andrew B; Graves, Martin J; Lomas, David J; Black, Richard T; Bowden, David J; Priest, Andrew N

    2014-01-01

    This study investigated the effect of temporal resolution on the dual-input pharmacokinetic (PK) modelling of dynamic contrast-enhanced MRI (DCE-MRI) data from normal volunteer livers and from patients with hepatocellular carcinoma. Eleven volunteers and five patients were examined at 3 T. Two sections, one optimized for the vascular input functions (VIF) and one for the tissue, were imaged within a single heart-beat (HB) using a saturation-recovery fast gradient echo sequence. The data was analysed using a dual-input single-compartment PK model. The VIFs and/or uptake curves were then temporally sub-sampled (at interval ▵t = [2–20] s) before being subject to the same PK analysis. Statistical comparisons of tumour and normal tissue PK parameter values using a 5% significance level gave rise to the same study results when temporally sub-sampling the VIFs to HB < ▵t <4 s. However, sub-sampling to ▵t > 4 s did adversely affect the statistical comparisons. Temporal sub-sampling of just the liver/tumour tissue uptake curves at ▵t ≤ 20 s, whilst using high temporal resolution VIFs, did not substantially affect PK parameter statistical comparisons. In conclusion, there is no practical advantage to be gained from acquiring very high temporal resolution hepatic DCE-MRI data. Instead the high temporal resolution could be usefully traded for increased spatial resolution or SNR. (paper)

  6. Investigating fine-scale spatio-temporal predator-prey patterns in dynamic marine ecosystems: a functional data analysis approach

    NARCIS (Netherlands)

    Embling, C.B.; Illian, J.; Armstrong, E.; van der Kooij, J.; Sharples, J.; Camphuysen, K.C.J.; Scott, B.E.

    2012-01-01

    1. Spatial management of marine ecosystems requires detailed knowledge of spatio-temporal mechanisms linking physical and biological processes. Tidal currents, the main driver of ecosystem dynamics in temperate coastal ecosystems, influence predator foraging ecology by affecting prey distribution

  7. Business model dynamics and innovation

    DEFF Research Database (Denmark)

    Cavalcante, Sergio Andre; Kesting, Peter; Ulhøi, John Parm

    2011-01-01

    the impact of specific changes to a firm's business model. Such a tool would be particularly useful in identifying path dependencies and resistance at the process level, and would therefore allow a firm's management to take focused action on this in advance. Originality/value – The paper makes two main...... and specifies four different types of business model change: business model creation, extension, revision, and termination. Each type of business model change is associated with specific challenges. Practical implications – The proposed typology can serve as a basis for developing a management tool to evaluate......Purpose – This paper aims to discuss the need to dynamize the existing conceptualization of business model, and proposes a new typology to distinguish different types of business model change. Design/methodology/approach – The paper integrates basic insights of innovation, business process...

  8. On whole Abelian model dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Chauca, J.; Doria, R. [CBPF, Rio de Janeiro (Brazil); Aprendanet, Petropolis, 25600 (Brazil)

    2012-09-24

    Physics challenge is to determine the objects dynamics. However, there are two ways for deciphering the part. The first one is to search for the ultimate constituents; the second one is to understand its behaviour in whole terms. Therefore, the parts can be defined either from elementary constituents or as whole functions. Historically, science has been moving through the first aspect, however, quarks confinement and complexity are interrupting this usual approach. These relevant facts are supporting for a systemic vision be introduced. Our effort here is to study on the whole meaning through gauge theory. Consider a systemic dynamics oriented through the U(1) - systemic gauge parameter which function is to collect a fields set {l_brace}A{sub {mu}I}{r_brace}. Derive the corresponding whole gauge invariant Lagrangian, equations of motion, Bianchi identities, Noether relationships, charges and Ward-Takahashi equations. Whole Lorentz force and BRST symmetry are also studied. These expressions bring new interpretations further than the usual abelian model. They are generating a systemic system governed by 2N+ 10 classical equations plus Ward-Takahashi identities. A whole dynamics based on the notions of directive and circumstance is producing a set determinism where the parts dynamics are inserted in the whole evolution. A dynamics based on state, collective and individual equations with a systemic interdependence.

  9. Understanding onsets of rainfall in Southern Africa using temporal probabilistic modelling

    CSIR Research Space (South Africa)

    Cheruiyot, D

    2010-12-01

    Full Text Available This research investigates an alternative approach to automatically evolve the hidden temporal distribution of onset of rainfall directly from multivariate time series (MTS) data in the absence of domain experts. Temporal probabilistic modelling...

  10. Modeling structural change in spatial system dynamics: A Daisyworld example.

    Science.gov (United States)

    Neuwirth, C; Peck, A; Simonović, S P

    2015-03-01

    System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed.

  11. Relating structure and dynamics in organisation models

    NARCIS (Netherlands)

    Jonkers, C.M.; Treur, J.

    2002-01-01

    To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems,

  12. Three-Dimensional Water and Carbon Cycle Modeling at High Spatial-Temporal Resolutions

    Science.gov (United States)

    Liao, C.; Zhuang, Q.

    2017-12-01

    Terrestrial ecosystems in cryosphere are very sensitive to the global climate change due to the presence of snow covers, mountain glaciers and permafrost, especially when the increase in near surface air temperature is almost twice as large as the global average. However, few studies have investigated the water and carbon cycle dynamics using process-based hydrological and biogeochemistry modeling approach. In this study, we used three-dimensional modeling approach at high spatial-temporal resolutions to investigate the water and carbon cycle dynamics for the Tanana Flats Basin in interior Alaska with emphases on dissolved organic carbon (DOC) dynamics. The results have shown that: (1) lateral flow plays an important role in water and carbon cycle, especially in dissolved organic carbon (DOC) dynamics. (2) approximately 2.0 × 104 kg C yr-1 DOC is exported to the hydrological networks and it compromises 1% and 0.01% of total annual gross primary production (GPP) and total organic carbon stored in soil, respectively. This study has established an operational and flexible framework to investigate and predict the water and carbon cycle dynamics under the changing climate.

  13. Modelling MIZ dynamics in a global model

    Science.gov (United States)

    Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

    2016-04-01

    Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

  14. Temporal analysis of text data using latent variable models

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Larsen, Jan; Goutte, Cyril

    2009-01-01

    Detecting and tracking of temporal data is an important task in multiple applications. In this paper we study temporal text mining methods for Music Information Retrieval. We compare two ways of detecting the temporal latent semantics of a corpus extracted from Wikipedia, using a stepwise...

  15. The effects of spatial and temporal heterogeneity on the population dynamics of four animal species in a Danish landscape

    Directory of Open Access Journals (Sweden)

    Forchhammer Mads C

    2009-06-01

    Full Text Available Abstract Background Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms

  16. Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images

    Directory of Open Access Journals (Sweden)

    Cécile Cazals

    2016-07-01

    Full Text Available In Europe, water levels in wetlands are widely controlled by environmental managers and farmers. However, the influence of these management practices on hydrodynamics and biodiversity remains poorly understood. This study assesses advantages of using radar data from the recently launched Sentinel-1A satellite to monitor hydrological dynamics of the Poitevin marshland in western France. We analyze a time series of 14 radar images acquired in VV and HV polarizations from December 2014 to May 2015 with a 12-day time step. Both polarizations are used with a hysteresis thresholding algorithm which uses both spatial and temporal information to distinguish open water, flooded vegetation and non-flooded grassland. Classification results are compared to in situ piezometric measurements combined with a Digital Terrain Model derived from LiDAR data. Results reveal that open water is successfully detected, whereas flooded grasslands with emergent vegetation and fine-grained patterns are detected with moderate accuracy. Five hydrological regimes are derived from the flood duration and mapped. Analysis of time steps in the time series shows that decreased temporal repetitivity induces significant differences in estimates of flood duration. These results illustrate the great potential to monitor variations in seasonal floods with the high temporal frequency of Sentinel-1A acquisitions.

  17. Verification of temporal-causal network models by mathematical analysis

    Directory of Open Access Journals (Sweden)

    Jan Treur

    2016-04-01

    Full Text Available Abstract Usually dynamic properties of models can be analysed by conducting simulation experiments. But sometimes, as a kind of prediction properties can also be found by calculations in a mathematical manner, without performing simulations. Examples of properties that can be explored in such a manner are: whether some values for the variables exist for which no change occurs (stationary points or equilibria, and how such values may depend on the values of the parameters of the model and/or the initial values for the variables whether certain variables in the model converge to some limit value (equilibria and how this may depend on the values of the parameters of the model and/or the initial values for the variables whether or not certain variables will show monotonically increasing or decreasing values over time (monotonicity how fast a convergence to a limit value takes place (convergence speed whether situations occur in which no convergence takes place but in the end a specific sequence of values is repeated all the time (limit cycle Such properties found in an analytic mathematical manner can be used for verification of the model by checking them for the values observed in simulation experiments. If one of these properties is not fulfilled, then there will be some error in the implementation of the model. In this paper some methods to analyse such properties of dynamical models will be described and illustrated for the Hebbian learning model, and for dynamic connection strengths in social networks. The properties analysed by the methods discussed cover equilibria, increasing or decreasing trends, recurring patterns (limit cycles, and speed of convergence to equilibria.

  18. Simulation of sensory integration dysfunction in autism with dynamic neural fields model

    NARCIS (Netherlands)

    Chonnaparamutt, W.; Barakova, E.I.; Rutkowski, L.; Taseusiewicz, R.

    2008-01-01

    This paper applies dynamic neural fields model [1,23,7] to multimodal interaction of sensory cues obtained from a mobile robot, and shows the impact of different temporal aspects of the integration to the precision of movements. We speculate that temporally uncoordinated sensory integration might be

  19. Social Dynamics Modeling and Inference

    Science.gov (United States)

    2018-03-29

    the experiment(s)/ theory and equipment or analyses. Development of innovative theoretical model and methodologies with experimental verifications...information. The methodology based on communication and information theory (thanks to leave at MIT supported by this research) is described in [J1], [C2...a dynamic system [C1] and as a social learning mechanism in details [J4]. Furthermore, by incentive seeding and rewiring connections, information

  20. The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

    Directory of Open Access Journals (Sweden)

    Yun Jian

    Full Text Available An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the

  1. Spatial and temporal dynamics of multidimensional well-being, livelihoods and ecosystem services in coastal Bangladesh

    Science.gov (United States)

    Adams, Helen; Adger, W. Neil; Ahmad, Sate; Ahmed, Ali; Begum, Dilruba; Lázár, Attila N.; Matthews, Zoe; Rahman, Mohammed Mofizur; Streatfield, Peter Kim

    2016-01-01

    Populations in resource dependent economies gain well-being from the natural environment, in highly spatially and temporally variable patterns. To collect information on this, we designed and implemented a 1586-household quantitative survey in the southwest coastal zone of Bangladesh. Data were collected on material, subjective and health dimensions of well-being in the context of natural resource use, particularly agriculture, aquaculture, mangroves and fisheries. The questionnaire included questions on factors that mediate poverty outcomes: mobility and remittances; loans and micro-credit; environmental perceptions; shocks; and women’s empowerment. The data are stratified by social-ecological system to take into account spatial dynamics and the survey was repeated with the same respondents three times within a year to incorporate seasonal dynamics. The dataset includes blood pressure measurements and height and weight of men, women and children. In addition, the household listing includes basic data on livelihoods and income for approximately 10,000 households. The dataset facilitates interdisciplinary research on spatial and temporal dynamics of well-being in the context of natural resource dependence in low income countries. PMID:27824340

  2. Femtosecond laser spectroscopy of spins: Magnetization dynamics in thin magnetic films with spatio-temporal resolution

    International Nuclear Information System (INIS)

    Carpene, E.; Mancini, E.; Dallera, C.; Puppin, E.; De Silvestri, S.

    2010-01-01

    Based on the Magneto-Optical Kerr Effect (MOKE), we have developed an experimental set-up that allows us to fully characterize the magnetization dynamics in thin magnetic films by measuring all three real space components of the magnetization vector M. By means of the pump-probe technique it is possible to extract the time dependence of each individual projection with sub-picosecond resolution. This method has been exploited to investigate the temporal evolution of the magnetization (modulus and orientation) induced by an ultrashort laser pulse in thin epitaxial iron films. According to our results, we deduced that the initial, sub-picosecond demagnetization is established at the electronic level through electron-magnon excitations. The subsequent dynamics is characterized by a precessional motion on the 100 ps time scale, around an effective, time-dependent magnetic field. Following the full dynamics of M, the temporal evolution of the magneto-crystalline anisotropy constant can be unambiguously determined, providing the experimental evidence that the precession is triggered by the rapid, optically-induced misalignment between the magnetization vector and the effective magnetic field. These results suggest a possible pathway toward the ultrarapid switching of the magnetization.

  3. Method to investigate temporal dynamics of ganglion and other retinal cells in the living human eye

    Science.gov (United States)

    Kurokawa, Kazuhiro; Liu, Zhuolin; Crowell, James; Zhang, Furu; Miller, Donald T.

    2018-02-01

    The inner retina is critical for visual processing, but much remains unknown about its neural circuitry and vulnerability to disease. A major bottleneck has been our inability to observe the structure and function of the cells composing these retinal layers in the living human eye. Here, we present a noninvasive method to observe both structural and functional information. Adaptive optics optical coherence tomography (AO-OCT) is used to resolve the inner retinal cells in all three dimensions and novel post processing algorithms are applied to extract structure and physiology down to the cellular level. AO-OCT captured the 3D mosaic of individual ganglion cell somas, retinal nerve fiber bundles of micron caliber, and microglial cells, all in exquisite detail. Time correlation analysis of the AO-OCT videos revealed notable temporal differences between the principal layers of the inner retina. The GC layer was more dynamic than the nerve fiber and inner plexiform layers. At the cellular level, we applied a customized correlation method to individual GCL somas, and found a mean time constant of activity of 0.57 s and spread of +/-0.1 s suggesting a range of physiological dynamics even in the same cell type. Extending our method to slower dynamics (from minutes to one year), time-lapse imaging and temporal speckle contrast revealed appendage and soma motion of resting microglial cells at the retinal surface.

  4. A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

    Directory of Open Access Journals (Sweden)

    LI Yinchao

    2016-07-01

    Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

  5. Dinâmica da epidemia de AIDS no Município do Rio de Janeiro, no período de 1988-1996: uma aplicação de análise estatística espaço-temporal Spatial-temporal modeling: dynamics of the AIDS epidemic in the municipality of Rio de Janeiro, Brazil, 1988-1996

    Directory of Open Access Journals (Sweden)

    Célia Landmann Szwarcwald

    2001-10-01

    Full Text Available Neste estudo, aplicou-se um modelo espaço-temporal para examinar a disseminação espacial da epidemia de AIDS entre os casos adultos do Município do Rio de Janeiro em três períodos: 1988-1990, 1991-1993 e 1994-1996. As regiões administrativas foram as unidades geográficas de estudo. Posteriormente, realizou-se análise espacial dos casos pediátricos por transmissão vertical do HIV, por período de nascimento, 1985-1990 e 1991-1996. Para a totalidade dos casos adultos, o período inicial é caracterizado por um conglomerado poligonal em torno da Zona Portuária, que se expande na direção oeste-leste. Entre os casos homossexuais, o crescimento in situ predominou, notando-se arrefecimento da disseminação espacial nos últimos anos. Entre os casos heterossexuais, a epidemia demonstrou expansão geográfica expressiva, sobretudo de 1988-1990 a 1991-1993. Entre os casos do sexo feminino, no último período, houve a formação de um conglomerado de taxas elevadas na direção noroeste, que compreende áreas muito pobres. Entre 1991 e 1996, observou-se correlação significativa das taxas de incidência de AIDS perinatal com o índice de concentração de pobreza. Os resultados sugerem que o entendimento da dinâmica espaço-temporal da epidemia pode subsidiar, de forma relevante, as ações preventivas.This study uses a spatial-temporal model to analyze the spatial spread of the AIDS epidemic (adult cases in the municipality of Rio de Janeiro, Brazil, during three periods: 1988-1990, 1991-1993, and 1994-1996. City districts were used as the geographic units of analysis. A spatial analysis was also performed for pediatric AIDS cases due to vertical HIV transmission, according to period of birth, 1985-90 and 1991-96. For total adult AIDS cases, the initial period was characterized by a polygonal cluster located around the harbor area, which expanded from west to east. Among homosexual cases, in situ growth predominated, and a decrease in

  6. Spatio-temporal Background Models for Outdoor Surveillance

    Directory of Open Access Journals (Sweden)

    Pless Robert

    2005-01-01

    Full Text Available Video surveillance in outdoor areas is hampered by consistent background motion which defeats systems that use motion to identify intruders. While algorithms exist for masking out regions with motion, a better approach is to develop a statistical model of the typical dynamic video appearance. This allows the detection of potential intruders even in front of trees and grass waving in the wind, waves across a lake, or cars moving past. In this paper we present a general framework for the identification of anomalies in video, and a comparison of statistical models that characterize the local video dynamics at each pixel neighborhood. A real-time implementation of these algorithms runs on an 800 MHz laptop, and we present qualitative results in many application domains.

  7. Microbial Dynamics During a Temporal Sequence of Bioreduction Stimulated by Emulsified Vegetable Oil

    Science.gov (United States)

    Schadt, C. W.; Gihring, T. M.; Yang, Z.; Wu, W.; Green, S.; Overholt, W.; Zhang, G.; Brandt, C. C.; Campbell, J. H.; Carroll, S. C.; Criddle, C.; Jardine, P. M.; Lowe, K.; Mehlhorn, T.; Kostka, J. E.; Watson, D. B.; Brooks, S. C.

    2011-12-01

    Amendments of slow-release substrates (e.g. emulsified vegetable oil; EVO) are potentially pragmatic alternatives to short-lived labile substrates for sustained uranium bioimmobilization within groundwater systems. The spatial and temporal dynamics of geochemical and microbial community changes during EVO amendment are likely to differ significantly from populations stimulated by readily utilizable soluble substrates (e.g. ethanol or acetate). We tracked dynamic changes in geochemistry and microbial communities for 270 days following a one-time EVO injection at the Oak Ridge Integrated Field Research Challenge (ORIFRC) site that resulted in decreased groundwater U concentrations for ~4 months. Pyrosequencing and quantitative PCR of 16S rRNA and dissimilatory sulfite reductase (dsrA) genes from monitoring well samples revealed a rapid decline in bacterial community richness and evenness after EVO injection, concurrent with increased 16S rRNA copy levels, indicating the selection of a narrow group consisting of 10-15 dominant OTUs, rather than a broad community stimulation. By association of the known physiology of close relatives identified in the pyrosequencing analysis, it is possible to infer a hypothesized sequence of microbial functions leading the major changes in electron donors and acceptors in the system. Members of the Firmicutes family Veillonellaceae dominated after injection and most likely catalyzed the initial oil decomposition and utilized the glycerol associated with the oils. Sulfate-reducing bacteria from the genus Desulforegula, known for LCFA oxidation to acetate, also dominated shortly after EVO amendment and are thought to catalyze this process. Acetate and H2 production during LCFA degradation appeared to stimulate NO3-, Fe(III), U(VI), and SO42- reduction by members of the Comamonadaceae, Geobacteriaceae, and Desulfobacterales. Methanogenic archaea flourished late in the experiment and in some samples constituted over 25 % of the total

  8. Embodiment of intersubjective time: relational dynamics as attractors in the temporal coordination of interpersonal behaviors and experiences.

    Science.gov (United States)

    Laroche, Julien; Berardi, Anna Maria; Brangier, Eric

    2014-01-01

    This paper addresses the issue of "being together," and more specifically the issue of "being together in time." We provide with an integrative framework that is inspired by phenomenology, the enactive approach and dynamical systems theories. To do so, we first define embodiment as a living and lived phenomenon that emerges from agent-world coupling. We then show that embodiment is essentially dynamical and therefore we describe experiential, behavioral and brain dynamics. Both lived temporality and the temporality of the living appear to be complex, multiscale phenomena. Next we discuss embodied dynamics in the context of interpersonal interactions, and briefly review the empirical literature on between-persons temporal coordination. Overall, we propose that being together in time emerges from the relational dynamics of embodied interactions and their flexible co-regulation.

  9. Impact of Partial Time Delay on Temporal Dynamics of Watts-Strogatz Small-World Neuronal Networks

    Science.gov (United States)

    Yan, Hao; Sun, Xiaojuan

    2017-06-01

    In this paper, we mainly discuss effects of partial time delay on temporal dynamics of Watts-Strogatz (WS) small-world neuronal networks by controlling two parameters. One is the time delay τ and the other is the probability of partial time delay pdelay. Temporal dynamics of WS small-world neuronal networks are discussed with the aid of temporal coherence and mean firing rate. With the obtained simulation results, it is revealed that for small time delay τ, the probability pdelay could weaken temporal coherence and increase mean firing rate of neuronal networks, which indicates that it could improve neuronal firings of the neuronal networks while destroying firing regularity. For large time delay τ, temporal coherence and mean firing rate do not have great changes with respect to pdelay. Time delay τ always has great influence on both temporal coherence and mean firing rate no matter what is the value of pdelay. Moreover, with the analysis of spike trains and histograms of interspike intervals of neurons inside neuronal networks, it is found that the effects of partial time delays on temporal coherence and mean firing rate could be the result of locking between the period of neuronal firing activities and the value of time delay τ. In brief, partial time delay could have great influence on temporal dynamics of the neuronal networks.

  10. Envelope detection using temporal magnetization dynamics of resonantly interacting spin-torque oscillator

    Science.gov (United States)

    Nakamura, Y.; Nishikawa, M.; Osawa, H.; Okamoto, Y.; Kanao, T.; Sato, R.

    2018-05-01

    In this article, we propose the detection method of the recorded data pattern by the envelope of the temporal magnetization dynamics of resonantly interacting spin-torque oscillator on the microwave assisted magnetic recording for three-dimensional magnetic recording. We simulate the envelope of the waveform from recorded dots with the staggered magnetization configuration, which are calculated by using a micromagnetic simulation. We study the data detection methods for the envelope and propose a soft-output Viterbi algorithm (SOVA) for partial response (PR) system as a signal processing system for three dimensional magnetic recording.

  11. From Brain-Environment Connections to Temporal Dynamics and Social Interaction: Principles of Human Brain Function.

    Science.gov (United States)

    Hari, Riitta

    2017-06-07

    Experimental data about brain function accumulate faster than does our understanding of how the brain works. To tackle some general principles at the grain level of behavior, I start from the omnipresent brain-environment connection that forces regularities of the physical world to shape the brain. Based on top-down processing, added by sparse sensory information, people are able to form individual "caricature worlds," which are similar enough to be shared among other people and which allow quick and purposeful reactions to abrupt changes. Temporal dynamics and social interaction in natural environments serve as further essential organizing principles of human brain function. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. A non-parametric hierarchical model to discover behavior dynamics from tracks

    NARCIS (Netherlands)

    Kooij, J.F.P.; Englebienne, G.; Gavrila, D.M.

    2012-01-01

    We present a novel non-parametric Bayesian model to jointly discover the dynamics of low-level actions and high-level behaviors of tracked people in open environments. Our model represents behaviors as Markov chains of actions which capture high-level temporal dynamics. Actions may be shared by

  13. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  14. A temporal modelling environment for internally grounded beliefs, desires and intentions

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

    In this paper the internal dynamics of mental states, in particular states based on beliefs, desires and intentions, is formalised using a temporal language. A software environment is presented that can be used to specify, simulate and analyse temporal dependencies between mental states in

  15. Models of neural dynamics in brain information processing - the developments of 'the decade'

    Energy Technology Data Exchange (ETDEWEB)

    Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B [Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation); Ivanitskii, Genrikh R [Institute for Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation)

    2002-10-31

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

  16. Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input.

    Science.gov (United States)

    Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P; Jansson, Janet K; Hopkins, David W; Aspray, Thomas J; Seely, Mary; Trindade, Marla I; Cowan, Don A

    2016-09-29

    The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO 2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.

  17. Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P.; Jansson, Janet K.; Hopkins, David W.; Aspray, Thomas J.; Seely, Mary; Trindade, Marla I.; Cowan, Don A.

    2016-09-29

    The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.

  18. Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast

    Directory of Open Access Journals (Sweden)

    Dong Wang

    2017-01-01

    Full Text Available Purpose. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. Methods. We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT, Haar wavelet transform (WT, total variation (TV, second-order total generalized variation (TGVα2, and nuclear norm (NN. We measured the signal-to-error ratio (SER of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs of the derived pharmacokinetic parameters Ktrans (volume transfer constant and ve (extravascular-extracellular volume fraction across a population of random sampling schemes. Results. NN produced the lowest image error (SER: 29.1, while TV/TGVα2 produced the most accurate Ktrans (CCC: 0.974/0.974 and ve (CCC: 0.916/0.917. WT produced the highest image error (SER: 21.8, while FT produced the least accurate Ktrans (CCC: 0.842 and ve (CCC: 0.799. Conclusion. TV/TGVα2 should be used as temporal constraints for CS DCE-MRI of the breast.

  19. Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks.

    Science.gov (United States)

    Lee, Wang Wei; Kukreja, Sunil L; Thakor, Nitish V

    2017-01-01

    This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications.

  20. Temporal Microbial Community Dynamics in Microbial Electrolysis Cells – Influence of Acetate and Propionate Concentration

    KAUST Repository

    Rao, Hari Ananda

    2017-07-20

    Microbial electrolysis cells (MECs) are widely considered as a next generation wastewater treatment system. However, fundamental insight on the temporal dynamics of microbial communities associated with MEC performance under different organic types with varied loading concentrations is still unknown, nevertheless this knowledge is essential for optimizing this technology for real-scale applications. Here, the temporal dynamics of anodic microbial communities associated with MEC performance was examined at low (0.5 g COD/L) and high (4 g COD/L) concentrations of acetate or propionate, which are important intermediates of fermentation of municipal wastewaters and sludge. The results showed that acetate-fed reactors exhibited higher performance in terms of maximum current density (I: 4.25 ± 0.23 A/m), coulombic efficiency (CE: 95 ± 8%), and substrate degradation rate (98.8 ± 1.2%) than propionate-fed reactors (I: 2.7 ± 0.28 A/m; CE: 68 ± 9.5%; substrate degradation rate: 84 ± 13%) irrespective of the concentrations tested. Despite of the repeated sampling of the anodic biofilm over time, the high-concentration reactors demonstrated lower and stable performance in terms of current density (I: 1.1 ± 0.14 to 4.2 ± 0.21 A/m), coulombic efficiency (CE: 44 ± 4.1 to 103 ± 7.2%) and substrate degradation rate (64.9 ± 6.3 to 99.7 ± 0.5%), while the low-concentration reactors produced higher and dynamic performance (I: 1.1 ± 0.12 to 4.6 ± 0.1 A/m; CE: 52 ± 2.5 to 105 ± 2.7%; substrate degradation rate: 87.2 ± 0.2 to 99.9 ± 0.06%) with the different substrates tested. Correlating reactor\\'s performance with temporal dynamics of microbial communities showed that relatively similar anodic microbial community composition but with varying relative abundances was observed in all the reactors despite differences in the substrate and concentrations tested. Particularly, Geobacter was the predominant bacteria on the anode biofilm of all MECs over time suggesting its

  1. Evaluating complementary networks of restoration plantings for landscape-scale occurrence of temporally dynamic species.

    Science.gov (United States)

    Ikin, Karen; Tulloch, Ayesha; Gibbons, Philip; Ansell, Dean; Seddon, Julian; Lindenmayer, David

    2016-10-01

    Multibillion dollar investments in land restoration make it critical that conservation goals are achieved cost-effectively. Approaches developed for systematic conservation planning offer opportunities to evaluate landscape-scale, temporally dynamic biodiversity outcomes from restoration and improve on traditional approaches that focus on the most species-rich plantings. We investigated whether it is possible to apply a complementarity-based approach to evaluate the extent to which an existing network of restoration plantings meets representation targets. Using a case study of woodland birds of conservation concern in southeastern Australia, we compared complementarity-based selections of plantings based on temporally dynamic species occurrences with selections based on static species occurrences and selections based on ranking plantings by species richness. The dynamic complementarity approach, which incorporated species occurrences over 5 years, resulted in higher species occurrences and proportion of targets met compared with the static complementarity approach, in which species occurrences were taken at a single point in time. For equivalent cost, the dynamic complementarity approach also always resulted in higher average minimum percent occurrence of species maintained through time and a higher proportion of the bird community meeting representation targets compared with the species-richness approach. Plantings selected under the complementarity approaches represented the full range of planting attributes, whereas those selected under the species-richness approach were larger in size. Our results suggest that future restoration policy should not attempt to achieve all conservation goals within individual plantings, but should instead capitalize on restoration opportunities as they arise to achieve collective value of multiple plantings across the landscape. Networks of restoration plantings with complementary attributes of age, size, vegetation structure, and

  2. Multiscale modeling of pedestrian dynamics

    CERN Document Server

    Cristiani, Emiliano; Tosin, Andrea

    2014-01-01

    This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.

  3. Modeling of glutamate-induced dynamical patterns

    DEFF Research Database (Denmark)

    Faurby-Bentzen, Christian Krefeld; Zhabotinsky, A.M.; Laugesen, Jakob Lund

    2009-01-01

    Based on established physiological mechanisms, the paper presents a detailed computer model, which supports the hypothesis that temporal lobe epilepsy may be caused by failure of glutamate reuptake from the extracellular space. The elevated glutamate concentration causes an increased activation...

  4. Fluid consumption and taste novelty determines transcription temporal dynamics in the gustatory cortex.

    Science.gov (United States)

    Inberg, Sharon; Jacob, Eyal; Elkobi, Alina; Edry, Efrat; Rappaport, Akiva; Simpson, T Ian; Armstrong, J Douglas; Shomron, Noam; Pasmanik-Chor, Metsada; Rosenblum, Kobi

    2016-02-09

    Novel taste memories, critical for animal survival, are consolidated to form long term memories which are dependent on translation regulation in the gustatory cortex (GC) hours following acquisition. However, the role of transcription regulation in the process is unknown. Here, we report that transcription in the GC is necessary for taste learning in rats, and that drinking and its consequences, as well as the novel taste experience, affect transcription in the GC during taste memory consolidation. We show differential effects of learning on temporal dynamics in set of genes in the GC, including Arc/Arg3.1, known to regulate the homeostasis of excitatory synapses. We demonstrate that in taste learning, transcription programs were activated following the physiological responses (i.e., fluid consumption following a water restriction regime, reward, arousal of the animal, etc.) and the specific information about a given taste (i.e., taste novelty). Moreover, the cortical differential prolonged kinetics of mRNA following novel versus familiar taste learning may represent additional novelty related molecular response, where not only the total amount, but also the temporal dynamics of transcription is modulated by sensory experience of novel information.

  5. Amygdala temporal dynamics: temperamental differences in the timing of amygdala response to familiar and novel faces

    Directory of Open Access Journals (Sweden)

    Shelton Richard C

    2009-12-01

    Full Text Available Abstract Background Inhibited temperament - the predisposition to respond to new people, places or things with wariness or avoidance behaviors - is associated with increased risk for social anxiety disorder and major depression. Although the magnitude of the amygdala's response to novelty has been identified as a neural substrate of inhibited temperament, there may also be differences in temporal dynamics (latency, duration, and peak. We hypothesized that persons with inhibited temperament would have faster responses to novel relative to familiar neutral faces compared to persons with uninhibited temperament. We used event-related functional magnetic resonance imaging to measure the temporal dynamics of the blood oxygen level dependent (BOLD response to both novel and familiar neutral faces in participants with inhibited or uninhibited temperament. Results Inhibited participants had faster amygdala responses to novel compared with familiar faces, and both longer and greater amygdala response to all faces. There were no differences in peak response. Conclusion Faster amygdala response to novelty may reflect a computational bias that leads to greater neophobic responses and represents a mechanism for the development of social anxiety.

  6. Left or right? Lateralizing temporal lobe epilepsy by dynamic amygdala fMRI.

    Science.gov (United States)

    Ives-Deliperi, Victoria; Butler, James Thomas; Jokeit, Hennric

    2017-05-01

    In this case series, the findings of 85 functional MRI studies employing a dynamic fearful face paradigm are reported. Previous findings have shown the paradigm to generate bilateral amygdala activations in healthy subjects and unilateral activations in patients with MTLE, in the contralateral hemisphere to seizure origin. Such findings suggest ipsilateral limbic pathology and offer collateral evidence in lateralizing MTLE. The series includes 60 patients with TLE, 12 patients with extra-temporal lobe epilepsy, and 13 healthy controls. Functional MRI studies using a 1.5T scanner were conducted over a three-year period at a single epilepsy center and individual results were compared with EEG findings. In the cohort of unilateral TLE patients, lateralized activations of the amygdala were concordant with EEG findings in 76% of patients (77% lTLE, 74% rTLE). The differences in the mean lateralized indices of the lTLE, rTLE, and healthy control groups were all statistically significant. Lateralized amygdala activations were concordant with EEG findings in only 31% of the 12 patients with extra-temporal lobe epilepsy and bilateral amygdala activations were generated in all but one of the healthy control subjects. This case series further endorses the utility of the dynamic fearful face functional MRI paradigm using the widely available 1.5T as an adjunctive investigation to lateralize TLE. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

    NARCIS (Netherlands)

    P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We

  8. Influence of fluvial environments on sediment archiving processes and temporal pollutant dynamics (Upper Loire River, France).

    Science.gov (United States)

    Dhivert, E; Grosbois, C; Rodrigues, S; Desmet, M

    2015-02-01

    Floodplains are often cored to build long-term pollutant trends at the basin scale. To highlight the influences of depositional environments on archiving processes, aggradation rates, archived trace element signals and vertical redistribution processes, two floodplain cores were sampled near in two different environments of the Upper Loire River (France): (i) a river bank ridge and (ii) a paleochannel connected by its downstream end. The base of the river bank core is composed of sandy sediments from the end of the Little Ice Age (late 18th century). This composition corresponds to a proximal floodplain aggradation (sediments that settled in the distal floodplain. In this distal floodplain environment, the aggradation rate depends on the topography and connection degree to the river channel. The temporal dynamics of anthropogenic trace element enrichments recorded in the distal floodplain are initially synchronous and present similar levels. Although the river bank core shows general temporal trends, the paleochannel core has a better resolution for short-time variations of trace element signals. After local water depth regulation began in the early 1930s, differences of connection degree were enhanced between the two cores. Therefore, large trace element signal divergences are recorded across the floodplain. The paleochannel core shows important temporal variations of enrichment levels from the 1930s to the coring date. However, the river bank core has no significant temporal variations of trace element enrichments and lower contamination levels because of a lower deposition of contaminated sediments and a pedogenetic trace elements redistribution. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Exploring spatial-temporal dynamics of fire regime features in mainland Spain

    Science.gov (United States)

    Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

    2017-10-01

    This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

  10. Exploring spatial–temporal dynamics of fire regime features in mainland Spain

    Directory of Open Access Journals (Sweden)

    A. Jiménez-Ruano

    2017-10-01

    Full Text Available This paper explores spatial–temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial – regional and provincial/NUTS3 – levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974–2013. Temporal shifts in fire features are investigated by means of change point detection procedures – Pettitt test, AMOC (at most one change, PELT (pruned exact linear time and BinSeg (binary segmentation – at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann–Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA and varimax rotation to trend outputs – mainly Sen's slope values – to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann–Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1, summer burnt area (PC2, large fires (PC3 and natural fires (PC4.

  11. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Science.gov (United States)

    Daya Sagar, B. S.

    2005-01-01

    Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  12. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Directory of Open Access Journals (Sweden)

    B. S. Daya Sagar

    2005-01-01

    Full Text Available Spatio-temporal patterns of small water bodies (SWBs under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  13. Assessing the Utility of Temporally Dynamic Terrain Indices in Alaskan Moose Resource Selection

    Science.gov (United States)

    Jennewein, J. S.; Hebblewhite, M.; Meddens, A. J.; Gilbert, S.; Vierling, L. A.; Boelman, N.; Eitel, J.

    2017-12-01

    The accelerated warming in arctic and boreal regions impacts ecosystem structure and plant species distribution, which have secondary effects on wildlife. In summer months, moose (Alces alces) are especially vulnerable to changes in the availability and quality of forage and foliage cover due to their thermoregulatory needs and high energetic demands post calving. Resource selection functions (RSFs) have been used with great success to model such tradeoffs in habitat selection. Recently, RSFs have expanded to include more dynamic representations of habitat selection through the use of time-varying covariates such as dynamic habitat indices. However, to date few studies have investigated dynamic terrain indices, which incorporate long-term, highly-dynamic meteorological data (e.g., albedo, air temperature) and their utility in modeling habitat selection. The purpose of this study is to compare two dynamic terrain indices (i.e., solar insolation and topographic wetness) to their static counterparts in Alaskan moose resource selection over a ten-year period (2008-2017). Additionally, the utility of a dynamic wind-shelter index is assessed. Three moose datasets (n=130 total), spanning a north-to-south gradient in Alaska, are analyzed independently to assess location-specific resource selection. The newly-released, high-resolution Arctic Digital Elevation Model (5m2) is used as the terrain input into both dynamic and static indices. Dynamic indices are programmed with meteorological data from the North American Regional Analysis (NARR) and NASA's Goddard Earth Sciences Data and Information Services Center (GES-DISC) databases. Static wetness and solar insolation indices are estimated using only topographic parameters (e.g., slope, aspect). Preliminary results from pilot analyses suggest that dynamic terrain indices may provide novel insights into resource selection of moose that could not be gained when using static counterparts. Future applications of such dynamic

  14. Temporal dynamics of distinct CA1 cell populations during unconscious state induced by ketamine.

    Directory of Open Access Journals (Sweden)

    Hui Kuang

    2010-12-01

    Full Text Available Ketamine is a widely used dissociative anesthetic which can induce some psychotic-like symptoms and memory deficits in some patients during the post-operative period. To understand its effects on neural population dynamics in the brain, we employed large-scale in vivo ensemble recording techniques to monitor the activity patterns of simultaneously recorded hippocampal CA1 pyramidal cells and various interneurons during several conscious and unconscious states such as awake rest, running, slow wave sleep, and ketamine-induced anesthesia. Our analyses reveal that ketamine induces distinct oscillatory dynamics not only in pyramidal cells but also in at least seven different types of CA1 interneurons including putative basket cells, chandelier cells, bistratified cells, and O-LM cells. These emergent unique oscillatory dynamics may very well reflect the intrinsic temporal relationships within the CA1 circuit. It is conceivable that systematic characterization of network dynamics may eventually lead to better understanding of how ketamine induces unconsciousness and consequently alters the conscious mind.

  15. Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  16. Modeling Temporal Bias of Uplift Events in Recommender Systems

    KAUST Repository

    Altaf, Basmah

    2013-05-08

    Today, commercial industry spends huge amount of resources in advertisement campaigns, new marketing strategies, and promotional deals to introduce their product to public and attract a large number of customers. These massive investments by a company are worthwhile because marketing tactics greatly influence the consumer behavior. Alternatively, these advertising campaigns have a discernible impact on recommendation systems which tend to promote popular items by ranking them at the top, resulting in biased and unfair decision making and loss of customers’ trust. The biasing impact of popularity of items on recommendations, however, is not fixed, and varies with time. Therefore, it is important to build a bias-aware recommendation system that can rank or predict items based on their true merit at given time frame. This thesis proposes a framework that can model the temporal bias of individual items defined by their characteristic contents, and provides a simple process for bias correction. Bias correction is done either by cleaning the bias from historical training data that is used for building predictive model, or by ignoring the estimated bias from the predictions of a standard predictor. Evaluated on two real world datasets, NetFlix and MovieLens, our framework is shown to be able to estimate and remove the bias as a result of adopted marketing techniques from the predicted popularity of items at a given time.

  17. Temporal expectation and information processing: A model-based analysis

    NARCIS (Netherlands)

    Jepma, M.; Wagenmakers, E.-J.; Nieuwenhuis, S.

    2012-01-01

    People are able to use temporal cues to anticipate the timing of an event, enabling them to process that event more efficiently. We conducted two experiments, using the fixed-foreperiod paradigm (Experiment 1) and the temporal-cueing paradigm (Experiment 2), to assess which components of information

  18. Temporal Expectation and Information Processing: A Model-Based Analysis

    Science.gov (United States)

    Jepma, Marieke; Wagenmakers, Eric-Jan; Nieuwenhuis, Sander

    2012-01-01

    People are able to use temporal cues to anticipate the timing of an event, enabling them to process that event more efficiently. We conducted two experiments, using the fixed-foreperiod paradigm (Experiment 1) and the temporal-cueing paradigm (Experiment 2), to assess which components of information processing are speeded when subjects use such…

  19. Characterizing and Modeling Citation Dynamics

    Science.gov (United States)

    Eom, Young-Ho; Fortunato, Santo

    2011-01-01

    Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387

  20. MATHEMATICAL MODEL FOR RIVERBOAT DYNAMICS

    Directory of Open Access Journals (Sweden)

    Aleksander Grm

    2017-01-01

    Full Text Available Present work describes a simple dynamical model for riverboat motion based on the square drag law. Air and water interactions with the boat are determined from aerodynamic coefficients. CFX simulations were performed with fully developed turbulent flow to determine boat aerodynamic coefficients for an arbitrary angle of attack for the air and water portions separately. The effect of wave resistance is negligible compared to other forces. Boat movement analysis considers only two-dimensional motion, therefore only six aerodynamics coefficients are required. The proposed model is solved and used to determine the critical environmental parameters (wind and current under which river navigation can be conducted safely. Boat simulator was tested in a single area on the Ljubljanica river and estimated critical wind velocity.

  1. CoDCon Dynamic Modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Cipiti, Benjamin B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    The Co-Decontamination (CoDCon) Demonstration project is designed to test the separation of a mixed U and Pu product from dissolved spent nuclear fuel. The primary purpose of the project is to quantify the accuracy and precision to which a U/Pu mass ratio can be achieved without removing a pure Pu product. The system includes an on-line monitoring system using spectroscopy to monitor the ratios throughout the process. A dynamic model of the CoDCon flowsheet and on-line monitoring system was developed in order to expand the range of scenarios that can be examined for process control and determine overall measurement uncertainty. The model development and initial results are presented here.

  2. Modeling the dynamics of choice.

    Science.gov (United States)

    Baum, William M; Davison, Michael

    2009-06-01

    A simple linear-operator model both describes and predicts the dynamics of choice that may underlie the matching relation. We measured inter-food choice within components of a schedule that presented seven different pairs of concurrent variable-interval schedules for 12 food deliveries each with no signals indicating which pair was in force. This measure of local choice was accurately described and predicted as obtained reinforcer sequences shifted it to favor one alternative or the other. The effect of a changeover delay was reflected in one parameter, the asymptote, whereas the effect of a difference in overall rate of food delivery was reflected in the other parameter, rate of approach to the asymptote. The model takes choice as a primary dependent variable, not derived by comparison between alternatives-an approach that agrees with the molar view of behaviour.

  3. A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

    Science.gov (United States)

    Schmidt, Rainer; Gierl, Lothar

    2005-03-01

    Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

  4. Spatio-temporal dynamics of the penetration resistance of recultivated soils formed after open cast mining

    Directory of Open Access Journals (Sweden)

    A. V. Zhukov

    2016-01-01

    Full Text Available On the basis of studying the spatio-temporal dynamics of soil penetration resistance we proved the existence of the technozem ecomorphs as above horizon soil formations. Research was carried out at a research center for study of recultivation processes in Ordzhonikidze city. Measurement of soils penetration was made in field conditions using an Eijkelkamp penetrometer on a regular grid at depths of up to50 cmwith intervals of5 cm. Calculation of average values and degrees of variation was performed by means of descriptive statistical tools. The extent of soil penetration spatial dependence was assessed and the existence of ecomorphs was proved by means of geostatistical analysis. The degree of associativity of spatial distribution of indicators of a soil body in different years of research was established by means of correlation analysis. The level of variation in space and in time of  technozem penetration generated on loess-like loams, grey-green, red-brown clays, and also pedozems was revealed. The degree of spatial dependence of  technozem penetration within soil layers and also the linear sizes of ecomorphs as above horizon soil structures was established. The time dynamics of  penetration of various recultozems were described. As a result of research into the spatio-temporal dynamics of penetration of technozems, data confirming the hypothesis of the existence of ecomorphs as above horizon morphological soil formations were obtained. An ecomorphic approach to the study of the morphological structure of technozems is proposed. The comparative characteristics of ecomorphs from various types of technozem are presented. The results obtained solve the problem of combining the higher and lowest levels in the hierarchical system of soil organisation as a natural body, which should raise the efficiency of the analysis of relations of morphological elements as a basis for detailed reconstruction of recultivation processes, soil formation, and

  5. Frontiers in Fluctuation Spectroscopy: Measuring protein dynamics and protein spatio-temporal connectivity

    Science.gov (United States)

    Digman, Michelle

    Fluorescence fluctuation spectroscopy has evolved from single point detection of molecular diffusion to a family of microscopy imaging correlation tools (i.e. ICS, RICS, STICS, and kICS) useful in deriving spatial-temporal dynamics of proteins in living cells The advantage of the imaging techniques is the simultaneous measurement of all points in an image with a frame rate that is increasingly becoming faster with better sensitivity cameras and new microscopy modalities such as the sheet illumination technique. A new frontier in this area is now emerging towards a high level of mapping diffusion rates and protein dynamics in the 2 and 3 dimensions. In this talk, I will discuss the evolution of fluctuation analysis from the single point source to mapping diffusion in whole cells and the technology behind this technique. In particular, new methods of analysis exploit correlation of molecular fluctuations originating from measurement of fluctuation correlations at distant points (pair correlation analysis) and methods that exploit spatial averaging of fluctuations in small regions (iMSD). For example the pair correlation fluctuation (pCF) analyses done between adjacent pixels in all possible radial directions provide a window into anisotropic molecular diffusion. Similar to the connectivity atlas of neuronal connections from the MRI diffusion tensor imaging these new tools will be used to map the connectome of protein diffusion in living cells. For biological reaction-diffusion systems, live single cell spatial-temporal analysis of protein dynamics provides a mean to observe stochastic biochemical signaling in the context of the intracellular environment which may lead to better understanding of cancer cell invasion, stem cell differentiation and other fundamental biological processes. National Institutes of Health Grant P41-RRO3155.

  6. Network-Oriented Modeling of Multi-Criteria Homophily and Opinion Dynamics in Social Media

    NARCIS (Netherlands)

    Kozyreva, Olga; Pechina, Anna; Treur, J.

    2018-01-01

    In this paper we model the opinion dynamics in social groups in combination with adaptation of the connections based on a multicriteria homophily principle. The adaptive network model has been designed according to a Network-Oriented Modeling approach based on temporal-causal networks. The model has

  7. Dynamical modeling of tidal streams

    International Nuclear Information System (INIS)

    Bovy, Jo

    2014-01-01

    I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

  8. Characterizing and modeling the dynamics of online popularity.

    Science.gov (United States)

    Ratkiewicz, Jacob; Fortunato, Santo; Flammini, Alessandro; Menczer, Filippo; Vespignani, Alessandro

    2010-10-08

    Online popularity has an enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems: the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and interevent time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.

  9. Temporal Precedence Checking for Switched Models and its Application to a Parallel Landing Protocol

    Science.gov (United States)

    Duggirala, Parasara Sridhar; Wang, Le; Mitra, Sayan; Viswanathan, Mahesh; Munoz, Cesar A.

    2014-01-01

    This paper presents an algorithm for checking temporal precedence properties of nonlinear switched systems. This class of properties subsume bounded safety and capture requirements about visiting a sequence of predicates within given time intervals. The algorithm handles nonlinear predicates that arise from dynamics-based predictions used in alerting protocols for state-of-the-art transportation systems. It is sound and complete for nonlinear switch systems that robustly satisfy the given property. The algorithm is implemented in the Compare Execute Check Engine (C2E2) using validated simulations. As a case study, a simplified model of an alerting system for closely spaced parallel runways is considered. The proposed approach is applied to this model to check safety properties of the alerting logic for different operating conditions such as initial velocities, bank angles, aircraft longitudinal separation, and runway separation.

  10. The Emergence of Visual Awareness: Temporal Dynamics in Relation to Task and Mask Type

    Science.gov (United States)

    Kiefer, Markus; Kammer, Thomas

    2017-01-01

    One aspect of consciousness phenomena, the temporal emergence of visual awareness, has been subject of a controversial debate. How can visual awareness, that is the experiential quality of visual stimuli, be characterized best? Is there a sharp discontinuous or dichotomous transition between unaware and fully aware states, or does awareness emerge gradually encompassing intermediate states? Previous studies yielded conflicting results and supported both dichotomous and gradual views. It is well conceivable that these conflicting results are more than noise, but reflect the dynamic nature of the temporal emergence of visual awareness. Using a psychophysical approach, the present research tested whether the emergence of visual awareness is context-dependent with a temporal two-alternative forced choice task. During backward masking of word targets, it was assessed whether the relative temporal sequence of stimulus thresholds is modulated by the task (stimulus presence, letter case, lexical decision, and semantic category) and by mask type. Four masks with different similarity to the target features were created. Psychophysical functions were then fitted to the accuracy data in the different task conditions as a function of the stimulus mask SOA in order to determine the inflection point (conscious threshold of each feature) and slope of the psychophysical function (transition from unaware to aware within each feature). Depending on feature-mask similarity, thresholds in the different tasks were highly dispersed suggesting a graded transition from unawareness to awareness or had less differentiated thresholds indicating that clusters of features probed by the tasks quite simultaneously contribute to the percept. The latter observation, although not compatible with the notion of a sharp all-or-none transition between unaware and aware states, suggests a less gradual or more discontinuous emergence of awareness. Analyses of slopes of the fitted psychophysical functions

  11. Spatial and temporal dynamics of deep percolation, lag time and recharge in an irrigated semi-arid region

    Science.gov (United States)

    Nazarieh, F.; Ansari, H.; Ziaei, A. N.; Izady, A.; Davari, K.; Brunner, P.

    2018-05-01

    The time required for deep percolating water to reach the water table can be considerable in areas with a thick vadose zone. Sustainable groundwater management, therefore, has to consider the spatial and temporal dynamics of groundwater recharge. The key parameters that control the lag time have been widely examined in soil physics using small-scale lysimeters and modeling studies. However, only a small number of studies have analyzed how deep-percolation rates affect groundwater recharge dynamics over large spatial scales. This study examined how the parameters influencing lag time affect groundwater recharge in a semi-arid catchment under irrigation (in northeastern Iran) using a numerical modeling approach. Flow simulations were performed by the MODFLOW-NWT code with the Vadose-Zone Flow (UZF) Package. Calibration of the groundwater model was based on data from 48 observation wells. Flow simulations showed that lag times vary from 1 to more than 100 months. A sensitivity analysis demonstrated that during drought conditions, the lag time was highly sensitive to the rate of deep percolation. The study illustrated two critical points: (1) the importance of providing estimates of the lag time as a basis for sustainable groundwater management, and (2) lag time not only depends on factors such as soil hydraulic conductivity or vadose zone depth but also depends on the deep-percolation rates and the antecedent soil-moisture condition. Therefore, estimates of the lag time have to be associated with specific percolation rates, in addition to depth to groundwater and soil properties.

  12. Translation of a High-Level Temporal Model into Lower Level Models: Impact of Modelling at Different Description Levels

    DEFF Research Database (Denmark)

    Kraft, Peter; Sørensen, Jens Otto

    2001-01-01

    given types of properties, and examine how descriptions on higher levels translate into descriptions on lower levels. Our example looks at temporal properties where the information is concerned with the existence in time. In a high level temporal model with information kept in a three-dimensional space...... the existences in time can be mapped precisely and consistently securing a consistent handling of the temporal properties. We translate the high level temporal model into an entity-relationship model, with the information in a two-dimensional graph, and finally we look at the translations into relational...... and other textual models. We also consider the aptness of models that include procedural mechanisms such as active and object databases...

  13. Application of dynamic susceptibility contrast-enhanced perfusion in temporal lobe epilepsy

    Energy Technology Data Exchange (ETDEWEB)

    Xing, Wu; Wang, Xiaoyi; Xie, Fangfang; Liao, Weihua [Dept. of Radiology, Xiangya Hospital of Central South Univ., Changsha (China)], e-mail: doctoring@sina.com

    2013-02-15

    Background: Accurately locatithe epileptogenic focus in temporal lobe epilepsy (TLE) is important in clinical practice. Single-photon emission computed tomography (SPECT) and positron-emission tomography (PET) have been widely used in the lateralization of TLE, but both have limitations. Magnetic resonance perfusion imaging can accurately and reliably reflect differences in cerebral blood flow and volume. Purpose: To investigate the diagnostic value of dynamic susceptibility contrast-enhanced (DSC) perfusion magnetic resonance imaging (MRI) in the lateralization of the epileptogenic focus in TLE. Material and Methods: Conventional MRI and DSC-MRI scanning was performed in 20 interictal cases of TLE and 20 healthy volunteers. The relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of the bilateral mesial temporal lobes of the TLE cases and healthy control groups were calculated. The differences in the perfusion asymmetry indices (AIs), derived from the rCBV and rCBF of the bilateral mesial temporal lobes, were pared between the two groups. Results: In the control group, there were no statistically significant differences between the left and right sides in terms of rCBV (left 1.55 {+-} 0.32, right 1.57 {+-} 0.28) or rCBF (left 99.00 {+-} 24.61, right 100.38 {+-} 23.46) of the bilateral mesial temporal lobes. However, in the case group the ipsilateral rCBV and rCBF values (1.75 {+-} 0.64 and 96.35 {+-} 22.63, respectively) were markedly lower than those of the contralateral side (2.01 {+-} 0.79 and 108.56 {+-} 26.92; P < 0.05). Both the AI of the rCBV (AIrCBV; 13.03 {+-} 10.33) and the AI of the rCBF (AIrCBF; 11.24 {+-} 8.70) of the case group were significantly higher than that of the control group (AIrCBV 5.55 {+-} 3.74, AIrCBF 5.12 {+-} 3.48; P < 0.05). The epileptogenic foci of nine patients were correctly lateralized using the 95th percentile of the AIrCBV and AIrCBF of the control group as the normal upper limits. Conclusion: In

  14. Application of dynamic susceptibility contrast-enhanced perfusion in temporal lobe epilepsy

    International Nuclear Information System (INIS)

    Xing, Wu; Wang, Xiaoyi; Xie, Fangfang; Liao, Weihua

    2013-01-01

    Background: Accurately locatithe epileptogenic focus in temporal lobe epilepsy (TLE) is important in clinical practice. Single-photon emission computed tomography (SPECT) and positron-emission tomography (PET) have been widely used in the lateralization of TLE, but both have limitations. Magnetic resonance perfusion imaging can accurately and reliably reflect differences in cerebral blood flow and volume. Purpose: To investigate the diagnostic value of dynamic susceptibility contrast-enhanced (DSC) perfusion magnetic resonance imaging (MRI) in the lateralization of the epileptogenic focus in TLE. Material and Methods: Conventional MRI and DSC-MRI scanning was performed in 20 interictal cases of TLE and 20 healthy volunteers. The relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of the bilateral mesial temporal lobes of the TLE cases and healthy control groups were calculated. The differences in the perfusion asymmetry indices (AIs), derived from the rCBV and rCBF of the bilateral mesial temporal lobes, were pared between the two groups. Results: In the control group, there were no statistically significant differences between the left and right sides in terms of rCBV (left 1.55 ± 0.32, right 1.57 ± 0.28) or rCBF (left 99.00 ± 24.61, right 100.38 ± 23.46) of the bilateral mesial temporal lobes. However, in the case group the ipsilateral rCBV and rCBF values (1.75 ± 0.64 and 96.35 ± 22.63, respectively) were markedly lower than those of the contralateral side (2.01 ± 0.79 and 108.56 ± 26.92; P < 0.05). Both the AI of the rCBV (AIrCBV; 13.03 ± 10.33) and the AI of the rCBF (AIrCBF; 11.24 ± 8.70) of the case group were significantly higher than that of the control group (AIrCBV 5.55 ± 3.74, AIrCBF 5.12 ± 3.48; P < 0.05). The epileptogenic foci of nine patients were correctly lateralized using the 95th percentile of the AIrCBV and AIrCBF of the control group as the normal upper limits. Conclusion: In patients with TLE interictal

  15. Modelling the Congo basin ecosystems with a dynamic vegetation model

    Science.gov (United States)

    Dury, Marie; Hambuckers, Alain; Trolliet, Franck; Huynen, Marie-Claude; Haineaux, Damien; Fontaine, Corentin M.; Fayolle, Adeline; François, Louis

    2014-05-01

    The scarcity of field observations in some parts of the world makes difficult a deep understanding of some ecosystems such as humid tropical forests in Central Africa. Therefore, modelling tools are interesting alternatives to study those regions even if the lack of data often prevents sharp calibration and validation of the model projections. Dynamic vegetation models (DVMs) are process-based models that simulate shifts in potential vegetation and its associated biogeochemical and hydrological cycles in response to climate. Initially run at the global scale, DVMs can be run at any spatial scale provided that climate and soil data are available. In the framework of the BIOSERF project ("Sustainability of tropical forest biodiversity and services under climate and human pressure"), we use and adapt the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) to study the Congo basin vegetation dynamics. The field campaigns have notably allowed the refinement of the vegetation representation from plant functional types (PFTs) to individual species through the collection of parameters such as the specific leaf area or the leaf C:N ratio of common tropical tree species and the location of their present-day occurrences from literature and available database. Here, we test the model ability to reproduce the present spatial and temporal variations of carbon stocks (e.g. biomass, soil carbon) and fluxes (e.g. gross and net primary productivities (GPP and NPP), net ecosystem production (NEP)) as well as the observed distribution of the studied species over the Congo basin. In the lack of abundant and long-term measurements, we compare model results with time series of remote sensing products (e.g. vegetation leaf area index (LAI), GPP and NPP). Several sensitivity tests are presented: we assess consecutively the impacts of the level at which the vegetation is simulated (PFTs or species), the spatial resolution and the initial land

  16. The cascade from local to global dust storms on Mars: Temporal and spatial thresholds on thermal and dynamical feedback

    Science.gov (United States)

    Toigo, Anthony D.; Richardson, Mark I.; Wang, Huiqun; Guzewich, Scott D.; Newman, Claire E.

    2018-03-01

    We use the MarsWRF general circulation model to examine the temporal and spatial response of the atmosphere to idealized local and regional dust storm radiative heating. The ability of storms to modify the atmosphere away from the location of dust heating is a likely prerequisite for dynamical feedbacks that aid the growth of storms beyond the local scale, while the ability of storms to modify the atmosphere after the cessation of dust radiative heating is potentially important in preconditioning the atmosphere prior to large scale storms. Experiments were conducted over a range of static, prescribed storm sizes, durations, optical depth strengths, locations, and vertical extents of dust heating. Our results show that for typical sizes (order 105 km2) and durations (1-10 sols) of local dust storms, modification of the atmosphere is less than the typical variability of the unperturbed (storm-free) state. Even if imposed on regional storm length scales (order 106 km2), a 1-sol duration storm similarly does not significantly modify the background atmosphere. Only when imposed for 10 sols does a regional dust storm create a significant impact on the background atmosphere, allowing for the possibility of self-induced dynamical storm growth. These results suggest a prototype for how the subjective observational categorization of storms may be related to objective dynamical growth feedbacks that only become available to storms after they achieve a threshold size and duration, or if they grow into an atmosphere preconditioned by a prior large and sustained storm.

  17. Clock-Controlled Prey-Predator Dynamics : Temporal Segregation of Activities

    OpenAIRE

    Hiroaki, DAIDO; Department of Mathematical Sciences, Graduate School of Engineering, University of Osaka Prefecture

    2003-01-01

    A new type of mathematical model of prey-predator dynamics is proposed. This model takes into account the fact that the daily activities of animals are governed by their body clocks. On the basis of it, we investigate the conditions under which the prey and predator can segregate into diurnal and nocturnal habits on a timescale that is short compared to evolutionary timescales.

  18. Spatio-temporal dynamics of ocean conditions and forage taxa reveal regional structuring of seabird–prey relationships.

    Science.gov (United States)

    Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J

    Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the

  19. A data model for simulation models relying on spatio-temporal urban data

    OpenAIRE

    Langlois , G ,; Tourre , Vincent; Servières , Myriam; Gervais , G ,; Gesquière , Gilles

    2016-01-01

    International audience; To understand the complexity of modern cities and anticipate their expansion, experts from various fields conceive simulation models that can be very different. Those simulation models work with a variety of data with their own organization. Furthermore, because the urban objects are studied in the context of the evolution of a city or urban area, they carry temporal and spatial information. In this paper, we present the base classes of a common data model robust and f...

  20. Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland.

    Directory of Open Access Journals (Sweden)

    Erica N Spotswood

    Full Text Available Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species, temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.

  1. Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland.

    Science.gov (United States)

    Spotswood, Erica N; Bartolome, James W; Allen-Diaz, Barbara

    2015-01-01

    Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.

  2. Quadratic temporal finite element method for linear elastic structural dynamics based on mixed convolved action

    International Nuclear Information System (INIS)

    Kim, Jin Kyu; Kim, Dong Keon

    2016-01-01

    A common approach for dynamic analysis in current practice is based on a discrete time-integration scheme. This approach can be largely attributed to the absence of a true variational framework for initial value problems. To resolve this problem, a new stationary variational principle was recently established for single-degree-of-freedom oscillating systems using mixed variables, fractional derivatives and convolutions of convolutions. In this mixed convolved action, all the governing differential equations and initial conditions are recovered from the stationarity of a single functional action. Thus, the entire description of linear elastic dynamical systems is encapsulated. For its practical application to structural dynamics, this variational formalism is systemically extended to linear elastic multidegree- of-freedom systems in this study, and a corresponding weak form is numerically implemented via a quadratic temporal finite element method. The developed numerical method is symplectic and unconditionally stable with respect to a time step for the underlying conservative system. For the forced-damped vibration, a three-story shear building is used as an example to investigate the performance of the developed numerical method, which provides accurate results with good convergence characteristics

  3. Quadratic temporal finite element method for linear elastic structural dynamics based on mixed convolved action

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Kyu [School of Architecture and Architectural Engineering, Hanyang University, Ansan (Korea, Republic of); Kim, Dong Keon [Dept. of Architectural Engineering, Dong A University, Busan (Korea, Republic of)

    2016-09-15

    A common approach for dynamic analysis in current practice is based on a discrete time-integration scheme. This approach can be largely attributed to the absence of a true variational framework for initial value problems. To resolve this problem, a new stationary variational principle was recently established for single-degree-of-freedom oscillating systems using mixed variables, fractional derivatives and convolutions of convolutions. In this mixed convolved action, all the governing differential equations and initial conditions are recovered from the stationarity of a single functional action. Thus, the entire description of linear elastic dynamical systems is encapsulated. For its practical application to structural dynamics, this variational formalism is systemically extended to linear elastic multidegree- of-freedom systems in this study, and a corresponding weak form is numerically implemented via a quadratic temporal finite element method. The developed numerical method is symplectic and unconditionally stable with respect to a time step for the underlying conservative system. For the forced-damped vibration, a three-story shear building is used as an example to investigate the performance of the developed numerical method, which provides accurate results with good convergence characteristics.

  4. System Dynamics Modelling for a Balanced Scorecard

    DEFF Research Database (Denmark)

    Nielsen, Steen; Nielsen, Erland Hejn

    2008-01-01

    /methodology/approach - We use a case study model to develop time or dynamic dimensions by using a System Dynamics modelling (SDM) approach. The model includes five perspectives and a number of financial and non-financial measures. All indicators are defined and related to a coherent number of different cause...... have a major influence on other indicators and profit and may be impossible to predict without using a dynamic model. Practical implications - The model may be used as the first step in quantifying the cause-and-effect relationships of an integrated BSC model. Using the System Dynamics model provides......Purpose - To construct a dynamic model/framework inspired by a case study based on an international company. As described by the theory, one of the main difficulties of BSC is to foresee the time lag dimension of different types of indicators and their combined dynamic effects. Design...

  5. Temporal dynamics of European bat Lyssavirus type 1 and survival of Myotis myotis bats in natural colonies.

    Science.gov (United States)

    Amengual, Blanca; Bourhy, Hervé; López-Roig, Marc; Serra-Cobo, Jordi

    2007-06-27

    Many emerging RNA viruses of public health concern have recently been detected in bats. However, the dynamics of these viruses in natural bat colonies is presently unknown. Consequently, prediction of the spread of these viruses and the establishment of appropriate control measures are hindered by a lack of information. To this aim, we collected epidemiological, virological and ecological data during a twelve-year longitudinal study in two colonies of insectivorous bats (Myotis myotis) located in Spain and infected by the most common bat lyssavirus found in Europe, the European bat lyssavirus subtype 1 (EBLV-1). This active survey demonstrates that cyclic lyssavirus infections occurred with periodic oscillations in the number of susceptible, immune and infected bats. Persistence of immunity for more than one year was detected in some individuals. These data were further used to feed models to analyze the temporal dynamics of EBLV-1 and the survival rate of bats. According to these models, the infection is characterized by a predicted low basic reproductive rate (R(0) = 1.706) and a short infectious period (D = 5.1 days). In contrast to observations in most non-flying animals infected with rabies, the survival model shows no variation in mortality after EBLV-1 infection of M. myotis. These findings have considerable public health implications in terms of management of colonies where lyssavirus-positive bats have been recorded and confirm the potential risk of rabies transmission to humans. A greater understanding of the dynamics of lyssavirus in bat colonies also provides a model to study how bats contribute to the maintenance and transmission of other viruses of public health concern.

  6. Temporal dynamics of European bat Lyssavirus type 1 and survival of Myotis myotis bats in natural colonies.

    Directory of Open Access Journals (Sweden)

    Blanca Amengual

    Full Text Available Many emerging RNA viruses of public health concern have recently been detected in bats. However, the dynamics of these viruses in natural bat colonies is presently unknown. Consequently, prediction of the spread of these viruses and the establishment of appropriate control measures are hindered by a lack of information. To this aim, we collected epidemiological, virological and ecological data during a twelve-year longitudinal study in two colonies of insectivorous bats (Myotis myotis located in Spain and infected by the most common bat lyssavirus found in Europe, the European bat lyssavirus subtype 1 (EBLV-1. This active survey demonstrates that cyclic lyssavirus infections occurred with periodic oscillations in the number of susceptible, immune and infected bats. Persistence of immunity for more than one year was detected in some individuals. These data were further used to feed models to analyze the temporal dynamics of EBLV-1 and the survival rate of bats. According to these models, the infection is characterized by a predicted low basic reproductive rate (R(0 = 1.706 and a short infectious period (D = 5.1 days. In contrast to observations in most non-flying animals infected with rabies, the survival model shows no variation in mortality after EBLV-1 infection of M. myotis. These findings have considerable public health implications in terms of management of colonies where lyssavirus-positive bats have been recorded and confirm the potential risk of rabies transmission to humans. A greater understanding of the dynamics of lyssavirus in bat colonies also provides a model to study how bats contribute to the maintenance and transmission of other viruses of public health concern.

  7. Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

    Science.gov (United States)

    Diao, Chunyuan

    In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of

  8. Temporal dynamics influenced by global change: bee community phenology in urban, agricultural, and natural landscapes.

    Science.gov (United States)

    Leong, Misha; Ponisio, Lauren C; Kremen, Claire; Thorp, Robbin W; Roderick, George K

    2016-03-01

    Urbanization and agricultural intensification of landscapes are important drivers of global change, which in turn have direct impacts on local ecological communities leading to shifts in species distributions and interactions. Here, we illustrate how human-altered landscapes, with novel ornamental and crop plant communities, result not only in changes to local community diversity of floral-dependent species, but also in shifts in seasonal abundance of bee pollinators. Three years of data on the spatio-temporal distributions of 91 bee species show that seasonal patterns of abundance and species richness in human-altered landscapes varied significantly less compared to natural habitats in which floral resources are relatively scarce in the dry summer months. These findings demonstrate that anthropogenic environmental changes in urban and agricultural systems, here mediated through changes in plant resources and water inputs, can alter the temporal dynamics of pollinators that depend on them. Changes in phenology of interactions can be an important, though frequently overlooked, mechanism of global change. © 2015 John Wiley & Sons Ltd.

  9. Spatio-temporal dynamics of action-effect associations in oculomotor control.

    Science.gov (United States)

    Riechelmann, Eva; Pieczykolan, Aleksandra; Horstmann, Gernot; Herwig, Arvid; Huestegge, Lynn

    2017-10-01

    While there is ample evidence that actions are guided by anticipating their effects (ideomotor control) in the manual domain, much less is known about the underlying characteristics and dynamics of effect-based oculomotor control. Here, we address three open issues. 1) Is action-effect anticipation in oculomotor control reflected in corresponding spatial saccade characteristics in inanimate environments? 2) Does the previously reported dependency of action latency on the temporal effect delay (action-effect interval) also occur in the oculomotor domain? 3) Which temporal effect delay is optimally suited to develop strong action-effect associations over time in the oculomotor domain? Participants executed left or right free-choice saccades to peripheral traffic lights, causing an (immediate or delayed) action-contingent light switch in the upper vs. lower part of the traffic light. Results indicated that saccades were spatially shifted toward the location of the upcoming change, indicating anticipation of the effect (location). Saccade latency was affected by effect delay, suggesting that corresponding time information is integrated into event representations. Finally, delayed (vs. immediate) effects were more effective in strengthening action-effect associations over the course of the experiment, likely due to greater saliency of perceptual changes occurring during target fixation as opposed to changes during saccades (saccadic suppression). Overall, basic principles underlying ideomotor control appear to generalize to the oculomotor domain. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Fish and phytoplankton exhibit contrasting temporal species abundance patterns in a dynamic north temperate lake.

    Directory of Open Access Journals (Sweden)

    Gretchen J A Hansen

    Full Text Available Temporal patterns of species abundance, although less well-studied than spatial patterns, provide valuable insight to the processes governing community assembly. We compared temporal abundance distributions of two communities, phytoplankton and fish, in a north temperate lake. We used both 17 years of observed relative abundance data as well as resampled data from Monte Carlo simulations to account for the possible effects of non-detection of rare species. Similar to what has been found in other communities, phytoplankton and fish species that appeared more frequently were generally more abundant than rare species. However, neither community exhibited two distinct groups of "core" (common occurrence and high abundance and "occasional" (rare occurrence and low abundance species. Both observed and resampled data show that the phytoplankton community was dominated by occasional species appearing in only one year that exhibited large variation in their abundances, while the fish community was dominated by core species occurring in all 17 years at high abundances. We hypothesize that the life-history traits that enable phytoplankton to persist in highly dynamic environments may result in communities dominated by occasional species capable of reaching high abundances when conditions allow. Conversely, longer turnover times and broad environmental tolerances of fish may result in communities dominated by core species structured primarily by competitive interactions.

  11. Fish and Phytoplankton Exhibit Contrasting Temporal Species Abundance Patterns in a Dynamic North Temperate Lake

    Science.gov (United States)

    Hansen, Gretchen J. A.; Carey, Cayelan C.

    2015-01-01

    Temporal patterns of species abundance, although less well-studied than spatial patterns, provide valuable insight to the processes governing community assembly. We compared temporal abundance distributions of two communities, phytoplankton and fish, in a north temperate lake. We used both 17 years of observed relative abundance data as well as resampled data from Monte Carlo simulations to account for the possible effects of non-detection of rare species. Similar to what has been found in other communities, phytoplankton and fish species that appeared more frequently were generally more abundant than rare species. However, neither community exhibited two distinct groups of “core” (common occurrence and high abundance) and “occasional” (rare occurrence and low abundance) species. Both observed and resampled data show that the phytoplankton community was dominated by occasional species appearing in only one year that exhibited large variation in their abundances, while the fish community was dominated by core species occurring in all 17 years at high abundances. We hypothesize that the life-history traits that enable phytoplankton to persist in highly dynamic environments may result in communities dominated by occasional species capable of reaching high abundances when conditions allow. Conversely, longer turnover times and broad environmental tolerances of fish may result in communities dominated by core species structured primarily by competitive interactions. PMID:25651399

  12. Temporal dynamics of genetic variability in a mountain goat (Oreamnos americanus) population.

    Science.gov (United States)

    Ortego, Joaquín; Yannic, Glenn; Shafer, Aaron B A; Mainguy, Julien; Festa-Bianchet, Marco; Coltman, David W; Côté, Steeve D

    2011-04-01

    The association between population dynamics and genetic variability is of fundamental importance for both evolutionary and conservation biology. We combined long-term population monitoring and molecular genetic data from 123 offspring and their parents at 28 microsatellite loci to investigate changes in genetic diversity over 14 cohorts in a small and relatively isolated population of mountain goats (Oreamnos americanus) during a period of demographic increase. Offspring heterozygosity decreased while parental genetic similarity and inbreeding coefficients (F(IS) ) increased over the study period (1995-2008). Immigrants introduced three novel alleles into the population and matings between residents and immigrants produced more heterozygous offspring than local crosses, suggesting that immigration can increase population genetic variability. The population experienced genetic drift over the study period, reflected by a reduced allelic richness over time and an 'isolation-by-time' pattern of genetic structure. The temporal decline of individual genetic diversity despite increasing population size probably resulted from a combination of genetic drift due to small effective population size, inbreeding and insufficient counterbalancing by immigration. This study highlights the importance of long-term genetic monitoring to understand how demographic processes influence temporal changes of genetic diversity in long-lived organisms. © 2011 Blackwell Publishing Ltd.

  13. Right mesial temporal lobe epilepsy impairs empathy-related brain responses to dynamic fearful faces.

    Science.gov (United States)

    Toller, Gianina; Adhimoolam, Babu; Grunwald, Thomas; Huppertz, Hans-Jürgen; Kurthen, Martin; Rankin, Katherine P; Jokeit, Hennric

    2015-03-01

    Unilateral mesial temporal lobe epilepsy (MTLE) has been associated with reduced amygdala responsiveness to fearful faces. However, the effect of unilateral MTLE on empathy-related brain responses in extra-amygdalar regions has not been investigated. Using functional magnetic resonance imaging, we measured empathy-related brain responses to dynamic fearful faces in 34 patients with unilateral MTLE (18 right sided), in an epilepsy (extra-MTLE; n = 16) and in a healthy control group (n = 30). The primary finding was that right MTLE (RMTLE) was associated with decreased activity predominantly in the right amygdala and also in bilateral periaqueductal gray (PAG) but normal activity in the right anterior insula. The results of the extra-MTLE group demonstrate that these reduced amygdala and PAG responses go beyond the attenuation caused by antiepileptic and antidepressant medication. These findings clearly indicate that RMTLE affects the function of mesial temporal and midbrain structures that mediate basic interoceptive input necessary for the emotional awareness of empathic experiences of fear. Together with the decreased empathic concern found in the RMTLE group, this study provides neurobehavioral evidence that patients with RMTLE are at increased risk for reduced empathy towards others' internal states and sheds new light on the nature of social-cognitive impairments frequently accompanying MTLE.

  14. Temporal and Spatial Dynamics of Sediment Anaerobic Ammonium Oxidation (Anammox) Bacteria in Freshwater Lakes.

    Science.gov (United States)

    Yang, Yuyin; Dai, Yu; Li, Ningning; Li, Bingxin; Xie, Shuguang; Liu, Yong

    2017-02-01

    Anaerobic ammonium-oxidizing (anammox) process can play an important role in freshwater nitrogen cycle. However, the distribution of anammox bacteria in freshwater lake and the associated environmental factors remain essentially unclear. The present study investigated the temporal and spatial dynamics of sediment anammox bacterial populations in eutrotrophic Dianchi Lake and mesotrophic Erhai Lake on the Yunnan Plateau (southwestern China). The remarkable spatial change of anammox bacterial abundance was found in Dianchi Lake, while the relatively slight spatial shift occurred in Erhai Lake. Dianchi Lake had greater anammox bacterial abundance than Erhai Lake. In both Dianchi Lake and Erhai Lake, anammox bacteria were much more abundant in summer than in spring. Anammox bacterial community richness, diversity, and structure in these two freshwater lakes were subjected to temporal and spatial variations. Sediment anammox bacterial communities in Dianchi Lake and Erhai Lake were dominated by Candidatus Brocadia and a novel phylotype followed by Candidatus Kuenenia; however, these two lakes had distinct anammox bacterial community structure. In addition, trophic status determined sediment anammox bacterial community structure.

  15. Spatial and temporal dynamics of dengue fever in Peru: 1994-2006.

    Science.gov (United States)

    Chowell, G; Torre, C A; Munayco-Escate, C; Suárez-Ognio, L; López-Cruz, R; Hyman, J M; Castillo-Chavez, C

    2008-12-01

    SUMMARYThe weekly number of dengue cases in Peru, South America, stratified by province for the period 1994-2006 were analysed in conjunction with associated demographic, geographic and climatological data. Estimates of the reproduction number, moderately correlated with population size (Spearman rho=0.28, P=0.03), had a median of 1.76 (IQR 0.83-4.46). The distributions of dengue attack rates and epidemic durations follow power-law (Pareto) distributions (coefficient of determination >85%, Pjungle areas. Our findings suggest a hierarchy of transmission events during the large 2000-2001 epidemic from large to small population areas when serotypes DEN-3 and DEN-4 were first identified (Spearman rho=-0.43, P=0.03). The need for spatial and temporal dengue epidemic data with a high degree of resolution not only increases our understanding of the dynamics of dengue but will also generate new hypotheses and provide a platform for testing innovative control policies.

  16. The surface chemistry determines the spatio-temporal interaction dynamics of quantum dots in atherosclerotic lesions.

    Science.gov (United States)

    Uhl, Bernd; Hirn, Stephanie; Mildner, Karina; Coletti, Raffaele; Massberg, Steffen; Reichel, Christoph A; Rehberg, Markus; Zeuschner, Dagmar; Krombach, Fritz

    2018-03-01

    To optimize the design of nanoparticles for diagnosis or therapy of vascular diseases, it is mandatory to characterize the determinants of nano-bio interactions in vascular lesions. Using ex vivo and in vivo microscopy, we analyzed the interactive behavior of quantum dots with different surface functionalizations in atherosclerotic lesions of ApoE-deficient mice. We demonstrate that quantum dots with different surface functionalizations exhibit specific interactive behaviors with distinct molecular and cellular components of the injured vessel wall. Moreover, we show a role for fibrinogen in the regulation of the spatio-temporal interaction dynamics in atherosclerotic lesions. Our findings emphasize the relevance of surface chemistry-driven nano-bio interactions on the differential in vivo behavior of nanoparticles in diseased tissue.

  17. Quantitative tradeoffs between spatial, temporal, and thermometric resolution of nonresonant Raman thermometry for dynamic experiments.

    Science.gov (United States)

    McGrane, Shawn D; Moore, David S; Goodwin, Peter M; Dattelbaum, Dana M

    2014-01-01

    The ratio of Stokes to anti-Stokes nonresonant spontaneous Raman can provide an in situ thermometer that is noncontact, independent of any material specific parameters or calibrations, can be multiplexed spatially with line imaging, and can be time resolved for dynamic measurements. However, spontaneous Raman cross sections are very small, and thermometric measurements are often limited by the amount of laser energy that can be applied without damaging the sample or changing its temperature appreciably. In this paper, we quantitatively detail the tradeoff space between spatial, temporal, and thermometric accuracy measurable with spontaneous Raman. Theoretical estimates are pinned to experimental measurements to form realistic expectations of the resolution tradeoffs appropriate to various experiments. We consider the effects of signal to noise, collection efficiency, laser heating, pulsed laser ablation, and blackbody emission as limiting factors, provide formulae to help choose optimal conditions and provide estimates relevant to planning experiments along with concrete examples for single-shot measurements.

  18. Temporal dynamics of the response to Al stress in Eucalyptus grandis × Eucalyptus camaldulensis

    Directory of Open Access Journals (Sweden)

    Berenice K. de Alcântara

    2015-06-01

    Full Text Available Lipid peroxidation and root elongation of Eucalyptus grandis × Eucalyptus camaldulensis were studied under stress conditions in response to aluminum (Al, a metal known to limit agricultural productivity in acidic soils primarily due to reduced root elongation. In Brazil, the Grancam 1277 hybrid (E. grandis × E. camaldulensis has been planted in the "Cerrado", a region of the country with a wide occurrence of acidic soils. The present study demonstrated that the hybrid exhibited root growth reduction and increased levels of lipid peroxidation after 24h of treatment with 100 µM of Al, which was followed by a reduction in lipid peroxidation levels and the recovery of root elongation after 48h of Al exposure, suggesting a rapid response to the early stressful conditions induced by Al. The understanding of the temporal dynamics of Al tolerance may be useful for selecting more tolerant genotypes and for identifying genes of interest for applications in bioengineering.

  19. Spatio-temporal dynamics of the white-eye square superlattice pattern in dielectric barrier discharge

    International Nuclear Information System (INIS)

    Wei, Lingyan; Dong, Lifang; Feng, Jianyu; Liu, Weibo; Fan, Weili; Pan, Yuyang

    2016-01-01

    We report on the first investigation of the white-eye square superlattice pattern (WESSP) in a dielectric barrier discharge system. The evolution of patterns with increasing voltage is given. A phase diagram of WESSP as functions of gas pressure p and argon concentration φ is presented. The spatio-temporal dynamics of the WESSP is studied by using an intensified charge-coupled device camera and photomultipliers. Results show that the WESSP consists of four different transient sublattices, whose discharge sequence is small spots—spots on the line—halos—central spots in each half voltage cycle. The discharge moment and position of each sublattice are dependent upon the field of the wall charges produced by all sublattices discharged previously. (paper)

  20. Comparing the temporal dynamics of thematic and taxonomic processing using event-related potentials.

    Directory of Open Access Journals (Sweden)

    Olivera Savic

    Full Text Available We report the results of a study comparing the temporal dynamics of thematic and taxonomic knowledge activation in a picture-word priming paradigm using event-related potentials. Although we found no behavioral differences between thematic and taxonomic processing, ERP data revealed distinct patterns of N400 and P600 amplitude modulation for thematic and taxonomic priming. Thematically related target stimuli elicited less negativity than taxonomic targets between 280-460 ms after stimulus onset, suggesting easier semantic processing of thematic than taxonomic relationships. Moreover, P600 mean amplitude was significantly increased for taxonomic targets between 520-600 ms, consistent with a greater need for stimulus reevaluation in that condition. These results offer novel evidence in favor of a dissociation between thematic and taxonomic thinking in the early phases of conceptual evaluation.

  1. Comparing the temporal dynamics of thematic and taxonomic processing using event-related potentials.

    Science.gov (United States)

    Savic, Olivera; Savic, Andrej M; Kovic, Vanja

    2017-01-01

    We report the results of a study comparing the temporal dynamics of thematic and taxonomic knowledge activation in a picture-word priming paradigm using event-related potentials. Although we found no behavioral differences between thematic and taxonomic processing, ERP data revealed distinct patterns of N400 and P600 amplitude modulation for thematic and taxonomic priming. Thematically related target stimuli elicited less negativity than taxonomic targets between 280-460 ms after stimulus onset, suggesting easier semantic processing of thematic than taxonomic relationships. Moreover, P600 mean amplitude was significantly increased for taxonomic targets between 520-600 ms, consistent with a greater need for stimulus reevaluation in that condition. These results offer novel evidence in favor of a dissociation between thematic and taxonomic thinking in the early phases of conceptual evaluation.

  2. Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

    Science.gov (United States)

    Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

    2015-12-01

    Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

  3. Temporal dynamics of abundance and composition of nitrogen-fixing communities across agricultural soils.

    Directory of Open Access Journals (Sweden)

    Michele C Pereira E Silva

    Full Text Available BACKGROUND: Despite the fact that the fixation of nitrogen is one of the most significant nutrient processes in the terrestrial ecosystem, a thorough study of the spatial and temporal patterns in the abundance and distribution of N-fixing communities has been missing so far. METHODOLOGY/PRINCIPAL FINDINGS: In order to understand the dynamics of diazotrophic communities and their resilience to external changes, we quantified the abundance and characterized the bacterial community structures based on the nifH gene, using real-time PCR, PCR-DGGE and 454-pyrosequencing, across four representative Dutch soils during one growing season. In general, higher nifH gene copy numbers were observed in soils with higher pH than in those with lower pH, but lower numbers were related to increased nitrate and ammonium levels. Results from nifH gene pyrosequencing confirmed the observed PCR-DGGE patterns, which indicated that the N fixers are highly dynamic across time, shifting around 60%. Forward selection on CCA analysis identified N availability as the main driver of these variations, as well as of the evenness of the communities, leading to very unequal communities. Moreover, deep sequencing of the nifH gene revealed that sandy soils (B and D had the lowest percentage of shared OTUs across time, compared with clayey soils (G and K, indicating the presence of a community under constant change. Cosmopolitan nifH species (present throughout the season were affiliated with Bradyrhizobium, Azospirillum and Methylocistis, whereas other species increased their abundances progressively over time, when appropriate conditions were met, as was notably the case for Paenibacilus and Burkholderia. CONCLUSIONS: Our study provides the first in-depth pyrosequencing analysis of the N-fixing community at both spatial and temporal scales, providing insights into the cosmopolitan and specific portions of the nitrogen fixing bacterial communities in soil.

  4. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  5. Prediction of the Dynamic Yield Strength of Metals Using Two Structural-Temporal Parameters

    Science.gov (United States)

    Selyutina, N. S.; Petrov, Yu. V.

    2018-02-01

    The behavior of the yield strength of steel and a number of aluminum alloys is investigated in a wide range of strain rates, based on the incubation time criterion of yield and the empirical models of Johnson-Cook and Cowper-Symonds. In this paper, expressions for the parameters of the empirical models are derived through the characteristics of the incubation time criterion; a satisfactory agreement of these data and experimental results is obtained. The parameters of the empirical models can depend on some strain rate. The independence of the characteristics of the incubation time criterion of yield from the loading history and their connection with the structural and temporal features of the plastic deformation process give advantage of the approach based on the concept of incubation time with respect to empirical models and an effective and convenient equation for determining the yield strength in a wider range of strain rates.

  6. Correlated continuous time random walks: combining scale-invariance with long-range memory for spatial and temporal dynamics

    International Nuclear Information System (INIS)

    Schulz, Johannes H P; Chechkin, Aleksei V; Metzler, Ralf

    2013-01-01

    Standard continuous time random walk (CTRW) models are renewal processes in the sense that at each jump a new, independent pair of jump length and waiting time are chosen. Globally, anomalous diffusion emerges through scale-free forms of the jump length and/or waiting time distributions by virtue of the generalized central limit theorem. Here we present a modified version of recently proposed correlated CTRW processes, where we incorporate a power-law correlated noise on the level of both jump length and waiting time dynamics. We obtain a very general stochastic model, that encompasses key features of several paradigmatic models of anomalous diffusion: discontinuous, scale-free displacements as in Lévy flights, scale-free waiting times as in subdiffusive CTRWs, and the long-range temporal correlations of fractional Brownian motion (FBM). We derive the exact solutions for the single-time probability density functions and extract the scaling behaviours. Interestingly, we find that different combinations of the model parameters lead to indistinguishable shapes of the emerging probability density functions and identical scaling laws. Our model will be useful for describing recent experimental single particle tracking data that feature a combination of CTRW and FBM properties. (paper)

  7. Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems

    International Nuclear Information System (INIS)

    Shin, Seung Ki; Seong, Poong Hyun

    2008-01-01

    Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables

  8. The Role of Inhibition in a Computational Model of an Auditory Cortical Neuron during the Encoding of Temporal Information

    Science.gov (United States)

    Bendor, Daniel

    2015-01-01

    In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex. PMID:25879843

  9. A time-domain binaural detection model and its predictions temporal-resolution data

    NARCIS (Netherlands)

    Breebaart, D.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.

    2002-01-01

    This paper discusses the application of a time-domain binaural signal-detection model in the context of estimates of the temporal resolution of the binaural auditory system. It is demonstrated that the optimal detector which is present in the model is crucial to account for specific temporal

  10. Temporal contrast enhancement and parametric imaging for the visualisation of time patterns in dynamic scintigraphic imaging

    International Nuclear Information System (INIS)

    Deconinck, F.; Bossuyt, A.; Lepoudre, R.

    1982-01-01

    Image contrast, photon noise and sampling frequency limit the visual extraction of relevant temporal information in scintigraphic image series. When the Unitation is mainly due to low temporal contrast, temporal contrast enhancement will strongly improve the perceptibility of time patterns in the series. When the limitation is due to photon noise and limited temporal sampling, parametric imaging by means of the Hadamard transform can visualise temporal patterns. (WU)

  11. Characterizing and modeling citation dynamics.

    Directory of Open Access Journals (Sweden)

    Young-Ho Eom

    Full Text Available Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.

  12. Building spatio-temporal database model based on ontological approach using relational database environment

    International Nuclear Information System (INIS)

    Mahmood, N.; Burney, S.M.A.

    2017-01-01

    Everything in this world is encapsulated by space and time fence. Our daily life activities are utterly linked and related with other objects in vicinity. Therefore, a strong relationship exist with our current location, time (including past, present and future) and event through with we are moving as an object also affect our activities in life. Ontology development and its integration with database are vital for the true understanding of the complex systems involving both spatial and temporal dimensions. In this paper we propose a conceptual framework for building spatio-temporal database model based on ontological approach. We have used relational data model for modelling spatio-temporal data content and present our methodology with spatio-temporal ontological accepts and its transformation into spatio-temporal database model. We illustrate the implementation of our conceptual model through a case study related to cultivated land parcel used for agriculture to exhibit the spatio-temporal behaviour of agricultural land and related entities. Moreover, it provides a generic approach for designing spatiotemporal databases based on ontology. The proposed model is capable to understand the ontological and somehow epistemological commitments and to build spatio-temporal ontology and transform it into a spatio-temporal data model. Finally, we highlight the existing and future research challenges. (author)

  13. Supply based on demand dynamical model

    Science.gov (United States)

    Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

    2018-04-01

    We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

  14. Opinion dynamics model based on quantum formalism

    Energy Technology Data Exchange (ETDEWEB)

    Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)

    2016-03-11

    Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

  15. Multi-material 3D Models for Temporal Bone Surgical Simulation.

    Science.gov (United States)

    Rose, Austin S; Kimbell, Julia S; Webster, Caroline E; Harrysson, Ola L A; Formeister, Eric J; Buchman, Craig A

    2015-07-01

    A simulated, multicolor, multi-material temporal bone model can be created using 3-dimensional (3D) printing that will prove both safe and beneficial in training for actual temporal bone surgical cases. As the process of additive manufacturing, or 3D printing, has become more practical and affordable, a number of applications for the technology in the field of Otolaryngology-Head and Neck Surgery have been considered. One area of promise is temporal bone surgical simulation. Three-dimensional representations of human temporal bones were created from temporal bone computed tomography (CT) scans using biomedical image processing software. Multi-material models were then printed and dissected in a temporal bone laboratory by attending and resident otolaryngologists. A 5-point Likert scale was used to grade the models for their anatomical accuracy and suitability as a simulation of cadaveric and operative temporal bone drilling. The models produced for this study demonstrate significant anatomic detail and a likeness to human cadaver specimens for drilling and dissection. Simulated temporal bones created by this process have potential benefit in surgical training, preoperative simulation for challenging otologic cases, and the standardized testing of temporal bone surgical skills. © The Author(s) 2015.

  16. Different relationships between temporal phylogenetic turnover and phylogenetic similarity and in two forests were detected by a new null model.

    Science.gov (United States)

    Huang, Jian-Xiong; Zhang, Jian; Shen, Yong; Lian, Ju-yu; Cao, Hong-lin; Ye, Wan-hui; Wu, Lin-fang; Bin, Yue

    2014-01-01

    Ecologists have been monitoring community dynamics with the purpose of understanding the rates and causes of community change. However, there is a lack of monitoring of community dynamics from the perspective of phylogeny. We attempted to understand temporal phylogenetic turnover in a 50 ha tropical forest (Barro Colorado Island, BCI) and a 20 ha subtropical forest (Dinghushan in southern China, DHS). To obtain temporal phylogenetic turnover under random conditions, two null models were used. The first shuffled names of species that are widely used in community phylogenetic analyses. The second simulated demographic processes with careful consideration on the variation in dispersal ability among species and the variations in mortality both among species and among size classes. With the two models, we tested the relationships between temporal phylogenetic turnover and phylogenetic similarity at different spatial scales in the two forests. Results were more consistent with previous findings using the second null model suggesting that the second null model is more appropriate for our purposes. With the second null model, a significantly positive relationship was detected between phylogenetic turnover and phylogenetic similarity in BCI at a 10 m×10 m scale, potentially indicating phylogenetic density dependence. This relationship in DHS was significantly negative at three of five spatial scales. This could indicate abiotic filtering processes for community assembly. Using variation partitioning, we found phylogenetic similarity contributed to variation in temporal phylogenetic turnover in the DHS plot but not in BCI plot. The mechanisms for community assembly in BCI and DHS vary from phylogenetic perspective. Only the second null model detected this difference indicating the importance of choosing a proper null model.

  17. A Relational Encoding of a Conceptual Model with Multiple Temporal Dimensions

    Science.gov (United States)

    Gubiani, Donatella; Montanari, Angelo

    The theoretical interest and the practical relevance of a systematic treatment of multiple temporal dimensions is widely recognized in the database and information system communities. Nevertheless, most relational databases have no temporal support at all. A few of them provide a limited support, in terms of temporal data types and predicates, constructors, and functions for the management of time values (borrowed from the SQL standard). One (resp., two) temporal dimensions are supported by historical and transaction-time (resp., bitemporal) databases only. In this paper, we provide a relational encoding of a conceptual model featuring four temporal dimensions, namely, the classical valid and transaction times, plus the event and availability times. We focus our attention on the distinctive technical features of the proposed temporal extension of the relation model. In the last part of the paper, we briefly show how to implement it in a standard DBMS.

  18. Spatial and temporal dynamics of corticosterone and corticosterone binding globulin are driven by environmental heterogeneity.

    Science.gov (United States)

    Shultz, Michael Todd; Kitaysky, Alexander Stanislav

    2008-02-01

    The question of whether changes in glucocorticoid concentrations reflect consistent changes in physiology associated with transitions between different stages of reproduction, or whether they reflect responses to environmental conditions, is one the central issues in field endocrinology studies. We examined the temporal and spatial dynamics of corticosterone (CORT, baseline, and acute stress-induced) and corticosterone binding globulin (CBG) concentrations in blood of Black-legged Kittiwakes (Rissa tridactyla) breeding at four major colonies in the Bering Sea, Alaska, during 1999-2005. We found that total CORT, free CORT, and CBG capacity varied inconsistently among reproductive stages, colonies, and years. Total CORT levels were positively correlated with CBG capacity. Variation in free CORT was largely driven by variation in total CORT. Results suggest that the adrenocortical function and CBG in breeding kittiwakes do not vary as a consequence of stage-specific modulation associated with a particular reproductive stage as in some short-lived passerine birds. Rather, in accord with predictions for a long-lived species, the lack of consistent colony, year, and reproductive stage patterns in baseline and maximum CORT, and CBG indicates that environmental factors, probably local dynamics of food availability, drive variation in these factors.

  19. Dynamic computed tomography based on spatio-temporal analysis in acute stroke: Preliminary study

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ha Young; Pyeon, Do Yeong; Kim, Da Hye; Jung, Young Jin [Dongseo University, Busan (Korea, Republic of)

    2016-12-15

    Acute stroke is a one of common disease that require fast diagnosis and treatment to save patients life. however, the acute stroke may cause lifelong disability due to brain damage with no prompt surgical procedure. In order to diagnose the Stroke, brain perfusion CT examination and possible rapid implementation of 3D angiography has been widely used. However, a low-dose technique should be applied for the examination since a lot of radiation exposure to the patient may cause secondary damage for the patients. Therefore, the degradation of the measured CT images may interferes with a clinical check in that blood vessel shapes o n the CT image are significantly affected by gaussian noise. In this study, we employed the spatio-temporal technique to analyze dynamic (brain perfusion) CT data to improve an image quality for successful clinical diagnosis. As a results, proposed technique could remove gaussian noise successfully, demonstrated a possibility of new image segmentation technique for CT angiography. Qualitative evaluation was conducted by skilled radiological technologists, indicated significant quality improvement of dynamic CT images. the proposed technique will be useful tools as a clinical application for brain perfusion CT examination.

  20. The Temporal Dynamics of Coastal Phytoplankton and Bacterioplankton in the Eastern Mediterranean Sea.

    Directory of Open Access Journals (Sweden)

    Ofrat Raveh

    Full Text Available This study considers variability in phytoplankton and heterotrophic bacterial abundances and production rates, in one of the most oligotrophic marine regions in the world-the Levantine Basin. The temporal dynamics of these planktonic groups were studied in the coastal waters of the southeastern Mediterranean Sea approximately every two weeks for a total of two years. Heterotrophic bacteria were abundant mostly during late summer and midwinter, and were positively correlated with bacterial production and with N2 fixation. Based on size fractionating, picophytoplankton was abundant during the summer, whereas nano-microphytoplankton predominated during the winter and early spring, which were also evident in the size-fractionated primary production rates. Autotrophic abundance and production correlated negatively with temperature, but did not correlate with inorganic nutrients. Furthermore, a comparison of our results with results from the open Levantine Basin demonstrates that autotrophic and heterotrophic production, as well as N2 fixation rates, are considerably higher in the coastal habitat than in the open sea, while nutrient levels or cell abundance are not different. These findings have important ecological implications for food web dynamics and for biological carbon sequestration in this understudied region.

  1. Fire in Fennoscandia: A palaeo-perspective of spatial and temporal variability in fire frequency and vegetation dynamics

    Science.gov (United States)

    Clear, Jennifer; Bradshaw, Richard; Seppä, Heikki

    2014-05-01

    Active fire suppression in Fennoscandia has created a boreal forest ecosystem that is almost free of fire. Absence of fire is thought to have contributed to the widespread dominance of Picea abies (Norway spruce), though the character and structure of spruce forests operates as a positive feedback retarding fire frequency. This lack of fire and dominance by Picea abies may have assisted declines in deciduous tree species, with a concomitant loss of floristic diversity. Forest fires are driven by a complex interplay between natural (climate, vegetation and topography) and anthropogenic disturbance and through palaeoecology we are able to explore spatio-temporal variability in the drivers of fire, changing fire dynamics and the subsequent consequences for forest succession, development and floristic diversity over long timescales. High resolution analysis of palaeoenvironmental proxies (pollen and macroscopic charcoal) allows Holocene vegetation and fire dynamics to be reconstructed at the local forest-stand scale. Comparisons of fire histories with pollen-derived quantitative reconstruction of vegetation at local- and regional-scales identify large-scale ecosystem responses and local-scale disturbance. Spatio-temporal heterogeneity and variability in biomass burning is explored to identify the drivers of fire and palaeovegetation reconstructions are compared to process-based, climate-driven dynamic vegetation model output to test the significance of fire frequency as a driver of vegetation composition and dynamics. Fire was not always so infrequent in the northern European forest with early-Holocene fire regimes driven by natural climate variations and fuel availability. The establishment and spread of Picea abies was probably driven by an increase in continentality of climate, but local natural and anthropogenic ecosystem disturbance may have aided this spread. Picea expansion led to a step-wise reduction in regional biomass burning and here we show the now

  2. Selective 4D modelling framework for spatial-temporal land information management system

    Science.gov (United States)

    Doulamis, Anastasios; Soile, Sofia; Doulamis, Nikolaos; Chrisouli, Christina; Grammalidis, Nikos; Dimitropoulos, Kosmas; Manesis, Charalambos; Potsiou, Chryssy; Ioannidis, Charalabos

    2015-06-01

    This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.

  3. Relating structure and dynamics in organisation models

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.

    2003-01-01

    To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems, on

  4. Applying Spatial-Temporal Model and Game Theory to Asymmetric Threat Prediction

    National Research Council Canada - National Science Library

    Wei, Mo; Chen, Genshe; Cruz, Jr., Jose B; Haynes, Leonard; Kruger, Martin

    2007-01-01

    .... In most Command and Control "C2" applications, the existing techniques, such as spatial-temporal point models for ECOA prediction or Discrete Choice Model "DCM", assume that insurgent attack features...

  5. Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

    KAUST Repository

    Zhang, Bohai

    2014-01-01

    Various continuously-indexed spatio-temporal process models have been constructed to characterize spatio-temporal dependence structures, but the computational complexity for model fitting and predictions grows in a cubic order with the size of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm is proposed to select knots automatically from a discrete set of spatio-temporal points. Our approach is applicable to nonseparable and nonstationary spatio-temporal covariance models. We illustrate the effectiveness of our method through simulation experiments and application to an ozone measurement dataset.

  6. Improved accuracy of quantitative parameter estimates in dynamic contrast-enhanced CT study with low temporal resolution

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sun Mo, E-mail: Sunmo.Kim@rmp.uhn.on.ca [Radiation Medicine Program, Princess Margaret Hospital/University Health Network, Toronto, Ontario M5G 2M9 (Canada); Haider, Masoom A. [Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada and Department of Medical Imaging, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Jaffray, David A. [Radiation Medicine Program, Princess Margaret Hospital/University Health Network, Toronto, Ontario M5G 2M9, Canada and Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Yeung, Ivan W. T. [Radiation Medicine Program, Princess Margaret Hospital/University Health Network, Toronto, Ontario M5G 2M9 (Canada); Department of Medical Physics, Stronach Regional Cancer Centre, Southlake Regional Health Centre, Newmarket, Ontario L3Y 2P9 (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5G 2M9 (Canada)

    2016-01-15

    Purpose: A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data. Methods: The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts’ model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference. Results: The patients’ AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the

  7. Temporal and spatial dynamics of phytoplankton near farm fish in eutrophic reservoir in Pernambuco, Brazil

    Directory of Open Access Journals (Sweden)

    Ariadne do Nascimento Moura

    2012-06-01

    Full Text Available Spatial and temporal variations in phytoplankton communities in continental waters have received attention from limnologists, since they are differently influenced by many physico-chemical and biological factors. This study was undertaken with the aim to identify the environmental variables that influence the temporal and spatial dynamics of the phytoplankton near a fish farm in the Jucazinho reservoir, in a semi-arid region of Northeastern Brazil. Samples were taken from three sampling sites, at two depths during the rainy (Aug 2008, Feb and Mar 2009 and dry (Oct, Nov and Dec 2008 seasons. Phytoplankton was identified, density determined, and biomass values obtained. Concomitantly, abiotic analyses were performed for the characterization of the system. The reservoir was homogeneous with regard to the spatial-temporal variation in hydrological variables: water well oxygenated at the surface and anoxic at the bottom; pH ranging from neutral to alkaline; temperatures always above 25ºC; high turbidity; and high electrical conductivity at all sampling sites and both depths. For both seasons, there was limited nitrogen and high concentrations of phosphorus. Cyanophyta species were predominant, generally representing 80% of the phytoplankton biomass throughout practically the entire study, at all sampling sites and both depths. Co-dominance of cyanobacteria belonging to H1, MP, S1 and Sn associations was recorded in most of the months studied, except August 2008, when there was a substitution of the S1 association (Planktothrix agardhii by the P association (Aulacoseira granulata. Water temperature, precipitation and pH were the parameters with the greatest influence over the temporal variation in phytoplankton, whereas the vertical distribution of the phytoplankton biomass was directly related to the availability of light in the wáter column. There were no spatial or temporal differences in water quality, likely due to the fact that the sampling

  8. Analysis of temporal dynamics in imagery during acute limb ischemia and reperfusion

    Science.gov (United States)

    Irvine, John M.; Regan, John; Spain, Tammy A.; Caruso, Joseph D.; Rodriquez, Maricela; Luthra, Rajiv; Forsberg, Jonathon; Crane, Nicole J.; Elster, Eric

    2014-03-01

    Ischemia and reperfusion injuries present major challenges for both military and civilian medicine. Improved methods for assessing the effects and predicting outcome could guide treatment decisions. Specific issues related to ischemia and reperfusion injury can include complications arising from tourniquet use, such as microvascular leakage in the limb, loss of muscle strength and systemic failures leading to hypotension and cardiac failure. Better methods for assessing the viability of limbs/tissues during ischemia and reducing complications arising from reperfusion are critical to improving clinical outcomes for at-risk patients. The purpose of this research is to develop and assess possible prediction models of outcome for acute limb ischemia using a pre-clinical model. Our model relies only on non-invasive imaging data acquired from an animal study. Outcome is measured by pathology and functional scores. We explore color, texture, and temporal features derived from both color and thermal motion imagery acquired during ischemia and reperfusion. The imagery features form the explanatory variables in a model for predicting outcome. Comparing model performance to outcome prediction based on direct observation of blood chemistry, blood gas, urinalysis, and physiological measurements provides a reference standard. Initial results show excellent performance for the imagery-base model, compared to predictions based direct measurements. This paper will present the models and supporting analysis, followed by recommendations for future investigations.

  9. Physical Exercise Leads to Rapid Adaptations in Hippocampal Vasculature : Temporal Dynamics and Relationship to Cell Proliferation and Neurogenesis

    NARCIS (Netherlands)

    Van der Borght, Karin; Kobor-Nyakas, Dora E.; Klauke, Karin; Eggen, Bart J. L.; Nyakas, Csaba; Van der Zee, Eddy A.; Meerlo, Peter

    2009-01-01

    Increased levels of angiogenesis and neurogenesis possibly mediate the beneficial effects of physical activity on hippocampal plasticity. This study was designed to investigate the temporal dynamics of exercise-induced changes in hippocampal angiogenesis and cell proliferation. Mice were housed with

  10. Temporal Dynamics of Social Exchange and the Development of Solidarity: "Testing the Waters" versus "Taking a Leap of Faith"

    Science.gov (United States)

    Kuwabara, Ko; Sheldon, Oliver

    2012-01-01

    In their concerted efforts to unpack the microprocesses that transform repeated exchanges into an exchange relation, exchange theorists have paid little attention to how actors perceive changes and dynamics in exchanges over time. We help fill this gap by studying how temporal patterns of exchange affect the development of cohesion. Some exchange…

  11. Detecting Temporal Change in Dynamic Sounds: On the Role of Stimulus Duration, Speed, and Emotion

    Directory of Open Access Journals (Sweden)

    Annett eSchirmer

    2016-01-01

    Full Text Available For dynamic sounds, such as vocal expressions, duration often varies alongside speed. Compared to longer sounds, shorter sounds unfold more quickly. Here, we asked whether listeners implicitly use this confound when representing temporal regularities in their environment. In addition, we explored the role of emotions in this process. Using a mismatch negativity (MMN paradigm, we asked participants to watch a silent movie while passively listening to a stream of task-irrelevant sounds. In Experiment 1, one surprised and one neutral vocalization were compressed and stretched to create stimuli of 378 and 600 ms duration. Stimuli were presented in four blocks, two of which used surprised and two of which used neutral expressions. In one surprised and one neutral block, short and long stimuli served as standards and deviants, respectively. In the other two blocks, the assignment of standards and deviants was reversed. We observed a climbing MMN-like negativity shortly after deviant onset, which suggests that listeners implicitly track sound speed and detect speed changes. Additionally, this MMN-like effect emerged earlier and was larger for long than short deviants, suggesting greater sensitivity to duration increments or slowing down than to decrements or speeding up. Last, deviance detection was facilitated in surprised relative to neutral blocks, indicating that emotion enhances temporal processing. Experiment 2 was comparable to Experiment 1 with the exception that sounds were spectrally rotated to remove vocal emotional content. This abolished the emotional processing benefit, but preserved the other effects. Together, these results provide insights into listener sensitivity to sound speed and raise the possibility that speed biases duration judgments implicitly in a feed-forward manner. Moreover, this bias may be amplified for duration increments relative to decrements and within an emotional relative to a neutral stimulus context.

  12. Spatio-temporal and stochastic modelling of severe acute respiratory syndrome

    Directory of Open Access Journals (Sweden)

    Poh-Chin Lai

    2013-11-01

    Full Text Available This study describes the development of a spatio-temporal disease model based on the episodes of severe acute respiratory syndrome (SARS that took place in Hong Kong in 2003. In contrast to conventional, deterministic modelling approaches, the model described here is predominantly spatial. It incorporates stochastic processing of environmental and social variables that interact in space and time to affect the patterns of disease transmission in a community. The model was validated through a comparative assessment between actual and modelled distribution of diseased locations. Our study shows that the inclusion of location-specific characteristics satisfactorily replicates the spatial dynamics of an infectious disease. The Pearson’s correlation coefficients for five trials based on 3-day aggregation of disease counts for 1-3, 4-6 and 7-9 day forecasts were 0.57- 0.95, 0.54-0.86 and 0.57-0.82, respectively, while the correlation based on 5-day aggregation for the 1-5 day forecast was 0.55- 0.94 and 0.58-0.81 for the 6-10 day forecast. The significant and strong relationship between actual results and forecast is encouraging for the potential development of an early warning system for detecting this type of disease outbreaks.

  13. Dynamic density functional theory of solid tumor growth: Preliminary models

    Directory of Open Access Journals (Sweden)

    Arnaud Chauviere

    2012-03-01

    Full Text Available Cancer is a disease that can be seen as a complex system whose dynamics and growth result from nonlinear processes coupled across wide ranges of spatio-temporal scales. The current mathematical modeling literature addresses issues at various scales but the development of theoretical methodologies capable of bridging gaps across scales needs further study. We present a new theoretical framework based on Dynamic Density Functional Theory (DDFT extended, for the first time, to the dynamics of living tissues by accounting for cell density correlations, different cell types, phenotypes and cell birth/death processes, in order to provide a biophysically consistent description of processes across the scales. We present an application of this approach to tumor growth.

  14. Temporal Dynamics of Soil Microbial Communities below the Seedbed under Two Contrasting Tillage Regimes

    Directory of Open Access Journals (Sweden)

    Florine Degrune

    2017-06-01

    Full Text Available Agricultural productivity relies on a wide range of ecosystem services provided by the soil biota. Plowing is a fundamental component of conventional farming, but long-term detrimental effects such as soil erosion and loss of soil organic matter have been recognized. Moving towards more sustainable management practices such as reduced tillage or crop residue retention can reduce these detrimental effects, but will also influence structure and function of the soil microbiota with direct consequences for the associated ecosystem services. Although there is increasing evidence that different tillage regimes alter the soil microbiome, we have a limited understanding of the temporal dynamics of these effects. Here, we used high-throughput sequencing of bacterial and fungal ribosomal markers to explore changes in soil microbial community structure under two contrasting tillage regimes (conventional and reduced tillage either with or without crop residue retention. Soil samples were collected over the growing season of two crops (Vicia faba and Triticum aestivum below the seedbed (15–20 cm. Tillage, crop and growing stage were significant determinants of microbial community structure, but the impact of tillage showed only moderate temporal dependency. Whereas the tillage effect on soil bacteria showed some temporal dependency and became less strong at later growing stages, the tillage effect on soil fungi was more consistent over time. Crop residue retention had only a minor influence on the community. Six years after the conversion from conventional to reduced tillage, soil moisture contents and nutrient levels were significantly lower under reduced than under conventional tillage. These changes in edaphic properties were related to specific shifts in microbial community structure. Notably, bacterial groups featuring copiotrophic lifestyles or potentially carrying the ability to degrade more recalcitrant compounds were favored under conventional

  15. Temporal Dynamics of Soil Microbial Communities below the Seedbed under Two Contrasting Tillage Regimes.

    Science.gov (United States)

    Degrune, Florine; Theodorakopoulos, Nicolas; Colinet, Gilles; Hiel, Marie-Pierre; Bodson, Bernard; Taminiau, Bernard; Daube, Georges; Vandenbol, Micheline; Hartmann, Martin

    2017-01-01

    Agricultural productivity relies on a wide range of ecosystem services provided by the soil biota. Plowing is a fundamental component of conventional farming, but long-term detrimental effects such as soil erosion and loss of soil organic matter have been recognized. Moving towards more sustainable management practices such as reduced tillage or crop residue retention can reduce these detrimental effects, but will also influence structure and function of the soil microbiota with direct consequences for the associated ecosystem services. Although there is increasing evidence that different tillage regimes alter the soil microbiome, we have a limited understanding of the temporal dynamics of these effects. Here, we used high-throughput sequencing of bacterial and fungal ribosomal markers to explore changes in soil microbial community structure under two contrasting tillage regimes (conventional and reduced tillage) either with or without crop residue retention. Soil samples were collected over the growing season of two crops ( Vicia faba and Triticum aestivum ) below the seedbed (15-20 cm). Tillage, crop and growing stage were significant determinants of microbial community structure, but the impact of tillage showed only moderate temporal dependency. Whereas the tillage effect on soil bacteria showed some temporal dependency and became less strong at later growing stages, the tillage effect on soil fungi was more consistent over time. Crop residue retention had only a minor influence on the community. Six years after the conversion from conventional to reduced tillage, soil moisture contents and nutrient levels were significantly lower under reduced than under conventional tillage. These changes in edaphic properties were related to specific shifts in microbial community structure. Notably, bacterial groups featuring copiotrophic lifestyles or potentially carrying the ability to degrade more recalcitrant compounds were favored under conventional tillage, whereas

  16. Dynamic modelling of nuclear steam generators

    International Nuclear Information System (INIS)

    Kerlin, T.W.; Katz, E.M.; Freels, J.; Thakkar, J.

    1980-01-01

    Moving boundary, nodal models with dynamic energy balances, dynamic mass balances, quasi-static momentum balances, and an equivalent single channel approach have been developed for steam generators used in nuclear power plants. The model for the U-tube recirculation type steam generator is described and comparisons are made of responses from models of different complexity; non-linear versus linear, high-order versus low order, detailed modeling of the control system versus a simple control assumption. The results of dynamic tests on nuclear power systems show that when this steam generator model is included in a system simulation there is good agreement with actual plant performance. (author)

  17. Dynamic Airspace Managment - Models and Algorithms

    OpenAIRE

    Cheng, Peng; Geng, Rui

    2010-01-01

    This chapter investigates the models and algorithms for implementing the concept of Dynamic Airspace Management. Three models are discussed. First two models are about how to use or adjust air route dynamically in order to speed up air traffic flow and reduce delay. The third model gives a way to dynamically generate the optimal sector configuration for an air traffic control center to both balance the controller’s workload and save control resources. The first model, called the Dynami...

  18. Wind Farm Decentralized Dynamic Modeling With Parameters

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

    2010-01-01

    Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

  19. System dynamics modelling of situation awareness

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2015-11-01

    Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...

  20. Temporal dominance of emotions: Measuring dynamics of food-related emotions during consumption

    NARCIS (Netherlands)

    Jager, G.; Schlich, P.; Tijssen, I.O.J.M.; Yao, Y.J.; Visalli, M.; Graaf, de C.; Stieger, M.A.

    2014-01-01

    Mapping food-evoked emotions in addition to sensory profiling is topical. In sensory profiling, the Temporal Dominance of Sensation (TDS) method focuses on the assessment of the temporal evolution of dominant sensory attributes over time. We hypothesize that food-evoked emotions also show temporal

  1. Temporal Scalability of Dynamic Volume Data using Mesh Compensated Wavelet Lifting.

    Science.gov (United States)

    Schnurrer, Wolfgang; Pallast, Niklas; Richter, Thomas; Kaup, Andre

    2017-10-12

    Due to their high resolution, dynamic medical 2D+t and 3D+t volumes from computed tomography (CT) and magnetic resonance tomography (MR) reach a size which makes them very unhandy for teleradiologic applications. A lossless scalable representation offers the advantage of a down-scaled version which can be used for orientation or previewing, while the remaining information for reconstructing the full resolution is transmitted on demand. The wavelet transform offers the desired scalability. A very high quality of the lowpass sub-band is crucial in order to use it as a down-scaled representation. We propose an approach based on compensated wavelet lifting for obtaining a scalable representation of dynamic CT and MR volumes with very high quality. The mesh compensation is feasible to model the displacement in dynamic volumes which is mainly given by expansion and contraction of tissue over time. To achieve this, we propose an optimized estimation of the mesh compensation parameters to optimally fit for dynamic volumes. Within the lifting structure, the inversion of the motion compensation is crucial in the update step. We propose to take this inversion directly into account during the estimation step and can improve the quality of the lowpass sub-band by 0.63 dB and 0.43 dB on average for our tested dynamic CT and MR volumes at the cost of an increase of the rate by 2.4% and 1.2% on average.

  2. Object Representations in Human Visual Cortex Formed Through Temporal Integration of Dynamic Partial Shape Views.

    Science.gov (United States)

    Orlov, Tanya; Zohary, Ehud

    2018-01-17

    the retina. The lateral occipital complex (LOC) represents shape faithfully in such conditions even if the object is partially occluded. However, shape must sometimes be reconstructed over both space and time. Such is the case in anorthoscopic perception, when an object is moving behind a narrow slit. In this scenario, spatial information is limited at any moment so the whole-shape percept can only be inferred by integration of successive shape views over time. We find that LOC carries shape-specific information recovered using such temporal integration processes. The shape representation is invariant to slit orientation and is similar to that evoked by a fully viewed image. Existing models of object recognition lack such capabilities. Copyright © 2018 the authors 0270-6474/18/380659-20$15.00/0.

  3. An Agent Model Integrating an Adaptive Model for Environmental Dynamics

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2011-01-01

    The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the

  4. Hydration dynamics near a model protein surface

    International Nuclear Information System (INIS)

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-01-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces

  5. Temporal and demographic blood parasite dynamics in two free-ranging neotropical primates

    Directory of Open Access Journals (Sweden)

    Gideon A. Erkenswick

    2017-08-01

    Full Text Available Parasite-host relationships are influenced by several factors intrinsic to hosts, such as social standing, group membership, sex, and age. However, in wild populations, temporal variation in parasite distributions and concomitant infections can alter these patterns. We used microscropy and molecular methods to screen for naturally occurring haemoparasitic infections in two Neotropical primate host populations, the saddleback (Leontocebus weddelli and emperor (Saguinus imperator tamarin, in the lowland tropical rainforests of southeastern Peru. Repeat sampling was conducted from known individuals over a three-year period to test for parasite-host and parasite-parasite associations. Three parasites were detected in L. weddelli including Trypanosoma minasense, Mansonella mariae, and Dipetalonema spp., while S. imperator only hosted the latter two. Temporal variation in prevalence was observed in T. minasense and Dipetalonema spp., confirming the necessity of a multi-year study to evaluate parasite-host relationships in this system. Although callitrichids display a distinct reproductive dominance hierarchy, characterized by single breeding females that typically mate polyandrously and can suppress the reproduction of subdominant females, logistic models did not identify sex or breeding status as determining factors in the presence of these parasites. However, age class had a positive effect on infection with M. mariae and T. minasense, and adults demonstrated higher parasite species richness than juveniles or sub-adults across both species. Body weight had a positive effect on the presence of Dipetalonema spp. The inclusion of co-infection variables in statistical models of parasite presence/absence data improved model fit for two of three parasites. This study verifies the importance and need for broad spectrum and long-term screening of parasite assemblages of natural host populations.

  6. Fault Tree Analysis with Temporal Gates and Model Checking Technique for Qualitative System Safety Analysis

    International Nuclear Information System (INIS)

    Koh, Kwang Yong; Seong, Poong Hyun

    2010-01-01

    Fault tree analysis (FTA) has suffered from several drawbacks such that it uses only static gates and hence can not capture dynamic behaviors of the complex system precisely, and it is in lack of rigorous semantics, and reasoning process which is to check whether basic events really cause top events is done manually and hence very labor-intensive and time-consuming for the complex systems while it has been one of the most widely used safety analysis technique in nuclear industry. Although several attempts have been made to overcome this problem, they can not still do absolute or actual time modeling because they adapt relative time concept and can capture only sequential behaviors of the system. In this work, to resolve the problems, FTA and model checking are integrated to provide formal, automated and qualitative assistance to informal and/or quantitative safety analysis. Our approach proposes to build a formal model of the system together with fault trees. We introduce several temporal gates based on timed computational tree logic (TCTL) to capture absolute time behaviors of the system and to give concrete semantics to fault tree gates to reduce errors during the analysis, and use model checking technique to automate the reasoning process of FTA

  7. The shape and temporal dynamics of phylogenetic trees arising from geographic speciation.

    Science.gov (United States)

    Pigot, Alex L; Phillimore, Albert B; Owens, Ian P F; Orme, C David L

    2010-12-01

    Phylogenetic trees often depart from the expectations of stochastic models, exhibiting imbalance in diversification among lineages and slowdowns in the rate of lineage accumulation through time. Such departures have led to a widespread perception that ecological differences among species or adaptation and subsequent niche filling are required to explain patterns of diversification. However, a key element missing from models of diversification is the geographical context of speciation and extinction. In this study, we develop a spatially explicit model of geographic range evolution and cladogenesis, where speciation arises via vicariance or peripatry, and explore the effects of these processes on patterns of diversification. We compare the results with those observed in 41 reconstructed avian trees. Our model shows that nonconstant rates of speciation and extinction are emergent properties of the apportioning of geographic ranges that accompanies speciation. The dynamics of diversification exhibit wide variation, depending on the mode of speciation, tendency for range expansion, and rate of range evolution. By varying these parameters, the model is able to capture many, but not all, of the features exhibited by birth-death trees and extant bird clades. Under scenarios with relatively stable geographic ranges, strong slowdowns in diversification rates are produced, with faster rates of range dynamics leading to constant or accelerating rates of apparent diversification. A peripatric model of speciation with stable ranges also generates highly unbalanced trees typical of bird phylogenies but fails to produce realistic range size distributions among the extant species. Results most similar to those of a birth-death process are reached under a peripatric speciation scenario with highly volatile range dynamics. Taken together, our results demonstrate that considering the geographical context of speciation and extinction provides a more conservative null model of

  8. Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    2010-01-01

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  9. Beach-dune dynamics: Spatio-temporal patterns of aeolian sediment transport under complex offshore airflow

    Science.gov (United States)

    Lynch, K.; Jackson, D.; Delgado-Fernandez, I.; Cooper, J. A.; Baas, A. C.; Beyers, M.

    2010-12-01

    This study examines sand transport and wind speed across a beach at Magilligan Strand, Northern Ireland, under offshore wind conditions. Traditionally the offshore component of local wind regimes has been ignored when quantifying beach-dune sediment budgets, with the sheltering effect of the foredune assumed to prohibit grain entrainment on the adjoining beach. Recent investigations of secondary airflow patterns over coastal dunes have suggested this may not be the case, that the turbulent nature of the airflow in these zones enhances sediment transport potential. Beach sediment may be delivered to the dune toe by re-circulating eddies under offshore winds in coastal areas, which may explain much of the dynamics of aeolian dunes on coasts where the dominant wind direction is offshore. The present study investigated aeolian sediment transport patterns under an offshore wind event. Empirical data were collected using load cell traps, for aeolian sediment transport, co-located with 3-D ultrasonic anemometers. The instrument positioning on the sub-aerial beach was informed by prior analysis of the airflow patterns using computational fluid dynamics. The array covered a total beach area of 90 m alongshore by 65 m cross-shore from the dune crest. Results confirm that sediment transport occurred in the ‘sheltered’ area under offshore winds. Over short time and space scales the nature of the transport is highly complex; however, preferential zones for sand entrainment may be identified. Alongshore spatial heterogeneity of sediment transport seems to show a relationship to undulations in the dune crest, while temporal and spatial variations may also be related to the position of the airflow reattachment zone. These results highlight the important feedbacks between flow characteristics and transport in a complex three dimensional surface.

  10. Does carbon availability control temporal dynamics of radial growth in Norway spruce (Picea abies)?

    Science.gov (United States)

    Oberhuber, Walter; Gruber, Andreas; Swidrak, Irene

    2015-04-01

    Intra-annual dynamics of cambial activity and wood formation of coniferous species exposed to soil dryness revealed early culmination of maximum growth in late spring prior to occurrence of more favourable environmental conditions, i.e., repeated high rainfall events during summer (Oberhuber et al. 2014). Because it is well known that plants can adjust carbon allocation patterns to optimize resource uptake under prevailing environmental constraints, we hypothesize that early decrease in radial stem growth is an adaptation to cope with drought stress, which might require an early switch of carbon allocation to belowground organs. Physical blockage of carbon transport in the phloem through girdling causes accumulation and depletion of carbohydrates above and below the girdle, respectively, making this method quite appropriate to investigate carbon relationships in trees. Hence, in a common garden experiment we will manipulate the carbon status of Norway spruce (Picea abies) saplings by phloem blockage at different phenological stages during the growing season. We will present the methodological approach and first results of the study aiming to test the hypothesis that carbon status of the tree affects temporal dynamics of cambial activity and wood formation in conifers under drought. Acknowledgment The research is funded by the Austrian Science Fund (FWF): P25643-B16 "Carbon allocation and growth of Scots pine". Reference Oberhuber W, A Gruber, W Kofler, I Swidrak (2014) Radial stem growth in response to microclimate and soil moisture in a drought-prone mixed coniferous forest at an inner Alpine site. Eur J For Res 133:467-479.

  11. Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2015-01-01

    We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

  12. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

    Science.gov (United States)

    Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

    2018-01-01

    Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

  13. Temporal dynamics of the longitudinal bunch profile in a laser wakefield accelerator

    Energy Technology Data Exchange (ETDEWEB)

    Heigoldt, Matthias

    2017-05-19

    iterative reconstruction algorithm by our collaborators from Oxford University. A major benefit of their algorithm is to avoid any a priori assumptions about the bunch shape or extrapolation of the spectrum outside the measured range, which are usually necessary in traditional methods. In the presented experiments, the ATLAS 50 TW Ti:Sa based laser system was used in conjunction with a hydrogen-filled gas cell. Under optimized conditions, the shortest bunch duration was determined to 4.8±0.2 fs for single electron bunches with a maximum energy of 650 MeV, a charge of 30 pC and a resulting peak current of 5.7±1.2 kA. In combination with the lengthtunable gas target, the single-shot measurement technique allows for the first time to study the temporal evolution of the electron bunch profile as a function of the acceleration distance. This technique sheds new light onto the acceleration regimes characterized by electron dephasing and laser depletion as well as the involved plasma dynamics. The results show that after electron dephasing a second electron bunch can be injected in the first or subsequent plasma periods. After laser depletion, the first bunch is further found to be dense enough to drive its own beam-driven wakefield. The obtained double bunch structure is well suited for further beam-driven experiments and may enable a demonstration scheme for an energy boost by afterburner acceleration in the near future.

  14. Temporal dynamics of the longitudinal bunch profile in a laser wakefield accelerator

    International Nuclear Information System (INIS)

    Heigoldt, Matthias

    2017-01-01

    iterative reconstruction algorithm by our collaborators from Oxford University. A major benefit of their algorithm is to avoid any a priori assumptions about the bunch shape or extrapolation of the spectrum outside the measured range, which are usually necessary in traditional methods. In the presented experiments, the ATLAS 50 TW Ti:Sa based laser system was used in conjunction with a hydrogen-filled gas cell. Under optimized conditions, the shortest bunch duration was determined to 4.8±0.2 fs for single electron bunches with a maximum energy of 650 MeV, a charge of 30 pC and a resulting peak current of 5.7±1.2 kA. In combination with the lengthtunable gas target, the single-shot measurement technique allows for the first time to study the temporal evolution of the electron bunch profile as a function of the acceleration distance. This technique sheds new light onto the acceleration regimes characterized by electron dephasing and laser depletion as well as the involved plasma dynamics. The results show that after electron dephasing a second electron bunch can be injected in the first or subsequent plasma periods. After laser depletion, the first bunch is further found to be dense enough to drive its own beam-driven wakefield. The obtained double bunch structure is well suited for further beam-driven experiments and may enable a demonstration scheme for an energy boost by afterburner acceleration in the near future.

  15. On the temporal dynamics of sign production: An ERP study in Catalan Sign Language (LSC).

    Science.gov (United States)

    Baus, Cristina; Costa, Albert

    2015-06-03

    This study investigates the temporal dynamics of sign production and how particular aspects of the signed modality influence the early stages of lexical access. To that end, we explored the electrophysiological correlates associated to sign frequency and iconicity in a picture signing task in a group of bimodal bilinguals. Moreover, a subset of the same participants was tested in the same task but naming the pictures instead. Our results revealed that both frequency and iconicity influenced lexical access in sign production. At the ERP level, iconicity effects originated very early in the course of signing (while absent in the spoken modality), suggesting a stronger activation of the semantic properties for iconic signs. Moreover, frequency effects were modulated by iconicity, suggesting that lexical access in signed language is determined by the iconic properties of the signs. These results support the idea that lexical access is sensitive to the same phenomena in word and sign production, but its time-course is modulated by particular aspects of the modality in which a lexical item will be finally articulated. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Spatio-temporal dynamics of the mirror neuron system during social intentions.

    Science.gov (United States)

    Cacioppo, Stephanie; Bolmont, Mylene; Monteleone, George

    2017-10-27

    Previous research has shown that specific goals and intentions influence a person's allocation of social attention. From a neural viewpoint, a growing body of evidence suggests that the inferior fronto-parietal network, including the mirror neuron system, plays a role in the planning and the understanding of motor intentions. However, it is unclear whether and when the mirror neuron system plays a role in social intentions. Combining a behavioral task with electrical neuroimaging in 22 healthy male participants, the current study investigates whether the temporal brain dynamic of the mirror neuron system differs during two types of social intentions i.e., lust vs. romantic intentions. Our results showed that 62% of the stimuli evoking lustful intentions also evoked romantic intentions, and both intentions were sustained by similar activations of the inferior frontal gyrus and the inferior parietal lobule/angular gyrus for the first 432 ms after stimulus onset. Intentions to not love or not lust, on the other hand, were characterized by earlier differential activations of the inferior fronto-parietal network i.e., as early as 244 ms after stimulus onset. These results suggest that the mirror neuron system may not only code for the motor correlates of intentions, but also for the social meaning of intentions and its valence at both early/automatic and later/more elaborative stages of information processing.

  17. Neural Temporal Dynamics of Facial Emotion Processing: Age Effects and Relationship to Cognitive Function

    Directory of Open Access Journals (Sweden)

    Xiaoyan Liao

    2017-06-01

    Full Text Available This study used event-related potentials (ERPs to investigate the effects of age on neural temporal dynamics of processing task-relevant facial expressions and their relationship to cognitive functions. Negative (sad, afraid, angry, and disgusted, positive (happy, and neutral faces were presented to 30 older and 31 young participants who performed a facial emotion categorization task. Behavioral and ERP indices of facial emotion processing were analyzed. An enhanced N170 for negative faces, in addition to intact right-hemispheric N170 for positive faces, was observed in older adults relative to their younger counterparts. Moreover, older adults demonstrated an attenuated within-group N170 laterality effect for neutral faces, while younger adults showed the opposite pattern. Furthermore, older adults exhibited sustained temporo-occipital negativity deflection over the time range of 200–500 ms post-stimulus, while young adults showed posterior positivity and subsequent emotion-specific frontal negativity deflections. In older adults, decreased accuracy for labeling negative faces was positively correlated with Montreal Cognitive Assessment Scores, and accuracy for labeling neutral faces was negatively correlated with age. These findings suggest that older people may exert more effort in structural encoding for negative faces and there are different response patterns for the categorization of different facial emotions. Cognitive functioning may be related to facial emotion categorization deficits observed in older adults. This may not be attributable to positivity effects: it may represent a selective deficit for the processing of negative facial expressions in older adults.

  18. Spatio-temporal dynamics of impulse responses to figure motion in optic flow neurons.

    Directory of Open Access Journals (Sweden)

    Yu-Jen Lee

    Full Text Available White noise techniques have been used widely to investigate sensory systems in both vertebrates and invertebrates. White noise stimuli are powerful in their ability to rapidly generate data that help the experimenter decipher the spatio-temporal dynamics of neural and behavioral responses. One type of white noise stimuli, maximal length shift register sequences (m-sequences, have recently become particularly popular for extracting response kernels in insect motion vision. We here use such m-sequences to extract the impulse responses to figure motion in hoverfly lobula plate tangential cells (LPTCs. Figure motion is behaviorally important and many visually guided animals orient towards salient features in the surround. We show that LPTCs respond robustly to figure motion in the receptive field. The impulse response is scaled down in amplitude when the figure size is reduced, but its time course remains unaltered. However, a low contrast stimulus generates a slower response with a significantly longer time-to-peak and half-width. Impulse responses in females have a slower time-to-peak than males, but are otherwise similar. Finally we show that the shapes of the impulse response to a figure and a widefield stimulus are very similar, suggesting that the figure response could be coded by the same input as the widefield response.

  19. Spatial and temporal dynamics of dengue fever in Peru: 1994–2006

    Science.gov (United States)

    CHOWELL, G.; TORRE, C. A.; MUNAYCO-ESCATE, C.; SUÁREZ-OGNIO, L.; LÓPEZ-CRUZ, R.; HYMAN, J. M.; CASTILLO-CHAVEZ, C.

    2008-01-01

    SUMMARY The weekly number of dengue cases in Peru, South America, stratified by province for the period 1994–2006 were analysed in conjunction with associated demographic, geographic and climatological data. Estimates of the reproduction number, moderately correlated with population size (Spearman ρ=0·28, P=0·03), had a median of 1·76 (IQR 0·83–4·46). The distributions of dengue attack rates and epidemic durations follow power-law (Pareto) distributions (coefficient of determination >85%, Pjungle areas. Our findings suggest a hierarchy of transmission events during the large 2000–2001 epidemic from large to small population areas when serotypes DEN-3 and DEN-4 were first identified (Spearman ρ=−0·43, P=0·03). The need for spatial and temporal dengue epidemic data with a high degree of resolution not only increases our understanding of the dynamics of dengue but will also generate new hypotheses and provide a platform for testing innovative control policies. PMID:18394264

  20. Amygdala and fusiform gyrus temporal dynamics: Responses to negative facial expressions

    Directory of Open Access Journals (Sweden)

    Rauch Scott L

    2008-05-01

    Full Text Available Abstract Background The amygdala habituates in response to repeated human facial expressions; however, it is unclear whether this brain region habituates to schematic faces (i.e., simple line drawings or caricatures of faces. Using an fMRI block design, 16 healthy participants passively viewed repeated presentations of schematic and human neutral and negative facial expressions. Percent signal changes within anatomic regions-of-interest (amygdala and fusiform gyrus were calculated to examine the temporal dynamics of neural response and any response differences based on face type. Results The amygdala and fusiform gyrus had a within-run "U" response pattern of activity to facial expression blocks. The initial block within each run elicited the greatest activation (relative to baseline and the final block elicited greater activation than the preceding block. No significant differences between schematic and human faces were detected in the amygdala or fusiform gyrus. Conclusion The "U" pattern of response in the amygdala and fusiform gyrus to facial expressions suggests an initial orienting, habituation, and activation recovery in these regions. Furthermore, this study is the first to directly compare brain responses to schematic and human facial expressions, and the similarity in brain responses suggest that schematic faces may be useful in studying amygdala activation.

  1. Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

    Directory of Open Access Journals (Sweden)

    Yongsheng Huang

    2011-08-01

    Full Text Available Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza.

  2. Spatial Temporal Dynamics and Molecular Evolution of Re-Emerging Rabies Virus in Taiwan

    Directory of Open Access Journals (Sweden)

    Yung-Cheng Lin

    2016-03-01

    Full Text Available Taiwan has been recognized by the World Organization for Animal Health as rabies-free since 1961. Surprisingly, rabies virus (RABV was identified in a dead Formosan ferret badger in July 2013. Later, more infected ferret badgers were reported from different geographic regions of Taiwan. In order to know its evolutionary history and spatial temporal dynamics of this virus, phylogeny was reconstructed by maximum likelihood and Bayesian methods based on the full-length of glycoprotein (G, matrix protein (M, and nucleoprotein (N genes. The evolutionary rates and phylogeographic were determined using Beast and SPREAD software. Phylogenetic trees showed a monophyletic group containing all of RABV isolates from Taiwan and it further separated into three sub-groups. The estimated nucleotide substitution rates of G, M, and N genes were between 2.49 × 10−4–4.75 × 10−4 substitutions/site/year, and the mean ratio of dN/dS was significantly low. The time of the most recent common ancestor was estimated around 75, 89, and 170 years, respectively. Phylogeographic analysis suggested the origin of the epidemic could be in Eastern Taiwan, then the Formosan ferret badger moved across the Central Range of Taiwan to western regions and separated into two branches. In this study, we illustrated the evolution history and phylogeographic of RABV in Formosan ferret badgers.

  3. Cue competition affects temporal dynamics of edge-assignment in human visual cortex.

    Science.gov (United States)

    Brooks, Joseph L; Palmer, Stephen E

    2011-03-01

    Edge-assignment determines the perception of relative depth across an edge and the shape of the closer side. Many cues determine edge-assignment, but relatively little is known about the neural mechanisms involved in combining these cues. Here, we manipulated extremal edge and attention cues to bias edge-assignment such that these two cues either cooperated or competed. To index their neural representations, we flickered figure and ground regions at different frequencies and measured the corresponding steady-state visual-evoked potentials (SSVEPs). Figural regions had stronger SSVEP responses than ground regions, independent of whether they were attended or unattended. In addition, competition and cooperation between the two edge-assignment cues significantly affected the temporal dynamics of edge-assignment processes. The figural SSVEP response peaked earlier when the cues causing it cooperated than when they competed, but sustained edge-assignment effects were equivalent for cooperating and competing cues, consistent with a winner-take-all outcome. These results provide physiological evidence that figure-ground organization involves competitive processes that can affect the latency of figural assignment.

  4. Temporal dynamic responses of roots in contrasting tomato genotypes to cadmium tolerance.

    Science.gov (United States)

    Borges, Karina Lima Reis; Salvato, Fernanda; Alcântara, Berenice Kussumoto; Nalin, Rafael Storto; Piotto, Fernando Ângelo; Azevedo, Ricardo Antunes

    2018-04-01

    Despite numerous studies on cadmium (Cd) uptake and accumulation in crops, relatively little is available considering the temporal dynamic of Cd uptake and responses to stress focused on the root system. Here we highlighted the responses to Cd-induced stress in roots of two tomato genotypes contrasting in Cd-tolerance: the tolerant Pusa Ruby and the sensitive Calabash Rouge. Tomato genotypes growing in the presence of 35 μM CdCl 2 exhibited a similar trend of Cd accumulation in tissues, mainly in the root system and overall plants exhibited reduction in the dry matter weight. Both genotypes showed similar trends for malondialdehyde and hydrogen peroxide accumulation with increases when exposed to Cd, being this response more pronounced in the sensitive genotype. When the antioxidant machinery is concerned, in the presence of Cd the reduced glutathione content was decreased in roots while ascorbate peroxidase (APX), glutathione reductase (GR) and glutathione S-transferase (GST) activities were increased in the presence of Cd in the tolerant genotype. Altogether these results suggest APX, GR and GST as the main players of the antioxidant machinery against Cd-induced oxidative stress.

  5. Adaptive numerical modeling of dynamic crack propagation

    International Nuclear Information System (INIS)

    Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.

    2006-01-01

    We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic stud