Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods

PubMed Central

Vizcaíno, Iván P.; Muñoz-Romero, Sergio; Cumbal, Luis H.

2017-01-01

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer’s kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer’s kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem. PMID:29035333

Forest forming process and dynamic vegetation models under global change

Treesearch

A. Shvidenko; E. Gustafson

2009-01-01

The paper analyzes mathematical models that are used to project the dynamics of forest ecosystems on different spatial and temporal scales. Landscape disturbance and succession models (LDSMs) are of a particular interest for studying the forest forming process in Northern Eurasia. They have a solid empirical background and are able to model ecological processes under...

Restoration of moving binary images degraded owing to phosphor persistence.

PubMed

Cherri, A K; Awwal, A A; Karim, M A; Moon, D L

1991-09-10

The degraded images of dynamic objects obtained by using a phosphor-based electro-optical display are analyzed in terms of dynamic modulation transfer function (DMTF) and temporal characteristics of the display system. The direct correspondence between the DMTF and image smear is used in developing real-time techniques for the restoration of degraded images.

Time-dynamics of the two-color emission from vertical-external-cavity surface-emitting lasers

NASA Astrophysics Data System (ADS)

Chernikov, A.; Wichmann, M.; Shakfa, M. K.; Scheller, M.; Moloney, J. V.; Koch, S. W.; Koch, M.

2012-01-01

The temporal stability of a two-color vertical-external-cavity surface-emitting laser is studied using single-shot streak-camera measurements. The collected data is evaluated via quantitative statistical analysis schemes. Dynamically stable and unstable regions for the two-color operation are identified and the dependence on the pump conditions is analyzed.

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

A Probabilistic Framework for Constructing Temporal Relations in Replica Exchange Molecular Trajectories.

PubMed

Chattopadhyay, Aditya; Zheng, Min; Waller, Mark Paul; Priyakumar, U Deva

2018-05-23

Knowledge of the structure and dynamics of biomolecules is essential for elucidating the underlying mechanisms of biological processes. Given the stochastic nature of many biological processes, like protein unfolding, it's almost impossible that two independent simulations will generate the exact same sequence of events, which makes direct analysis of simulations difficult. Statistical models like Markov Chains, transition networks etc. help in shedding some light on the mechanistic nature of such processes by predicting long-time dynamics of these systems from short simulations. However, such methods fall short in analyzing trajectories with partial or no temporal information, for example, replica exchange molecular dynamics or Monte Carlo simulations. In this work we propose a probabilistic algorithm, borrowing concepts from graph theory and machine learning, to extract reactive pathways from molecular trajectories in the absence of temporal data. A suitable vector representation was chosen to represent each frame in the macromolecular trajectory (as a series of interaction and conformational energies) and dimensionality reduction was performed using principal component analysis (PCA). The trajectory was then clustered using a density-based clustering algorithm, where each cluster represents a metastable state on the potential energy surface (PES) of the biomolecule under study. A graph was created with these clusters as nodes with the edges learnt using an iterative expectation maximization algorithm. The most reactive path is conceived as the widest path along this graph. We have tested our method on RNA hairpin unfolding trajectory in aqueous urea solution. Our method makes the understanding of the mechanism of unfolding in RNA hairpin molecule more tractable. As this method doesn't rely on temporal data it can be used to analyze trajectories from Monte Carlo sampling techniques and replica exchange molecular dynamics (REMD).

Dynamic Bayesian network modeling for longitudinal brain morphometry

PubMed Central

Chen, Rong; Resnick, Susan M; Davatzikos, Christos; Herskovits, Edward H

2011-01-01

Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment — the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group. PMID:21963916

Time Allocation in Social Networks: Correlation Between Social Structure and Human Communication Dynamics

NASA Astrophysics Data System (ADS)

Miritello, Giovanna; Lara, Rubén; Moro, Esteban

Recent research has shown the deep impact of the dynamics of human interactions (or temporal social networks) on the spreading of information, opinion formation, etc. In general, the bursty nature of human interactions lowers the interaction between people to the extent that both the speed and reach of information diffusion are diminished. Using a large database of 20 million users of mobile phone calls we show evidence this effect is not homogeneous in the social network but in fact, there is a large correlation between this effect and the social topological structure around a given individual. In particular, we show that social relations of hubs in a network are relatively weaker from the dynamical point than those that are poorer connected in the information diffusion process. Our results show the importance of the temporal patterns of communication when analyzing and modeling dynamical process on social networks.

Child allowances, fertility, and chaotic dynamics.

PubMed

Chen, Hung-Ju; Li, Ming-Chia

2013-06-01

This paper analyzes the dynamics in an overlapping generations model with the provision of child allowances. Fertility is an increasing function of child allowances and there exists a threshold effect of the marginal effect of child allowances on fertility. We show that if the effectiveness of child allowances is sufficiently high, an intermediate-sized tax rate will be enough to generate chaotic dynamics. Besides, a decrease in the inter-temporal elasticity of substitution will prevent the occurrence of irregular cycles.

Emergence and temporal structure of Lead-Lag correlations in collective stock dynamics

NASA Astrophysics Data System (ADS)

Xia, Lisi; You, Daming; Jiang, Xin; Chen, Wei

2018-07-01

Understanding the correlations among stock returns is crucial for reducing the risk of investment in stock markets. As an important stylized correlation, lead-lag effect plays a major role in analyzing market volatility and deriving trading strategies. Here, we explore historical lead-lag relationships among stocks in the Chinese stock market. Strongly positive lagged correlations can be empirically observed. We demonstrate this lead-lag phenomenon is not constant but temporally emerges during certain periods. By introducing moving time window method, we transform the lead-lag dynamics into a series of asymmetric lagged correlation matrices. Dynamic lead-lag structures are uncovered in the form of temporal network structures. We find that the size of lead-lag group experienced a rapid drop during the year 2012, which signaled a re-balance of the stock market. On the daily timescale, we find the lead-lag structure exhibits several persistent patterns, which can be characterized by the Jaccard matrix. We show significant market events can be distinguished in the Jaccard matrix diagram. Taken together, we study an integration of all the temporal networks and identify several leading stock sectors, which are in accordance with the common Chinese economic fundamentals.

Visualization of spatial-temporal data based on 3D virtual scene

NASA Astrophysics Data System (ADS)

Wang, Xianghong; Liu, Jiping; Wang, Yong; Bi, Junfang

2009-10-01

The main purpose of this paper is to realize the expression of the three-dimensional dynamic visualization of spatialtemporal data based on three-dimensional virtual scene, using three-dimensional visualization technology, and combining with GIS so that the people's abilities of cognizing time and space are enhanced and improved by designing dynamic symbol and interactive expression. Using particle systems, three-dimensional simulation, virtual reality and other visual means, we can simulate the situations produced by changing the spatial location and property information of geographical entities over time, then explore and analyze its movement and transformation rules by changing the interactive manner, and also replay history and forecast of future. In this paper, the main research object is the vehicle track and the typhoon path and spatial-temporal data, through three-dimensional dynamic simulation of its track, and realize its timely monitoring its trends and historical track replaying; according to visualization techniques of spatialtemporal data in Three-dimensional virtual scene, providing us with excellent spatial-temporal information cognitive instrument not only can add clarity to show spatial-temporal information of the changes and developments in the situation, but also be used for future development and changes in the prediction and deduction.

Spatial and temporal variations of the ion velocity measured in the Venus ionosphere

NASA Technical Reports Server (NTRS)

Miller, K. L.; Knudsen, W. C.

1987-01-01

Temporal and spatial deviations of ion velocity from the dominant flow of the Venusian ionosphere were detected in data collected from a retarding potential analyzer (RPA) aboard the Pioneer-Venus orbiter spectrometer. The ion velocity measurements were analyzed for the first 3.5 Venus years of the Pioneer-Venus mission, approximately through orbit 780. The deviations of ion velocity from the dominant velocity of the Venusian ionosphere, which generally flows nightward and is almost symmetric about the sun-Venus axis, affect both the ionospheric structure and dynamics. Two examples of departure from steady symmetric flow that were measured by the RPA are discussed.

On Patterns in Affective Media

NASA Astrophysics Data System (ADS)

ADAMATZKY, ANDREW

In computational experiments with cellular automaton models of affective solutions, where chemical species represent happiness, anger, fear, confusion and sadness, we study phenomena of space time dynamic of emotions. We demonstrate feasibility of the affective solution paradigm in example of emotional abuse therapy. Results outlined in the present paper offer unconventional but promising technique to design, analyze and interpret spatio-temporal dynamic of mass moods in crowds.

Dynamics of nonspherical microbubble oscillations above instability threshold

NASA Astrophysics Data System (ADS)

Guédra, Matthieu; Cleve, Sarah; Mauger, Cyril; Blanc-Benon, Philippe; Inserra, Claude

2017-12-01

Time-resolved dynamics of nonspherical oscillations of micrometer-sized bubbles are captured and analyzed using high-speed imaging. The axisymmetry of the bubble shape is ensured with certainty for the first time from the recordings of two synchronous high-speed cameras located at 90∘. The temporal dynamics of finite-amplitude nonspherical oscillations are then analyzed for various acoustic pressures above the instability threshold. The experimental results are compared with recent theories accounting for nonlinearities and mode coupling, highlighting particular effects inherent to these mechanisms (saturation of the instability, triggering of nonparametric shape modes). Finally, the amplitude of the nonspherical oscillations is given as function of the driving pressure both for quadrupolar and octupolar bubbles.

MULTIMEDIA ENVIRONMENTAL DISTRIBUTION OF TOXICS (MEND-TOX): PART II, SOFTWARE IMPLEMENTATION AND CASE STUDIES

EPA Science Inventory

An integrated hybrid spatial-compartmental simulator is presented for analyzing the dynamic distribution of chemicals in the multimedia environment. Information obtained from such analysis, which includes temporal chemical concentration profiles in various media, mass distribu...

MULTIMEDIA ENVIRONMENTAL DISTRIBUTION OF TOXICS (MEND-TOX): PART I, HYBRID COMPARTMENTAL-SPATIAL MODELING FRAMEWORK

EPA Science Inventory

An integrated hybrid spatial-compartmental modeling approach is presented for analyzing the dynamic distribution of chemicals in the multimedia environment. Information obtained from such analysis, which includes temporal chemical concentration profiles in various media, mass ...

Real-time monitoring of corks' water absorption using laser speckle temporal correlation

NASA Astrophysics Data System (ADS)

Nassif, Rana; Abou Nader, Christelle; Pellen, Fabrice; Le Jeune, Bernard; Le Brun, Guy; Abboud, Marie

2015-08-01

Physical and mechanical properties of cork allow it solving many types of problems and make it suitable for a wide range of applications. Our objective consists into studying cork's water absorption by analyzing the dynamic speckle field using the temporal correlation method. Experimental results show that the medium was inert at first with the absence of activity, and as the cap cork was more and more immersed into water, the presence of the activity becomes more significant. This temporal parameter revealed the sensibility of biospeckle method to monitor the amount of absorbed water by cork caps.

Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

PubMed Central

Chen, Hong; Li, Yang

2014-01-01

The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

Temporal scaling and spatial statistical analyses of groundwater level fluctuations

NASA Astrophysics Data System (ADS)

Sun, H.; Yuan, L., Sr.; Zhang, Y.

2017-12-01

Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.

Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics

NASA Astrophysics Data System (ADS)

Roca, Carlos P.; Cuesta, José A.; Sánchez, Angel

2009-12-01

Evolutionary game dynamics is one of the most fruitful frameworks for studying evolution in different disciplines, from Biology to Economics. Within this context, the approach of choice for many researchers is the so-called replicator equation, that describes mathematically the idea that those individuals performing better have more offspring and thus their frequency in the population grows. While very many interesting results have been obtained with this equation in the three decades elapsed since it was first proposed, it is important to realize the limits of its applicability. One particularly relevant issue in this respect is that of non-mean-field effects, that may arise from temporal fluctuations or from spatial correlations, both neglected in the replicator equation. This review discusses these temporal and spatial effects focusing on the non-trivial modifications they induce when compared to the outcome of replicator dynamics. Alongside this question, the hypothesis of linearity and its relation to the choice of the rule for strategy update is also analyzed. The discussion is presented in terms of the emergence of cooperation, as one of the current key problems in Biology and in other disciplines.

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms.

PubMed

Ahn, Sungwoo; Rubchinsky, Leonid L

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Rubchinsky, Leonid L.

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

Spatio-temporal error growth in the multi-scale Lorenz'96 model

NASA Astrophysics Data System (ADS)

Herrera, S.; Fernández, J.; Rodríguez, M. A.; Gutiérrez, J. M.

2010-07-01

The influence of multiple spatio-temporal scales on the error growth and predictability of atmospheric flows is analyzed throughout the paper. To this aim, we consider the two-scale Lorenz'96 model and study the interplay of the slow and fast variables on the error growth dynamics. It is shown that when the coupling between slow and fast variables is weak the slow variables dominate the evolution of fluctuations whereas in the case of strong coupling the fast variables impose a non-trivial complex error growth pattern on the slow variables with two different regimes, before and after saturation of fast variables. This complex behavior is analyzed using the recently introduced Mean-Variance Logarithmic (MVL) diagram.

Glacier changes in the Nanga Parbat Himalayas: a re-photographic survey between the 1930s and now

NASA Astrophysics Data System (ADS)

Schmidt, S.; Nüsser, M.

2009-04-01

In contrast to the relatively well investigated glacier and landscape changes in the mountains of Europe and North America, very little investigations and documentations using repeat photography have been undertaken in the Himalayas and other high mountain regions of Asia. The present study seeks to investigate glacier and landscape changes in the Nanga Parbat region (NW-Himalaya) using a multi-temporal and multi-spatial approach which is based on terrestrial repeat photography and remote sensing data. A comprehensive collection of historical landscape photographs, taken by members of the German Himalaya expeditions 1934 and 1937, forms a valuable baseline data set for the area. Recent fieldwork made it possible to repeat a large number of these photographs viewpoints identical to the earlier ones, and the direct comparisons illustrate glacier dynamics and landscape changes over a span of seventy years. Furthermore, in order to fill the temporal gap and to analyze temporal and spatial dynamics of glaciers over the last 40 years we use different satellite sensors (Corona, Aster, Landsat, Spot, QuickBird). First investigations were carried out at the Raikot Glacier, which is located at the northern declivity of the Nanga Parbat, the ninth highest peak on earth. The multi-temporal comparison detects only small down-wasting rates of the Raikot Glacier over the last 70 years and a retreat of the terminus of about 250 m which is characterized by great fluctuations. Based on this multi-temporal and multi-data approach, we will detect and analyze glacier and landscape changes in the whole Nanga Parbat region.

Multiscale analysis of the intensity fluctuation in a time series of dynamic speckle patterns.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2007-04-10

We propose the application of a method based on the discrete wavelet transform to detect, identify, and measure scaling behavior in dynamic speckle. The multiscale phenomena presented by a sample and displayed by its speckle activity are analyzed by processing the time series of dynamic speckle patterns. The scaling analysis is applied to the temporal fluctuation of the speckle intensity and also to the two derived data sets generated by its magnitude and sign. The application of the method is illustrated by analyzing paint-drying processes and bruising in apples. The results are discussed taking into account the different time organizations obtained for the scaling behavior of the magnitude and the sign of the intensity fluctuation.

Spatio-temporal diffusion pattern and hotspot detection of dengue in Chachoengsao province, Thailand.

PubMed

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

2011-01-01

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

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

Predicting and controlling infectious disease epidemics using temporal networks

PubMed Central

Holme, Petter

2013-01-01

Infectious diseases can be considered to spread over social networks of people or animals. Mainly owing to the development of data recording and analysis techniques, an increasing amount of social contact data with time stamps has been collected in the last decade. Such temporal data capture the dynamics of social networks on a timescale relevant to epidemic spreading and can potentially lead to better ways to analyze, forecast, and prevent epidemics. However, they also call for extended analysis tools for network epidemiology, which has, to date, mostly viewed networks as static entities. We review recent results of network epidemiology for such temporal network data and discuss future developments. PMID:23513178

Predicting and controlling infectious disease epidemics using temporal networks.

PubMed

Masuda, Naoki; Holme, Petter

2013-01-01

Infectious diseases can be considered to spread over social networks of people or animals. Mainly owing to the development of data recording and analysis techniques, an increasing amount of social contact data with time stamps has been collected in the last decade. Such temporal data capture the dynamics of social networks on a timescale relevant to epidemic spreading and can potentially lead to better ways to analyze, forecast, and prevent epidemics. However, they also call for extended analysis tools for network epidemiology, which has, to date, mostly viewed networks as static entities. We review recent results of network epidemiology for such temporal network data and discuss future developments.

Temporal Response Properties of Accessory Olfactory Bulb Neurons: Limitations and Opportunities for Decoding.

PubMed

Yoles-Frenkel, Michal; Kahan, Anat; Ben-Shaul, Yoram

2018-05-23

The vomeronasal system (VNS) is a major vertebrate chemosensory system that functions in parallel to the main olfactory system (MOS). Despite many similarities, the two systems dramatically differ in the temporal domain. While MOS responses are governed by breathing and follow a subsecond temporal scale, VNS responses are uncoupled from breathing and evolve over seconds. This suggests that the contribution of response dynamics to stimulus information will differ between these systems. While temporal dynamics in the MOS are widely investigated, similar analyses in the accessory olfactory bulb (AOB) are lacking. Here, we have addressed this issue using controlled stimulus delivery to the vomeronasal organ of male and female mice. We first analyzed the temporal properties of AOB projection neurons and demonstrated that neurons display prolonged, variable, and neuron-specific characteristics. We then analyzed various decoding schemes using AOB population responses. We showed that compared with the simplest scheme (i.e., integration of spike counts over the entire response period), the division of this period into smaller temporal bins actually yields poorer decoding accuracy. However, optimal classification accuracy can be achieved well before the end of the response period by integrating spike counts within temporally defined windows. Since VNS stimulus uptake is variable, we analyzed decoding using limited information about stimulus uptake time, and showed that with enough neurons, such time-invariant decoding is feasible. Finally, we conducted simulations that demonstrated that, unlike the main olfactory bulb, the temporal features of AOB neurons disfavor decoding with high temporal accuracy, and, rather, support decoding without precise knowledge of stimulus uptake time. SIGNIFICANCE STATEMENT A key goal in sensory system research is to identify which metrics of neuronal activity are relevant for decoding stimulus features. Here, we describe the first systematic analysis of temporal coding in the vomeronasal system (VNS), a chemosensory system devoted to socially relevant cues. Compared with the main olfactory system, timescales of VNS function are inherently slower and variable. Using various analyses of real and simulated data, we show that the consideration of response times relative to stimulus uptake can aid the decoding of stimulus information from neuronal activity. However, response properties of accessory olfactory bulb neurons favor decoding schemes that do not rely on the precise timing of stimulus uptake. Such schemes are consistent with the variable nature of VNS stimulus uptake. Copyright © 2018 the authors 0270-6474/18/384957-20$15.00/0.

Global Genetic Response in a Cancer Cell: Self-Organized Coherent Expression Dynamics

PubMed Central

Tsuchiya, Masa; Hashimoto, Midori; Takenaka, Yoshiko; Motoike, Ikuko N.; Yoshikawa, Kenichi

2014-01-01

Understanding the basic mechanism of the spatio-temporal self-control of genome-wide gene expression engaged with the complex epigenetic molecular assembly is one of major challenges in current biological science. In this study, the genome-wide dynamical profile of gene expression was analyzed for MCF-7 breast cancer cells induced by two distinct ErbB receptor ligands: epidermal growth factor (EGF) and heregulin (HRG), which drive cell proliferation and differentiation, respectively. We focused our attention to elucidate how global genetic responses emerge and to decipher what is an underlying principle for dynamic self-control of genome-wide gene expression. The whole mRNA expression was classified into about a hundred groups according to the root mean square fluctuation (rmsf). These expression groups showed characteristic time-dependent correlations, indicating the existence of collective behaviors on the ensemble of genes with respect to mRNA expression and also to temporal changes in expression. All-or-none responses were observed for HRG and EGF (biphasic statistics) at around 10–20 min. The emergence of time-dependent collective behaviors of expression occurred through bifurcation of a coherent expression state (CES). In the ensemble of mRNA expression, the self-organized CESs reveals distinct characteristic expression domains for biphasic statistics, which exhibits notably the presence of criticality in the expression profile as a route for genomic transition. In time-dependent changes in the expression domains, the dynamics of CES reveals that the temporal development of the characteristic domains is characterized as autonomous bistable switch, which exhibits dynamic criticality (the temporal development of criticality) in the genome-wide coherent expression dynamics. It is expected that elucidation of the biophysical origin for such critical behavior sheds light on the underlying mechanism of the control of whole genome. PMID:24831017

Analyzing neuronal networks using discrete-time dynamics

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Smith, Brian H.; Borisyuk, Alla; Terman, David

2010-05-01

We develop mathematical techniques for analyzing detailed Hodgkin-Huxley like models for excitatory-inhibitory neuronal networks. Our strategy for studying a given network is to first reduce it to a discrete-time dynamical system. The discrete model is considerably easier to analyze, both mathematically and computationally, and parameters in the discrete model correspond directly to parameters in the original system of differential equations. While these networks arise in many important applications, a primary focus of this paper is to better understand mechanisms that underlie temporally dynamic responses in early processing of olfactory sensory information. The models presented here exhibit several properties that have been described for olfactory codes in an insect’s Antennal Lobe. These include transient patterns of synchronization and decorrelation of sensory inputs. By reducing the model to a discrete system, we are able to systematically study how properties of the dynamics, including the complex structure of the transients and attractors, depend on factors related to connectivity and the intrinsic and synaptic properties of cells within the network.

[Wave-type time series variation of the correlation between NDVI and climatic factors].

PubMed

Bi, Xiaoli; Wang, Hui; Ge, Jianping

2005-02-01

Based on the 1992-1996 data of 1 km monthly NDVI and those of the monthly precipitation and mean temperature collected by 400 standard meteorological stations in China, this paper analyzed the temporal and spatial dynamic changes of the correlation between NDVI and climatic factors in different climate districts of this country. The results showed that there was a significant correlation between monthly precipitations and NDVI. The wave-type time series model could simulate well the temporal dynamic changes of the correlation between NDVI and climatic factors, and the simulated results of the correlation between NDVI and precipitation was better than that between NDVI and temperature. The correlation coefficients (R2) were 0.91 and 0.86, respectively for the whole country.

Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China.

PubMed

Cao, Chunxiang; Chen, Wei; Zheng, Sheng; Zhao, Jian; Wang, Jinfeng; Cao, Wuchun

2016-01-01

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases.

Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China

PubMed Central

Cao, Chunxiang; Zheng, Sheng; Zhao, Jian; Wang, Jinfeng; Cao, Wuchun

2016-01-01

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases. PMID:27597972

Quantitative Spatial and Temporal Analysis of Fluorescein Angiography Dynamics in the Eye

PubMed Central

Hui, Flora; Nguyen, Christine T. O.; Bedggood, Phillip A.; He, Zheng; Fish, Rebecca L.; Gurrell, Rachel; Vingrys, Algis J.; Bui, Bang V.

2014-01-01

Purpose We describe a novel approach to analyze fluorescein angiography to investigate fluorescein flow dynamics in the rat posterior retina as well as identify abnormal areas following laser photocoagulation. Methods Experiments were undertaken in adult Long Evans rats. Using a rodent retinal camera, videos were acquired at 30 frames per second for 30 seconds following intravenous introduction of sodium fluorescein in a group of control animals (n = 14). Videos were image registered and analyzed using principle components analysis across all pixels in the field. This returns fluorescence intensity profiles from which, the half-rise (time to 50% brightness), half-fall (time for 50% decay) back to an offset (plateau level of fluorescence). We applied this analysis to video fluorescein angiography data collected 30 minutes following laser photocoagulation in a separate group of rats (n = 7). Results Pixel-by-pixel analysis of video angiography clearly delineates differences in the temporal profiles of arteries, veins and capillaries in the posterior retina. We find no difference in half-rise, half-fall or offset amongst the four quadrants (inferior, nasal, superior, temporal). We also found little difference with eccentricity. By expressing the parameters at each pixel as a function of the number of standard deviation from the average of the entire field, we could clearly identify the spatial extent of the laser injury. Conclusions This simple registration and analysis provides a way to monitor the size of vascular injury, to highlight areas of subtle vascular leakage and to quantify vascular dynamics not possible using current fluorescein angiography approaches. This can be applied in both laboratory and clinical settings for in vivo dynamic fluorescent imaging of vasculature. PMID:25365578

Computational dynamic approaches for temporal omics data with applications to systems medicine.

PubMed

Liang, Yulan; Kelemen, Arpad

2017-01-01

Modeling and predicting biological dynamic systems and simultaneously estimating the kinetic structural and functional parameters are extremely important in systems and computational biology. This is key for understanding the complexity of the human health, drug response, disease susceptibility and pathogenesis for systems medicine. Temporal omics data used to measure the dynamic biological systems are essentials to discover complex biological interactions and clinical mechanism and causations. However, the delineation of the possible associations and causalities of genes, proteins, metabolites, cells and other biological entities from high throughput time course omics data is challenging for which conventional experimental techniques are not suited in the big omics era. In this paper, we present various recently developed dynamic trajectory and causal network approaches for temporal omics data, which are extremely useful for those researchers who want to start working in this challenging research area. Moreover, applications to various biological systems, health conditions and disease status, and examples that summarize the state-of-the art performances depending on different specific mining tasks are presented. We critically discuss the merits, drawbacks and limitations of the approaches, and the associated main challenges for the years ahead. The most recent computing tools and software to analyze specific problem type, associated platform resources, and other potentials for the dynamic trajectory and interaction methods are also presented and discussed in detail.

Spatiotemporal dynamics of Puumala hantavirus associated with its rodent host, Myodes glareolus

PubMed Central

Weber de Melo, Vanessa; Sheikh Ali, Hanan; Freise, Jona; Kühnert, Denise; Essbauer, Sandra; Mertens, Marc; Wanka, Konrad M; Drewes, Stephan; Ulrich, Rainer G; Heckel, Gerald

2015-01-01

Many viruses significantly impact human and animal health. Understanding the population dynamics of these viruses and their hosts can provide important insights for epidemiology and virus evolution. Puumala virus (PUUV) is a European hantavirus that may cause regional outbreaks of hemorrhagic fever with renal syndrome in humans. Here, we analyzed the spatiotemporal dynamics of PUUV circulating in local populations of its rodent reservoir host, the bank vole (Myodes glareolus) during eight years. Phylogenetic and population genetic analyses of all three genome segments of PUUV showed strong geographical structuring at a very local scale. There was a high temporal turnover of virus strains in the local bank vole populations, but several virus strains persisted through multiple years. Phylodynamic analyses showed no significant changes in the local effective population sizes of PUUV, although vole numbers and virus prevalence fluctuated widely. Microsatellite data demonstrated also a temporally persisting subdivision between local vole populations, but these groups did not correspond to the subdivision in the virus strains. We conclude that restricted transmission between vole populations and genetic drift play important roles in shaping the genetic structure and temporal dynamics of PUUV in its natural host which has several implications for zoonotic risks of the human population. PMID:26136821

Analyzing Group Coordination when Solving Geometry Problems with Dynamic Geometry Software

ERIC Educational Resources Information Center

Oner, Diler

2013-01-01

In CSCL research, collaborative activity is conceptualized along various yet intertwined dimensions. When functioning within these multiple dimensions, participants make use of several resources, which can be social or content-related (and sometimes temporal) in nature. It is the effective coordination of these resources that appears to…

Resting state networks in empirical and simulated dynamic functional connectivity.

PubMed

Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2017-10-01

It is well-established that patterns of functional connectivity (FC) - measures of correlated activity between pairs of voxels or regions observed in the human brain using neuroimaging - are robustly expressed in spontaneous activity during rest. These patterns are not static, but exhibit complex spatio-temporal dynamics. Over the last years, a multitude of methods have been proposed to reveal these dynamics on the level of the whole brain. One finding is that the brain transitions through different FC configurations over time, and substantial effort has been put into characterizing these configurations. However, the dynamics governing these transitions are more elusive, specifically, the contribution of stationary vs. non-stationary dynamics is an active field of inquiry. In this study, we use a whole-brain approach, considering FC dynamics between 66 ROIs covering the entire cortex. We combine an innovative dimensionality reduction technique, tensor decomposition, with a mean field model which possesses stationary dynamics. It has been shown to explain resting state FC averaged over time and multiple subjects, however, this average FC summarizes the spatial distribution of correlations while hiding their temporal dynamics. First, we apply tensor decomposition to resting state scans from 24 healthy controls in order to characterize spatio-temporal dynamics present in the data. We simultaneously utilize temporal and spatial information by creating tensors that are subsequently decomposed into sets of brain regions ("communities") that share similar temporal dynamics, and their associated time courses. The tensors contain pairwise FC computed inside of overlapping sliding windows. Communities are discovered by clustering features pooled from all subjects, thereby ensuring that they generalize. We find that, on the group level, the data give rise to four distinct communities that resemble known resting state networks (RSNs): default mode network, visual network, control networks, and somatomotor network. Second, we simulate data with our stationary mean field model whose nodes are connected according to results from DTI and fiber tracking. In this model, all spatio-temporal structure is due to noisy fluctuations around the average FC. We analyze the simulated data in the same way as the empirical data in order to determine whether stationary dynamics can explain the emergence of distinct FC patterns (RSNs) which have their own time courses. We find that this is the case for all four networks using the spatio-temporal information revealed by tensor decomposition if nodes in the simulation are connected according to model-based effective connectivity. Furthermore, we find that these results require only a small part of the FC values, namely the highest values that occur across time and ROI pair. Our findings show that stationary dynamics can account for the emergence of RSNs. We provide an innovative method that does not make strong assumptions about the underlying data and is generally applicable to resting state or task data from different subject populations. Copyright © 2017 Elsevier Inc. All rights reserved.

Investigation of Portevin-Le Chatelier band with temporal phase analysis of speckle interferometry

NASA Astrophysics Data System (ADS)

Jiang, Zhenyu; Zhang, Qingchuan; Wu, Xiaoping

2003-04-01

A new method combining temporal phase analysis with dynamic digital speckle pattern interferometry is proposed to study Portevin-Le Chatelier effect quantitatively. The principle bases on that the phase difference of interference speckle patterns is a time-dependent function related to the object deformation. The interference speckle patterns of specimen are recorded with high sampling rate while PLC effect occurs, and the 2D displacement map of PLC band and its width are obtained by analyzing the displacement of specimen with proposed method.

Spatiotemporal Dynamics of Bumblebees Foraging under Predation Risk

NASA Astrophysics Data System (ADS)

Lenz, Friedrich; Ings, Thomas C.; Chittka, Lars; Chechkin, Aleksei V.; Klages, Rainer

2012-03-01

We analyze 3D flight paths of bumblebees searching for nectar in a laboratory experiment with and without predation risk from artificial spiders. For the flight velocities we find mixed probability distributions reflecting the access to the food sources while the threat posed by the spiders shows up only in the velocity correlations. The bumblebees thus adjust their flight patterns spatially to the environment and temporally to predation risk. Key information on response to environmental changes is contained in temporal correlation functions, as we explain by a simple emergent model.

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

Temporal dynamics and impact of event interactions in cyber-social populations

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qing; Li, Xiang

2013-03-01

The advance of information technologies provides powerful measures to digitize social interactions and facilitate quantitative investigations. To explore large-scale indoor interactions of a social population, we analyze 18 715 users' Wi-Fi access logs recorded in a Chinese university campus during 3 months, and define event interaction (EI) to characterize the concurrent interactions of multiple users inferred by their geographic coincidences—co-locating in the same small region at the same time. We propose three rules to construct a transmission graph, which depicts the topological and temporal features of event interactions. The vertex dynamics of transmission graph tells that the active durations of EIs fall into the truncated power-law distributions, which is independent on the number of involved individuals. The edge dynamics of transmission graph reports that the transmission durations present a truncated power-law pattern independent on the daily and weekly periodicities. Besides, in the aggregated transmission graph, low-degree vertices previously neglected in the aggregated static networks may participate in the large-degree EIs, which is verified by three data sets covering different sizes of social populations with various rendezvouses. This work highlights the temporal significance of event interactions in cyber-social populations.

Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors

PubMed Central

Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming

2007-01-01

Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359

Human dynamics of spending: Longitudinal study of a coalition loyalty program

NASA Astrophysics Data System (ADS)

Yi, Il Gu; Jeong, Hyang Min; Choi, Woosuk; Jang, Seungkwon; Lee, Heejin; Kim, Beom Jun

2014-09-01

Large-scale data of a coalition loyalty program is analyzed in terms of the temporal dynamics of customers' behaviors. We report that the two main activities of a loyalty program, earning and redemption of points, exhibit very different behaviors. It is also found that as customers become older from their early 20's, both male and female customers increase their earning and redemption activities until they arrive at the turning points, beyond which both activities decrease. The positions of turning points as well as the maximum earned and redeemed points are found to differ for males and females. On top of these temporal behaviors, we identify that there exists a learning effect and customers learn how to earn and redeem points as their experiences accumulate in time.

Neural dynamics in Parkinsonian brain: The boundary between synchronized and nonsynchronized dynamics

NASA Astrophysics Data System (ADS)

Park, Choongseok; Worth, Robert M.; Rubchinsky, Leonid L.

2011-04-01

Synchronous oscillatory dynamics is frequently observed in the human brain. We analyze the fine temporal structure of phase-locking in a realistic network model and match it with the experimental data from Parkinsonian patients. We show that the experimentally observed intermittent synchrony can be generated just by moderately increased coupling strength in the basal ganglia circuits due to the lack of dopamine. Comparison of the experimental and modeling data suggest that brain activity in Parkinson's disease resides in the large boundary region between synchronized and nonsynchronized dynamics. Being on the edge of synchrony may allow for easy formation of transient neuronal assemblies.

Dynamic factor analysis of long-term growth trends of the intertidal seagrass Thalassia hemprichii in southern Taiwan

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Lin, Hsing-Juh

2010-01-01

We examined environmental factors which are most responsible for the 8-year temporal dynamics of the intertidal seagrass Thalassia hemprichii in southern Taiwan. A dynamic factor analysis (DFA), a dimension-reduction technique, was applied to identify common trends in a multivariate time series and the relationships between this series and interacting environmental variables. The results of dynamic factor models (DFMs) showed that the leaf growth rate of the seagrass was mainly influenced by salinity (Sal), tidal range (TR), turbidity ( K), and a common trend representing an unexplained variability in the observed time series. Sal was the primary variable that explained the temporal dynamics of the leaf growth rate compared to TR and K. K and TR had larger influences on the leaf growth rate in low- than in high-elevation beds. In addition to K, TR, and Sal, UV-B radiation (UV-B), sediment depth (SD), and a common trend accounted for long-term temporal variations of the above-ground biomass. Thus, K, TR, Sal, UV-B, and SD are the predominant environmental variables that described temporal growth variations of the intertidal seagrass T. hemprichii in southern Taiwan. In addition to environmental variables, human activities may be contributing to negative impacts on the seagrass beds; this human interference may have been responsible for the unexplained common trend in the DFMs. Due to successfully applying the DFA to analyze complicated ecological and environmental data in this study, important environmental variables and impacts of human activities along the coast should be taken into account when managing a coastal environment for the conservation of intertidal seagrass beds.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2009-07-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Spatial and temporal variability in minimum temperature trends in the western U.S. sagebrush steppe

USDA-ARS?s Scientific Manuscript database

Climate is a major driver of ecosystem dynamics. In recent years there has been considerable interest in future climate change and potential impacts on ecosystems and management options. In this paper, we analyzed minimum monthly temperature (T min) for ten rural locations in the western sagebrush...

To Tip or Not to Tip: The Case of the Congo Basin Rainforest Realm

NASA Astrophysics Data System (ADS)

Pietsch, S.; Bednar, J. E.; Fath, B. D.; Winter, P. A.

2017-12-01

The future response of the Congo basin rainforest, the second largest tropical carbon reservoir, to climate change is still under debate. Different Climate projections exist stating increase and decrease in rainfall and different changes in rainfall patterns. Within this study we assess all options of climate change possibilities to define the climatic thresholds of Congo basin rainforest stability and assess the limiting conditions for rainforest persistence. We use field data from 199 research plots from the Western Congo basin to calibrate and validate a complex BioGeoChemistry model (BGC-MAN) and assess model performance against an array of possible future climates. Next, we analyze the reasons for the occurrence of tipping points, their spatial and temporal probability of occurrence, will present effects of hysteresis and derive probabilistic spatial-temporal resilience landscapes for the region. Additionally, we will analyze attractors of forest growth dynamics and assess common linear measures for early warning signals of sudden shifts in system dynamics for their robustness in the context of the Congo Basin case, and introduce the correlation integral as a nonlinear measure of risk assessment.

A generalized procedure for analyzing sustained and dynamic vocal fold vibrations from laryngeal high-speed videos using phonovibrograms.

PubMed

Unger, Jakob; Schuster, Maria; Hecker, Dietmar J; Schick, Bernhard; Lohscheller, Jörg

2016-01-01

This work presents a computer-based approach to analyze the two-dimensional vocal fold dynamics of endoscopic high-speed videos, and constitutes an extension and generalization of a previously proposed wavelet-based procedure. While most approaches aim for analyzing sustained phonation conditions, the proposed method allows for a clinically adequate analysis of both dynamic as well as sustained phonation paradigms. The analysis procedure is based on a spatio-temporal visualization technique, the phonovibrogram, that facilitates the documentation of the visible laryngeal dynamics. From the phonovibrogram, a low-dimensional set of features is computed using a principle component analysis strategy that quantifies the type of vibration patterns, irregularity, lateral symmetry and synchronicity, as a function of time. Two different test bench data sets are used to validate the approach: (I) 150 healthy and pathologic subjects examined during sustained phonation. (II) 20 healthy and pathologic subjects that were examined twice: during sustained phonation and a glissando from a low to a higher fundamental frequency. In order to assess the discriminative power of the extracted features, a Support Vector Machine is trained to distinguish between physiologic and pathologic vibrations. The results for sustained phonation sequences are compared to the previous approach. Finally, the classification performance of the stationary analyzing procedure is compared to the transient analysis of the glissando maneuver. For the first test bench the proposed procedure outperformed the previous approach (proposed feature set: accuracy: 91.3%, sensitivity: 80%, specificity: 97%, previous approach: accuracy: 89.3%, sensitivity: 76%, specificity: 96%). Comparing the classification performance of the second test bench further corroborates that analyzing transient paradigms provides clear additional diagnostic value (glissando maneuver: accuracy: 90%, sensitivity: 100%, specificity: 80%, sustained phonation: accuracy: 75%, sensitivity: 80%, specificity: 70%). The incorporation of parameters describing the temporal evolvement of vocal fold vibration clearly improves the automatic identification of pathologic vibration patterns. Furthermore, incorporating a dynamic phonation paradigm provides additional valuable information about the underlying laryngeal dynamics that cannot be derived from sustained conditions. The proposed generalized approach provides a better overall classification performance than the previous approach, and hence constitutes a new advantageous tool for an improved clinical diagnosis of voice disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

High resolution mapping of riffle-pool dynamics based on ADCP and close-range remote sensing data

NASA Astrophysics Data System (ADS)

Salmela, Jouni; Kasvi, Elina; Alho, Petteri

2017-04-01

Present development of mobile laser scanning (MLS) and close-range photogrammetry with unmanned aerial vehicle (UAV) enable us to create seamless digital elevation models (DEMs) of the riverine environment. Remote-controlled flow measurement platforms have also improved spatio-temporal resolution of the flow field data. In this study, acoustic Doppler current profiler (ADCP) attached to remote-controlled mini-boat, UAV-based bathymetry and MLS techniques were utilized to create the high-resolution DEMs of the river channel. These high-resolution measurements can be used in many fluvial applications such as computational fluid dynamics, channel change detection, habitat mapping or hydro-electric power plant planning. In this study we aim: 1) to analyze morphological changes of river channel especially riffle and pool formations based on fine-scale DEMs and ADCP measurements, 2) to analyze flow fields and their effect on morphological changes. The interest was mainly focused on reach-scale riffle-pool dynamics within two-year period of 2013 and 2014. The study was performed in sub-arctic meandering Pulmankijoki River located in Northern Finland. The river itself has shallow and clear water and sandy bed sediment. Discharge remains typically below 10 m3s-1 most of the year but during snow melt period in spring the discharge may exceed 70 m3s-1. We compared DEMs and ADCP measurements to understand both magnitude and spatio-temporal change of the river bed. Models were accurate enough to study bed form changes and locations and persistence of riffles and pools. We analyzed their locations with relation to flow during the peak and low discharge. Our demonstrated method has improved significantly spatio-temporal resolution of riverine DEMs compared to other cross-sectional and photogrammetry based models. Together with flow field measurements we gained better understanding of riverbed-water interaction

Dynamic mode decomposition for plasma diagnostics and validation.

PubMed

Taylor, Roy; Kutz, J Nathan; Morgan, Kyle; Nelson, Brian A

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Dynamic mode decomposition for plasma diagnostics and validation

NASA Astrophysics Data System (ADS)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Towards the utilization of EEG as a brain imaging tool.

PubMed

Michel, Christoph M; Murray, Micah M

2012-06-01

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications. Copyright © 2011 Elsevier Inc. All rights reserved.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries.

PubMed

Rogers, Lauren A; Schindler, Daniel E; Lisi, Peter J; Holtgrieve, Gordon W; Leavitt, Peter R; Bunting, Lynda; Finney, Bruce P; Selbie, Daniel T; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J; Walsh, Patrick B

2013-01-29

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries

PubMed Central

Rogers, Lauren A.; Schindler, Daniel E.; Lisi, Peter J.; Holtgrieve, Gordon W.; Leavitt, Peter R.; Bunting, Lynda; Finney, Bruce P.; Selbie, Daniel T.; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J.; Walsh, Patrick B.

2013-01-01

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems. PMID:23322737

Dynamic strain aging and plastic instabilities

NASA Astrophysics Data System (ADS)

Mesarovic, Sinisa Dj.

1995-05-01

A constitutive model proposed by McCormick [(1988) Theory of flow localization due to dynamic strain ageing. Acta. Metall.36, 3061-3067] based on dislocation-solute interaction and describing dynamic strain aging behavior, is analyzed for the simple loading case of uniaxial tension. The model is rate dependent and includes a time-varying state variable, representing the local concentration of the impurity atoms at dislocations. Stability of the system and its post-instability behavior are considered. The methods used include analytical and numerical stability and bifurcation analysis with a numerical continuation technique. Yield point behavior and serrated yielding are found to result for well defined intervals of temperature and strain rate. Serrated yielding emerges as a branch of periodic solutions of the relaxation oscillation type, similar to frictional stick-slip. The distinction between the temporal and spatial (loss of homogeneity of strain) instability is emphasized. It is found that a critical machine stiffness exists above which a purely temporal instability cannot occur. The results are compared to the available experimental data.

Visibility graphlet approach to chaotic time series

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mutua, Stephen; Computer Science Department, Masinde Muliro University of Science and Technology, P.O. Box 190-50100, Kakamega; Gu, Changgui, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn

Many novel methods have been proposed for mapping time series into complex networks. Although some dynamical behaviors can be effectively captured by existing approaches, the preservation and tracking of the temporal behaviors of a chaotic system remains an open problem. In this work, we extended the visibility graphlet approach to investigate both discrete and continuous chaotic time series. We applied visibility graphlets to capture the reconstructed local states, so that each is treated as a node and tracked downstream to create a temporal chain link. Our empirical findings show that the approach accurately captures the dynamical properties of chaotic systems.more » Networks constructed from periodic dynamic phases all converge to regular networks and to unique network structures for each model in the chaotic zones. Furthermore, our results show that the characterization of chaotic and non-chaotic zones in the Lorenz system corresponds to the maximal Lyapunov exponent, thus providing a simple and straightforward way to analyze chaotic systems.« less

Experimental and theoretical investigation of radiation and dynamics properties in laser-produced carbon plasmas

NASA Astrophysics Data System (ADS)

Min, Qi; Su, Maogen; Wang, Bo; Cao, Shiquan; Sun, Duixiong; Dong, Chenzhong

2018-05-01

The radiation and dynamics properties of laser-produced carbon plasma in vacuum were studied experimentally with aid of a spatio-temporally resolved emission spectroscopy technique. In addition, a radiation hydrodynamics model based on the fluid dynamic equations and the radiative transfer equation was presented, and calculation of the charge states was performed within the time-dependent collisional radiative model. Detailed temporal and spatial evolution behavior about plasma parameters have been analyzed, such as velocity, electron temperature, charge state distribution, energy level population, and various atomic processes. At the same time, the effects of different atomic processes on the charge state distribution were examined. Finally, the validity of assuming a local thermodynamic equilibrium in the carbon plasma expansion was checked, and the results clearly indicate that the assumption was valid only at the initial (<80 ns) stage of plasma expansion. At longer delay times, it was not applicable near the plasma boundary because of a sharp drop of plasma temperature and electron density.

Quasi-dynamic earthquake fault systems with rheological heterogeneity

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

2009-12-01

Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

EYE MOVEMENT RECORDING AND NONLINEAR DYNAMICS ANALYSIS – THE CASE OF SACCADES#

PubMed Central

Aştefănoaei, Corina; Pretegiani, Elena; Optican, L.M.; Creangă, Dorina; Rufa, Alessandra

2015-01-01

Evidence of a chaotic behavioral trend in eye movement dynamics was examined in the case of a saccadic temporal series collected from a healthy human subject. Saccades are highvelocity eye movements of very short duration, their recording being relatively accessible, so that the resulting data series could be studied computationally for understanding the neural processing in a motor system. The aim of this study was to assess the complexity degree in the eye movement dynamics. To do this we analyzed the saccadic temporal series recorded with an infrared camera eye tracker from a healthy human subject in a special experimental arrangement which provides continuous records of eye position, both saccades (eye shifting movements) and fixations (focusing over regions of interest, with rapid, small fluctuations). The semi-quantitative approach used in this paper in studying the eye functioning from the viewpoint of non-linear dynamics was accomplished by some computational tests (power spectrum, portrait in the state space and its fractal dimension, Hurst exponent and largest Lyapunov exponent) derived from chaos theory. A high complexity dynamical trend was found. Lyapunov largest exponent test suggested bi-stability of cellular membrane resting potential during saccadic experiment. PMID:25698889

Impact of Fast Sodium Channel Inactivation on Spike Threshold Dynamics and Synaptic Integration

PubMed Central

Platkiewicz, Jonathan; Brette, Romain

2011-01-01

Neurons spike when their membrane potential exceeds a threshold value. In central neurons, the spike threshold is not constant but depends on the stimulation. Thus, input-output properties of neurons depend both on the effect of presynaptic spikes on the membrane potential and on the dynamics of the spike threshold. Among the possible mechanisms that may modulate the threshold, one strong candidate is Na channel inactivation, because it specifically impacts spike initiation without affecting the membrane potential. We collected voltage-clamp data from the literature and we found, based on a theoretical criterion, that the properties of Na inactivation could indeed cause substantial threshold variability by itself. By analyzing simple neuron models with fast Na inactivation (one channel subtype), we found that the spike threshold is correlated with the mean membrane potential and negatively correlated with the preceding depolarization slope, consistent with experiments. We then analyzed the impact of threshold dynamics on synaptic integration. The difference between the postsynaptic potential (PSP) and the dynamic threshold in response to a presynaptic spike defines an effective PSP. When the neuron is sufficiently depolarized, this effective PSP is briefer than the PSP. This mechanism regulates the temporal window of synaptic integration in an adaptive way. Finally, we discuss the role of other potential mechanisms. Distal spike initiation, channel noise and Na activation dynamics cannot account for the observed negative slope-threshold relationship, while adaptive conductances (e.g. K+) and Na inactivation can. We conclude that Na inactivation is a metabolically efficient mechanism to control the temporal resolution of synaptic integration. PMID:21573200

Complex responses of spring alpine vegetation phenology to snow cover dynamics over the Tibetan Plateau, China.

PubMed

Wang, Siyuan; Wang, Xiaoyue; Chen, Guangsheng; Yang, Qichun; Wang, Bin; Ma, Yuanxu; Shen, Ming

2017-09-01

Snow cover dynamics are considered to play a key role on spring phenological shifts in the high-latitude, so investigating responses of spring phenology to snow cover dynamics is becoming an increasingly important way to identify and predict global ecosystem dynamics. In this study, we quantified the temporal trends and spatial variations of spring phenology and snow cover across the Tibetan Plateau by calibrating and analyzing time series of the NOAA AVHRR-derived normalized difference vegetation index (NDVI) during 1983-2012. We also examined how snow cover dynamics affect the spatio-temporal pattern of spring alpine vegetation phenology over the plateau. Our results indicated that 52.21% of the plateau experienced a significant advancing trend in the beginning of vegetation growing season (BGS) and 34.30% exhibited a delaying trend. Accordingly, the snow cover duration days (SCD) and snow cover melt date (SCM) showed similar patterns with a decreasing trend in the west and an increasing trend in the southeast, but the start date of snow cover (SCS) showed an opposite pattern. Meanwhile, the spatial patterns of the BGS, SCD, SCS and SCM varied in accordance with the gradients of temperature, precipitation and topography across the plateau. The response relationship of spring phenology to snow cover dynamics varied within different climate, terrain and alpine plant community zones, and the spatio-temporal response patterns were primarily controlled by the long-term local heat-water conditions and topographic conditions. Moreover, temperature and precipitation played a profound impact on diverse responses of spring phenology to snow cover dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

Formal analysis of temporal dynamics in anxiety states and traits for virtual patients

NASA Astrophysics Data System (ADS)

Aziz, Azizi Ab; Ahmad, Faudziah; Yusof, Nooraini; Ahmad, Farzana Kabir; Yusof, Shahrul Azmi Mohd

2016-08-01

This paper presents a temporal dynamic model of anxiety states and traits for an individual. Anxiety is a natural part of life, and most of us experience it from time to time. But for some people, anxiety can be extreme. Based on several personal characteristics, traits, and a representation of events (i.e. psychological and physiological stressors), the formal model can represent whether a human that experience certain scenarios will fall into an anxiety states condition. A number of well-known relations between events and the course of anxiety are summarized from the literature and it is shown that the model exhibits those patterns. In addition, the formal model has been mathematically analyzed to find out which stable situations exist. Finally, it is pointed out how this model can be used in therapy, supported by a software agent.

Dissipative gravitational bouncer on a vibrating surface

NASA Astrophysics Data System (ADS)

Espinoza Ortiz, J. S.; Lagos, R. E.

2017-12-01

We study the dynamical behavior of a particle flying under the influence of a gravitational field, with dissipation constant λ (Stokes-like), colliding successive times against a rigid surface vibrating harmonically with restitution coefficient α. We define re-scaled dimensionless dynamical variables, such as the relative particle velocity Ω with respect to the surface’s velocity; and the real parameter τ accounting for the temporal evolution of the system. At the particle-surface contact point and for the k‧th collision, we construct the mapping described by (τk ; Ω k ) in order to analyze the system’s nonlinear dynamical behavior. From the dynamical mapping, the fixed point trajectory is computed and its stability is analyzed. We find the dynamical behavior of the fixed point trajectory to be stable or unstable, depending on the values of the re-scaled vibrating surface amplitude Γ, the restitution coefficient α and the damping constant λ. Other important dynamical aspects such as the phase space volume and the one cycle vibrating surface (decomposed into absorbing and transmitting regions) are also discussed. Furthermore, the model rescues well known results in the limit λ = 0.

Characterizing and modeling the dynamics of online popularity.

PubMed

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.

The attractor dimension of solar decimetric radio pulsations

NASA Technical Reports Server (NTRS)

Kurths, J.; Benz, A. O.; Aschwanden, M. J.

1991-01-01

The temporal characteristics of decimetric pulsations and related radio emissions during solar flares are analyzed using statistical methods recently developed for nonlinear dynamic systems. The results of the analysis is consistent with earlier reports on low-dimensional attractors of such events and yield a quantitative description of their temporal characteristics and hidden order. The estimated dimensions of typical decimetric pulsations are generally in the range of 3.0 + or - 0.5. Quasi-periodic oscillations and sudden reductions may have dimensions as low as 2. Pulsations of decimetric type IV continua have typically a dimension of about 4.

Local orientational mobility in regular hyperbranched polymers.

PubMed

Dolgushev, Maxim; Markelov, Denis A; Fürstenberg, Florian; Guérin, Thomas

2016-07-01

We study the dynamics of local bond orientation in regular hyperbranched polymers modeled by Vicsek fractals. The local dynamics is investigated through the temporal autocorrelation functions of single bonds and the corresponding relaxation forms of the complex dielectric susceptibility. We show that the dynamic behavior of single segments depends on their remoteness from the periphery rather than on the size of the whole macromolecule. Remarkably, the dynamics of the core segments (which are most remote from the periphery) shows a scaling behavior that differs from the dynamics obtained after structural average. We analyze the most relevant processes of single segment motion and provide an analytic approximation for the corresponding relaxation times. Furthermore, we describe an iterative method to calculate the orientational dynamics in the case of very large macromolecular sizes.

Nonlinear dynamics of the magnetosphere and space weather

NASA Technical Reports Server (NTRS)

Sharma, A. Surjalal

1996-01-01

The solar wind-magnetosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity on the dynamics. The observational time series data were used together with phase space reconstruction techniques to analyze the magnetospheric dynamics. Analysis of the solar wind, auroral electrojet and Dst indices showed low dimensionality of the dynamics and accurate prediction can be made with an input/output model. The predictability of the magnetosphere in spite of the apparent complexity arises from its dynamical synchronism with the solar wind. The electrodynamic coupling between different regions of the magnetosphere yields its coherent, low dimensional behavior. The data from multiple satellites and ground stations can be used to develop a spatio-temporal model that identifies the coupling between different regions. These nonlinear dynamical models provide space weather forecasting capabilities.

Two distinct modes of forebrain circuit dynamics underlie temporal patterning in the vocalizations of young songbirds

PubMed Central

Aronov, Dmitriy; Veit, Lena; Goldberg, Jesse H.; Fee, Michale S.

2011-01-01

Accurate timing is a critical aspect of motor control, yet the temporal structure of many mature behaviors emerges during learning from highly variable exploratory actions. How does a developing brain acquire the precise control of timing in behavioral sequences? To investigate the development of timing, we analyzed the songs of young juvenile zebra finches. These highly variable vocalizations, akin to human babbling, gradually develop into temporally-stereotyped adult songs. We find that the durations of syllables and silences in juvenile singing are formed by a mixture of two distinct modes of timing – a random mode producing broadly-distributed durations early in development, and a stereotyped mode underlying the gradual emergence of stereotyped durations. Using lesions, inactivations, and localized brain cooling we investigated the roles of neural dynamics within two premotor cortical areas in the production of these temporal modes. We find that LMAN (lateral magnocellular nucleus of the nidopallium) is required specifically for the generation of the random mode of timing, and that mild cooling of LMAN causes an increase in the durations produced by this mode. On the contrary, HVC (used as a proper name) is required specifically for producing the stereotyped mode of timing, and its cooling causes a slowing of all stereotyped components. These results show that two neural pathways contribute to the timing of juvenile songs, and suggest an interesting organization in the forebrain, whereby different brain areas are specialized for the production of distinct forms of neural dynamics. PMID:22072687

Ecohydrological interfaces as hot spots of ecosystem processes

NASA Astrophysics Data System (ADS)

Krause, Stefan; Lewandowski, Jörg; Grimm, Nancy B.; Hannah, David M.; Pinay, Gilles; McDonald, Karlie; Martí, Eugènia; Argerich, Alba; Pfister, Laurent; Klaus, Julian; Battin, Tom; Larned, Scott T.; Schelker, Jacob; Fleckenstein, Jan; Schmidt, Christian; Rivett, Michael O.; Watts, Glenn; Sabater, Francesc; Sorolla, Albert; Turk, Valentina

2017-08-01

The movement of water, matter, organisms, and energy can be altered substantially at ecohydrological interfaces, the dynamic transition zones that often develop within ecotones or boundaries between adjacent ecosystems. Interdisciplinary research over the last two decades has indicated that ecohydrological interfaces are often "hot spots" of ecological, biogeochemical, and hydrological processes and may provide refuge for biota during extreme events. Ecohydrological interfaces can have significant impact on global hydrological and biogeochemical cycles, biodiversity, pollutant removal, and ecosystem resilience to disturbance. The organizational principles (i.e., the drivers and controls) of spatially and temporally variable processes at ecohydrological interfaces are poorly understood and require the integrated analysis of hydrological, biogeochemical, and ecological processes. Our rudimentary understanding of the interactions between different drivers and controls critically limits our ability to predict complex system responses to change. In this paper, we explore similarities and contrasts in the functioning of diverse freshwater ecohydrological interfaces across spatial and temporal scales. We use this comparison to develop an integrated, interdisciplinary framework, including a roadmap for analyzing ecohydrological processes and their interactions in ecosystems. We argue that, in order to fully account for their nonlinear process dynamics, ecohydrological interfaces need to be conceptualized as unique, spatially and temporally dynamic entities, which represents a step change from their current representation as boundary conditions at investigated ecosystems.

Dynamics of Conflicts in Wikipedia

PubMed Central

Yasseri, Taha; Sumi, Robert; Rung, András; Kornai, András; Kertész, János

2012-01-01

In this work we study the dynamical features of editorial wars in Wikipedia (WP). Based on our previously established algorithm, we build up samples of controversial and peaceful articles and analyze the temporal characteristics of the activity in these samples. On short time scales, we show that there is a clear correspondence between conflict and burstiness of activity patterns, and that memory effects play an important role in controversies. On long time scales, we identify three distinct developmental patterns for the overall behavior of the articles. We are able to distinguish cases eventually leading to consensus from those cases where a compromise is far from achievable. Finally, we analyze discussion networks and conclude that edit wars are mainly fought by few editors only. PMID:22745683

Analysis of absence seizure generation using EEG spatial-temporal regularity measures.

PubMed

Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

2012-12-01

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

Cycles, scaling and crossover phenomenon in length of the day (LOD) time series

NASA Astrophysics Data System (ADS)

Telesca, Luciano

2007-06-01

The dynamics of the temporal fluctuations of the length of the day (LOD) time series from January 1, 1962 to November 2, 2006 were investigated. The power spectrum of the whole time series has revealed annual, semi-annual, decadal and daily oscillatory behaviors, correlated with oceanic-atmospheric processes and interactions. The scaling behavior was analyzed by using the detrended fluctuation analysis (DFA), which has revealed two different scaling regimes, separated by a crossover timescale at approximately 23 days. Flicker-noise process can describe the dynamics of the LOD time regime involving intermediate and long timescales, while Brownian dynamics characterizes the LOD time series for small timescales.

Use of soil moisture dynamics and patterns for the investigation of runoff generation processes with emphasis on preferential flow

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2007-08-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Monitoring CO2 concentration and δ13C in an underground cavity using a commercial isotope ratio infrared spectrometer

NASA Astrophysics Data System (ADS)

Guillon, Sophie; Agrinier, Pierre; Pili, Éric

2015-04-01

CO2 stable carbon isotopes are very attractive in environmental research to investigate both natural and anthropogenic carbon sources. Laser-based isotope ratio infrared spectrometers (IRIS) allow in situ continuous monitoring of CO2 isotopes, and therefore they have a potential for unprecedented understanding of carbon sources and dynamics with a high temporal resolution. Here we present the performance assessment of a commercial IRIS analyzer, including the measurement setup and the data processing scheme that we used. Even if the analyzer performs 1-Hz measurements, an integration time of the order of 1 h is commonly needed to obtain acceptable precision for δ13C. The main sources of uncertainty on δ13C come from the concentration dependence and from the temporal instability of the analyzer. The method is applied to the in situ monitoring of the CO2 carbon isotopes in an underground cavity (Roselend Natural Laboratory, France) during several months. On a weekly timescale, the temporal variability of CO2 is dominated by transient contamination by human breath. Discarding these anthropogenic contaminations, CO2 and δ13C backgrounds do not show diurnal or seasonal fluctuations. A CO2 flux released into the tunnel by the surrounding rocks is measured. The carbon isotope composition of this CO2, identified with a Keeling plot, is consistent with a main production by microbial respiration and a minor production from weathering of carbonate minerals. The presented instrument and application study are relevant to cave monitoring, whether to understand CO2 dynamics in visited and/or painted caves for preservation purposes or to understand paleoclimate recording in speleothems.

Microsatellite DNA Analysis Revealed a Drastic Genetic Change of Plasmodium vivax Population in the Republic of Korea During 2002 and 2003

PubMed Central

Iwagami, Moritoshi; Hwang, Seung-Young; Kim, So-Hee; Park, So-Jung; Lee, Ga-Young; Matsumoto-Takahashi, Emilie Louise Akiko; Kho, Weon-Gyu; Kano, Shigeyuki

2013-01-01

Background Vivax malaria was successfully eliminated in the Republic of Korea (South Korea) in the late 1970s, but it was found to have re-emerged from 1993. In order to control malaria and evaluate the effectiveness of malaria controls, it is important to develop a spatiotemporal understanding of the genetic structure of the parasite population. Here, we estimated the population structure and temporal dynamics of the transmission of Plasmodium vivax in South Korea by analyzing microsatellite DNA markers of the parasite. Methodology/Principal Findings We analyzed 14 microsatellite DNA loci of the P. vivax genome from 163 South Korean isolates collected from 1994 to 2008. Allelic data were used to analyze linkage disequilibrium (LD), genetic differentiation and population structure, in order to make a detailed estimate of temporal change in the parasite population. The LD analysis showed a gradual decrease in LD levels, while the levels of genetic differentiation between successive years and analysis of the population structure based on the Bayesian approach suggested that a drastic genetic change occurred in the South Korean population during 2002 and 2003. Conclusions/Significance Although relapse and asymptomatic parasite carriage might influence the population structure to some extent, our results suggested the continual introduction of P. vivax into South Korea through other parasite population sources. One possible source, particularly during 2002 and 2003, is North Korea. Molecular epidemiology using microsatellite DNA of the P. vivax population is effective for assessing the population structure and temporal dynamics of parasite transmission; information that can assist in the elimination of vivax malaria in endemic areas. PMID:24205429

Multiple remote sensing data sources to assess spatio-temporal patterns of fire incidence over Campos Amazônicos Savanna Vegetation Enclave (Brazilian Amazon).

PubMed

Alves, Daniel Borini; Pérez-Cabello, Fernando

2017-12-01

Fire activity plays an important role in the past, present and future of Earth system behavior. Monitoring and assessing spatial and temporal fire dynamics have a fundamental relevance in the understanding of ecological processes and the human impacts on different landscapes and multiple spatial scales. This work analyzes the spatio-temporal distribution of burned areas in one of the biggest savanna vegetation enclaves in the southern Brazilian Amazon, from 2000 to 2016, deriving information from multiple remote sensing data sources (Landsat and MODIS surface reflectance, TRMM pluviometry and Vegetation Continuous Field tree cover layers). A fire scars database with 30 m spatial resolution was generated using a Landsat time series. MODIS daily surface reflectance was used for accurate dating of the fire scars. TRMM pluviometry data were analyzed to dynamically establish time limits of the yearly dry season and burning periods. Burned area extent, frequency and recurrence were quantified comparing the results annually/seasonally. Additionally, Vegetation Continuous Field tree cover layers were used to analyze fire incidence over different types of tree cover domains. In the last seventeen years, 1.03millionha were burned within the study area, distributed across 1432 fire occurrences, highlighting 2005, 2010 and 2014 as the most affected years. Middle dry season fires represent 86.21% of the total burned areas and 32.05% of fire occurrences, affecting larger amount of higher density tree surfaces than other burning periods. The results provide new insights into the analysis of burned areas of the neotropical savannas, spatially and statistically reinforcing important aspects linked to the seasonality patterns of fire incidence in this landscape. Copyright © 2017 Elsevier B.V. All rights reserved.

Individual Differences in Temporal Selective Attention as Reflected in Pupil Dilation.

PubMed

Willems, Charlotte; Herdzin, Johannes; Martens, Sander

2015-01-01

Attention is restricted for the second of two targets when it is presented within 200-500 ms of the first target. This attentional blink (AB) phenomenon allows one to study the dynamics of temporal selective attention by varying the interval between the two targets (T1 and T2). Whereas the AB has long been considered as a robust and universal cognitive limitation, several studies have demonstrated that AB task performance greatly differs between individuals, with some individuals showing no AB whatsoever. Here, we studied these individual differences in AB task performance in relation to differences in attentional timing. Furthermore, we investigated whether AB magnitude is predictive for the amount of attention allocated to T1. For both these purposes pupil dilation was measured, and analyzed with our recently developed deconvolution method. We found that the dynamics of temporal attention in small versus large blinkers differ in a number of ways. Individuals with a relatively small AB magnitude seem better able to preserve temporal order information. In addition, they are quicker to allocate attention to both T1 and T2 than large blinkers. Although a popular explanation of the AB is that it is caused by an unnecessary overinvestment of attention allocated to T1, a more complex picture emerged from our data, suggesting that this may depend on whether one is a small or a large blinker. The use of pupil dilation deconvolution seems to be a powerful approach to study the temporal dynamics of attention, bringing us a step closer to understanding the elusive nature of the AB. We conclude that the timing of attention to targets may be more important than the amount of allocated attention in accounting for individual differences.

Identifying Changes of Complex Flood Dynamics with Recurrence Analysis

NASA Astrophysics Data System (ADS)

Wendi, D.; Merz, B.; Marwan, N.

2016-12-01

Temporal changes in flood hazard system are known to be difficult to detect and attribute due to multiple drivers that include complex processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defense, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. Moreover hydrological time series (i.e. discharge) are often subject to measurement errors, such as rating curve error especially in the case of extremes where observation are actually derived through extrapolation. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. Sensitivity of the common measurement errors and noise on recurrence analysis will also be analyzed and evaluated against conventional methods. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic to certain flood events.

The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela.

PubMed

Grillet, María-Eugenia; El Souki, Mayida; Laguna, Francisco; León, José Rafael

2014-01-01

We investigated the periodicity of Plasmodium vivax and P. falciparum incidence in time-series of malaria data (1990-2010) from three endemic regions in Venezuela. In particular, we determined whether disease epidemics were related to local climate variability and regional climate anomalies such as the El Niño Southern Oscillation (ENSO). Malaria periodicity was found to exhibit unique features in each studied region. Significant multi-annual cycles of 2- to about 6-year periods were identified. The inter-annual variability of malaria cases was coherent with that of SSTs (ENSO), mainly at temporal scales within the 3-6 year periods. Additionally, malaria cases were intensified approximately 1 year after an El Niño event, a pattern that highlights the role of climate inter-annual variability in the epidemic patterns. Rainfall mediated the effect of ENSO on malaria locally. Particularly, rains from the last phase of the season had a critical role in the temporal dynamics of Plasmodium. The malaria-climate relationship was complex and transient, varying in strength with the region and species. By identifying temporal cycles of malaria we have made a first step in predicting high-risk years in Venezuela. Our findings emphasize the importance of analyzing high-resolution spatial-temporal data to better understand malaria transmission dynamics. Copyright © 2013 Elsevier B.V. All rights reserved.

Sensitivity to low-temperature events: Implications for CO2 dynamics in subtropical coastal ecosystems

Treesearch

Sparkle L. Malone; Jordan Barr; Jose D. Fuentes; Steven F. Oberbauer; Christina L. Staudhammer; Evelyn E. Gaiser; Gregory Starr

2016-01-01

We analyzed the ecosystem effects of low-temperature events (<5 °C) over 4 years (2009-2012) in subtropical short and long hydroperiod freshwater marsh and mangrove forests within Everglades National Park. To evaluate changes in ecosystem productivity, we measured temporal patterns of CO2 and the normalized difference vegetation index over the study period. Both...

Regional synchroneity in fire regimes of western Oregon and Washington, USA.

Treesearch

P.J. Weisberg; F.J. Swanson

2003-01-01

For much of the world's forested area, the history of fire has significant implications for understanding forest dynamics over stand to regional scales. We analyzed temporal patterns of area burned at 25-year intervals over a 600-year period, using 10 treering-based fire history studies located west of the crest of the Cascade Range in the Pacific Northwest (PNW...

Using Temporal Correlations and Full Distributions to Separate Intrinsic and Extrinsic Fluctuations in Biological Systems

NASA Astrophysics Data System (ADS)

Hilfinger, Andreas; Chen, Mark; Paulsson, Johan

2012-12-01

Studies of stochastic biological dynamics typically compare observed fluctuations to theoretically predicted variances, sometimes after separating the intrinsic randomness of the system from the enslaving influence of changing environments. But variances have been shown to discriminate surprisingly poorly between alternative mechanisms, while for other system properties no approaches exist that rigorously disentangle environmental influences from intrinsic effects. Here, we apply the theory of generalized random walks in random environments to derive exact rules for decomposing time series and higher statistics, rather than just variances. We show for which properties and for which classes of systems intrinsic fluctuations can be analyzed without accounting for extrinsic stochasticity and vice versa. We derive two independent experimental methods to measure the separate noise contributions and show how to use the additional information in temporal correlations to detect multiplicative effects in dynamical systems.

A Multilayer Naïve Bayes Model for Analyzing User's Retweeting Sentiment Tendency.

PubMed

Wang, Mengmeng; Zuo, Wanli; Wang, Ying

2015-01-01

Today microblogging has increasingly become a means of information diffusion via user's retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user's retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to exploit dynamic retweeting sentiment features in retweeting sentiment tendency analysis. On the basis of time series of user's network structure information and published text information, we first model dynamic retweeting sentiment features. Then we build Naïve Bayes models from profile-, relationship-, and emotion-based dimensions, respectively. Finally, we build a multilayer Naïve Bayes model based on multidimensional Naïve Bayes models to analyze user's retweeting sentiment tendency towards a microblog. Experiments on real-world dataset demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of dynamic retweeting sentiment features and temporal information in retweeting sentiment tendency analysis. What is more, we provide a new train of thought for retweeting sentiment tendency analysis in dynamic social networks.

Comprehensive framework for visualizing and analyzing spatio-temporal dynamics of racial diversity in the entire United States

PubMed Central

Netzel, Pawel

2017-01-01

The United States is increasingly becoming a multi-racial society. To understand multiple consequences of this overall trend to our neighborhoods we need a methodology capable of spatio-temporal analysis of racial diversity at the local level but also across the entire U.S. Furthermore, such methodology should be accessible to stakeholders ranging from analysts to decision makers. In this paper we present a comprehensive framework for visualizing and analyzing diversity data that fulfills such requirements. The first component of our framework is a U.S.-wide, multi-year database of race sub-population grids which is freely available for download. These 30 m resolution grids have being developed using dasymetric modeling and are available for 1990-2000-2010. We summarize numerous advantages of gridded population data over commonly used Census tract-aggregated data. Using these grids frees analysts from constructing their own and allows them to focus on diversity analysis. The second component of our framework is a set of U.S.-wide, multi-year diversity maps at 30 m resolution. A diversity map is our product that classifies the gridded population into 39 communities based on their degrees of diversity, dominant race, and population density. It provides spatial information on diversity in a single, easy-to-understand map that can be utilized by analysts and end users alike. Maps based on subsequent Censuses provide information about spatio-temporal dynamics of diversity. Diversity maps are accessible through the GeoWeb application SocScape (http://sil.uc.edu/webapps/socscape_usa/) for an immediate online exploration. The third component of our framework is a proposal to quantitatively analyze diversity maps using a set of landscape metrics. Because of its form, a grid-based diversity map could be thought of as a diversity “landscape” and analyzed quantitatively using landscape metrics. We give a brief summary of most pertinent metrics and demonstrate how they can be applied to diversity maps. PMID:28358862

Interictal Epileptiform Discharges Impair Word Recall in Multiple Brain Areas

PubMed Central

Horak, Peter C.; Meisenhelter, Stephen; Song, Yinchen; Testorf, Markus E.; Kahana, Michael J.; Viles, Weston D.; Bujarski, Krzysztof A.; Connolly, Andrew C.; Robbins, Ashlee A.; Sperling, Michael R.; Sharan, Ashwini D.; Worrell, Gregory A.; Miller, Laura R.; Gross, Robert E.; Davis, Kathryn A.; Roberts, David W.; Lega, Bradley; Sheth, Sameer A.; Zaghloul, Kareem A.; Stein, Joel M.; Das, Sandhitsu R.; Rizzuto, Daniel S.; Jobst, Barbara C.

2016-01-01

Summary Objectives Interictal epileptiform discharges (IEDs) have been linked to memory impairment, but the spatial and temporal dynamics of this relationship remain elusive. In the present study, we aim to systematically characterize the brain areas and times at which IEDs affect memory. Methods Eighty epilepsy patients participated in a delayed free recall task while undergoing intracranial EEG monitoring. We analyzed the locations and timing of IEDs relative to the behavioral data in order to measure their effects on memory. Results Overall IED rates did not correlate with task performance across subjects (r = 0.03, p = 0.8). However, at a finer temporal scale, within-subject memory was negatively affected by IEDs during the encoding and recall periods of the task but not during the rest and distractor periods (p < 0.01, p < 0.001, p = 0.3, and p = 0.8 respectively). The effects of IEDs during encoding and recall were stronger in the left hemisphere than in the right (p < 0.05). Out of six brain areas analyzed, IEDs in the inferior temporal, medial temporal, and parietal areas significantly affected memory (false discovery rate < 0.05). Significance These findings reveal a network of brain areas sensitive to IEDs with key nodes in temporal as well as parietal lobes. They also demonstrate the time-dependent effects of IEDs in this network on memory. PMID:27935031

Inferring the relative resilience of alternative states

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Rojo, Carmen; Alvarez-Cobelas, Miguel; Rodrigo, Maria A.; Sanchez-Carrillo, Salvador

2013-01-01

Ecological systems may occur in alternative states that differ in ecological structures, functions and processes. Resilience is the measure of disturbance an ecological system can absorb before changing states. However, how the intrinsic structures and processes of systems that characterize their states affects their resilience remains unclear. We analyzed time series of phytoplankton communities at three sites in a floodplain in central Spain to assess the dominant frequencies or “temporal scales” in community dynamics and compared the patterns between a wet and a dry alternative state. The identified frequencies and cross-scale structures are expected to arise from positive feedbacks that are thought to reinforce processes in alternative states of ecological systems and regulate emergent phenomena such as resilience. Our analyses show a higher species richness and diversity but lower evenness in the dry state. Time series modeling revealed a decrease in the importance of short-term variability in the communities, suggesting that community dynamics slowed down in the dry relative to the wet state. The number of temporal scales at which community dynamics manifested, and the explanatory power of time series models, was lower in the dry state. The higher diversity, reduced number of temporal scales and the lower explanatory power of time series models suggest that species dynamics tended to be more stochastic in the dry state. From a resilience perspective our results highlight a paradox: increasing species richness may not necessarily enhance resilience. The loss of cross-scale structure (i.e. the lower number of temporal scales) in community dynamics across sites suggests that resilience erodes during drought. Phytoplankton communities in the dry state are therefore likely less resilient than in the wet state. Our case study demonstrates the potential of time series modeling to assess attributes that mediate resilience. The approach is useful for assessing resilience of alternative states across ecological and other complex systems.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

ERIC Educational Resources Information Center

Shen, Jung; Souza, Pamela E.

2017-01-01

Purpose: This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for…

Noise-induced hearing loss alters the temporal dynamics of auditory-nerve responses

PubMed Central

Scheidt, Ryan E.; Kale, Sushrut; Heinz, Michael G.

2010-01-01

Auditory-nerve fibers demonstrate dynamic response properties in that they adapt to rapid changes in sound level, both at the onset and offset of a sound. These dynamic response properties affect temporal coding of stimulus modulations that are perceptually relevant for many sounds such as speech and music. Temporal dynamics have been well characterized in auditory-nerve fibers from normal-hearing animals, but little is known about the effects of sensorineural hearing loss on these dynamics. This study examined the effects of noise-induced hearing loss on the temporal dynamics in auditory-nerve fiber responses from anesthetized chinchillas. Post-stimulus time histograms were computed from responses to 50-ms tones presented at characteristic frequency and 30 dB above fiber threshold. Several response metrics related to temporal dynamics were computed from post-stimulus-time histograms and were compared between normal-hearing and noise-exposed animals. Results indicate that noise-exposed auditory-nerve fibers show significantly reduced response latency, increased onset response and percent adaptation, faster adaptation after onset, and slower recovery after offset. The decrease in response latency only occurred in noise-exposed fibers with significantly reduced frequency selectivity. These changes in temporal dynamics have important implications for temporal envelope coding in hearing-impaired ears, as well as for the design of dynamic compression algorithms for hearing aids. PMID:20696230

Temporal efficiency evaluation and small-worldness characterization in temporal networks

PubMed Central

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-01-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks. PMID:27682314

Temporal efficiency evaluation and small-worldness characterization in temporal networks

NASA Astrophysics Data System (ADS)

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-09-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks.

Temporal dynamics of optical-microphysical characteristics of atmospheric aerosol at the Spitsbergen Archipelago in 2011-2014

NASA Astrophysics Data System (ADS)

Chernov, D. G.; Kozlov, V. S.; Panchenko, M. V.; Turchinovich, Yu. S.; Radionov, V. F.; Gubin, A. V.; Prakhov, A. N.

2015-11-01

In 2011-2014, the Institute of Atmospheric Optics (IAO SB RAS, Tomsk) and the Arctic and Antarctic Research Institute (AARI, St. Petersburg) conducted field investigations of the near-ground aerosol characteristics near Barentsburg (Spitsbergen Archipelago) in the spring and summer seasons. The particle number density in the size range 0.3-20 μm, size distribution of particles, and mass concentrations of aerosol and black carbon were measured round-the-clock every hour with Grimm 1.108 and 1.109; and AZ-10 optical counters. The mass concentration of black carbon was measured by the MDA-02 aethalometer developed by the IAO SB RAS. Series of observations are obtained, annual and seasonal average values and their standard deviations are estimated, and seasonal and annual dynamics of the studied parameters is analyzed. Peculiarities of the temporal dynamics of average values of the aerosol characteristics are revealed and compared with the data of observations at other stations of the Spitsbergen Archipelago and in different regions of the Russian Arctic and Subarctic.

Self-expressive Dictionary Learning for Dynamic 3D Reconstruction.

PubMed

Zheng, Enliang; Ji, Dinghuang; Dunn, Enrique; Frahm, Jan-Michael

2017-08-22

We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information across video sequences. Our proposed compressed sensing framework poses the estimation of 3D structure as the problem of dictionary learning, where the dictionary is defined as an aggregation of the temporally varying 3D structures. Given the smooth motion of dynamic objects, we observe any element in the dictionary can be well approximated by a sparse linear combination of other elements in the same dictionary (i.e. self-expression). Our formulation optimizes a biconvex cost function that leverages a compressed sensing formulation and enforces both structural dependency coherence across video streams, as well as motion smoothness across estimates from common video sources. We further analyze the reconstructability of our approach under different capture scenarios, and its comparison and relation to existing methods. Experimental results on large amounts of synthetic data as well as real imagery demonstrate the effectiveness of our approach.

Impact of cloud timing on surface temperature and related hydroclimatic dynamics

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Yin, J.

2015-12-01

Cloud feedbacks have long been identified as one of the largest source of uncertainty in climate change predictions. Differences in the spatial distribution of clouds and the related impact on surface temperature and climate dynamics have been recently emphasized in quasi-equilibrium General Circulation Models (GCM). However, much less attention has been paid to the temporal variation of cloud presence and thickness. Clouds in fact shade the solar radiation during the daytime, but also acts as greenhouse gas to reduce the emission of longwave radiation to the outer space anytime of the day. Thus it is logical to expect that even small differences in timing and thickness of clouds could result in very different predictions in GCMs. In this study, these two effects of cloud dynamics are analyzed by tracking the cloud impacts on longwave and shortwave radiation in a minimalist transient thermal balance model of the land surface. The marked changes in surface temperature due to alterations in the timing of onset of clouds demonstrate that capturing temporal variation of cloud at sub-daily scale should be a priority in cloud parameterization schemes in GCMs.

Ikeda-like chaos on a dynamically filtered supercontinuum light source

NASA Astrophysics Data System (ADS)

Chembo, Yanne K.; Jacquot, Maxime; Dudley, John M.; Larger, Laurent

2016-08-01

We demonstrate temporal chaos in a color-selection mechanism from the visible spectrum of a supercontinuum light source. The color-selection mechanism is governed by an acousto-optoelectronic nonlinear delayed-feedback scheme modeled by an Ikeda-like equation. Initially motivated by the design of a broad audience live demonstrator in the framework of the International Year of Light 2015, the setup also provides a different experimental tool to investigate the dynamical complexity of delayed-feedback dynamics. Deterministic hyperchaos is analyzed here from the experimental time series. A projection method identifies the delay parameter, for which the chaotic strange attractor originally evolving in an infinite-dimensional phase space can be revealed in a two-dimensional subspace.

Unveiling causal activity of complex networks

NASA Astrophysics Data System (ADS)

Williams-García, Rashid V.; Beggs, John M.; Ortiz, Gerardo

2017-07-01

We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs), to be separated from other non-causally-related events. This tool shows that traditionally-conceived avalanches may contain mixtures of spatially-distinct but temporally-overlapping cascades of events, and dynamical disorder or noise. In contrast, c-webs separate these components, unveiling previously hidden features of the network and dynamics. We apply our method to mouse cortical data with resulting statistics which demonstrate for the first time that neuronal avalanches are not merely composed of causally-related events. The original version of this article was uploaded to the arXiv on March 17th, 2016 [1].

Orientation dependent modulation of apparent speed: a model based on the dynamics of feed-forward and horizontal connectivity in V1 cortex.

PubMed

Seriès, Peggy; Georges, Sébastien; Lorenceau, Jean; Frégnac, Yves

2002-11-01

Psychophysical and physiological studies suggest that long-range horizontal connections in primary visual cortex participate in spatial integration and contour processing. Until recently, little attention has been paid to their intrinsic temporal properties. Recent physiological studies indicate, however, that the propagation of activity through long-range horizontal connections is slow, with time scales comparable to the perceptual scales involved in motion processing. Using a simple model of V1 connectivity, we explore some of the implications of this slow dynamics. The model predicts that V1 responses to a stimulus in the receptive field can be modulated by a previous stimulation, a few milliseconds to a few tens of milliseconds before, in the surround. We analyze this phenomenon and its possible consequences on speed perception, as a function of the spatio-temporal configuration of the visual inputs (relative orientation, spatial separation, temporal interval between the elements, sequence speed). We show that the dynamical interactions between feed-forward and horizontal signals in V1 can explain why the perceived speed of fast apparent motion sequences strongly depends on the orientation of their elements relative to the motion axis and can account for the range of speed for which this perceptual effect occurs (Georges, Seriès, Frégnac and Lorenceau, this issue).

Digital characterization of a neuromorphic IRFPA

NASA Astrophysics Data System (ADS)

Caulfield, John T.; Fisher, John; Zadnik, Jerome A.; Mak, Ernest S.; Scribner, Dean A.

1995-05-01

This paper reports on the performance of the Neuromorphic IRFPA, the first IRFPA designed and fabricated to conduct temporal and spatial processing on the focal plane. The Neuromorphic IRFPA's unique on-chip processing capability can perform retina-like functions such as lateral inhibition and contrast enhancement, spatial and temporal filtering, image compression and edge enhancement, and logarithmic response. Previously, all evaluations of the Neuromorphic IRFPA camera have been performed on the analog video output. In the work leading up to this paper, the Neuromorphic was integrated to a digital recorder to collect quantitative laboratory and field data. This paper describes the operation and characterization of specific on-chip processes such as spatial and temporal kernel size control. The use of Neuromorphic on-chip processing in future IRFPAs is analyzed as applied to improving SNR via adaptive nonuniformity, charge handling, and dynamic range problems.

Analysis of Dynamic Characteristics of the 21st Century Maritime Silk Road

NASA Astrophysics Data System (ADS)

Zhang, Xudong; Zhang, Jie; Fan, Chenqing; Meng, Junmin; Wang, Jing; Wan, Yong

2018-06-01

The 21st century Maritime Silk Road (MSR) proposed by China strongly promotes the maritime industry. In this paper, we use wind and ocean wave datasets from 1979 to 2014 to analyze the spatial and temporal distributions of the wind speed, significant wave height (SWH), mean wave direction (MWD), and mean wave period (MWP) in the MSR. The analysis results indicate that the Luzon Strait and Gulf of Aden have the most obvious seasonal variations and that the central Indian Ocean is relatively stable. We analyzed the distributions of the maximum wind speed and SWH in the MSR over this 36-year period. The results show that the distribution of the monthly average frequency for SWH exceeds 4 m (huge waves) and that of the corresponding wind speed exceeds 13.9 m s-1 (high wind speed). The occurrence frequencies of huge waves and high winds in regions east of the Gulf of Aden are as high as 56% and 80%, respectively. We also assessed the wave and wind energies in different seasons. Based on our analyses, we propose a risk factor (RF) for determining navigation safety levels, based on the wind speed and SWH. We determine the spatial and temporal RF distributions for different seasons and analyze the corresponding impact on four major sea routes. Finally, we determine the spatial distribution of tropical cyclones from 2000 to 2015 and analyze the corresponding impact on the four sea routes. The analysis of the dynamic characteristics of the MSR provides references for ship navigation as well as ocean engineering.

Network traffic behaviour near phase transition point

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-03-01

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.

The mathematical cell model reconstructed from interference microscopy data

NASA Astrophysics Data System (ADS)

Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.

2017-09-01

The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.

Cyber War Game in Temporal Networks

PubMed Central

Cho, Jin-Hee; Gao, Jianxi

2016-01-01

In a cyber war game where a network is fully distributed and characterized by resource constraints and high dynamics, attackers or defenders often face a situation that may require optimal strategies to win the game with minimum effort. Given the system goal states of attackers and defenders, we study what strategies attackers or defenders can take to reach their respective system goal state (i.e., winning system state) with minimum resource consumption. However, due to the dynamics of a network caused by a node’s mobility, failure or its resource depletion over time or action(s), this optimization problem becomes NP-complete. We propose two heuristic strategies in a greedy manner based on a node’s two characteristics: resource level and influence based on k-hop reachability. We analyze complexity and optimality of each algorithm compared to optimal solutions for a small-scale static network. Further, we conduct a comprehensive experimental study for a large-scale temporal network to investigate best strategies, given a different environmental setting of network temporality and density. We demonstrate the performance of each strategy under various scenarios of attacker/defender strategies in terms of win probability, resource consumption, and system vulnerability. PMID:26859840

Temporal dynamics of online petitions.

PubMed

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.

Simultaneous application of multiple platforms (Glider, Scanfish, profiling mooring, CTD) to improve detection and quantification of temporal ocean dynamics

NASA Astrophysics Data System (ADS)

Meyer, D.; Prien, R. D.; Lips, U.; Naumann, M.; Liblik, T.; Schulz-Bull, D. E.

2016-02-01

Ocean dynamics are difficult to observe given the broad spectrum of temporal and spatial scales. Robotic technology can be used to address this issue, and help to investigate the variability of physical and biogeochemical processes. This work focuses on ocean robots and in particular on glider technology which seems to be one of the most promising oceanographic tools for future marine research. In this context, we present the results of an observational program conducted in the Baltic Sea combining a profiling mooring (GODESS - Gotland Deep Environmental Sampling Station) and glider technology (Slocum). The temporal variability is captured by the mooring, while the spatial variability is obtained from the glider sampling the surrounding area. Furthermore, classical CTD-measurements and an underwater vehicle (Scanfish) are used simultaneously by two different research vessels to validate and complement the observing network. The main aim of the study is to identify possible synergies between the different platforms and to get a better understanding of maximizing the information content of the data collected by this network. The value and the quality of the data of each individual platform is analyzed and their contribution to the performance of the network itself evaluated.

Temporal Statistics of Natural Image Sequences Generated by Movements with Insect Flight Characteristics

PubMed Central

Schwegmann, Alexander; Lindemann, Jens Peter; Egelhaaf, Martin

2014-01-01

Many flying insects, such as flies, wasps and bees, pursue a saccadic flight and gaze strategy. This behavioral strategy is thought to separate the translational and rotational components of self-motion and, thereby, to reduce the computational efforts to extract information about the environment from the retinal image flow. Because of the distinguishing dynamic features of this active flight and gaze strategy of insects, the present study analyzes systematically the spatiotemporal statistics of image sequences generated during saccades and intersaccadic intervals in cluttered natural environments. We show that, in general, rotational movements with saccade-like dynamics elicit fluctuations and overall changes in brightness, contrast and spatial frequency of up to two orders of magnitude larger than translational movements at velocities that are characteristic of insects. Distinct changes in image parameters during translations are only caused by nearby objects. Image analysis based on larger patches in the visual field reveals smaller fluctuations in brightness and spatial frequency composition compared to small patches. The temporal structure and extent of these changes in image parameters define the temporal constraints imposed on signal processing performed by the insect visual system under behavioral conditions in natural environments. PMID:25340761

Spatio-Temporal Fluctuations of the Earthquake Magnitude Distribution: Robust Estimation and Predictive Power

NASA Astrophysics Data System (ADS)

Olsen, S.; Zaliapin, I.

2008-12-01

We establish positive correlation between the local spatio-temporal fluctuations of the earthquake magnitude distribution and the occurrence of regional earthquakes. In order to accomplish this goal, we develop a sequential Bayesian statistical estimation framework for the b-value (slope of the Gutenberg-Richter's exponential approximation to the observed magnitude distribution) and for the ratio a(t) between the earthquake intensities in two non-overlapping magnitude intervals. The time-dependent dynamics of these parameters is analyzed using Markov Chain Models (MCM). The main advantage of this approach over the traditional window-based estimation is its "soft" parameterization, which allows one to obtain stable results with realistically small samples. We furthermore discuss a statistical methodology for establishing lagged correlations between continuous and point processes. The developed methods are applied to the observed seismicity of California, Nevada, and Japan on different temporal and spatial scales. We report an oscillatory dynamics of the estimated parameters, and find that the detected oscillations are positively correlated with the occurrence of large regional earthquakes, as well as with small events with magnitudes as low as 2.5. The reported results have important implications for further development of earthquake prediction and seismic hazard assessment methods.

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

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends 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) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise.

PubMed

Shen, Jing; Souza, Pamela E

2017-09-18

This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

PubMed Central

Souza, Pamela E.

2017-01-01

Purpose This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Method Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. Results The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Conclusions Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss. PMID:28800370

The numerical dynamic for highly nonlinear partial differential equations

NASA Technical Reports Server (NTRS)

Lafon, A.; Yee, H. C.

1992-01-01

Problems associated with the numerical computation of highly nonlinear equations in computational fluid dynamics are set forth and analyzed in terms of the potential ranges of spurious behaviors. A reaction-convection equation with a nonlinear source term is employed to evaluate the effects related to spatial and temporal discretizations. The discretization of the source term is described according to several methods, and the various techniques are shown to have a significant effect on the stability of the spurious solutions. Traditional linearized stability analyses cannot provide the level of confidence required for accurate fluid dynamics computations, and the incorporation of nonlinear analysis is proposed. Nonlinear analysis based on nonlinear dynamical systems complements the conventional linear approach and is valuable in the analysis of hypersonic aerodynamics and combustion phenomena.

Dynamics of comb-of-comb-network polymers in random layered flows

NASA Astrophysics Data System (ADS)

Katyal, Divya; Kant, Rama

2016-12-01

We analyze the dynamics of comb-of-comb-network polymers in the presence of external random flows. The dynamics of such structures is evaluated through relevant physical quantities, viz., average square displacement (ASD) and the velocity autocorrelation function (VACF). We focus on comparing the dynamics of the comb-of-comb network with the linear polymer. The present work displays an anomalous diffusive behavior of this flexible network in the random layered flows. The effect of the polymer topology on the dynamics is analyzed by varying the number of generations and branch lengths in these networks. In addition, we investigate the influence of external flow on the dynamics by varying flow parameters, like the flow exponent α and flow strength Wα. Our analysis highlights two anomalous power-law regimes, viz., subdiffusive (intermediate-time polymer stretching and flow-induced diffusion) and superdiffusive (long-time flow-induced diffusion). The anomalous long-time dynamics is governed by the temporal exponent ν of ASD, viz., ν =2 -α /2 . Compared to a linear polymer, the comb-of-comb network shows a shorter crossover time (from the subdiffusive to superdiffusive regime) but a reduced magnitude of ASD. Our theory displays an anomalous VACF in the random layered flows that scales as t-α /2. We show that the network with greater total mass moves faster.

The Effects of Aging and Dual Tasking on Human Gait Complexity During Treadmill Walking: A Comparative Study Using Quantized Dynamical Entropy and Sample Entropy.

PubMed

Ahmadi, Samira; Wu, Christine; Sepehri, Nariman; Kantikar, Anuprita; Nankar, Mayur; Szturm, Tony

2018-01-01

Quantized dynamical entropy (QDE) has recently been proposed as a new measure to quantify the complexity of dynamical systems with the purpose of offering a better computational efficiency. This paper further investigates the viability of this method using five different human gait signals. These signals are recorded while normal walking and while performing secondary tasks among two age groups (young and older age groups). The results are compared with the outcomes of previously established sample entropy (SampEn) measure for the same signals. We also study how analyzing segmented and spatially and temporally normalized signal differs from analyzing whole data. Our findings show that human gait signals become more complex as people age and while they are cognitively loaded. Center of pressure (COP) displacement in mediolateral direction is the best signal for showing the gait changes. Moreover, the results suggest that by segmenting data, more information about intrastride dynamical features are obtained. Most importantly, QDE is shown to be a reliable measure for human gait complexity analysis.

Potential role for microfluctuations as a temporal directional cue to accommodation

PubMed Central

Metlapally, Sangeetha; Tong, Jianliang L.; Tahir, Humza J.; Schor, Clifton M.

2016-01-01

The goal was to revisit an important, yet unproven notion that accommodative microfluctuations facilitate the determination of direction (sign) of abrupt focus changes in the stimulus to accommodation. We contaminated the potential temporal cues from natural accommodative microfluctuations by presenting uncorrelated external (screen) temporal defocus noise that combined with the retinal image effects of natural microfluctuations. A polychromatic Maltese spoke pattern thus either modulated defocus at a combination of two temporal frequencies (on-screen noise condition) or was static (control condition). The on-screen conditions were combined with step changes in optical vergence that were randomized in direction and magnitude. Five subjects monocularly viewed stimuli through a Badal optical system in a Maxwellian view. An artificial 4-mm aperture was imaged at the entrance pupil of the eye. Wavefront aberrations were measured dynamically at 50 Hz using a custom Shack–Hartmann aberrometer. Dynamic changes in the Zernike defocus term with step changes in optical vergence were analyzed. We calculated the percentage of correct directional responses for 1, 2, and 3 D accommodative and disaccommodative step stimuli using preset criteria for latency, velocity, and persistence of the response. The on-screen noise condition reduced the percent-correct responses compared to the static stimulus, suggesting that this manipulation affected the detectability of the sign of the accommodative stimulus. Several possible reasons and implications of this result are discussed. PMID:27120075

Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

USGS Publications Warehouse

Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

2014-01-01

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

PubMed Central

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

Exploring the structure and function of temporal networks with dynamic graphlets

PubMed Central

Hulovatyy, Y.; Chen, H.; Milenković, T.

2015-01-01

Motivation: With increasing availability of temporal real-world networks, how to efficiently study these data? One can model a temporal network as a single aggregate static network, or as a series of time-specific snapshots, each being an aggregate static network over the corresponding time window. Then, one can use established methods for static analysis on the resulting aggregate network(s), but losing in the process valuable temporal information either completely, or at the interface between different snapshots, respectively. Here, we develop a novel approach for studying a temporal network more explicitly, by capturing inter-snapshot relationships. Results: We base our methodology on well-established graphlets (subgraphs), which have been proven in numerous contexts in static network research. We develop new theory to allow for graphlet-based analyses of temporal networks. Our new notion of dynamic graphlets is different from existing dynamic network approaches that are based on temporal motifs (statistically significant subgraphs). The latter have limitations: their results depend on the choice of a null network model that is required to evaluate the significance of a subgraph, and choosing a good null model is non-trivial. Our dynamic graphlets overcome the limitations of the temporal motifs. Also, when we aim to characterize the structure and function of an entire temporal network or of individual nodes, our dynamic graphlets outperform the static graphlets. Clearly, accounting for temporal information helps. We apply dynamic graphlets to temporal age-specific molecular network data to deepen our limited knowledge about human aging. Availability and implementation: http://www.nd.edu/∼cone/DG. Contact: tmilenko@nd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072480

Dynamic CRM occupancy reflects a temporal map of developmental progression.

PubMed

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.

The analysis of the influence of fractal structure of stimuli on fractal dynamics in fixational eye movements and EEG signal

NASA Astrophysics Data System (ADS)

Namazi, Hamidreza; Kulish, Vladimir V.; Akrami, Amin

2016-05-01

One of the major challenges in vision research is to analyze the effect of visual stimuli on human vision. However, no relationship has been yet discovered between the structure of the visual stimulus, and the structure of fixational eye movements. This study reveals the plasticity of human fixational eye movements in relation to the ‘complex’ visual stimulus. We demonstrated that the fractal temporal structure of visual dynamics shifts towards the fractal dynamics of the visual stimulus (image). The results showed that images with higher complexity (higher fractality) cause fixational eye movements with lower fractality. Considering the brain, as the main part of nervous system that is engaged in eye movements, we analyzed the governed Electroencephalogram (EEG) signal during fixation. We have found out that there is a coupling between fractality of image, EEG and fixational eye movements. The capability observed in this research can be further investigated and applied for treatment of different vision disorders.

Temporal-spatial measurement of electron relaxation time in femtosecond laser induced plasma using two-color pump-probe imaging technique

NASA Astrophysics Data System (ADS)

Pan, Changji; Jiang, Lan; Wang, Qingsong; Sun, Jingya; Wang, Guoyan; Lu, Yongfeng

2018-05-01

The femtosecond (fs) laser is a powerful tool to study ultrafast plasma dynamics, especially electron relaxation in strong ionization of dielectrics. Herein, temporal-spatial evolution of femtosecond laser induced plasma in fused silica was investigated using a two-color pump-probe technique (i.e., 400 nm and 800 nm, respectively). We demonstrated that when ionized electron density is lower than the critical density, free electron relaxation time is inversely proportional to electron density, which can be explained by the electron-ion scattering regime. In addition, electron density evolution within plasma was analyzed in an early stage (first 800 fs) of the laser-material interaction.

Spatial and temporal variations in lagoon and coastal processes of the southern Brazilian coast

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Herz, R.

1980-01-01

From a collection of information gathered during a long period, through the orbital platforms SKYLAB and LANDSAT, it was possible to establish a method for the systematic study of the dynamical regime of lagoon and marine surface waters, on coastal plain of Rio Grande do Sul. The series of multispectral images analyzed by visual and automatic techniques put in evidence spatial and temporal variations reflected in the optical properties of waters, which carry different loads of materials in suspension. The identified patterns offer a synoptic picture of phenomena of great amplitude, from which trends of circulation can be inferred, correlating the atmospheric and hydrologic variables simultaneously to the overflight of orbital vehicles.

The dynamic monitoring of warm-water discharge based on the airborne high-resolution thermal infrared remote sensing data

NASA Astrophysics Data System (ADS)

Shao, Honglan; Xie, Feng; Liu, Chengyu; Liu, Zhihui; Zhang, Changxing; Yang, Gui; Wang, Jianyu

2016-04-01

The cooling water discharged from the coastal plants flow into the sea continuously, whose temperature is higher than original sea surface temperature (SST). The fact will have non-negligible influence on the marine environment in and around where the plants site. Hence, it's significant to monitor the temporal and spatial variation of the warm-water discharge for the assessment of the effect of the plant on its surrounding marine environment. The paper describes an approach for the dynamic monitoring of the warm-water discharge of coastal plants based on the airborne high-resolution thermal infrared remote sensing technology. Firstly, the geometric correction was carried out for the thermal infrared remote sensing images acquired on the aircraft. Secondly, the atmospheric correction method was used to retrieve the sea surface temperature of the images. Thirdly, the temperature-rising districts caused by the warm-water discharge were extracted. Lastly, the temporal and spatial variations of the warm-water discharge were analyzed through the geographic information system (GIS) technology. The approach was applied to Qinshan nuclear power plant (NPP), in Zhejiang Province, China. In considering with the tide states, the diffusion, distribution and temperature-rising values of the warm-water discharged from the plant were calculated and analyzed, which are useful to the marine environment assessment.

Analysis of Supergranule Sizes and Velocities Using Solar Dynamics Observatory (SDO)/Helioseismic Magnetic Imager (HMI) and Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) Dopplergrams

NASA Technical Reports Server (NTRS)

Williams, Peter E.; Pesnell, W. Dean; Beck, John G.; Lee, Shannon

2013-01-01

Co-temporal Doppler images from Solar and Heliospheric Observatory (SOHO)/ Michelson Doppler Imager (MDI) and Solar Dynamics Observatory (SDO)/Helioseismic Magnetic Imager (HMI) have been analyzed to extract quantitative information about global properties of the spatial and temporal characteristics of solar supergranulation. Preliminary comparisons show that supergranules appear to be smaller and have stronger horizontal velocity flows within HMI data than was measured with MDI. There appears to be no difference in their evolutionary timescales. Supergranule sizes and velocities were analyzed over a ten-day time period at a 15-minute cadence. While the averages of the time-series retain the aforementioned differences, fluctuations of these parameters first observed in MDI data were seen in both MDI and HMI time-series, exhibiting a strong cross-correlation. This verifies that these fluctuations are not instrumental, but are solar in origin. The observed discrepancies between the averaged values from the two sets of data are a consequence of instrument resolution. The lower spatial resolution of MDI results in larger observed structures with lower velocities than is seen in HMI. While these results offer a further constraint on the physical nature of supergranules, they also provide a level of calibration between the two instruments.

Suspended sediment propagation in a long river reach: spatial and temporal dynamics of the Suspended Sediment Concentration-Water Discharge diagram for several hydrological events in the Northern French Alps.

NASA Astrophysics Data System (ADS)

Antoine, Germain; Jodeau, Magali; Camenen, Benoit; Esteves, Michel

2014-05-01

The relative propagation of water and suspended sediment is a key parameter to understand the suspended sediment transfers at the catchment scale. Several studies have shown the interest of performing detailed investigations of both temporal suspended sediment concentration (SSC) and water discharge signals. Most of them used temporal data from one measurement site, and classified hydrological events by studying the SSC curve as a function of water discharge (SSC-WD diagrams). Theoretical interpretations of these curves have been used to estimate the different sources of suspended sediment supply from sub-catchments, to evaluate the effect of seasons on the dynamics of suspended sediment, or to highlight the effect of a critical change at the catchment scale. However, few studies have focused on the signal propagation along the river channel. In this study, we analyze sampled data from a very well instrumented river reach in the Northern French Alps: the Arc-Isère River system. This gravel-bed river system is characterized by large concentrations of fines sediments, coming from the highly erodible mountains around. To control the hydraulic, sedimentary and chemical parameters from the catchment head, several gauging stations have been established since 2006. The continuous data measured at 4 gauging stations along 120 km of river have been analyzed to estimate the spatial and temporal dynamics of both SSC and water discharge. More precisely, about 40 major hydrological events have been sampled statistically between 2006 and 2012 from the data set and are analyzed in details. The study shows that the mean value of the propagation velocity is equal to 2 m/s and 3 m/s respectively for the SSC signal and the water discharge. These different propagation velocities imply that the suspended sediment mass is not only transported by the advection of the water at the river scale. The dispersion, erosion or deposition processes, and also the suspended sediment and discharge supply from the intermediate sub-catchments must be considered. Moreover, the SSC-WD diagrams are modified from one measurement site to another along the river. The spatial changes of the SSC-WD diagrams highlight different type of events, from local debris flows to generalized natural floods. A conceptual approach is proposed to better take into account the channel erosion or deposition processes in the analysis of these diagrams.

Disturbed temporal dynamics of brain synchronization in vision loss.

PubMed

Bola, Michał; Gall, Carolin; Sabel, Bernhard A

2015-06-01

Damage along the visual pathway prevents bottom-up visual input from reaching further processing stages and consequently leads to loss of vision. But perception is not a simple bottom-up process - rather it emerges from activity of widespread cortical networks which coordinate visual processing in space and time. Here we set out to study how vision loss affects activity of brain visual networks and how networks' activity is related to perception. Specifically, we focused on studying temporal patterns of brain activity. To this end, resting-state eyes-closed EEG was recorded from partially blind patients suffering from chronic retina and/or optic-nerve damage (n = 19) and healthy controls (n = 13). Amplitude (power) of oscillatory activity and phase locking value (PLV) were used as measures of local and distant synchronization, respectively. Synchronization time series were created for the low- (7-9 Hz) and high-alpha band (11-13 Hz) and analyzed with three measures of temporal patterns: (i) length of synchronized-/desynchronized-periods, (ii) Higuchi Fractal Dimension (HFD), and (iii) Detrended Fluctuation Analysis (DFA). We revealed that patients exhibit less complex, more random and noise-like temporal dynamics of high-alpha band activity. More random temporal patterns were associated with worse performance in static (r = -.54, p = .017) and kinetic perimetry (r = .47, p = .041). We conclude that disturbed temporal patterns of neural synchronization in vision loss patients indicate disrupted communication within brain visual networks caused by prolonged deafferentation. We propose that because the state of brain networks is essential for normal perception, impaired brain synchronization in patients with vision loss might aggravate the functional consequences of reduced visual input. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multifunctional System for Observing, Measuring and Analyzing Stimulation-Evoked Neurochemical Signaling

PubMed Central

Kimble, Christopher J.; Boesche, Joshua B.; Eaker, Diane R.; Kressin, Kenneth R.; Trevathan, James K.; Paek, Seungleal; Asp, Anders J.; McIntosh, Malcolm B.; Lujan, J. Luis

2017-01-01

The ability to measure neurotransmitter activity using implanted electrochemical sensors offers researchers a potent technique for analyzing neural activity across specific neural circuitry. We have developed a wirelessly controlled device, WINCS Harmoni, to observe and measure neurotransmitter dynamics at up to four separate sensors, with high temporal and spatial resolution. WINCS Harmoni also incorporates a versatile neurostimulator that can be synchronized with electrochemical recording. The WINCS Harmoni platform is thus optimally suited for probing the neurochemical effects of neurostimulation, and may in turn enable the development of personalized therapies for multiple brain disorders. PMID:29202131

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

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends 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) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

Information Theory to Probe Intrapartum Fetal Heart Rate Dynamics

NASA Astrophysics Data System (ADS)

Granero-Belinchon, Carlos; Roux, Stéphane; Abry, Patrice; Doret, Muriel; Garnier, Nicolas

2017-11-01

Intrapartum fetal heart rate (FHR) monitoring constitutes a reference tool in clinical practice to assess the baby health status and to detect fetal acidosis. It is usually analyzed by visual inspection grounded on FIGO criteria. Characterization of Intrapartum fetal heart rate temporal dynamics remains a challenging task and continuously receives academic research efforts. Complexity measures, often implemented with tools referred to as \\emph{Approximate Entropy} (ApEn) or \\emph{Sample Entropy} (SampEn), have regularly been reported as significant features for intrapartum FHR analysis. We explore how Information Theory, and especially {\\em auto mutual information} (AMI), is connected to ApEn and SampEn and can be used to probe FHR dynamics. Applied to a large (1404 subjects) and documented database of FHR data, collected in a French academic hospital, it is shown that i) auto mutual information outperforms ApEn and SampEn for acidosis detection in the first stage of labor and continues to yield the best performance in the second stage; ii) Shannon entropy increases as labor progresses, and is always much larger in the second stage;iii) babies suffering from fetal acidosis additionally show more structured temporal dynamics than healthy ones and that this progressive structuration can be used for early acidosis detection.

Insights into the bacterial community and its temporal succession during the fermentation of wine grapes

PubMed Central

Piao, Hailan; Hawley, Erik; Kopf, Scott; DeScenzo, Richard; Sealock, Steven; Henick-Kling, Thomas; Hess, Matthias

2015-01-01

Grapes harbor complex microbial communities. It is well known that yeasts, typically Saccharomyces cerevisiae, and bacteria, commonly the lactic acid fermenting Oenococcus oeni, work sequentially during primary and secondary wine fermentation. In addition to these main players, several microbes, often with undesirable effects on wine quality, have been found in grapes and during wine fermentation. However, still little is known about the dynamics of the microbial community during the fermentation process. In previous studies culture dependent methods were applied to detect and identify microbial organisms associated with grapes and grape products, which resulted in a picture that neglected the non-culturable fraction of the microbes. To obtain a more complete picture of how microbial communities change during grape fermentation and how different fermentation techniques might affect the microbial community composition, we employed next-generation sequencing (NGS)—a culture-independent method. A better understanding of the microbial dynamics and their effect on the final product is of great importance to help winemakers produce wine styles of consistent and high quality. In this study, we focused on the bacterial community dynamics during wine vinification by amplifying and sequencing the hypervariable V1–V3 region of the 16S rRNA gene—a phylogenetic marker gene that is ubiquitous within prokaryotes. Bacterial communities and their temporal succession was observed for communities associated with organically and conventionally produced wines. In addition, we analyzed the chemical characteristics of the grape musts during the organic and conventional fermentation process. These analyses revealed distinct bacterial population with specific temporal changes as well as different chemical profiles for the organically and conventionally produced wines. In summary these results suggest a possible correlation between the temporal succession of the bacterial population and the chemical wine profiles. PMID:26347718

Dynamic Controllability and Dispatchability Relationships

NASA Technical Reports Server (NTRS)

Morris, Paul Henry

2014-01-01

An important issue for temporal planners is the ability to handle temporal uncertainty. Recent papers have addressed the question of how to tell whether a temporal network is Dynamically Controllable, i.e., whether the temporal requirements are feasible in the light of uncertain durations of some processes. We present a fast algorithm for Dynamic Controllability. We also note a correspondence between the reduction steps in the algorithm and the operations involved in converting the projections to dispatchable form. This has implications for the complexity for sparse networks.

Classical and quantum dynamics of a kicked relativistic particle in a box

NASA Astrophysics Data System (ADS)

Yusupov, J. R.; Otajanov, D. M.; Eshniyazov, V. E.; Matrasulov, D. U.

2018-03-01

We study classical and quantum dynamics of a kicked relativistic particle confined in a one dimensional box. It is found that in classical case for chaotic motion the average kinetic energy grows in time, while for mixed regime the growth is suppressed. However, in case of regular motion energy fluctuates around certain value. Quantum dynamics is treated by solving the time-dependent Dirac equation with delta-kicking potential, whose exact solution is obtained for single kicking period. In quantum case, depending on the values of the kicking parameters, the average kinetic energy can be quasi periodic, or fluctuating around some value. Particle transport is studied by considering spatio-temporal evolution of the Gaussian wave packet and by analyzing the trembling motion.

How Does the Electron Dynamics Affect the Global Reconnection Rate

NASA Technical Reports Server (NTRS)

Hesse, Michael

2012-01-01

The question of whether the microscale controls the macroscale or vice-versa remains one of the most challenging problems in plasmas. A particular topic of interest within this context is collisionless magnetic reconnection, where both points of views are espoused by different groups of researchers. This presentation will focus on this topic. We will begin by analyzing the properties of electron diffusion region dynamics both for guide field and anti-parallel reconnection, and how they can be scaled to different inflow conditions. As a next step, we will study typical temporal variations of the microscopic dynamics with the objective of understanding the potential for secular changes to the macroscopic system. The research will be based on a combination of analytical theory and numerical modeling.

Universal Critical Dynamics in High Resolution Neuronal Avalanche Data

NASA Astrophysics Data System (ADS)

Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; DeVille, R. E. Lee; Dahmen, Karin A.; Beggs, John M.; Butler, Thomas C.

2012-05-01

The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. However, experimental evidence for critical dynamics has been inconclusive. Here, we show that the dynamics of cultured cortical networks are critical. We analyze neuronal network data collected at the individual neuron level using the framework of nonequilibrium phase transitions. Among the most striking predictions confirmed is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.

A Structural Characterization of Temporal Dynamic Controllability

NASA Technical Reports Server (NTRS)

Morris, Paul

2006-01-01

An important issue for temporal planners is the ability to handle temporal uncertainty. Recent papers have addressed the question of how to tell whether a temporal network is Dynamically Controllable, i.e., whether the temporal requirements are feasible in the light of uncertain durations of some processes. Previous work has presented an O(N5) algorithm for testing this property. Here, we introduce a new analysis of temporal cycles that leads to an O(N4) algorithm.

Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

PubMed Central

Roach, Shane M.; Song, Dong; Berger, Theodore W.

2012-01-01

Activity-dependent variation of neuronal thresholds for action potential (AP) generation is one of the key determinants of spike-train temporal-pattern transformations from presynaptic to postsynaptic spike trains. In this study, we model the nonlinear dynamics of the threshold variation during synaptically driven broadband intracellular activity. First, membrane potentials of single CA1 pyramidal cells were recorded under physiologically plausible broadband stimulation conditions. Second, a method was developed to measure AP thresholds from the continuous recordings of membrane potentials. It involves measuring the turning points of APs by analyzing the third-order derivatives of the membrane potentials. Four stimulation paradigms with different temporal patterns were applied to validate this method by comparing the measured AP turning points and the actual AP thresholds estimated with varying stimulation intensities. Results show that the AP turning points provide consistent measurement of the AP thresholds, except for a constant offset. It indicates that 1) the variation of AP turning points represents the nonlinearities of threshold dynamics; and 2) an optimization of the constant offset is required to achieve accurate spike prediction. Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities. Results show that the model can predict threshold accurately based on the preceding APs. Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction. PMID:22156947

Mapping permafrost change hot-spots with Landsat time-series

NASA Astrophysics Data System (ADS)

Grosse, G.; Nitze, I.

2016-12-01

Recent and projected future climate warming strongly affects permafrost stability over large parts of the terrestrial Arctic with local, regional and global scale consequences. The monitoring and quantification of permafrost and associated land surface changes in these areas is crucial for the analysis of hydrological and biogeochemical cycles as well as vegetation and ecosystem dynamics. However, detailed knowledge of the spatial distribution and the temporal dynamics of these processes is scarce and likely key locations of permafrost landscape dynamics may remain unnoticed. As part of the ERC funded PETA-CARB and ESA GlobPermafrost projects, we developed an automated processing chain based on data from the entire Landsat archive (excluding MSS) for the detection of permafrost change related processes and hotspots. The automated method enables us to analyze thousands of Landsat scenes, which allows for a multi-scaled spatio-temporal analysis at 30 meter spatial resolution. All necessary processing steps are carried out automatically with minimal user interaction, including data extraction, masking, reprojection, subsetting, data stacking, and calculation of multi-spectral indices. These indices, e.g. Landsat Tasseled Cap and NDVI among others, are used as proxies for land surface conditions, such as vegetation status, moisture or albedo. Finally, a robust trend analysis is applied to each multi-spectral index and each pixel over the entire observation period of up to 30 years from 1985 to 2015, depending on data availability. Large transects of around 2 million km² across different permafrost types in Siberia and North America have been processed. Permafrost related or influencing landscape dynamics were detected within the trend analysis, including thermokarst lake dynamics, fires, thaw slumps, and coastal dynamics. The produced datasets will be distributed to the community as part of the ERC PETA-CARB and ESA GlobPermafrost projects. Users are encouraged to provide feedback and ground truth data for a continuous improvement of our methodology and datasets, which will lead to a better understanding of the spatial and temporal distribution of changes within the vulnerable permafrost zone.

Dynamic Reorganization of Functional Connectivity Reveals Abnormal Temporal Efficiency in Schizophrenia.

PubMed

Sun, Yu; Collinson, Simon L; Suckling, John; Sim, Kang

2018-06-07

Emerging evidence suggests that schizophrenia is associated with brain dysconnectivity. Nonetheless, the implicit assumption of stationary functional connectivity (FC) adopted in most previous resting-state functional magnetic resonance imaging (fMRI) studies raises an open question of schizophrenia-related aberrations in dynamic properties of resting-state FC. This study introduces an empirical method to examine the dynamic functional dysconnectivity in patients with schizophrenia. Temporal brain networks were estimated from resting-state fMRI of 2 independent datasets (patients/controls = 18/19 and 53/57 for self-recorded dataset and a publicly available replication dataset, respectively) by the correlation of sliding time-windowed time courses among regions of a predefined atlas. Through the newly introduced temporal efficiency approach and temporal random network models, we examined, for the first time, the 3D spatiotemporal architecture of the temporal brain network. We found that although prominent temporal small-world properties were revealed in both groups, temporal brain networks of patients with schizophrenia in both datasets showed a significantly higher temporal global efficiency, which cannot be simply attributable to head motion and sampling error. Specifically, we found localized changes of temporal nodal properties in the left frontal, right medial parietal, and subcortical areas that were associated with clinical features of schizophrenia. Our findings demonstrate that altered dynamic FC may underlie abnormal brain function and clinical symptoms observed in schizophrenia. Moreover, we provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network and highlight the potential of aberrant brain dynamic FC in unraveling the pathophysiologic mechanisms of the disease.

Ultrafast electrical spectrum analyzer based on all-optical Fourier transform and temporal magnification.

PubMed

Duan, Yuhua; Chen, Liao; Zhou, Haidong; Zhou, Xi; Zhang, Chi; Zhang, Xinliang

2017-04-03

Real-time electrical spectrum analysis is of great significance for applications involving radio astronomy and electronic warfare, e.g. the dynamic spectrum monitoring of outer space signal, and the instantaneous capture of frequency from other electronic systems. However, conventional electrical spectrum analyzer (ESA) has limited operation speed and observation bandwidth due to the electronic bottleneck. Therefore, a variety of photonics-assisted methods have been extensively explored due to the bandwidth advantage of the optical domain. Alternatively, we proposed and experimentally demonstrated an ultrafast ESA based on all-optical Fourier transform and temporal magnification in this paper. The radio-frequency (RF) signal under test is temporally multiplexed to the spectrum of an ultrashort pulse, thus the frequency information is converted to the time axis. Moreover, since the bandwidth of this ultrashort pulse is far beyond that of the state-of-the-art photo-detector, a temporal magnification system is applied to stretch the time axis, and capture the RF spectrum with 1-GHz resolution. The observation bandwidth of this ultrafast ESA is over 20 GHz, limited by that of the electro-optic modulator. Since all the signal processing is in the optical domain, the acquisition frame rate can be as high as 50 MHz. This ultrafast ESA scheme can be further improved with better dispersive engineering, and is promising for some ultrafast spectral information acquisition applications.

Temporal Dynamic Controllability Revisited

NASA Technical Reports Server (NTRS)

Morris, Paul H.; Muscettola, Nicola

2005-01-01

An important issue for temporal planners is the ability to handle temporal uncertainty. We revisit the question of how to determine whether a given set of temporal requirements are feasible in the light of uncertain durations of some processes. In particular, we consider how best to determine whether a network is Dynamically Controllable, i.e., whether a dynamic strategy exists for executing the network that is guaranteed to satisfy the requirements. Previous work has shown the existence of a pseudo-polynomial algorithm for testing Dynamic Controllability. Here, we greatly simplify the previous framework, and present a true polynomial algorithm with a cutoff based only on the number of nodes.

Spatial distribution of volcanic ash deposits of 2011 Puyehue-Cordón Caulle eruption in Patagonia as measured by a perturbation in NDVI temporal dynamics

NASA Astrophysics Data System (ADS)

Easdale, M. H.; Bruzzone, O.

2018-03-01

Volcanic ash fallout is a recurrent environmental disturbance in forests, arid and semi-arid rangelands of Patagonia, South America. The ash deposits over large areas are responsible for several impacts on ecological processes, agricultural production and health of local communities. Public policy decision making needs monitoring information of the affected areas by ash fallout, in order to better orient social, economic and productive aids. The aim of this study was to analyze the spatial distribution of volcanic ash deposits from the eruption of Puyehue-Cordón Caulle in 2011, by identifying a sudden change in the Normalized Difference Vegetation Index (NDVI) temporal dynamics, defined as a perturbation located in the time series. We applied a sparse-wavelet transform using the Basis Pursuit algorithm to NDVI time series obtained from the Moderate Resolution Image Spectroradiometer (MODIS) sensor, to identify perturbations at a pixel level. The spatial distribution of the perturbation promoted by ash deposits in Patagonia was successfully identified and characterized by means of a perturbation in NDVI temporal dynamics. Results are encouraging for the future development of a new platform, in combination with data from forecasting models and tracking of ash cloud trajectories and dispersion, to inform stakeholders to mitigate impact of volcanic ash on agricultural production and to orient public intervention strategies after a volcanic eruption followed by ash fallout over a wide region.

Towards a Predictive Theory of Malaria: Connections to Spatio-temporal Variability of Climate and Hydrology

NASA Astrophysics Data System (ADS)

Endo, N.; Eltahir, E. A. B.

2015-12-01

Malaria transmission is closely linked to climatology, hydrology, environment, and the biology of local vectors. These factors interact with each other and non-linearly influence malaria transmission dynamics, making prediction and prevention challenging. Our work attempts to find a universality in the multi-dimensional system of malaria transmission and to develop a theory to predict emergence of malaria given a limited set of environmental and biological inputs.A credible malaria transmission dynamics model, HYDREMATS (Bomblies et al., 2008), was used under hypothetical settings to investigate the role of spatial and temporal distribution of vector breeding pools. HYDREMATS is a mechanistic model and capable of simulating the basic reproduction rate (Ro) without bold assumptions even under dynamic conditions. The spatial distribution of pools is mainly governed by hydrological factors; the impact of pool persistence and rainy season length on malaria transmission were investigated. Also analyzed was the impact of the temporal distribution of pools relative to human houses. We developed non-dimensional variables combining the hydrological and biological parameters. Simulated values of Ro from HYDREMATS are presented in a newly-introduced non-dimensional plane, which leads to a some-what universal theory describing the condition for sustainable malaria transmission. The findings were tested against observations both from the West Africa and the Ethiopian Highland, representing diverse hydroclimatological conditions. Predicated Ro values from the theory over the two regions are in good agreement with the observed malaria transmission data.

Information processing and dynamics in minimally cognitive agents.

PubMed

Beer, Randall D; Williams, Paul L

2015-01-01

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be combined into a categorization decision. Dynamical analysis reveals the key geometrical and temporal interrelationships underlying the categorization decision. Finally, we propose a framework for directly relating these two different styles of explanation and discuss the possible implications of our analysis for some of the ongoing debates in cognitive science. Copyright © 2014 Cognitive Science Society, Inc.

Situation awareness - A critical but ill-defined phenomenon

NASA Technical Reports Server (NTRS)

Sarter, Nadine B.; Woods, David D.

1991-01-01

The significance of the temporal dimension of situation awareness is examined. Its study requires the staging of complex dynamic situations and the development of less intrusive in-flight probing techniques to assess the pilot's ability to adequately and rapidly retrieve and integrate flight-related information. The cognitive basis of the concept is analyzed, embedding it in the context of related psychological concepts. Methodological approaches to the investigation of situation awareness are discussed on this basis.

Towards the dynamic prediction of wildfire danger. Modeling temporal scenarios of fire-occurrence in Northeast Spain

NASA Astrophysics Data System (ADS)

Martín, Yago; Rodrigues, Marcos

2017-04-01

Up to date models of human-caused ignition probability have commonly been developed from a static or structural point of view, regardless of the time cycles that drive human behavior or environmental conditions. However, human drivers mostly have a temporal dimension, and fuel conditions are subjected to temporal changes as well, which is why a historical/temporal perspective is often required. Previous studies in the region suggest that human driving factors of wildfires have undergone significant shifts in inter-annual occurrence probability models, thus varying over time. On the other hand, an increasing role of environmental conditions has also been reported. This research comprehensively analyzes the intra-annual dimension of fire occurrence and fire-triggering factors using NW Spain as a test area, moving one-step forward towards achieving more accurate predictions, to ultimately develop dynamic predictive models. To this end, several intra-annual presence-only models have been calibrated, exploring seasonal variations of environmental conditions and short-term cycles of human activity (working- vs non-working days). Models were developed from accurately geolocated fire data in the 2008-2012 period, and GIS and remote sensing (MOD1A2 and MOD16) information . Specifically, 8 occurrence data subsets (scenarios) were constructed by splitting fire records into 4 seasons (winter, spring, summer and autumn) then separating each season into 2 new categories (working and non-working days). This allows analyzing the temporal variation of socioeconomic (urban- and agricultural-interfaces, transport and road networks, and human settlements) and environmental (fuel conditions) factors associated with occurrence. Models were calibrated applying the Maximum Entropy algorithm (MaxEnt). The MaxEnt algorithm was selected as it is the most widespread approach to deal with presence-only data, as may be the case of fire occurrence. The dependent variable for each scenario was created on a conceptual framework which assumed that there were no true cases of fire absence. Model accuracy was assessed using a cross-validation k-fold procedure, whereas variable importance was addressed using a jacknife approach combined with AUC estimation. Results reported model performances around 0.8 AUC in all temporal scenarios. In addition, large variability was observed in the contribution of explanatory factors, with accessibility variables and fuel conditions as key factors along models. Overall, we believe our approach is reliable enough to derive dynamic predictions of human-caused fire occurrence probability. To our knowledge, this is the first attempt to combine presence-only models based on XY located fire data, with remote sensing information and intra-annual scenarios also including cycles of human activity.

MicroRNA networks in mouse lung organogenesis.

PubMed

Dong, Jie; Jiang, Guoqian; Asmann, Yan W; Tomaszek, Sandra; Jen, Jin; Kislinger, Thomas; Wigle, Dennis A

2010-05-26

MicroRNAs (miRNAs) are known to be important regulators of both organ development and tumorigenesis. MiRNA networks and their regulation of messenger RNA (mRNA) translation and protein expression in specific biological processes are poorly understood. We explored the dynamic regulation of miRNAs in mouse lung organogenesis. Comprehensive miRNA and mRNA profiling was performed encompassing all recognized stages of lung development beginning at embryonic day 12 and continuing to adulthood. We analyzed the expression patterns of dynamically regulated miRNAs and mRNAs using a number of statistical and computational approaches, and in an integrated manner with protein levels from an existing mass-spectrometry derived protein database for lung development. In total, 117 statistically significant miRNAs were dynamically regulated during mouse lung organogenesis and clustered into distinct temporal expression patterns. 11,220 mRNA probes were also shown to be dynamically regulated and clustered into distinct temporal expression patterns, with 3 major patterns accounting for 75% of all probes. 3,067 direct miRNA-mRNA correlation pairs were identified involving 37 miRNAs. Two defined correlation patterns were observed upon integration with protein data: 1) increased levels of specific miRNAs directly correlating with downregulation of predicted mRNA targets; and 2) increased levels of specific miRNAs directly correlating with downregulation of translated target proteins without detectable changes in mRNA levels. Of 1345 proteins analyzed, 55% appeared to be regulated in this manner with a direct correlation between miRNA and protein level, but without detectable change in mRNA levels. Systematic analysis of microRNA, mRNA, and protein levels over the time course of lung organogenesis demonstrates dynamic regulation and reveals 2 distinct patterns of miRNA-mRNA interaction. The translation of target proteins affected by miRNAs independent of changes in mRNA level appears to be a prominent mechanism of developmental regulation in lung organogenesis.

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

PubMed

Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco

2014-01-01

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 abundance of the underlying population.

Perspectives on the geographic stability and mobility of people in cities

PubMed Central

Hanson, Susan

2005-01-01

A class of questions in the human environment sciences focuses on the relationship between individual or household behavior and local geographic context. Central to these questions is the nature of people's geographic mobility as well as the duration of their locational stability at varying spatial and temporal scales. The problem for researchers is that the processes of mobility/stability are temporally and spatially dynamic and therefore difficult to measure. Whereas time and space are continuous, analysts must select levels of aggregation for both length of time in place and spatial scale of place that fit with the problem in question. Previous work has emphasized mobility and suppressed stability as an analytic category. I focus here on stability and show how analyzing individuals' stability requires also analyzing their mobility. Through an empirical example centered on the relationship between entrepreneurship and place, I demonstrate how a spotlight on stability illuminates a resolution to the measurement problem by highlighting the interdependence between the time and space dimensions of stability/mobility. PMID:16230616

Hierarchic spatio-temporal dynamics in glycolysis

NASA Astrophysics Data System (ADS)

Shinjyo, Takahiro; Nakagawa, Yoshiyuki; Ueda, Tetsuo

Yeast extracts exhibit oscillations when the glycolytic system is far away from equilibrium. Spatio-temporal dynamics in this system was studied in the newly developed gel as well as in the solution. Small regions (about 10 um) with very complex shape with high or low concentrations of NADH appeared, and upon these small structures large-scale dynamics were superimposed. Concentration waves propagated, and the source of wave was induced by contact with high ADP. Sink of waves was generated by contacting the reaction gel to two small gels rich in ADP. Upon these spatio-temporal dynamics were superimposed much slower global oscillations throughout the system with a period of about 40 min. Similar dynamics was seen in a solution of yeast extract, but the size of domains was about ten times larger than that in the gel. In this way, the multi-enzyme system of glycolysis exhibits self-organization of hierarchy in spatio-temporal dynamics.

Acousto-Optic Spectrum Analyzer: Temporal Response and Detection of Pulsed Signals.

DTIC Science & Technology

1986-12-01

ACOUSTO - OPTIC SPECTRUM ANALYZER: TEMPORAL RESPONSE AND I/i DETECTION OF PULSED SIGUALS(U) DEFENCE RESEARCH ESTABLISHMENT OTTANA (ONTARIO) J...8217:. -.....:.-...............--.. - ---:-..--.-..,. ,: i’,.. IJT~c FILE C P National Defe’ se + Deence nationale 0 0 ACOUSTO - OPTIC SPECTRUM ANALYZER: TEMPORAL RESPONSE AND DETECTION 0 OF PULSED...Ottawa |S, .±~ |-----------------------..,---.-- -- - - - rNatiorna! Defen~se Deterice r dornale ACOUSTO - OPTIC SPECTRUM ANALYZER: TEMPORAL RESPONSE

Natural image sequences constrain dynamic receptive fields and imply a sparse code.

PubMed

Häusler, Chris; Susemihl, Alex; Nawrot, Martin P

2013-11-06

In their natural environment, animals experience a complex and dynamic visual scenery. Under such natural stimulus conditions, neurons in the visual cortex employ a spatially and temporally sparse code. For the input scenario of natural still images, previous work demonstrated that unsupervised feature learning combined with the constraint of sparse coding can predict physiologically measured receptive fields of simple cells in the primary visual cortex. This convincingly indicated that the mammalian visual system is adapted to the natural spatial input statistics. Here, we extend this approach to the time domain in order to predict dynamic receptive fields that can account for both spatial and temporal sparse activation in biological neurons. We rely on temporal restricted Boltzmann machines and suggest a novel temporal autoencoding training procedure. When tested on a dynamic multi-variate benchmark dataset this method outperformed existing models of this class. Learning features on a large dataset of natural movies allowed us to model spatio-temporal receptive fields for single neurons. They resemble temporally smooth transformations of previously obtained static receptive fields and are thus consistent with existing theories. A neuronal spike response model demonstrates how the dynamic receptive field facilitates temporal and population sparseness. We discuss the potential mechanisms and benefits of a spatially and temporally sparse representation of natural visual input. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

A unified approach to the study of temporal, correlational, and rate coding.

PubMed

Panzeri, S; Schultz, S R

2001-06-01

We demonstrate that the information contained in the spike occurrence times of a population of neurons can be broken up into a series of terms, each reflecting something about potential coding mechanisms. This is possible in the coding regime in which few spikes are emitted in the relevant time window. This approach allows us to study the additional information contributed by spike timing beyond that present in the spike counts and to examine the contributions to the whole information of different statistical properties of spike trains, such as firing rates and correlation functions. It thus forms the basis for a new quantitative procedure for analyzing simultaneous multiple neuron recordings and provides theoretical constraints on neural coding strategies. We find a transition between two coding regimes, depending on the size of the relevant observation timescale. For time windows shorter than the timescale of the stimulus-induced response fluctuations, there exists a spike count coding phase, in which the purely temporal information is of third order in time. For time windows much longer than the characteristic timescale, there can be additional timing information of first order, leading to a temporal coding phase in which timing information may affect the instantaneous information rate. In this new framework, we study the relative contributions of the dynamic firing rate and correlation variables to the full temporal information, the interaction of signal and noise correlations in temporal coding, synergy between spikes and between cells, and the effect of refractoriness. We illustrate the utility of the technique by analyzing a few cells from the rat barrel cortex.

Temporal dynamics of online petitions

PubMed Central

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. PMID:28542492

A method for analyzing temporal patterns of variability of a time series from Poincare plots.

PubMed

Fishman, Mikkel; Jacono, Frank J; Park, Soojin; Jamasebi, Reza; Thungtong, Anurak; Loparo, Kenneth A; Dick, Thomas E

2012-07-01

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.

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

NASA Astrophysics Data System (ADS)

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.

Spatially uniform but temporally variable bacterioplankton in a semi-enclosed coastal area.

PubMed

Meziti, Alexandra; Kormas, Konstantinos A; Moustaka-Gouni, Maria; Karayanni, Hera

2015-07-01

Studies focusing on the temporal and spatial dynamics of bacterioplankton communities within littoral areas undergoing direct influences from the coast are quite limited. In addition, they are more complicated to resolve compared to communities in the open ocean. In order to elucidate the effects of spatial vs. temporal variability on bacterial communities in a highly land-influenced semi-enclosed gulf, surface bacterioplankton communities from five coastal sites in Igoumenitsa Gulf (Ionian Sea, Greece) were analyzed over a nine-month period using 16S rDNA 454-pyrosequencing. Temporal differences were more pronounced than spatial ones, with lower diversity indices observed during the summer months. During winter and early spring, bacterial communities were dominated by SAR11 representatives, while this pattern changed in May when they were abruptly replaced by members of Flavobacteriales, Pseudomonadales, and Alteromonadales. Additionally, correlation analysis showed high negative correlations between the presence of SAR11 OTUs in relation to temperature and sunlight that might have driven, directly or indirectly, the disappearance of these OTUs in the summer months. The dominance of SAR11 during the winter months further supported the global distribution of the clade, not only in the open-sea, but also in coastal systems. This study revealed that specific bacteria exhibited distinct succession patterns in an anthropogenic-impacted coastal system. The major bacterioplankton component was represented by commonly found marine bacteria exhibiting seasonal dynamics, while freshwater and terrestrial-related phylotypes were absent. Copyright © 2015 Elsevier GmbH. All rights reserved.

Application of biospeckles for assessment of structural and cellular changes in muscle tissue

NASA Astrophysics Data System (ADS)

Maksymenko, Oleksandr P.; Muravsky, Leonid I.; Berezyuk, Mykola I.

2015-09-01

A modified spatial-temporal speckle correlation technique for operational assessment of structural changes in muscle tissues after slaughtering is considered. Coefficient of biological activity as a quantitative indicator of structural changes of biochemical processes in biological tissues is proposed. The experimental results have shown that this coefficient properly evaluates the biological activity of pig and chicken muscle tissue samples. Studying the degradation processes in muscle tissue during long-time storage in a refrigerator by measuring the spatial-temporal dynamics of biospeckle patterns is carried out. The reduction of the bioactivity level of refrigerated muscle tissue samples connected with the initiation of muscle fiber cracks and ruptures, reduction of sarcomeres, nuclei deformation, nuclear chromatin diminishing, and destruction of mitochondria is analyzed.

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

PubMed

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

Dynamic analysis and assessment for sustainable development.

PubMed

Shi, Xiao-qing

2002-01-01

The assessment of sustainable development is crucial for constituting sustainable development strategies. Assessment methods that exist so far usually only use an indicator system for making sustainable judgement. These indicators rarely reflect dynamic characteristics. However, sustainable development is influenced by changes in the social-economic system and in the eco-environmental system at different times. Besides the spatial character, sustainable development has a temporal character that can not be neglected; therefore the research system should also be dynamic. This paper focuses on this dynamic trait, so that the assessment results obtained provide more information for judgements in decision-making processes. Firstly the dynamic characteristics of sustainable development are analyzed, which point to a track of sustainable development that is an upward undulating curve. According to the dynamic character and the development rules of a social, economic and ecological system, a flexible assessment approach that is based on tendency analysis, restrictive conditions and a feedback system is then proposed for sustainable development.

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

NASA Astrophysics Data System (ADS)

Gollas, Frank; Tetzlaff, Ronald

2009-05-01

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

Sensitivity evaluation of dynamic speckle activity measurements using clustering methods.

PubMed

Etchepareborda, Pablo; Federico, Alejandro; Kaufmann, Guillermo H

2010-07-01

We evaluate and compare the use of competitive neural networks, self-organizing maps, the expectation-maximization algorithm, K-means, and fuzzy C-means techniques as partitional clustering methods, when the sensitivity of the activity measurement of dynamic speckle images needs to be improved. The temporal history of the acquired intensity generated by each pixel is analyzed in a wavelet decomposition framework, and it is shown that the mean energy of its corresponding wavelet coefficients provides a suited feature space for clustering purposes. The sensitivity obtained by using the evaluated clustering techniques is also compared with the well-known methods of Konishi-Fujii, weighted generalized differences, and wavelet entropy. The performance of the partitional clustering approach is evaluated using simulated dynamic speckle patterns and also experimental data.

How Does the Electron Dynamics Affect the Reconnection Rate in a Typical Reconnection Layer?

NASA Technical Reports Server (NTRS)

Hesse, Michael

2009-01-01

The question of whether the microscale controls the macroscale or vice-versa remains one of the most challenging problems in plasmas. A particular topic of interest within this context is collisionless magnetic reconnection, where both points of views are espoused by different groups of researchers. This presentation will focus on this topic. We will begin by analyzing the properties of electron diffusion region dynamics both for guide field and anti-parallel reconnection, and how they can be scaled to different inflow conditions. As a next step, we will study typical temporal variations of the microscopic dynamics with the objective of understanding the potential for secular changes to the macroscopic system. The research will be based on a combination of analytical theory and numerical modeling.

Node Survival in Networks under Correlated Attacks

PubMed Central

Hao, Yan; Armbruster, Dieter; Hütt, Marc-Thorsten

2015-01-01

We study the interplay between correlations, dynamics, and networks for repeated attacks on a socio-economic network. As a model system we consider an insurance scheme against disasters that randomly hit nodes, where a node in need receives support from its network neighbors. The model is motivated by gift giving among the Maasai called Osotua. Survival of nodes under different disaster scenarios (uncorrelated, spatially, temporally and spatio-temporally correlated) and for different network architectures are studied with agent-based numerical simulations. We find that the survival rate of a node depends dramatically on the type of correlation of the disasters: Spatially and spatio-temporally correlated disasters increase the survival rate; purely temporally correlated disasters decrease it. The type of correlation also leads to strong inequality among the surviving nodes. We introduce the concept of disaster masking to explain some of the results of our simulations. We also analyze the subsets of the networks that were activated to provide support after fifty years of random disasters. They show qualitative differences for the different disaster scenarios measured by path length, degree, clustering coefficient, and number of cycles. PMID:25932635

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

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

ERIC Educational Resources Information Center

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.…

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Chaotic dynamics of flexible Euler-Bernoulli beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Awrejcewicz, J., E-mail: awrejcew@p.lodz.pl; Krysko, A. V., E-mail: anton.krysko@gmail.com; Kutepov, I. E., E-mail: iekutepov@gmail.com

2013-12-15

Mathematical modeling and analysis of spatio-temporal chaotic dynamics of flexible simple and curved Euler-Bernoulli beams are carried out. The Kármán-type geometric non-linearity is considered. Algorithms reducing partial differential equations which govern the dynamics of studied objects and associated boundary value problems are reduced to the Cauchy problem through both Finite Difference Method with the approximation of O(c{sup 2}) and Finite Element Method. The obtained Cauchy problem is solved via the fourth and sixth-order Runge-Kutta methods. Validity and reliability of the results are rigorously discussed. Analysis of the chaotic dynamics of flexible Euler-Bernoulli beams for a series of boundary conditions ismore » carried out with the help of the qualitative theory of differential equations. We analyze time histories, phase and modal portraits, autocorrelation functions, the Poincaré and pseudo-Poincaré maps, signs of the first four Lyapunov exponents, as well as the compression factor of the phase volume of an attractor. A novel scenario of transition from periodicity to chaos is obtained, and a transition from chaos to hyper-chaos is illustrated. In particular, we study and explain the phenomenon of transition from symmetric to asymmetric vibrations. Vibration-type charts are given regarding two control parameters: amplitude q{sub 0} and frequency ω{sub p} of the uniformly distributed periodic excitation. Furthermore, we detected and illustrated how the so called temporal-space chaos is developed following the transition from regular to chaotic system dynamics.« less

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

NASA/MSFC FY91 Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Leslie, Fred W. (Editor)

1991-01-01

The reports presented at the annual Marshall Research Review of Earth Science and Applications are compiled. The following subject areas are covered: understanding of atmospheric processes in a variety of spatial and temporal scales; measurements of geophysical parameters; measurements on a global scale from space; the Mission to Planet Earth Program (comprised of and Earth Observation System and the scientific strategy to analyze these data); and satellite data analysis and fundamental studies of atmospheric dynamics.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition.

PubMed

Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E

2016-07-15

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

PubMed

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis.

PubMed

Zinchenko, Oksana; Yaple, Zachary A; Arsalidou, Marie

2018-01-01

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Digital micromirror device camera with per-pixel coded exposure for high dynamic range imaging.

PubMed

Feng, Wei; Zhang, Fumin; Wang, Weijing; Xing, Wei; Qu, Xinghua

2017-05-01

In this paper, we overcome the limited dynamic range of the conventional digital camera, and propose a method of realizing high dynamic range imaging (HDRI) from a novel programmable imaging system called a digital micromirror device (DMD) camera. The unique feature of the proposed new method is that the spatial and temporal information of incident light in our DMD camera can be flexibly modulated, and it enables the camera pixels always to have reasonable exposure intensity by DMD pixel-level modulation. More importantly, it allows different light intensity control algorithms used in our programmable imaging system to achieve HDRI. We implement the optical system prototype, analyze the theory of per-pixel coded exposure for HDRI, and put forward an adaptive light intensity control algorithm to effectively modulate the different light intensity to recover high dynamic range images. Via experiments, we demonstrate the effectiveness of our method and implement the HDRI on different objects.

Temporal Clustering of Regional-Scale Extreme Precipitation Events in Southern Switzerland

NASA Astrophysics Data System (ADS)

Barton, Yannick; Giannakaki, Paraskevi; Von Waldow, Harald; Chevalier, Clément; Pfhal, Stephan; Martius, Olivia

2017-04-01

Temporal clustering of extreme precipitation events on subseasonal time scales is a form of compound extremes and is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering. An observation-based gridded precipitation dataset of Swiss daily rainfall sums and ECMWF reanalysis datasets are used. To analyze the clustering in the precipitation time series a modified version of Ripley's K function is used. It determines the average number of extreme events in a time period, to characterize temporal clustering on subseasonal time scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on subseasonal time scales during the fall season. Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upperlevel breaking Rossby wave over western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.

[Three-dimension temporal and spatial dynamics of soil water for the artificial vegetation in the center of Taklimakan desert under saline water drip-irrigation].

PubMed

Ding, Xin-yuan; Zhou, Zhi-bin; Xu, Xin-wen; Lei, Jia-qiang; Lu, Jing-jing; Ma, Xue-xi; Feng, Xiao

2015-09-01

Three-dimension temporal and spatial dynamics of the soil water characteristics during four irrigating cycles of months from April to July for the artificial vegetation in the center of Taklimakan Desert under saline water drip-irrigation had been analyzed by timely measuring the soil water content in horizontal and vertical distances 60 cm and 120 cm away from the irrigating drips, respectively. Periodic spatial and temporal variations of soil water content were observed. When the precipitation effect was not considered, there were no significant differences in the characteristics of soil water among the irrigation intervals in different months, while discrepancies were obvious in the temporal and spatial changes of soil moisture content under the conditions of rainfall and non-rainfall. When it referred to the temporal changes of soil water, it was a little higher in April but a bit lower in July, and the soil water content in June was the highest among four months because some remarkable events of precipitation happened in this month. However, as a whole, the content of soil moisture was reduced as months (from April to July) went on and it took a decreasing tendency along with days (1-15 d) following a power function. Meanwhile, the characteristics of soil water content displayed three changeable stages in an irrigation interval. When it referred to the spatial distributions of soil water, the average content of soil moisture was reduced along with the horizontal distance following a linear regression function, and varied with double peaks along with the vertical distance. In addition, the spatial distribution characteristics of the soil water were not influenced by the factors of precipitation and irrigating time but the physical properties of soil.

Spatio-Temporal Fluctuations of Neural Dynamics in Mild Cognitive Impairment and Alzheimer's Disease.

PubMed

Poza, Jesús; Gómez, Carlos; García, María; Tola-Arribas, Miguel A; Carreres, Alicia; Cano, Mónica; Hornero, Roberto

2017-01-01

An accurate characterization of neural dynamics in mild cognitive impairment (MCI) is of paramount importance to gain further insights into the underlying neural mechanisms in Alzheimer's disease (AD). Nevertheless, there has been relatively little research on brain dynamics in prodromal AD. As a consequence, its neural substrates remain unclear. In the present research, electroencephalographic (EEG) recordings from patients with dementia due to AD, subjects with MCI due to AD and healthy controls (HC) were analyzed using relative power (RP) in conventional EEG frequency bands and a novel parameter useful to explore the spatio-temporal fluctuations of neural dynamics: the spectral flux (SF). Our results suggest that dementia due to AD is associated with a significant slowing of EEG activity and several significant alterations in spectral fluctuations at low (i.e. theta) and high (i.e. beta and gamma) frequency bands compared to HC (p < 0.05). Furthermore, subjects with MCI due to AD exhibited a specific frequency-dependent pattern of spatio-temporal abnormalities, which can help identify neural mechanisms involved in cognitive impairment preceding AD. Classification analyses using linear discriminant analysis with a leave-one-out cross-validation procedure showed that the combination of RP and within-electrode SF at the beta band was useful to obtain a 77.3 % of accuracy to discriminate between HC and AD patients. In the case of comparison between HC and MCI subjects, the classification accuracy reached a value of 79.2 %, combining within-electrode SF at beta and gamma bands. SF has proven to be a useful measure to obtain an original description of brain dynamics at different stages of AD. Consequently, SF may contribute to gain a more comprehensive understanding into neural substrates underlying MCI, as well as to develop potential early AD biomarkers. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

PubMed

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Optogenetic Platform for Real-Time, Single-Cell Interrogation of Stochastic Transcriptional Regulation.

PubMed

Rullan, Marc; Benzinger, Dirk; Schmidt, Gregor W; Milias-Argeitis, Andreas; Khammash, Mustafa

2018-05-17

Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae. We show that transcriptional activation and deactivation are fast and memoryless. By analyzing the temporal activity of individual cells, we found that transcription occurs in bursts, whose duration and timing are modulated by transcription factor activity. Using our platform, we regulated transcription via light-driven feedback loops at the single-cell level. Feedback markedly reduced cell-to-cell variability and led to qualitative differences in cellular transcriptional dynamics. Our platform establishes a flexible method for studying transcriptional dynamics in single cells. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

GIS-based analysis and modelling with empirical and remotely-sensed data on coastline advance and retreat

NASA Astrophysics Data System (ADS)

Ahmad, Sajid Rashid

With the understanding that far more research remains to be done on the development and use of innovative and functional geospatial techniques and procedures to investigate coastline changes this thesis focussed on the integration of remote sensing, geographical information systems (GIS) and modelling techniques to provide meaningful insights on the spatial and temporal dynamics of coastline changes. One of the unique strengths of this research was the parameterization of the GIS with long-term empirical and remote sensing data. Annual empirical data from 1941--2007 were analyzed by the GIS, and then modelled with statistical techniques. Data were also extracted from Landsat TM and ETM+ images. The band ratio method was used to extract the coastlines. Topographic maps were also used to extract digital map data. All data incorporated into ArcGIS 9.2 were analyzed with various modules, including Spatial Analyst, 3D Analyst, and Triangulated Irregular Networks. The Digital Shoreline Analysis System was used to analyze and predict rates of coastline change. GIS results showed the spatial locations along the coast that will either advance or retreat over time. The linear regression results highlighted temporal changes which are likely to occur along the coastline. Box-Jenkins modelling procedures were utilized to determine statistical models which best described the time series (1941--2007) of coastline change data. After several iterations and goodness-of-fit tests, second-order spatial cyclic autoregressive models, first-order autoregressive models and autoregressive moving average models were identified as being appropriate for describing the deterministic and random processes operating in Guyana's coastal system. The models highlighted not only cyclical patterns in advance and retreat of the coastline, but also the existence of short and long-term memory processes. Long-term memory processes could be associated with mudshoal propagation and stabilization while short-term memory processes were indicative of transitory hydrodynamic and other processes. An innovative framework for a spatio-temporal information-based system (STIBS) was developed. STIBS incorporated diverse datasets within a GIS, dynamic computer-based simulation models, and a spatial information query and graphical subsystem. Tests of the STIBS proved that it could be used to simulate and visualize temporal variability in shifting morphological states of the coastline.

Cyclicity of Suicides May Be Modulated by Internal or External - 11-Year Cycles: An Example of Suicide Rates in Finland

NASA Astrophysics Data System (ADS)

Dimitrov, B. D.; Atanassova, P. A.; Rachkova, M. I.

2009-12-01

Multicomponent cyclicity in monthly suicides (periods T = 18, 46 and 198 months) was found and close similarity with heliogeophysical activity (HGA) suggested by Dimitrov in 1999. The current report aimed at scrutinizing the results on suicide annual cyclicity (seasonality) in Slovenia as reported by Oravecz et al in 2007 as well as at analyzing suicide data from Finland in this regard. We postulated that: (i) trans-year (12-24 months) or far-trans-year long-term cycles of suicides might interfere with their seasonality; and (ii) associations to environmental factors with alike cyclicity (e.g. HGA, temperature) could exist. Annual suicide incidence from Oulu, Finland over years 1987-1999 was analyzed. Annual data on solar activity (sunspot index Rz or Wolf number), planetary geomagnetic activity (aa-index) and local daily mean temperatures were used. The exploration of underlying chronomes (time structures) was done by periodogram regression analysis with trigonometric approximation. We analyzed temporal dynamics, revealed cyclicity, decomposed and reconstructed significant cycles and correlated the time series data. Suicide seasonality in Slovenia during the years 1971-2002 (n=384 months, peak May-June) was considered and, although some discrepancies and methodological weaknesses were suspected, we further hypothesized about trans-year and/or longer (far-transyear) cyclic components. Suicide incidence data from Finland indicated that the 12.5-year cyclic component (or trend) was almost parallel (coherent) to the cyclic heliogeophysical parameters and similar to local decreasing temperature dynamics. Also, 8-year and 24.5-year cycles were revealed. A correlation between the 12.5-year suicide cycle and 11-year solar cycle was found (R=0.919, p=0.000009). Above findings on cyclicity and temporal correlations of suicides with cyclic environmental factors, even being still preliminary, might not only allow for further more specific analyses. They might also corroborate to improved forecasting and prevention and confer a better understanding of suicide dynamics and aetiology.

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

NASA Astrophysics Data System (ADS)

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.

Automated Video Based Facial Expression Analysis of Neuropsychiatric Disorders

PubMed Central

Wang, Peng; Barrett, Frederick; Martin, Elizabeth; Milanova, Marina; Gur, Raquel E.; Gur, Ruben C.; Kohler, Christian; Verma, Ragini

2008-01-01

Deficits in emotional expression are prominent in several neuropsychiatric disorders, including schizophrenia. Available clinical facial expression evaluations provide subjective and qualitative measurements, which are based on static 2D images that do not capture the temporal dynamics and subtleties of expression changes. Therefore, there is a need for automated, objective and quantitative measurements of facial expressions captured using videos. This paper presents a computational framework that creates probabilistic expression profiles for video data and can potentially help to automatically quantify emotional expression differences between patients with neuropsychiatric disorders and healthy controls. Our method automatically detects and tracks facial landmarks in videos, and then extracts geometric features to characterize facial expression changes. To analyze temporal facial expression changes, we employ probabilistic classifiers that analyze facial expressions in individual frames, and then propagate the probabilities throughout the video to capture the temporal characteristics of facial expressions. The applications of our method to healthy controls and case studies of patients with schizophrenia and Asperger’s syndrome demonstrate the capability of the video-based expression analysis method in capturing subtleties of facial expression. Such results can pave the way for a video based method for quantitative analysis of facial expressions in clinical research of disorders that cause affective deficits. PMID:18045693

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

NASA Astrophysics Data System (ADS)

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.

Charging of a conducting sphere in a weakly ionized collisional plasma: Temporal dynamics and stationary state

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grach, V. S., E-mail: vsgrach@app.sci-nnov.ru; Garasev, M. A.

2015-07-15

We consider the interaction of a isolated conducting sphere with a collisional weakly ionized plasma in an external field. We assume that the plasma consists of two species of ions neglecting of electrons. We take into account charging of the sphere due to sedimentation of plasma ions on it, the field of the sphere charge and the space charge, as well as recombination and molecular diffusion. The nonstationary problem of interaction of the sphere with the surrounding plasma is solved numerically. The temporal dynamics of the sphere charge and plasma perturbations is analyzed, as well as the properties of themore » stationary state. It is shown that the duration of transient period is determined by the recombination time and by the reverse conductivity of ions. The temporal dynamics of the sphere charge and plasma perturbations is determined by the intensity of recombination processes relative to the influence of the space charge field and diffusion. The stationary absolute value of the sphere charge increases linearly with the external electric field, decreases with the relative intensity of recombination processes and increases in the presence of substantial diffusion. The scales of the perturbed region in the plasma are determined by the radius of the sphere, the external field, the effect of diffusion, and the relative intensity of recombination processes. In the limiting case of the absence of molecular diffusion and a strong external field, the properties of the stationary state coincide with those obtained earlier as a result of approximate solution.« less

Spatial-temporal dynamics of NDVI and Chl-a concentration from 1998 to 2009 in the East coastal zone of China: integrating terrestrial and oceanic components.

PubMed

Hou, Xiyong; Li, Mingjie; Gao, Meng; Yu, Liangju; Bi, Xiaoli

2013-01-01

Annual normalized difference vegetation index (NDVI) and chlorophyll-a (Chl-a) concentration are the most important large-scale indicators of terrestrial and oceanic ecosystem net primary productivity. In this paper, the Sea-viewing Wide Field-of-view Sensor level 3 standard mapped image annual products from 1998 to 2009 are used to study the spatial-temporal characters of terrestrial NDVI and oceanic Chl-a concentration on two sides of the coastline of China by using the methods of mean value (M), coefficient of variation (CV), the slope of unary linear regression model (Slope), and the Hurst index (H). In detail, we researched and analyzed the spatial-temporal dynamics, the longitudinal zonality and latitudinal zonality, the direction, intensity, and persistency of historical changes. The results showed that: (1) spatial patterns of M and CV between NDVI and Chl-a concentration from 1998 to 2009 were very different. The dynamic variation of terrestrial NDVI was much mild, while the variation of oceanic Chl-a concentration was relatively much larger; (2) distinct longitudinal zonality was found for Chl-a concentration and NDVI due to their hypersensitivity to the distance to shoreline, and strong latitudinal zonality existed for Chl-a concentration while terrestrial NDVI had a very weak latitudinal zonality; (3) overall, the NDVI showed a slight decreasing trend while the Chl-a concentration showed a significant increasing trend in the past 12 years, and both of them exhibit strong self-similarity and long-range dependence which indicates opposite future trends between land and ocean.

Stochastic optimal control of ultradiffusion processes with application to dynamic portfolio management

NASA Astrophysics Data System (ADS)

Marcozzi, Michael D.

2008-12-01

We consider theoretical and approximation aspects of the stochastic optimal control of ultradiffusion processes in the context of a prototype model for the selling price of a European call option. Within a continuous-time framework, the dynamic management of a portfolio of assets is effected through continuous or point control, activation costs, and phase delay. The performance index is derived from the unique weak variational solution to the ultraparabolic Hamilton-Jacobi equation; the value function is the optimal realization of the performance index relative to all feasible portfolios. An approximation procedure based upon a temporal box scheme/finite element method is analyzed; numerical examples are presented in order to demonstrate the viability of the approach.

Monitoring of endogenous carbon monoxide dynamics in human breath by tunable diode laser

NASA Astrophysics Data System (ADS)

Stepanov, Eugene V.; Daraselia, Mikhail V.; Zyrianov, Pavel V.; Shulagin, Yurii A.; Skrupskii, Vladimir A.

1996-01-01

High sensitive CO gas analyzer based on tunable diode laser (TDL) was used as a real time monitor of endogenous carbon monoxide in a set of breath physiology experiments. The measurements of the CO content dynamics in exhaled air with 10 ppb sensitivity were attended with detection of carbon dioxide and O2 in breath, lung ventilation parameters, heart rate and blood analysis using conventional techniques. Temporal variations of endogenous CO in human breath caused by hyperoxia, hypoxia, hyperventilation and sport loading were first studied in real time. Scattering of the CO variation time constants was observed for different tested persons. Possible reasons for this scattering related with the organisms' physiology peculiarities are discussed.

Modelling and investigation of partial wetting surfaces for drop dynamics using lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Pravinraj, T.; Patrikar, Rajendra

2017-07-01

Partial wetting surfaces and its influence on the droplet movement of micro and nano scale being contemplated for many useful applications. The dynamics of the droplet usually analyzed with a multiphase lattice Boltzmann method (LBM). In this paper, the influence of partial wetting surface on the dynamics of droplet is systematically analyzed for various cases. Splitting of droplets due to chemical gradient of the surface is studied and analyses of splitting time for various widths of the strips for different Weber numbers are computed. With the proposed model one can tune the splitting volume and time by carefully choosing a strip width and droplet position. The droplet spreading on chemically heterogeneous surfaces shows that the spreading can be controlled not only by parameters of Weber number but also by tuning strip width ratio. The transportation of the droplet from hydrophobic surface to hydrophilic surface due to chemical gradient is simulated and analyzed using our hybrid thermodynamic-image processing technique. The results prove that with the progress of time the surface free energy decreases with increase in spreading area. Finally, the transportation of a droplet on microstructure gradient is demonstrated. The model explains the temporal behaviour of droplet during the spreading, recoiling and translation along with tracking of contact angle hysteresis phenomenon.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland

PubMed Central

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. PMID:26222069

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland.

PubMed

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.

Noise-induced hearing loss increases the temporal precision of complex envelope coding by auditory-nerve fibers

PubMed Central

Henry, Kenneth S.; Kale, Sushrut; Heinz, Michael G.

2014-01-01

While changes in cochlear frequency tuning are thought to play an important role in the perceptual difficulties of people with sensorineural hearing loss (SNHL), the possible role of temporal processing deficits remains less clear. Our knowledge of temporal envelope coding in the impaired cochlea is limited to two studies that examined auditory-nerve fiber responses to narrowband amplitude modulated stimuli. In the present study, we used Wiener-kernel analyses of auditory-nerve fiber responses to broadband Gaussian noise in anesthetized chinchillas to quantify changes in temporal envelope coding with noise-induced SNHL. Temporal modulation transfer functions (TMTFs) and temporal windows of sensitivity to acoustic stimulation were computed from 2nd-order Wiener kernels and analyzed to estimate the temporal precision, amplitude, and latency of envelope coding. Noise overexposure was associated with slower (less negative) TMTF roll-off with increasing modulation frequency and reduced temporal window duration. The results show that at equal stimulus sensation level, SNHL increases the temporal precision of envelope coding by 20–30%. Furthermore, SNHL increased the amplitude of envelope coding by 50% in fibers with CFs from 1–2 kHz and decreased mean response latency by 0.4 ms. While a previous study of envelope coding demonstrated a similar increase in response amplitude, the present study is the first to show enhanced temporal precision. This new finding may relate to the use of a more complex stimulus with broad frequency bandwidth and a dynamic temporal envelope. Exaggerated neural coding of fast envelope modulations may contribute to perceptual difficulties in people with SNHL by acting as a distraction from more relevant acoustic cues, especially in fluctuating background noise. Finally, the results underscore the value of studying sensory systems with more natural, real-world stimuli. PMID:24596545

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions.

PubMed

Saha, Tanumoy; Rathmann, Isabel; Galic, Milos

2017-07-11

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways.

PubMed

Hardy, Simon; Robillard, Pierre N

2008-01-15

Cellular signaling networks are dynamic systems that propagate and process information, and, ultimately, cause phenotypical responses. Understanding the circuitry of the information flow in cells is one of the keys to understanding complex cellular processes. The development of computational quantitative models is a promising avenue for attaining this goal. Not only does the analysis of the simulation data based on the concentration variations of biological compounds yields information about systemic state changes, but it is also very helpful for obtaining information about the dynamics of signal propagation. This article introduces a new method for analyzing the dynamics of signal propagation in signaling pathways using Petri net theory. The method is demonstrated with the Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) regulation network. The results constitute temporal information about signal propagation in the network, a simplified graphical representation of the network and of the signal propagation dynamics and a characterization of some signaling routes as regulation motifs.

Probabilistic density function method for nonlinear dynamical systems driven by colored noise.

PubMed

Barajas-Solano, David A; Tartakovsky, Alexandre M

2016-05-01

We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integrodifferential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified large-eddy-diffusivity (LED) closure. In contrast to the classical LED closure, the proposed closure accounts for advective transport of the PDF in the approximate temporal deconvolution of the integrodifferential equation. In addition, we introduce the generalized local linearization approximation for deriving a computable PDF equation in the form of a second-order partial differential equation. We demonstrate that the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary autocorrelation time. We apply the proposed PDF method to analyze a set of Kramers equations driven by exponentially autocorrelated Gaussian colored noise to study nonlinear oscillators and the dynamics and stability of a power grid. Numerical experiments show the PDF method is accurate when the noise autocorrelation time is either much shorter or longer than the system's relaxation time, while the accuracy decreases as the ratio of the two timescales approaches unity. Similarly, the PDF method accuracy decreases with increasing standard deviation of the noise.

Dynamic functional connectivity and its behavioral correlates beyond vigilance.

PubMed

Patanaik, Amiya; Tandi, Jesisca; Ong, Ju Lynn; Wang, Chenhao; Zhou, Juan; Chee, Michael W L

2018-04-25

Fluctuations in resting-state functional connectivity and global signal have been found to correspond with vigilance fluctuations, but their associations with other behavioral measures are unclear. We evaluated 52 healthy adolescents after a week of adequate sleep followed by five nights of sleep restriction to unmask inter-individual differences in cognition and mood. Resting state scans obtained at baseline only, analyzed using sliding window analysis, consistently yielded two polar dynamic functional connectivity states (DCSs) corresponding to previously reported 'low arousal' and 'high arousal' states. We found that the relative temporal preponderance of two dynamic connectivity states (DCS) in well-rested participants, indexed by a median split of participants, based on the relative time spent in these DCS, revealed highly significant group differences in vigilance at baseline and its decline following multiple nights of sleep restriction. Group differences in processing speed and working memory following manipulation but not at baseline suggest utility of DCS in predicting cognitive vulnerabilities unmasked by a stressor like sleep restriction. DCS temporal predominance was uninformative about mood and sleepiness speaking to specificity in its behavioral predictions. Global signal fluctuation provided information confined to vigilance. This appears to be related to head motion, which increases during periods of low arousal. Copyright © 2018. Published by Elsevier Inc.

The calculation of weakly non-spherical cavitation bubble impact on a solid

NASA Astrophysics Data System (ADS)

Aganin, A. A.; Guseva, T. S.; Kosolapova, L. A.; Khismatullina, N. A.

2016-11-01

The effect of small spheroidal non-sphericity of a cavitation bubble touching a solid at the beginning of its collapse on its impact on the solid of a copper-nickel alloy is investigated. The impact on the solid is realized by means of a high-speed liquid jet arising at collapse on the bubble surface. The shape of the jet, its velocity and pressure are calculated by the boundary element method. The spatial and temporal characteristics of the pressure pulses on the solid surface are determined by the CIP-CUP method on dynamically adaptive grids without explicitly separating the gas-liquid interface. The solid surface layer dynamics is evaluated by the Godunov method. The results are analyzed in dimensionless variables obtained with using the water hammer pressure, the time moment and the jet-solid contact area radius at which the jet begins to spread on the solid surface. It is shown that in those dimensionless variables, the dependence of the spatial and temporal characteristics of the solid surface pressure pulses on the initial bubble shape non-sphericity is relatively small. The nonsphericity also slightly influences the main qualitative features of the dynamic processes inside the solid, whereas its effect on their quantitative characteristics can be significant.

Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

PubMed Central

Blonder, Benjamin; Dornhaus, Anna

2011-01-01

Background An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. Methodology/Findings Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. Conclusions/Significance Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales. PMID:21625450

[Spatial-temporal evolution characterization of land subsidence by multi-temporal InSAR method and GIS technology].

PubMed

Chen, Bei-Bei; Gong, Hui-Li; Li, Xiao-Juan; Lei, Kun-Chao; Duan, Guang-Yao; Xie, Jin-Rong

2014-04-01

Long-term over-exploitation of underground resources, and static and dynamic load increase year by year influence the occurrence and development of regional land subsidence to a certain extent. Choosing 29 scenes Envisat ASAR images covering plain area of Beijing, China, the present paper used the multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches, and obtained monitoring information of regional land subsidence. Under different situation of space development and utilization, the authors chose five typical settlement areas; With classified information of land-use, multi-spectral remote sensing image, and geological data, and adopting GIS spatial analysis methods, the authors analyzed the time series evolution characteristics of uneven settlement. The comprehensive analysis results suggests that the complex situations of space development and utilization affect the trend of uneven settlement; the easier the situation of space development and utilization, the smaller the settlement gradient, and the less the uneven settlement trend.

Spatial and Temporal Extent of Ion Spectral Structures at the Inner Edge of the Plasma Sheet

NASA Astrophysics Data System (ADS)

Ferradas, C.; Reeves, G. D.; Zhang, J.; Spence, H. E.; Kistler, L. M.; Larsen, B.; Skoug, R. M.; Funsten, H. O.

2017-12-01

Several ion spectral structures are observed near the inner edge of the plasma sheet and constitute the signatures of ion drift and loss in the highly dynamic environment of the inner magnetosphere. Their study helps us understand ion access and losses in this region. Several studies have found that these structures vary with geomagnetic activity, local time, and ion species, but their spatial and temporal extent remain undetermined. We use data from the Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometers onboard the Van Allen Probes to analyze the spectral structures in the energy range of 1- 50 keV. HOPE measurements on both Van Allen Probes spacecraft enable us to resolve the extent of these ion structures in space and time. As the structures respond to changes in the convection electric field on a variety of time scales, the lapping of the two spacecraft on time scales of minutes to hours helps determine their spatial and temporal evolution.

The dynamic-stimulus advantage of visual symmetry perception.

PubMed

Niimi, Ryosuke; Watanabe, Katsumi; Yokosawa, Kazuhiko

2008-09-01

It has been speculated that visual symmetry perception from dynamic stimuli involves mechanisms different from those for static stimuli. However, previous studies found no evidence that dynamic stimuli lead to active temporal processing and improve symmetry detection. In this study, four psychophysical experiments investigated temporal processing in symmetry perception using both dynamic and static stimulus presentations of dot patterns. In Experiment 1, rapid successive presentations of symmetric patterns (e.g., 16 patterns per 853 ms) produced more accurate discrimination of orientations of symmetry axes than static stimuli (single pattern presented through 853 ms). In Experiments 2-4, we confirmed that the dynamic-stimulus advantage depended upon presentation of a large number of unique patterns within a brief period (853 ms) in the dynamic conditions. Evidently, human vision takes advantage of temporal processing for symmetry perception from dynamic stimuli.

CHARACTERIZING SPATIAL AND TEMPORAL DYNAMICS: DEVELOPMENT OF A GRID-BASED WATERSHED MERCURY LOADING MODEL

EPA Science Inventory

A distributed grid-based watershed mercury loading model has been developed to characterize spatial and temporal dynamics of mercury from both point and non-point sources. The model simulates flow, sediment transport, and mercury dynamics on a daily time step across a diverse lan...

Watershed geomorphological characteristics

USGS Publications Warehouse

Fitzpatrick, Faith A.

2016-01-01

This chapter describes commonly used geomorphological characteristics that are useful for analyzing watershed-scale hydrology and sediment dynamics. It includes calculations and measurements for stream network features and areal basin characteristics that cover a range of spatial and temporal scales and dimensions of watersheds. Construction and application of longitudinal profiles are described in terms of understanding the three-dimensional development of stream networks. A brief discussion of outstanding problems and directions for future work, particularly as they relate to water-resources management, is provided. Notations with preferred units are given.

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Zheng, Rui; Hui, Pan

2017-02-01

We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered signal. We find distinct patterns in the entropy growth rate of the aggregate network at different memory scales for time series with different dynamics ranging from white noise, 1/f noise, autoregressive process, periodic to chaotic dynamics. Interestingly, for a chaotic time series, an exponential scaling emerges in the memory entropy analysis. We demonstrate that the memory exponent can successfully characterize bifurcation phenomenon, and differentiate the human cardiac system in healthy and pathological states. Moreover, we show that the betweenness preference analysis of these temporal networks can further characterize dynamical systems and separate distinct electrocardiogram recordings. Our work explores the memory effect and betweenness preference in temporal networks constructed from time series data, providing a new perspective to understand the underlying dynamical systems.

Quasi 18 h wave activity in ground-based observed mesospheric H2O over Bern, Switzerland

NASA Astrophysics Data System (ADS)

Lainer, Martin; Hocke, Klemens; Rüfenacht, Rolf; Kämpfer, Niklaus

2017-12-01

Observations of oscillations in the abundance of middle-atmospheric trace gases can provide insight into the dynamics of the middle atmosphere. Long-term, high-temporal-resolution and continuous measurements of dynamical tracers within the strato- and mesosphere are rare but would facilitate better understanding of the impact of atmospheric waves on the middle atmosphere. Here we report on water vapor measurements from the ground-based microwave radiometer MIAWARA (MIddle Atmospheric WAter vapor RAdiometer) located close to Bern during two winter periods of 6 months from October to March. Oscillations with periods between 6 and 30 h are analyzed in the pressure range 0.02-2 hPa. Seven out of 12 months have the highest wave amplitudes between 15 and 21 h periods in the mesosphere above 0.1 hPa. The quasi 18 h wave signature in the water vapor tracer is studied in more detail by analyzing its temporal evolution in the mesosphere up to an altitude of 75 km. Eighteen-hour oscillations in midlatitude zonal wind observations from the microwave Doppler wind radiometer WIRA (WInd RAdiometer) could be identified within the pressure range 0.1-1 hPa during an ARISE (Atmospheric dynamics Research InfraStructure in Europe)-affiliated measurement campaign at the Observatoire de Haute-Provence (355 km from Bern) in France in 2013. The origin of the observed upper-mesospheric quasi 18 h oscillations is uncertain and could not be determined with our available data sets. Possible drivers could be low-frequency inertia-gravity waves or a nonlinear wave-wave interaction between the quasi 2-day wave and the diurnal tide.

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

USDA-ARS?s Scientific Manuscript database

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...

Temporal, spatial, and body size effects on growth rates of loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic

USGS Publications Warehouse

Bjorndal, Karen A.; Schroeder, Barbara A.; Foley, Allen M.; Witherington, Blair E.; Bresette, Michael; Clark, David; Herren, Richard M.; Arendt, Michael D.; Schmid, Jeffrey R.; Meylan, Anne B.; Meylan, Peter A.; Provancha, Jane A.; Hart, Kristen M.; Lamont, Margaret M.; Carthy, Raymond R.; Bolten, Alan B.

2013-01-01

In response to a call from the US National Research Council for research programs to combine their data to improve sea turtle population assessments, we analyzed somatic growth data for Northwest Atlantic (NWA) loggerhead sea turtles (Caretta caretta) from 10 research programs. We assessed growth dynamics over wide ranges of geography (9–33°N latitude), time (1978–2012), and body size (35.4–103.3 cm carapace length). Generalized additive models revealed significant spatial and temporal variation in growth rates and a significant decline in growth rates with increasing body size. Growth was more rapid in waters south of the USA (<24°N) than in USA waters. Growth dynamics in southern waters in the NWA need more study because sample size was small. Within USA waters, the significant spatial effect in growth rates of immature loggerheads did not exhibit a consistent latitudinal trend. Growth rates declined significantly from 1997 through 2007 and then leveled off or increased. During this same interval, annual nest counts in Florida declined by 43 % (Witherington et al. in Ecol Appl 19:30–54, 2009) before rebounding. Whether these simultaneous declines reflect responses in productivity to a common environmental change should be explored to determine whether somatic growth rates can help interpret population trends based on annual counts of nests or nesting females. Because of the significant spatial and temporal variation in growth rates, population models of NWA loggerheads should avoid employing growth data from restricted spatial or temporal coverage to calculate demographic metrics such as age at sexual maturity.

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran.

PubMed

Ghaemi, Z; Alimohammadi, A; Farnaghi, M

2018-04-20

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.

Underestimation of myocardial blood flow by dynamic perfusion CT: Explanations by two-compartment model analysis and limited temporal sampling of dynamic CT.

PubMed

Ishida, Masaki; Kitagawa, Kakuya; Ichihara, Takashi; Natsume, Takahiro; Nakayama, Ryohei; Nagasawa, Naoki; Kubooka, Makiko; Ito, Tatsuro; Uno, Mio; Goto, Yoshitaka; Nagata, Motonori; Sakuma, Hajime

2016-01-01

Previous studies using dynamic perfusion CT and volume perfusion CT (VPCT) software consistently underestimated the stress myocardial blood flow (MBF) in normal myocardium to be 1.1-1.4 ml/min/g, whilst the O 15-water PET studies demonstrated the normal stress MBF of 3-5 ml/min/g. We hypothesized that the MBF determined by VPCT (MBF-VPCT) is actually presenting the blood-to-myocardium transfer constant, K1. In this study, we determined K1 using Patlak plot (K1-Patlak) and compared the results with MBF-VPCT. 17 patients (66 ± 9 years, 7 males) with suspected coronary artery disease (CAD) underwent stress dynamic perfusion CT, followed by rest coronary CT angiography (CTA). Arterial input and myocardial output curves were analyzed with Patlak plot to quantify myocardial K1. Significant CAD was defined as >50% stenosis on CTA. A simulation study was also performed to investigate the influence of limited temporal sampling in dynamic CT acquisition on K1 using the undersampling data generated from MRI. There were 3 patients with normal CTA, 7 patients with non-significant CAD, and 7 patients with significant CAD. K1-patlak was 0.98 ± 0.35 (range 0.22-1.67) ml/min/g, whereas MBF-VPCT was 0.83 ± 0.23 (range 0.34-1.40) ml/min/g. There was a linear relationship between them: (MBF-VPCT) = 0.58 x (K1-patlak) + 0.27 (r(2) = 0.65, p < 0.001). The simulation study done on MRI data demonstrated that Patlak plot substantially underestimated true K1 by 41% when true K1 was 2.0 ml/min/g with the temporal sampling of 2RR for arterial input and 4RR for myocardial output functions. The results of our study are generating hypothesis that MBF-VPCT is likely to be calculating K1-patlak equivalent, not MBF. In addition, these values may be substantially underestimated because of limited temporal sampling rate. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Disrupted dynamic network reconfiguration of the language system in temporal lobe epilepsy.

PubMed

He, Xiaosong; Bassett, Danielle S; Chaitanya, Ganne; Sperling, Michael R; Kozlowski, Lauren; Tracy, Joseph I

2018-05-01

Temporal lobe epilepsy tends to reshape the language system causing maladaptive reorganization that can be characterized by task-based functional MRI, and eventually can contribute to surgical decision making processes. However, the dynamic interacting nature of the brain as a complex system is often neglected, with many studies treating the language system as a static monolithic structure. Here, we demonstrate that as a specialized and integrated system, the language network is inherently dynamic, characterized by rich patterns of regional interactions, whose transient dynamics are disrupted in patients with temporal lobe epilepsy. Specifically, we applied tools from dynamic network neuroscience to functional MRI data collected from 50 temporal lobe epilepsy patients and 30 matched healthy controls during performance of a verbal fluency task, as well as during rest. By assigning 16 language-related regions into four subsystems (i.e. bilateral frontal and temporal), we observed regional specialization in both the probability of transient interactions and the frequency of such changes, in both healthy controls and patients during task performance but not rest. Furthermore, we found that both left and right temporal lobe epilepsy patients displayed reduced interactions within the left frontal 'core' subsystem compared to the healthy controls, while left temporal lobe epilepsy patients were unique in showing enhanced interactions between the left frontal 'core' and the right temporal subsystems. Also, both patient groups displayed reduced flexibility in the transient interactions of the left temporal and right frontal subsystems, which formed the 'periphery' of the language network. Importantly, such group differences were again evident only during task condition. Lastly, through random forest regression, we showed that dynamic reconfiguration of the language system tracks individual differences in verbal fluency with superior prediction accuracy compared to traditional activation-based static measures. Our results suggest dynamic network measures may be an effective biomarker for detecting the language dysfunction associated with neurological diseases such as temporal lobe epilepsy, specifying both the type of neuronal communications that are missing in these patients and those that are potentially added but maladaptive. Further advancements along these lines, transforming how we characterize and map language networks in the brain, have a high probability of altering clinical decision making in neurosurgical centres.10.1093/brain/awy042_video1awy042media15754656112001.

Spatio-Temporal Dynamics of Exploited Groundfish Species Assemblages Faced to Environmental and Fishing Forcings: Insights from the Mauritanian Exclusive Economic Zone

PubMed Central

Kidé, Saïkou Oumar; Manté, Claude; Dubroca, Laurent; Demarcq, Hervé; Mérigot, Bastien

2015-01-01

Environmental changes and human activities can have strong impacts on biodiversity and ecosystem functioning. This study investigates how, from a quantitative point of view, simultaneously both environmental and anthropogenic factors affect species composition and abundance of exploited groundfish assemblages (i.e. target and non-target species) at large spatio-temporal scales. We aim to investigate (1) the spatial and annual stability of groundfish assemblages, (2) relationships between these assemblages and structuring factors in order to better explain the dynamic of the assemblages’ structure. The Mauritanian Exclusive Economic Zone (MEEZ) is of particular interest as it embeds a productive ecosystem due to upwelling, producing abundant and diverse resources which constitute an attractive socio-economic development. We applied the multi-variate and multi-table STATICO method on a data set consisting of 854 hauls collected during 14-years (1997–2010) from scientific trawl surveys (species abundance), logbooks of industrial fishery (fishing effort), sea surface temperature and chlorophyll a concentration as environmental variables. Our results showed that abiotic factors drove four main persistent fish assemblages. Overall, chlorophyll a concentration and sea surface temperature mainly influenced the structure of assemblages of coastal soft bottoms and those of the offshore near rocky bottoms where upwellings held. While highest levels of fishing effort were located in the northern permanent upwelling zone, effects of this variable on species composition and abundances of assemblages were relatively low, even if not negligible in some years and areas. The temporal trajectories between environmental and fishing conditions and assemblages did not match for all the entire time series analyzed in the MEEZ, but interestingly for some specific years and areas. The quantitative approach used in this work may provide to stakeholders, scientists and fishers a useful assessment for the spatio-temporal dynamics of exploited assemblages under stable or changing conditions in fishing and environment. PMID:26505198

Self-localized structures in vertical-cavity surface-emitting lasers with external feedback.

PubMed

Paulau, P V; Gomila, D; Ackemann, T; Loiko, N A; Firth, W J

2008-07-01

In this paper, we analyze a model of broad area vertical-cavity surface-emitting lasers subjected to frequency-selective optical feedback. In particular, we analyze the spatio-temporal regimes arising above threshold and the existence and dynamical properties of cavity solitons. We build the bifurcation diagram of stationary self-localized states, finding that branches of cavity solitons emerge from the degenerate Hopf bifurcations marking the homogeneous solutions with maximal and minimal gain. These branches collide in a saddle-node bifurcation, defining a maximum pump current for soliton existence that lies below the threshold of the laser without feedback. The properties of these cavity solitons are in good agreement with those observed in recent experiments.

Water-quality assessment of the largely urban blue river basin, Metropolitan Kansas City, USA, 1998 to 2007

USGS Publications Warehouse

Wilkison, D.H.; Armstrong, D.J.; Hampton, S.A.

2009-01-01

From 1998 through 2007, over 750 surface-water or bed-sediment samples in the Blue River Basin - a largely urban basin in metropolitan Kansas City - were analyzed for more than 100 anthropogenic compounds. Compounds analyzed included nutrients, fecal-indicator bacteria, suspended sediment, pharmaceuticals and personal care products. Non-point source runoff, hydrologic alterations, and numerous waste-water discharge points resulted in the routine detection of complex mixtures of anthropogenic compounds in samples from basin stream sites. Temporal and spatial variations in concentrations and loads of nutrients, pharmaceuticals, and organic wastewater compounds were observed, primarily related to a site's proximity to point-source discharges and stream-flow dynamics. ?? 2009 ASCE.

Hydrodynamic Stability Analysis of Multi-jet Effects in Swirling Jet Combustors

NASA Astrophysics Data System (ADS)

Emerson, Benjamin; Lieuwen, Tim

2016-11-01

Many practical combustion devices use multiple swirling jets to stabilize flames. However, much of the understanding of swirling jet dynamics has been generated from experimental and computational studies of single reacting, swirling jets. A smaller body of literature has begun to explore the effects of multi-jet systems and the role of jet-jet interactions on the macro-system dynamics. This work uses local temporal and spatio-temporal stability analyses to isolate the hydrodynamic interactions of multiple reacting, swirling jets, characterized by jet diameter, D, and spacing, L. The results first identify the familiar helical modes in the single jet. Comparison to the multi-jet configuration reveals these same familiar modes simultaneously oscillating in each of the jets. Jet-jet interaction is mostly limited to a spatial synchronization of each jet's oscillations at the jet spacing values analyzed here (L/D =3.5). The presence of multiple jets vs a single jet has little influence on the temporal and absolute growth rates. The biggest difference between the single and multi-jet configurations is the presence of nearly degenerate pairs of hydrodynamic modes in the multi-jet case, with one mode dominated by oscillations in the inner jet, and the other in the outer jets. The close similarity between the single and multi-jet hydrodynamics lends insight into experiments from our group.

Enhancing molecular logic through modulation of temporal and spatial constraints with quantum dot-based systems that use fluorescent (Förster) resonance energy transfer

NASA Astrophysics Data System (ADS)

Claussen, Jonathan C.; Algar, W. Russ; Hildebrandt, Niko; Susumu, Kimihiro; Ancona, Mario G.; Medintz, Igor L.

2013-10-01

Luminescent semiconductor nanocrystals or quantum dots (QDs) contain favorable photonic properties (e.g., resistance to photobleaching, size-tunable PL, and large effective Stokes shifts) that make them well-suited for fluorescence (Förster) resonance energy transfer (FRET) based applications including monitoring proteolytic activity, elucidating the effects of nanoparticles-mediated drug delivery, and analyzing the spatial and temporal dynamics of cellular biochemical processes. Herein, we demonstrate how unique considerations of temporal and spatial constraints can be used in conjunction with QD-FRET systems to open up new avenues of scientific discovery in information processing and molecular logic circuitry. For example, by conjugating both long lifetime luminescent terbium(III) complexes (Tb) and fluorescent dyes (A647) to a single QD, we can create multiple FRET lanes that change temporally as the QD acts as both an acceptor and donor at distinct time intervals. Such temporal FRET modulation creates multi-step FRET cascades that produce a wealth of unique photoluminescence (PL) spectra that are well-suited for the construction of a photonic alphabet and photonic logic circuits. These research advances in bio-based molecular logic open the door to future applications including multiplexed biosensing and drug delivery for disease diagnostics and treatment.

Automatic classification of acetowhite temporal patterns to identify precursor lesions of cervical cancer

NASA Astrophysics Data System (ADS)

Gutiérrez-Fragoso, K.; Acosta-Mesa, H. G.; Cruz-Ramírez, N.; Hernández-Jiménez, R.

2013-12-01

Cervical cancer has remained, until now, as a serious public health problem in developing countries. The most common method of screening is the Pap test or cytology. When abnormalities are reported in the result, the patient is referred to a dysplasia clinic for colposcopy. During this test, a solution of acetic acid is applied, which produces a color change in the tissue and is known as acetowhitening phenomenon. This reaction aims to obtaining a sample of tissue and its histological analysis let to establish a final diagnosis. During the colposcopy test, digital images can be acquired to analyze the behavior of the acetowhitening reaction from a temporal approach. In this way, we try to identify precursor lesions of cervical cancer through a process of automatic classification of acetowhite temporal patterns. In this paper, we present the performance analysis of three classification methods: kNN, Naïve Bayes and C4.5. The results showed that there is similarity between some acetowhite temporal patterns of normal and abnormal tissues. Therefore we conclude that it is not sufficient to only consider the temporal dynamic of the acetowhitening reaction to establish a diagnosis by an automatic method. Information from cytologic, colposcopic and histopathologic disciplines should be integrated as well.

Age-related changes in trunk neuromuscular activation patterns during a controlled functional transfer task include amplitude and temporal synergies.

PubMed

Quirk, D Adam; Hubley-Kozey, Cheryl L

2014-12-01

While healthy aging is associated with physiological changes that can impair control of trunk motion, few studies examine how spinal muscle responses change with increasing age. This study examined whether older (over 65 years) compared to younger (20-45 years) adults had higher overall amplitude and altered temporal recruitment patterns of trunk musculature when performing a functional transfer task. Surface electromyograms from twelve bilateral trunk muscle (24) sites were analyzed using principal component analysis, extracting amplitude and temporal features (PCs) from electromyographic waveforms. Two PCs explained 96% of the waveform variance. Three factor ANOVA models tested main effects (group, muscle and reach) and interactions for PC scores. Significant (p<.0125) group interactions were found for all PC scores. Post hoc analysis revealed that relative to younger adults, older adults recruited higher agonist and antagonistic activity, demonstrated continuous activation levels in specific muscle sites despite changing external moments, and had altered temporal synergies within abdominal and back musculature. In summary both older and younger adults recruit highly organized activation patterns in response to changing external moments. Differences in temporal trunk musculature recruitment patterns suggest that older adults experience different dynamic spinal stiffness and loading compared to younger adults during a functional lifting task. Copyright © 2014 Elsevier B.V. All rights reserved.

Deconstruction of spatial integrity in visual stimulus detected by modulation of synchronized activity in cat visual cortex.

PubMed

Zhou, Zhiyi; Bernard, Melanie R; Bonds, A B

2008-04-02

Spatiotemporal relationships among contour segments can influence synchronization of neural responses in the primary visual cortex. We performed a systematic study to dissociate the impact of spatial and temporal factors in the signaling of contour integration via synchrony. In addition, we characterized the temporal evolution of this process to clarify potential underlying mechanisms. With a 10 x 10 microelectrode array, we recorded the simultaneous activity of multiple cells in the cat primary visual cortex while stimulating with drifting sine-wave gratings. We preserved temporal integrity and systematically degraded spatial integrity of the sine-wave gratings by adding spatial noise. Neural synchronization was analyzed in the time and frequency domains by conducting cross-correlation and coherence analyses. The general association between neural spike trains depends strongly on spatial integrity, with coherence in the gamma band (35-70 Hz) showing greater sensitivity to the change of spatial structure than other frequency bands. Analysis of the temporal dynamics of synchronization in both time and frequency domains suggests that spike timing synchronization is triggered nearly instantaneously by coherent structure in the stimuli, whereas frequency-specific oscillatory components develop more slowly, presumably through network interactions. Our results suggest that, whereas temporal integrity is required for the generation of synchrony, spatial integrity is critical in triggering subsequent gamma band synchronization.

Effects of speckle/pixel size ratio on temporal and spatial speckle-contrast analysis of dynamic scattering systems: Implications for measurements of blood-flow dynamics.

PubMed

Ramirez-San-Juan, J C; Mendez-Aguilar, E; Salazar-Hermenegildo, N; Fuentes-Garcia, A; Ramos-Garcia, R; Choi, B

2013-01-01

Laser Speckle Contrast Imaging (LSCI) is an optical technique used to generate blood flow maps with high spatial and temporal resolution. It is well known that in LSCI, the speckle size must exceed the Nyquist criterion to maximize the speckle's pattern contrast. In this work, we study experimentally the effect of speckle-pixel size ratio not only in dynamic speckle contrast, but also on the calculation of the relative flow speed for temporal and spatial analysis. Our data suggest that the temporal LSCI algorithm is more accurate at assessing the relative changes in flow speed than the spatial algorithm.

Models, Entropy and Information of Temporal Social Networks

NASA Astrophysics Data System (ADS)

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.

Impact of Seasonal Variability in Water, Plant and Soil Nutrient Dynamics in Agroecosystems

NASA Astrophysics Data System (ADS)

Pelak, N. F., III; Revelli, R.; Porporato, A. M.

2017-12-01

Agroecosystems cover a significant fraction of the Earth's surface, making their water and nutrient cycles a major component of global cycles across spatial and temporal scales. Most agroecosystems experience seasonality via variations in precipitation, temperature, and radiation, in addition to human activities which also occur seasonally, such as fertilization, irrigation, and harvesting. These seasonal drivers interact with the system in complex ways which are often poorly characterized. Crop models, which are widely used for research, decision support, and prediction of crop yields, are among the best tools available to analyze these systems. Though normally constructed as a set of dynamical equations forced by hydroclimatic variability, they are not often analyzed using dynamical systems theory and methods from stochastic ecohydrology. With the goal of developing this viewpoint and thus elucidating the roles of key feedbacks and forcings on system stability and on optimal fertilization and irrigation strategies, we develop a minimal dynamical system which contains the key components of a crop model, coupled to a carbon and nitrogen cycling model, driven by seasonal fluctuations in water and nutrient availability, temperature, and radiation. External drivers include seasonally varying climatic conditions and random rainfall forcing, irrigation and fertilization as well as harvesting. The model is used to analyze the magnitudes and interactions of the effects of seasonality on carbon and nutrient cycles, crop productivity, nutrient export of agroecosystems, and optimal management strategies with reference to productivity, sustainability and profitability. The impact of likely future climate scenarios on these systems is also discussed.

Phylodynamics with Migration: A Computational Framework to Quantify Population Structure from Genomic Data.

PubMed

Kühnert, Denise; Stadler, Tanja; Vaughan, Timothy G; Drummond, Alexei J

2016-08-01

When viruses spread, outbreaks can be spawned in previously unaffected regions. Depending on the time and mode of introduction, each regional outbreak can have its own epidemic dynamics. The migration and phylodynamic processes are often intertwined and need to be taken into account when analyzing temporally and spatially structured virus data. In this article, we present a fully probabilistic approach for the joint reconstruction of phylodynamic history in structured populations (such as geographic structure) based on a multitype birth-death process. This approach can be used to quantify the spread of a pathogen in a structured population. Changes in epidemic dynamics through time within subpopulations are incorporated through piecewise constant changes in transmission parameters.We analyze a global human influenza H3N2 virus data set from a geographically structured host population to demonstrate how seasonal dynamics can be inferred simultaneously with the phylogeny and migration process. Our results suggest that the main migration path among the northern, tropical, and southern region represented in the sample analyzed here is the one leading from the tropics to the northern region. Furthermore, the time-dependent transmission dynamics between and within two HIV risk groups, heterosexuals and injecting drug users, in the Latvian HIV epidemic are investigated. Our analyses confirm that the Latvian HIV epidemic peaking around 2001 was mainly driven by the injecting drug user risk group. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

PubMed

Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

2013-05-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.

Kalman Filter Techniques for Accelerated Cartesian Dynamic Cardiac Imaging

PubMed Central

Feng, Xue; Salerno, Michael; Kramer, Christopher M.; Meyer, Craig H.

2012-01-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories, because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and SNR. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. PMID:22926804

Dynamic Interaction of Spindles and Gamma Activity during Cortical Slow Oscillations and Its Modulation by Subcortical Afferents

PubMed Central

Valencia, Miguel; Artieda, Julio; Bolam, J. Paul; Mena-Segovia, Juan

2013-01-01

Slow oscillations are a hallmark of slow wave sleep. They provide a temporal framework for a variety of phasic events to occur and interact during sleep, including the expression of high-frequency oscillations and the discharge of neurons across the entire brain. Evidence shows that the emergence of distinct high-frequency oscillations during slow oscillations facilitates the communication among brain regions whose activity was correlated during the preceding waking period. While the frequencies of oscillations involved in such interactions have been identified, their dynamics and the correlations between them require further investigation. Here we analyzed the structure and dynamics of these signals in anesthetized rats. We show that spindles and gamma oscillations coexist but have distinct temporal dynamics across the slow oscillation cycle. Furthermore, we observed that spindles and gamma are functionally coupled to the slow oscillations and between each other. Following the activation of ascending pathways from the brainstem by means of a carbachol injection in the pedunculopontine nucleus, we were able to modify the gain in the gamma oscillations that are independent of the spindles while the spindle amplitude was reduced. Furthermore, carbachol produced a decoupling of the gamma oscillations that are dependent on the spindles but with no effect on their amplitude. None of the changes in the high-frequency oscillations affected the onset or shape of the slow oscillations, suggesting that slow oscillations occur independently of the phasic events that coexist with them. Our results provide novel insights into the regulation, dynamics and homeostasis of cortical slow oscillations. PMID:23844020

Challenges of flood monitoring in the Senegal river valley using multi-temporal data

NASA Astrophysics Data System (ADS)

Bruckmann, Laurent; Delbart, Nicolas

2017-04-01

In Sub-Saharan Africa, floodplains wetlands play an important role for livelihoods and economy, especially for agriculture and fishing. However, tropical rivers flows are increasingly modified by climate change and dam regulation. In the Senegal river valley, the annual flood, from August to November, is an important water resources creating ecosystems services for people. Senegal river basin face to hydrological changes, due to rainfall diminution during the 1970's and building of large dams during 1980's to secure water resources. Water management and development of irrigation have modified the floodplain functioning. Flood recession agriculture, grazing and fishing are now confronted to a high uncertainty about floods level, duration and extension. Thus, spatiotemporal information of flood extension and duration are important for local communities and stakeholders to ensure food security and ecosystems services. Multi-temporal satellite data demonstrates an important applicability for flood mapping. Aims of this work is to present potentiality of using multi-temporal data from MODIS and new satellite Sentinel-2 for flood monitoring in a Sahelian context. It will also discuss the potential of flood mapping for the analysis of the dynamics of riparian vegetation and flood recession agriculture. This study uses two datasets to explore flood monitoring in Senegal river valley. Firstly, MODIS 8-days data (MOD09A) are first used, because of its temporal resolution of 8 days covering the period from 2000 to 2016. However, MODIS data are limited due to a low spatial resolution, that's why we also use Sentinel-2 data, available since summer 2015. The data were processed by constructing NDWI time-series (NDWI threshold is empirically defined) and extracting NDWI values for each inundated pixel during flood. First results demonstrate that using MODIS on a large scale is enough for analyze interannual variability of the flooded surfaces. We present here maps of flood frequency of the pixels between 2000 and 2016. MODIS spatial resolution is insufficient to analyze the interaction between flood hydrology and vegetation dynamics, whereas flood monitoring by Sentinel data seems to offer better potential. We illustrate our observations through a cartographic example of these interactions at local scale in Senegal river floodplain.

Impacts of large dams on the complexity of suspended sediment dynamics in the Yangtze River

NASA Astrophysics Data System (ADS)

Wang, Yuankun; Rhoads, Bruce L.; Wang, Dong; Wu, Jichun; Zhang, Xiao

2018-03-01

The Yangtze River is one of the largest and most important rivers in the world. Over the past several decades, the natural sediment regime of the Yangtze River has been altered by the construction of dams. This paper uses multi-scale entropy analysis to ascertain the impacts of large dams on the complexity of high-frequency suspended sediment dynamics in the Yangtze River system, especially after impoundment of the Three Gorges Dam (TGD). In this study, the complexity of sediment dynamics is quantified by framing it within the context of entropy analysis of time series. Data on daily sediment loads for four stations located in the mainstem are analyzed for the past 60 years. The results indicate that dam construction has reduced the complexity of short-term (1-30 days) variation in sediment dynamics near the structures, but that complexity has actually increased farther downstream. This spatial pattern seems to reflect a filtering effect of the dams on the on the temporal pattern of sediment loads as well as decreased longitudinal connectivity of sediment transfer through the river system, resulting in downstream enhancement of the influence of local sediment inputs by tributaries on sediment dynamics. The TGD has had a substantial impact on the complexity of sediment series in the mainstem of the Yangtze River, especially after it became fully operational. This enhanced impact is attributed to the high trapping efficiency of this dam and its associated large reservoir. The sediment dynamics "signal" becomes more spatially variable after dam construction. This study demonstrates the spatial influence of dams on the high-frequency temporal complexity of sediment regimes and provides valuable information that can be used to guide environmental conservation of the Yangtze River.

Dynamic full-scalability conversion in scalable video coding

NASA Astrophysics Data System (ADS)

Lee, Dong Su; Bae, Tae Meon; Thang, Truong Cong; Ro, Yong Man

2007-02-01

For outstanding coding efficiency with scalability functions, SVC (Scalable Video Coding) is being standardized. SVC can support spatial, temporal and SNR scalability and these scalabilities are useful to provide a smooth video streaming service even in a time varying network such as a mobile environment. But current SVC is insufficient to support dynamic video conversion with scalability, thereby the adaptation of bitrate to meet a fluctuating network condition is limited. In this paper, we propose dynamic full-scalability conversion methods for QoS adaptive video streaming in SVC. To accomplish full scalability dynamic conversion, we develop corresponding bitstream extraction, encoding and decoding schemes. At the encoder, we insert the IDR NAL periodically to solve the problems of spatial scalability conversion. At the extractor, we analyze the SVC bitstream to get the information which enable dynamic extraction. Real time extraction is achieved by using this information. Finally, we develop the decoder so that it can manage the changing scalability. Experimental results showed that dynamic full-scalability conversion was verified and it was necessary for time varying network condition.

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rasca, Anthony P.; Chen, James; Pevtsov, Alexei A., E-mail: anthony.rasca.ctr@nrl.navy.mil

Recent observations of the photosphere using high spatial and temporal resolution show small dynamic features at or below the current resolving limits. A new pixel dynamics method has been developed to analyze spectral profiles and quantify changes in line displacement, width, asymmetry, and peakedness of photospheric absorption lines. The algorithm evaluates variations of line profile properties in each pixel and determines the statistics of such fluctuations averaged over all pixels in a given region. The method has been used to derive statistical characteristics of pixel fluctuations in observed quiet-Sun regions, an active region with no eruption, and an active regionmore » with an ongoing eruption. Using Stokes I images from the Vector Spectromagnetograph (VSM) of the Synoptic Optical Long-term Investigations of the Sun (SOLIS) telescope on 2012 March 13, variations in line width and peakedness of Fe i 6301.5 Å are shown to have a distinct spatial and temporal relationship with an M7.9 X-ray flare in NOAA 11429. This relationship is observed as stationary and contiguous patches of pixels adjacent to a sunspot exhibiting intense flattening in the line profile and line-center displacement as the X-ray flare approaches peak intensity, which is not present in area scans of the non-eruptive active region. The analysis of pixel dynamics allows one to extract quantitative information on differences in plasma dynamics on sub-pixel scales in these photospheric regions. The analysis can be extended to include the Stokes parameters and study signatures of vector components of magnetic fields and coupled plasma properties.« less

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram.

PubMed

Li, Chen; Nagasaki, Masao; Saito, Ayumu; Miyano, Satoru

2010-04-01

With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics.

Rift Valley fever in a zone potentially occupied by Aedes vexans in Senegal: dynamics and risk mapping

NASA Astrophysics Data System (ADS)

Tourre, Y. M.; Vignolles, C.; Lacaux, J.-P.; Bigeard, G.; Ndione, J.-A.; Lafaye, M.

2009-09-01

This paper presents an analysis of the interaction between the various variables associated with Rift Valley fever (RVF) such as the mosquito vector, available hosts and rainfall distribution. To that end, the varying zones potentially occupied by mosquitoes (ZPOM), rainfall events and pond dynamics, and the associated exposure of hosts to the RVF virus by Aedes vexans, were analyzed in the Barkedji area of the Ferlo, Senegal, during the 2003 rainy season. Ponds were identified by remote sensing using a high-resolution SPOT-5 satellite image. Additional data on ponds and rainfall events from the Tropical Rainfall Measuring Mission were combined with in-situ entomological and limnimetric measurements, and the localization of vulnerable ruminant hosts (data derived from QuickBird satellite). Since "Ae. vexans productive events” are dependent on the timing of rainfall for their embryogenesis (six days without rain are necessary to trigger hatching), the dynamic spatio-temporal distribution of Ae. vexans density was based on the total rainfall amount and pond dynamics. Detailed ZPOM mapping was obtained on a daily basis and combined with aggressiveness temporal profiles. Risks zones, i.e. zones where hazards and vulnerability are combined, are expressed by the percentages of parks where animals are potentially exposed to mosquito bites. This new approach, simply relying upon rainfall distribution evaluated from space, is meant to contribute to the implementation of a new, operational early warning system for RVF based on environmental risks linked to climatic and environmental conditions.

Obstructive sleep apnea alters sleep stage transition dynamics.

PubMed

Bianchi, Matt T; Cash, Sydney S; Mietus, Joseph; Peng, Chung-Kang; Thomas, Robert

2010-06-28

Enhanced characterization of sleep architecture, compared with routine polysomnographic metrics such as stage percentages and sleep efficiency, may improve the predictive phenotyping of fragmented sleep. One approach involves using stage transition analysis to characterize sleep continuity. We analyzed hypnograms from Sleep Heart Health Study (SHHS) participants using the following stage designations: wake after sleep onset (WASO), non-rapid eye movement (NREM) sleep, and REM sleep. We show that individual patient hypnograms contain insufficient number of bouts to adequately describe the transition kinetics, necessitating pooling of data. We compared a control group of individuals free of medications, obstructive sleep apnea (OSA), medical co-morbidities, or sleepiness (n = 374) with mild (n = 496) or severe OSA (n = 338). WASO, REM sleep, and NREM sleep bout durations exhibited multi-exponential temporal dynamics. The presence of OSA accelerated the "decay" rate of NREM and REM sleep bouts, resulting in instability manifesting as shorter bouts and increased number of stage transitions. For WASO bouts, previously attributed to a power law process, a multi-exponential decay described the data well. Simulations demonstrated that a multi-exponential process can mimic a power law distribution. OSA alters sleep architecture dynamics by decreasing the temporal stability of NREM and REM sleep bouts. Multi-exponential fitting is superior to routine mono-exponential fitting, and may thus provide improved predictive metrics of sleep continuity. However, because a single night of sleep contains insufficient transitions to characterize these dynamics, extended monitoring of sleep, probably at home, would be necessary for individualized clinical application.

Design specification of an acousto-optic spectrum analyzer that could be used as an auxiliary receiver for CANEWS

NASA Astrophysics Data System (ADS)

Studenny, John; Johnstone, Eric

1991-01-01

The acousto-optic spectrum analyzer has undergone a theoretical design review and a basic parameter tradeoff analysis has been performed. The main conclusion is that for the given scenario of a 55 dB dynamic range and for a one-second temporal resolution, a 3.9 MHz resolution is a reasonable compromise with respect to current technology. Additional configurations are suggested. Noise testing of the signal detection processor algorithm was conducted. Additive white Gaussian noise was introduced to pure data. As expected, the tradeoff was between algorithm sensitivity and false alarms. No additional algorithm improvements could be made. The algorithm was observed to be robust, provided that the noise floor was set at a proper level. The digitization scheme was mainly driven by hardware constraints. To implement an analog to digital conversion scheme that linearly covers a 55 dB dynamic range would require a minimum of 17 bits. The general consensus was that 17 bits would be untenable for very large scale integration.

Urbanization-induced habitat fragmentation erodes multiple components of temporal diversity in a Southern California native bee assemblage

PubMed Central

Ascher, John S.; Holway, David A.

2017-01-01

Despite a large number of ecological studies that document diversity loss resulting from anthropogenic disturbance, surprisingly few consider how disturbance affects temporal patterns of diversity that result from seasonal turnover of species. Temporal dynamics can play an important role in the structure and function of biological assemblages. Here, we investigate the temporal diversity patterns of bee faunas in Southern California coastal sage scrub ecosystems that have been extensively fragmented by urbanization. Using a two-year dataset of 235 bee species (n = 12,036 specimens), we compared 1-ha plots in scrub fragments and scrub reserves with respect to three components of temporal diversity: overall plot-level diversity pooled over time (temporal gamma diversity), diversity at discrete points in time (temporal alpha diversity), and seasonal turnover in assemblage composition (temporal beta diversity). Compared to reserves, fragments harbored bee assemblages with lower species richness and assemblage evenness both when summed across temporal samples (i.e., lower temporal gamma diversity) and at single points in time (i.e., lower temporal alpha diversity). Bee assemblages in fragments also exhibited reduced seasonal turnover (i.e., lower temporal beta diversity). While fragments and reserves did not differ in overall bee abundance, bee abundance in fragments peaked later in the season compared to that in reserves. Our results argue for an increased awareness of temporal diversity patterns, as information about the distinct components of temporal diversity is essential both for characterizing the assemblage dynamics of seasonal organisms and for identifying potential impacts of anthropogenic disturbance on ecosystem function through its effects on assemblage dynamics. PMID:28854229

Anticipatory neural dynamics of spatial-temporal orienting of attention in younger and older adults.

PubMed

Heideman, Simone G; Rohenkohl, Gustavo; Chauvin, Joshua J; Palmer, Clare E; van Ede, Freek; Nobre, Anna C

2018-05-04

Spatial and temporal expectations act synergistically to facilitate visual perception. In the current study, we sought to investigate the anticipatory oscillatory markers of combined spatial-temporal orienting and to test whether these decline with ageing. We examined anticipatory neural dynamics associated with joint spatial-temporal orienting of attention using magnetoencephalography (MEG) in both younger and older adults. Participants performed a cued covert spatial-temporal orienting task requiring the discrimination of a visual target. Cues indicated both where and when targets would appear. In both age groups, valid spatial-temporal cues significantly enhanced perceptual sensitivity and reduced reaction times. In the MEG data, the main effect of spatial orienting was the lateralised anticipatory modulation of posterior alpha and beta oscillations. In contrast to previous reports, this modulation was not attenuated in older adults; instead it was even more pronounced. The main effect of temporal orienting was a bilateral suppression of posterior alpha and beta oscillations. This effect was restricted to younger adults. Our results also revealed a striking interaction between anticipatory spatial and temporal orienting in the gamma-band (60-75 Hz). When considering both age groups separately, this effect was only clearly evident and only survived statistical evaluation in the older adults. Together, these observations provide several new insights into the neural dynamics supporting separate as well as combined effects of spatial and temporal orienting of attention, and suggest that different neural dynamics associated with attentional orienting appear differentially sensitive to ageing. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Temporal patterns of phyto- and bacterioplankton and their relationships with environmental factors in Lake Taihu, China.

PubMed

Su, Xiaomei; Steinman, Alan D; Xue, Qingju; Zhao, Yanyan; Tang, Xiangming; Xie, Liqiang

2017-10-01

Phytoplankton and bacterioplankton are integral components of aquatic food webs and play essential roles in the structure and function of freshwater ecosystems. However, little is known about how phyto- and bacterioplankton may respond synchronously to changing environmental conditions. Thus, we analyzed simultaneously the composition and structure of phyto- and bacterioplankton on a monthly basis over 12 months in cyanobacteria-dominated areas of Lake Taihu and compared their responses to changes in environmental factors. Metric multi-dimensional scaling (mMDS) revealed that the temporal variations of phyto- and bacterioplankton were significant. Time lag analysis (TLA) indicated that the temporal pattern of phytoplankton tended to exhibit convergent dynamics while bacterioplankton showed highly stable or stochastic variation. A significant directional change was found for bacterioplankton at the genus level and the slopes (rate of change) and regression R 2 (low stochasticity or stability) were greater if Cyanobacteria were included, suggesting a higher level of instability in the bacterial community at lower taxonomy level. Consequently, phytoplankton responded more rapidly to the change in environmental conditions than bacterioplankton when analyzed at the phylum level, while bacterioplankton were more sensitive at the finer taxonomic resolution in Lake Taihu. Redundancy analysis (RDA) results showed that environmental variables collectively explained 51.0% variance of phytoplankton and 46.7% variance of bacterioplankton, suggesting that environmental conditions have a significant influence on the temporal variations of phyto- and bacterioplankton. Furthermore, variance partitioning indicated that the bacterial community structure was largely explained by water temperature and nitrogen, suggesting that these factors were the primary drivers shaping bacterioplankton. Copyright © 2017. Published by Elsevier Ltd.

Optimal growth entails risky localization in population dynamics

NASA Astrophysics Data System (ADS)

Gueudré, Thomas; Martin, David G.

2018-03-01

Essential to each other, growth and exploration are jointly observed in alive and inanimate entities, such as animals, cells or goods. But how the environment's structural and temporal properties weights in this balance remains elusive. We analyze a model of stochastic growth with time correlations and diffusive dynamics that sheds light on the way populations grow and spread over general networks. This model suggests natural explanations of empirical facts in econo-physics or ecology, such as the risk-return trade-off and the Zipf law. We conclude that optimal growth leads to a localized population distribution, but such risky position can be mitigated through the space geometry. These results have broad applicability and are subsequently illustrated over an empirical study of financial data.

Characterizing scientific production and consumption in Physics

PubMed Central

Zhang, Qian; Perra, Nicola; Gonçalves, Bruno; Ciulla, Fabio; Vespignani, Alessandro

2013-01-01

We analyze the entire publication database of the American Physical Society generating longitudinal (50 years) citation networks geolocalized at the level of single urban areas. We define the knowledge diffusion proxy, and scientific production ranking algorithms to capture the spatio-temporal dynamics of Physics knowledge worldwide. By using the knowledge diffusion proxy we identify the key cities in the production and consumption of knowledge in Physics as a function of time. The results from the scientific production ranking algorithm allow us to characterize the top cities for scholarly research in Physics. Although we focus on a single dataset concerning a specific field, the methodology presented here opens the path to comparative studies of the dynamics of knowledge across disciplines and research areas. PMID:23571320

Measuring calcium dynamics in living cells with Genetically Encodable Calcium Indicators

PubMed Central

McCombs, Janet E.

2008-01-01

Genetically encoded calcium indicators (GECIs) allow researchers to measure calcium dynamics in specific targeted locations within living cells. Such indicators enable dissection of the spatial and temporal control of calcium signaling processes. Here we review recent progress in the development of GECIs, highlighting which indicators are most appropriate for measuring calcium in specific organelles and localized domains in mammalian tissue culture cells. An overview of recent approaches that have been undertaken to ensure that the GECIs are minimally perturbed by the cellular environment is provided. Additionally, the procedures for introducing GECIs into mammalian cells, conducting calcium imaging experiments, and analyzing data are discussed. Because organelle-targeted indicators often pose an additional challenge, we underscore strategies for calibrating GECIs in these locations. PMID:18848629

Visualization and Analysis of Microtubule Dynamics Using Dual Color-Coded Display of Plus-End Labels

PubMed Central

Garrison, Amy K.; Xia, Caihong; Wang, Zheng; Ma, Le

2012-01-01

Investigating spatial and temporal control of microtubule dynamics in live cells is critical to understanding cell morphogenesis in development and disease. Tracking fluorescently labeled plus-end-tracking proteins over time has become a widely used method to study microtubule assembly. Here, we report a complementary approach that uses only two images of these labels to visualize and analyze microtubule dynamics at any given time. Using a simple color-coding scheme, labeled plus-ends from two sequential images are pseudocolored with different colors and then merged to display color-coded ends. Based on object recognition algorithms, these colored ends can be identified and segregated into dynamic groups corresponding to four events, including growth, rescue, catastrophe, and pause. Further analysis yields not only their spatial distribution throughout the cell but also provides measurements such as growth rate and direction for each labeled end. We have validated the method by comparing our results with ground-truth data derived from manual analysis as well as with data obtained using the tracking method. In addition, we have confirmed color-coded representation of different dynamic events by analyzing their history and fate. Finally, we have demonstrated the use of the method to investigate microtubule assembly in cells and provided guidance in selecting optimal image acquisition conditions. Thus, this simple computer vision method offers a unique and quantitative approach to study spatial regulation of microtubule dynamics in cells. PMID:23226282

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks.

PubMed

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.

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks

NASA Astrophysics Data System (ADS)

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.

Analysis of one gravitational slope cycle

NASA Astrophysics Data System (ADS)

Palis, Edouard; Lebourg, Thomas; Vidal, Maurin; Tric, Emmanuel

2015-04-01

Since about twenty years of studies on landslides, we realized the role and subtle interactions that existed between the structural complexity, masses dynamics and complex internal circulation of fluids. The La Clapière DSL (Deep-Seated Landslide) is now very well known by the scientific community (volume, impact, challenges, observations...), but this mass of knowledge, has not yet been compiled nor looked through a coupled analysis of its spatial and temporal variability. Since 2007, a will to share and access to uniform data was set up by the Versant Instabilities Multidisciplinary Observatory (OMIV, National Service of French Observation (SNO)). This observatory (with associated laboratories) allowed the installation of permanent and autonomous measuring stations: GPS, meteorology, seismology, water chemistry sources. For two years now, a permanent electrical tomography device is installed at the bottom of the slope to complement the current monitoring system, and allowed a deeper understanding of the physical changes in the massif. The analysis of these data allows to observe different dynamic regimes, as well as different responses to external factors: instantaneous, delayed, long-term variability. The purpose of this synthesis study is to analyze the temporal and spatial evolution of the electrical resistivity, displacement and hydrometeors for one year cycle (November 2012 to November 2013). Thus, a qualitative and statistical approach by clusters, principal component analysis (PCA), and temporal pseudo-3D of these variables was established. This new statistical study also explains the major role of the fault and the base of the landslide, as well as the chronology of the water flow in the massif, allowing a better understanding of the complex and uneven in time dynamic in this area.

Spatial and temporal dynamics of root exudation: how important is heterogeneity in allelopathic interactions?

PubMed

Weidenhamer, Jeffrey D; Mohney, Brian K; Shihada, Nader; Rupasinghe, Maduka

2014-08-01

Understanding allelopathy has been hindered by the lack of methods available to monitor the dynamics of allelochemicals in the soil. Previous work has demonstrated the feasibility of using polydimethylsiloxane (PDMS) microtubing (silicone tubing microextraction, or STME) to construct sampling devices to monitor the release of lipophilic allelochemicals from plant roots. The objective of this study was to use such sampling devices to intensively monitor thiophene fluxes beneath marigolds over several weeks to gain insight into the magnitude of temporal and spatial heterogeneity in these fluxes. Marigolds were grown in rhizoboxes (20.5 x 20.5 x 3.0 cm) with 16 individual STME samplers per box. Thiophene sampling and HPLC analysis began 45 days after planting. At the end of the study, roots around each sampler were analyzed by HPLC. Results confirmed the tremendous spatial and temporal heterogeneity in thiophene production seen in our previous studies. STME probes show that thiophene concentrations generally increase over time; however, these effects were sampling-port specific. When sampling ports were monitored at 12 h intervals, fluxes at each port ranged from 0 to 2,510 ng day(-1). Fluxes measured over daylight hr averaged 29 % higher than those measured overnight. Fluxes were less than 1 % on average of the total thiophene content of surrounding roots. While the importance of such heterogeneity, or "patchiness", in the root zone has been recognized for soil nutrients, the potential importance in allelopathic interactions has seldom been considered. The reasons for this variability are unclear, but are being investigated. Our results demonstrate that STME can be used as a tool to provide a more finely-resolved picture of allelochemical dynamics in the root zone than has previously been available.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Facilitation drives 65 years of vegetation change in the Sonoran Desert

USGS Publications Warehouse

Butterfield, Bradley J.; Betancourt, Julio L.; Turner, Raymond M.; Briggs, John M.

2010-01-01

Ecological processes of low-productivity ecosystems have long been considered to be driven by abiotic controls with biotic interactions playing an insignificant role. However, existing studies present conflicting evidence concerning the roles of these factors, in part due to the short temporal extent of most data sets and inability to test indirect effects of environmental variables modulated by biotic interactions. Using structural equation modeling to analyze 65 years of perennial vegetation change in the Sonoran Desert, we found that precipitation had a stronger positive effect on recruitment beneath existing canopies than in open microsites due to reduced evaporation rates. Variation in perennial canopy cover had additional facilitative effects on juvenile recruitment, which was indirectly driven by effects of density and precipitation on cover. Mortality was strongly influenced by competition as indicated by negative density-dependence, whereas precipitation had no effect. The combined direct, indirect, and interactive facilitative effects of precipitation and cover on recruitment were substantial, as was the effect of competition on mortality, providing strong evidence for dual control of community dynamics by climate and biotic interactions. Through an empirically derived simulation model, we also found that the positive feedback of density on cover produces unique temporal abundance patterns, buffering changes in abundance from high frequency variation in precipitation, amplifying effects of low frequency variation, and decoupling community abundance from precipitation patterns at high abundance. Such dynamics should be generally applicable to low-productivity systems in which facilitation is important and can only be understood within the context of long-term variation in climatic patterns. This predictive model can be applied to better manage low-productivity ecosystems, in which variation in biogeochemical processes and trophic dynamics may be driven by positive density-dependent feedbacks that influence temporal abundance and productivity patterns.

The Role of the Dynamic Sensory Perception in the Reformulation of Shakes: Use of TDS for Studying the Effect of Milk, Fiber, and Flavor Addition.

PubMed

Tomadoni, Barbara; Fiszman, Susana; Moreira, María R; Tarrega, Amparo

2018-01-01

Various factors need to be taken into account when reformulating a food or beverage. The food components, not only macronutrients but also minor ingredients such as flavoring agents, could affect the perception of the sensory sensations, importantly their dynamic aspects, as rising and duration, which are not normally considered. The novelty of this approach is the study of the effects of the addition of several ingredients (fiber, extra milk powder, and strawberry flavoring) on the dynamic perception of a food item (strawberry shakes) using the temporal dominance of sensations (TDS) technique. The occurrence and duration of the key sensory sensations (acid, natural strawberry flavor, thick, sweet, candy strawberry flavor, and milk flavor) extracted from the TDS curves were analyzed and linked to the composition factors and liking and expectations of satiety scores. For example, the addition of flavoring increased the liking scores (increments ranging from 0.3 to 1.1) that was linked to the attenuation of acid sensation; and the addition of extra milk powder increased the expectation of satiety scores (increments ranging from 0.5 to 0.7) that was linked to the perception of early thick sensation in the mouth. In general, the more complex sensory profiles the higher liking and expectations of satiety. This work is a case study on how temporal sensory methods can contribute important information on the actual perception of food during consumption. Depending on the ingredients added these sensory properties appear at different times and with different dominance during evaluation affecting liking or fullness expectations. In consequence, the temporal sensory properties should be taken into account when designing or reformulating food. © 2017 Institute of Food Technologists®.

Team Learning: New Insights Through a Temporal Lens.

PubMed

Lehmann-Willenbrock, Nale

2017-04-01

Team learning is a complex social phenomenon that develops and changes over time. Hence, to promote understanding of the fine-grained dynamics of team learning, research should account for the temporal patterns of team learning behavior. Taking important steps in this direction, this special issue offers novel insights into the dynamics of team learning by advocating a temporal perspective. Based on a symposium presented at the 2016 Interdisciplinary Network for Group Research (INGRoup) Conference in Helsinki, the four empirical articles in this special issue showcase four different and innovative approaches to implementing a temporal perspective in team learning research. Specifically, the contributions highlight team learning dynamics in student teams, self-managing teams, teacher teams, and command and control teams. The articles cover a broad range of methods and designs, including both qualitative and quantitative methodologies, and longitudinal as well as micro-temporal approaches. The contributors represent four countries and five different disciplines in group research.

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

PubMed

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, and demonstrate that expectations about when mnemonic items are most relevant can dynamically and reversibly prioritize these items in time. Moreover, we uncover a neural substrate of such dynamic prioritization in contralateral visual brain areas and show that this substrate predicts working memory retrieval times on a trial-by-trial basis. This places the experimental study of working memory, and its neuronal underpinnings, in a more dynamic and ecologically valid context, and provides new insights into the neural implementation of attentional prioritization within working memory. Copyright © 2017 van Ede et al.

Nonlinear bivariate dependency of price-volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Chen, Shu-Peng

2011-01-01

Nonlinear dependency between characteristic financial and commodity market quantities (variables) is crucially important, especially between trading volume and market price. Studies on nonlinear dependency between price and volume can provide practical insights into market trading characteristics, as well as the theoretical understanding of market dynamics. Actually, nonlinear dependency and its underlying dynamical mechanisms between price and volume can help researchers and technical analysts in understanding the market dynamics by integrating the market variables, instead of investigating them in the current literature. Therefore, for investigating nonlinear dependency of price-volume relationships in agricultural commodity futures markets in China and the US, we perform a new statistical test to detect cross-correlations and apply a new methodology called Multifractal Detrended Cross-Correlation Analysis (MF-DCCA), which is an efficient algorithm to analyze two spatially or temporally correlated time series. We discuss theoretically the relationship between the bivariate cross-correlation exponent and the generalized Hurst exponents for time series of respective variables. We also perform an empirical study and find that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the analyzed agricultural commodity futures markets.

The dynamics of neuronal redundancy in decision making

NASA Astrophysics Data System (ADS)

Daniels, Bryan; Flack, Jessica; Krakauer, David

We propose two temporal phases of collective computation in a visual motion direction discrimination task by analyzing recordings from 169 neural channels in the prefrontal cortex of macaque monkeys. Phase I is a distributed phase in which uncertainty is substantially reduced by pooling information from many cells. Phase II is a redundant phase in which numerous single cells contain all the information present at the population level in Phase I. A dynamic distributed model connects low redundancy to a slow timescale of information aggregation, and provides a common explanation for both behaviors that differs only in the degree of recurrent excitation. We attribute the slow timescale of information accumulation to critical slowing down near the transition to a memory-carrying collective state. We suggest that this dynamic of slow distributed accumulation followed by fast collective propagation is a generic feature of robust collective computing systems related to consensus formation.

Dynamic Analysis of Soil Erosion in Songhua River Watershed

NASA Astrophysics Data System (ADS)

Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan

2018-01-01

In this paper, based on RS and GIS technology and Revised Universal Soil Loss Equation (RUSLE), the soil erosion dynamic changes during the two periods of 1990 and 2010 in Bin County was analyzed by using the Landsat TM data of the two periods, so as to reveal the soil erosion spatial distribution pattern and spatial and temporal dynamic evolution rule in the region. The results showed that: the overall patterns of soil erosion were basically the same in both periods, mainly featuring slight erosion and mild erosion, with the area proportions of 80.68% and 74.71% respectively. The slight and extremely intensive erosion changing rates showed a narrowing trend; mild, moderate and intensive erosion was increasing, with a trend of increased soil erosion; mild and intensive erosion were developing towards moderate erosion and moderate and extremely intensive erosion were progressing towards intensive erosion.

Dynamic diffraction effects and coherent breathing oscillations in ultrafast electron diffraction in layered 1T-TaSeTe

PubMed Central

Wei, Linlin; Sun, Shuaishuai; Guo, Cong; Li, Zhongwen; Sun, Kai; Liu, Yu; Lu, Wenjian; Sun, Yuping; Tian, Huanfang; Yang, Huaixin; Li, Jianqi

2017-01-01

Anisotropic lattice movements due to the difference between intralayer and interlayer bonding are observed in the layered transition-metal dichalcogenide 1T-TaSeTe following femtosecond laser pulse excitation. Our ultrafast electron diffraction investigations using 4D-transmission electron microscopy (4D-TEM) clearly reveal that the intensity of Bragg reflection spots often changes remarkably due to the dynamic diffraction effects and anisotropic lattice movement. Importantly, the temporal diffracted intensity from a specific crystallographic plane depends on the deviation parameter s, which is commonly used in the theoretical study of diffraction intensity. Herein, we report on lattice thermalization and structural oscillations in layered 1T-TaSeTe, analyzed by dynamic diffraction theory. Ultrafast alterations of satellite spots arising from the charge density wave in the present system are also briefly discussed. PMID:28470025

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

PubMed Central

Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

2013-01-01

Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform. PMID:23843732

Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

PubMed

Linel, Patrice; Wu, Shuang; Deng, Nan; Wu, Hulin

2014-10-01

Recent studies demonstrate that human blood transcriptional signatures may be used to support diagnosis and clinical decisions for acute respiratory viral infections such as influenza. In this article, we propose to use a newly developed systems biology approach for time course gene expression data to identify significant dynamically response genes and dynamic gene network responses to viral infection. We illustrate the methodological pipeline by reanalyzing the time course gene expression data from a study with healthy human subjects challenged by live influenza virus. We observed clear differences in the number of significant dynamic response genes (DRGs) between the symptomatic and asymptomatic subjects and also identified DRG signatures for symptomatic subjects with influenza infection. The 505 common DRGs shared by the symptomatic subjects have high consistency with the signature genes for predicting viral infection identified in previous works. The temporal response patterns and network response features were carefully analyzed and investigated.

Analysis of Influenza and RSV dynamics in the community using a ‘Local Transmission Zone’ approach

NASA Astrophysics Data System (ADS)

Almogy, Gal; Stone, Lewi; Bernevig, B. Andrei; Wolf, Dana G.; Dorozko, Marina; Moses, Allon E.; Nir-Paz, Ran

2017-02-01

Understanding the dynamics of pathogen spread within urban areas is critical for the effective prevention and containment of communicable diseases. At these relatively small geographic scales, short-distance interactions and tightly knit sub-networks dominate the dynamics of pathogen transmission; yet, the effective boundaries of these micro-scale groups are generally not known and often ignored. Using clinical test results from hospital admitted patients we analyze the spatio-temporal distribution of Influenza Like Illness (ILI) in the city of Jerusalem over a period of three winter seasons. We demonstrate that this urban area is not a single, perfectly mixed ecology, but is in fact comprised of a set of more basic, relatively independent pathogen transmission units, which we term here Local Transmission Zones, LTZs. By identifying these LTZs, and using the dynamic pathogen-content information contained within them, we are able to differentiate between disease-causes at the individual patient level often with near-perfect predictive accuracy.

Temporal dynamics of periphyton exposed to tetracycline in stream mesocosms

EPA Science Inventory

Significant amounts of antibiotics enter the environment via point and non-point sources. We examined the temporal dynamics of tetracycline exposure to stream periphyton and associated organisms across a logarithmically dosed series of experimental mesocosms, designed to mimic na...

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

Treesearch

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...

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.

Environmental and management impacts on temporal variability of soil hydraulic properties

NASA Astrophysics Data System (ADS)

Bodner, G.; Scholl, P.; Loiskandl, W.; Kaul, H.-P.

2012-04-01

Soil hydraulic properties underlie temporal changes caused by different natural and management factors. Rainfall intensity, wet-dry cycles, freeze-thaw cycles, tillage and plant effects are potential drivers of the temporal variability. For agricultural purposes it is important to determine the possibility of targeted influence via management. In no-till systems e.g. root induced soil loosening (biopores) is essential to counteract natural soil densification by settling. The present work studies two years of temporal evolution of soil hydraulic properties in a no-till crop rotation (durum wheat-field pea) with two cover crops (mustard and rye) having different root systems (taproot vs. fibrous roots) as well as a bare soil control. Soil hydraulic properties such as near-saturated hydraulic conductivity, flow weighted pore radius, pore number and macroporosity are derived from measurements using a tension infiltrometer. The temporal dynamics are then analysed in terms of potential driving forces. Our results revealed significant temporal changes of hydraulic conductivity. When approaching saturation, spatial variability tended to dominate over the temporal evolution. Changes in near-saturated hydraulic conductivity were mainly a result of changing pore number, while the flow weighted mean pore radius showed less temporal dynamic in the no-till system. Macroporosity in the measured range of 0 to -10 cm pressure head ranged from 1.99e-4 to 8.96e-6 m3m-3. The different plant coverage revealed only minor influences on the observed system dynamics. Mustard increased slightly the flow weighted mean pore radius, being 0.090 mm in mustard compared to 0.085 mm in bare soil and 0.084 mm in rye. Still pore radius changes were of minor importance for the overall temporal dynamics. Rainfall was detected as major driving force of the temporal evolution of structural soil hydraulic properties at the site. Soil hydraulic conductivity in the slightly unsaturated range (-7 cm to -10 cm) showed a similar time course as a moving average of rainfall. Drying induced a decrease in conductivity while wetting of the soil resulted in higher conductivity values. Approaching saturation however, the drying phase showed a different behaviour with increasing values of hydraulic conductivity. This may be explained probably by formation of cracks acting as large macropores. We concluded that aggregate coalescence as a function of capillary forces and soil rheologic properties (cf. Or et al., 2002) are a main predictor of temporal dynamics of near saturated soil hydraulic properties while different plant covers only had a minor effect on the observed system dynamics. Or, D., Ghezzehei, T.A. 2002. Modeling post-tillage soil structural dynamics. a review. Soil Till Res. 64, 41-59.

Temporal Dynamics of Visual Attention Measured with Event-Related Potentials

PubMed Central

Kashiwase, Yoshiyuki; Matsumiya, Kazumichi; Kuriki, Ichiro; Shioiri, Satoshi

2013-01-01

How attentional modulation on brain activities determines behavioral performance has been one of the most important issues in cognitive neuroscience. This issue has been addressed by comparing the temporal relationship between attentional modulations on neural activities and behavior. Our previous study measured the time course of attention with amplitude and phase coherence of steady-state visual evoked potential (SSVEP) and found that the modulation latency of phase coherence rather than that of amplitude was consistent with the latency of behavioral performance. In this study, as a complementary report, we compared the time course of visual attention shift measured by event-related potentials (ERPs) with that by target detection task. We developed a novel technique to compare ERPs with behavioral results and analyzed the EEG data in our previous study. Two sets of flickering stimulus at different frequencies were presented in the left and right visual hemifields, and a target or distracter pattern was presented randomly at various moments after an attention-cue presentation. The observers were asked to detect targets on the attended stimulus after the cue. We found that two ERP components, P300 and N2pc, were elicited by the target presented at the attended location. Time-course analyses revealed that attentional modulation of the P300 and N2pc amplitudes increased gradually until reaching a maximum and lasted at least 1.5 s after the cue onset, which is similar to the temporal dynamics of behavioral performance. However, attentional modulation of these ERP components started later than that of behavioral performance. Rather, the time course of attentional modulation of behavioral performance was more closely associated with that of the concurrently recorded SSVEPs analyzed. These results suggest that neural activities reflected not by either the P300 or N2pc, but by the SSVEPs, are the source of attentional modulation of behavioral performance. PMID:23976966

Activation amplitude and temporal synchrony among back extensor and abdominal muscles during a controlled transfer task: comparison of men and women.

PubMed

Hubley-Kozey, Cheryl L; Butler, Heather L; Kozey, John W

2012-08-01

Muscle synergies are important for spinal stability, but few studies examine temporal responses of spinal muscles to dynamic perturbations. This study examined activation amplitudes and temporal synergies among compartments of the back extensor and among abdominal wall muscles in response to dynamic bidirectional moments of force. We further examined whether responses were different between men and women. 19 women and 18 men performed a controlled transfer task. Surface electromyograms from bilateral sites over 6 back extensor compartments and 6 abdominal wall muscle sites were analyzed using principal component analysis. Key features were extracted from the measured electromyographic waveforms capturing amplitude and temporal variations among muscle sites. Three features explained 97% of the variance. Scores for each feature were computed for each measured waveform and analysis of variance found significant (p<.05) muscle main effects and a sex by muscle interaction. For the back extensors, post hoc analysis revealed that upper and more medial sites were recruited to higher amplitudes, medial sites responded to flexion moments, and the more lateral sites responded to lateral flexion moments. Women had more differences among muscle sites than men for the lateral flexion moment feature. For the abdominal wall muscles the oblique muscles responded with synergies related to fiber orientation, with women having higher amplitudes and more responsiveness to the lateral flexion moment than men. Synergies between the abdominal and back extensor sites as the moment demands change are discussed. These findings illustrate differential activation among erector spinae compartments and abdominal wall muscle sites supporting a highly organized pattern of response to bidirectional external moments with asynchronies more apparent in women. Copyright © 2012 Elsevier B.V. All rights reserved.

Modeling change from large-scale high-dimensional spatio-temporal array data

NASA Astrophysics Data System (ADS)

Lu, Meng; Pebesma, Edzer

2014-05-01

The massive data that come from Earth observation satellite and other sensors provide significant information for modeling global change. At the same time, the high dimensionality of the data has brought challenges in data acquisition, management, effective querying and processing. In addition, the output of earth system modeling tends to be data intensive and needs methodologies for storing, validation, analyzing and visualization, e.g. as maps. An important proportion of earth system observations and simulated data can be represented as multi-dimensional array data, which has received increasingly attention in big data management and spatial-temporal analysis. Study cases will be developed in natural science such as climate change, hydrological modeling, sediment dynamics, from which the addressing of big data problems is necessary. Multi-dimensional array-based database management and analytics system such as Rasdaman, SciDB, and R will be applied to these cases. From these studies will hope to learn the strengths and weaknesses of these systems, how they might work together or how semantics of array operations differ, through addressing the problems associated with big data. Research questions include: • How can we reduce dimensions spatially and temporally, or thematically? • How can we extend existing GIS functions to work on multidimensional arrays? • How can we combine data sets of different dimensionality or different resolutions? • Can map algebra be extended to an intelligible array algebra? • What are effective semantics for array programming of dynamic data driven applications? • In which sense are space and time special, as dimensions, compared to other properties? • How can we make the analysis of multi-spectral, multi-temporal and multi-sensor earth observation data easy?

A full Bayes before-after study accounting for temporal and spatial effects: Evaluating the safety impact of new signal installations.

PubMed

Sacchi, Emanuele; Sayed, Tarek; El-Basyouny, Karim

2016-09-01

Recently, important advances in road safety statistics have been brought about by methods able to address issues other than the choice of the best error structure for modeling crash data. In particular, accounting for spatial and temporal interdependence, i.e., the notion that the collision occurrence of a site or unit times depend on those of others, has become an important issue that needs further research. Overall, autoregressive models can be used for this purpose as they can specify that the output variable depends on its own previous values and on a stochastic term. Spatial effects have been investigated and applied mostly in the context of developing safety performance functions (SPFs) to relate crash occurrence to highway characteristics. Hence, there is a need for studies that attempt to estimate the effectiveness of safety countermeasures by including the spatial interdependence of road sites within the context of an observational before-after (BA) study. Moreover, the combination of temporal dynamics and spatial effects on crash frequency has not been explored in depth for SPF development. Therefore, the main goal of this research was to carry out a BA study accounting for spatial effects and temporal dynamics in evaluating the effectiveness of a road safety treatment. The countermeasure analyzed was the installation of traffic signals at unsignalized urban/suburban intersections in British Columbia (Canada). The full Bayes approach was selected as the statistical framework to develop the models. The results demonstrated that zone variation was a major component of total crash variability and that spatial effects were alleviated by clustering intersections together. Finally, the methodology used also allowed estimation of the treatment's effectiveness in the form of crash modification factors and functions with time trends. Copyright © 2016 Elsevier Ltd. All rights reserved.

Limitation of degree information for analyzing the interaction evolution in online social networks

NASA Astrophysics Data System (ADS)

Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

2014-04-01

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

Spatio temporal analysis of microbial habitats in soil-root interfaces

NASA Astrophysics Data System (ADS)

Eickhorst, Thilo; Schmidt, Hannes

2017-04-01

Microbial habitats in soils are formed by the arrangement and availability of inorganic and organic compounds. They can be characterized by physico-chemical parameters and the resulting colonization by microorganisms. Areas being preferably colonized are known as microbial hot spots which can be found in (bio)pores within the aggregatusphere or in the rhizosphere. The latter is directly influenced by plants i.e. the growth and activity of plant roots which has an influence on physico-chemical dynamics in the rhizosphere and can even shape plants' root microbiome. As microbial communities play an important role in nutrient cycling their response in soil-root interfaces is of great importance. Especially in complex systems such as paddy soils used for the cultivation of wetland rice the analysis of spatio-temporal aspects is important to get knowledge about their influence on the microbial dynamics in the respective habitats. But also other spatial variations on larger scales up to landscape scale may have an impact on the soil microorganisms in their habitats. This PICO presentation will introduce a set of techniques which are useful to analyze both the physico-chemical characteristics of microbial habitats and the microbial colonization and dynamics in soil-root interfaces. Examples will be given on various studies from rice cultivation in different paddy soils up to an European transect representing rhizosphere soils of selected plant species.

Mean field model of acetylcholine mediated dynamics in the cerebral cortex.

PubMed

Clearwater, J M; Rennie, C J; Robinson, P A

2007-12-01

A recent continuum model of the large scale electrical activity of the cerebral cortex is generalized to include cholinergic modulation. In this model, dynamic modulation of synaptic strength acts over the time scales of nicotinic and muscarinic receptor action. The cortical model is analyzed to determine the effect of acetylcholine (ACh) on its steady states, linear stability, spectrum, and temporal responses to changes in subcortical input. ACh increases the firing rate in steady states of the system. Changing ACh concentration does not introduce oscillatory behavior into the system, but increases the overall spectral power. Model responses to pulses in subcortical input are affected by the tonic level of ACh concentration, with higher levels of ACh increasing the magnitude firing rate response of excitatory cortical neurons to pulses of subcortical input. Numerical simulations are used to explore the temporal dynamics of the model in response to changes in ACh concentration. Evidence is seen of a transition from a state in which intracortical inputs are emphasized to a state where thalamic afferents have enhanced influence. Perturbations in ACh concentration cause changes in the firing rate of cortical neurons, with rapid responses due to fast acting facilitatory effects of nicotinic receptors on subcortical afferents, and slower responses due to muscarinic suppression of intracortical connections. Together, these numerical simulations demonstrate that the actions of ACh could be a significant factor modulating early components of evoked response potentials.

Dynamic generation of concentration- and temporal-dependent chemical signals in an integrated microfluidic device for single-cell analysis.

PubMed

Gonzalez-Suarez, Alan Mauricio; Peña-Del Castillo, Johanna G; Hernandez-Cruz, Arturo; Garcia-Cordero, Jose Luis

2018-06-19

Intracellular signaling pathways are affected by the temporal nature of external chemical signaling molecules such as neuro-transmitters or hormones. Developing high-throughput technologies to mimic these time-varying chemical signals and to analyze the response of single cells would deepen our understanding of signaling networks. In this work, we introduce a microfluidic platform to stimulate hundreds of single cells with chemical waveforms of tunable frequency and amplitude. Our device produces a linear gradient of 9 concentrations that are delivered to an equal number of chambers, each containing 492 microwells, where individual cells are captured. The device can alternate between the different stimuli concentrations and a control buffer, with a maximum operating frequency of 33 mHz that can be adjusted from a computer. Fluorescent time-lapse microscopy enables to obtain hundreds of thousands of data points from one experiment. We characterized the gradient performance and stability by staining hundreds of cells with calcein AM. We also assessed the capacity of our device to introduce periodic chemical stimuli of different amplitudes and frequencies. To demonstrate our device performance, we studied the dynamics of intracellular Ca2+ release from intracellular stores of HEK cells when stimulated with carbachol at 4.5 and 20 mHz. Our work opens the possibility of characterizing the dynamic responses in real time of signaling molecules to time-varying chemical stimuli with single cell resolution.

NASA/MSFC FY92 Earth Science and Applications Program Research Review

NASA Technical Reports Server (NTRS)

Arnold, James E. (Editor); Leslie, Fred W. (Editor)

1993-01-01

A large amount of attention has recently been given to global issues such as the ozone hole, tropospheric temperature variability, etc. A scientific challenge is to better understand atmospheric processes on a variety of spatial and temporal scales in order to predict environmental changes. Measurement of geophysical parameters such as wind, temperature, and moisture are needed to validate theories, provide analyzed data sets, and initialize or constrain numerical models. One of NASA's initiatives is the Mission to Planet Earth Program comprised of an Earth Observation System (EOS) and the scientific strategy to analyze these data. This work describes these efforts in the context of satellite data analysis and fundamental studies of atmospheric dynamics which examine selected processes important to the global circulation.

Quasiperiodic waves at the onset of zero-Prandtl-number convection with rotation.

PubMed

Kumar, Krishna; Chaudhuri, Sanjay; Das, Alaka

2002-02-01

We show the possibility of temporally quasiperiodic waves at the onset of thermal convection in a thin horizontal layer of slowly rotating zero-Prandtl-number Boussinesq fluid confined between stress-free conducting boundaries. Two independent frequencies emerge due to an interaction between straight rolls and waves along these rolls in the presence of Coriolis force, if the Taylor number is raised above a critical value. Constructing a dynamical system for the hydrodynamical problem, the competition between the interacting instabilities is analyzed. The forward bifurcation from the conductive state is self-tuned.

Signature of phase singularities in diffusive regimes in disordered waveguide lattices: interplay and qualitative analysis

NASA Astrophysics Data System (ADS)

Ghosh, Somnath

2018-05-01

Co-existence and interplay between mesoscopic light dynamics with singular optics in spatially random but temporally coherent disordered waveguide lattices is reported. Two CW light beams of 1.55 micron operating wavelength are launched as inputs to 1D waveguide lattices with controllable weak disorder in refractive index profile. Direct observation of phase singularities in the speckle pattern along the length is numerically demonstrated. Quantitative analysis of onset of such singular behavior and diffusive wave propagation is analyzed for the first time.

Time-series analysis of foreign exchange rates using time-dependent pattern entropy

NASA Astrophysics Data System (ADS)

Ishizaki, Ryuji; Inoue, Masayoshi

2013-08-01

Time-dependent pattern entropy is a method that reduces variations to binary symbolic dynamics and considers the pattern of symbols in a sliding temporal window. We use this method to analyze the instability of daily variations in foreign exchange rates, in particular, the dollar-yen rate. The time-dependent pattern entropy of the dollar-yen rate was found to be high in the following periods: before and after the turning points of the yen from strong to weak or from weak to strong, and the period after the Lehman shock.

On the Magnetism and Dynamics of Prominence Legs Hosting Tornadoes

NASA Astrophysics Data System (ADS)

Martínez González, M. J.; Asensio Ramos, A.; Arregui, I.; Collados, M.; Beck, C.; de la Cruz Rodríguez, J.

2016-07-01

Solar tornadoes are dark vertical filamentary structures observed in the extreme ultraviolet associated with prominence legs and filament barbs. Their true nature and relationship to prominences requires an understanding of their magnetic structure and dynamic properties. Recently, a controversy has arisen: is the magnetic field organized forming vertical, helical structures or is it dominantly horizontal? And concerning their dynamics, are tornadoes really rotating or is it just a visual illusion? Here we analyze four consecutive spectro-polarimetric scans of a prominence hosting tornadoes on its legs, which helps us shed some light on their magnetic and dynamical properties. We show that the magnetic field is very smooth in all the prominence, which is probably an intrinsic property of the coronal field. The prominence legs have vertical helical fields that show slow temporal variation that is probably related to the motion of the fibrils. Concerning the dynamics, we argue that (1) if rotation exists, it is intermittent, lasting no more than one hour, and (2) the observed velocity pattern is also consistent with an oscillatory velocity pattern (waves).

ON THE MAGNETISM AND DYNAMICS OF PROMINENCE LEGS HOSTING TORNADOES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martínez González, M. J.; Ramos, A. Asensio; Arregui, I.

2016-07-10

Solar tornadoes are dark vertical filamentary structures observed in the extreme ultraviolet associated with prominence legs and filament barbs. Their true nature and relationship to prominences requires an understanding of their magnetic structure and dynamic properties. Recently, a controversy has arisen: is the magnetic field organized forming vertical, helical structures or is it dominantly horizontal? And concerning their dynamics, are tornadoes really rotating or is it just a visual illusion? Here we analyze four consecutive spectro-polarimetric scans of a prominence hosting tornadoes on its legs, which helps us shed some light on their magnetic and dynamical properties. We show thatmore » the magnetic field is very smooth in all the prominence, which is probably an intrinsic property of the coronal field. The prominence legs have vertical helical fields that show slow temporal variation that is probably related to the motion of the fibrils. Concerning the dynamics, we argue that (1) if rotation exists, it is intermittent, lasting no more than one hour, and (2) the observed velocity pattern is also consistent with an oscillatory velocity pattern (waves).« less

Traffic Video Image Segmentation Model Based on Bayesian and Spatio-Temporal Markov Random Field

NASA Astrophysics Data System (ADS)

Zhou, Jun; Bao, Xu; Li, Dawei; Yin, Yongwen

2017-10-01

Traffic video image is a kind of dynamic image and its background and foreground is changed at any time, which results in the occlusion. In this case, using the general method is more difficult to get accurate image segmentation. A segmentation algorithm based on Bayesian and Spatio-Temporal Markov Random Field is put forward, which respectively build the energy function model of observation field and label field to motion sequence image with Markov property, then according to Bayesian' rule, use the interaction of label field and observation field, that is the relationship of label field’s prior probability and observation field’s likelihood probability, get the maximum posterior probability of label field’s estimation parameter, use the ICM model to extract the motion object, consequently the process of segmentation is finished. Finally, the segmentation methods of ST - MRF and the Bayesian combined with ST - MRF were analyzed. Experimental results: the segmentation time in Bayesian combined with ST-MRF algorithm is shorter than in ST-MRF, and the computing workload is small, especially in the heavy traffic dynamic scenes the method also can achieve better segmentation effect.

Integrated built-in-test false and missed alarms reduction based on forward infinite impulse response & recurrent finite impulse response dynamic neural networks

NASA Astrophysics Data System (ADS)

Cui, Yiqian; Shi, Junyou; Wang, Zili

2017-11-01

Built-in tests (BITs) are widely used in mechanical systems to perform state identification, whereas the BIT false and missed alarms cause trouble to the operators or beneficiaries to make correct judgments. Artificial neural networks (ANN) are previously used for false and missed alarms identification, which has the features such as self-organizing and self-study. However, these ANN models generally do not incorporate the temporal effect of the bottom-level threshold comparison outputs and the historical temporal features are not fully considered. To improve the situation, this paper proposes a new integrated BIT design methodology by incorporating a novel type of dynamic neural networks (DNN) model. The new DNN model is termed as Forward IIR & Recurrent FIR DNN (FIRF-DNN), where its component neurons, network structures, and input/output relationships are discussed. The condition monitoring false and missed alarms reduction implementation scheme based on FIRF-DNN model is also illustrated, which is composed of three stages including model training, false and missed alarms detection, and false and missed alarms suppression. Finally, the proposed methodology is demonstrated in the application study and the experimental results are analyzed.

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

PubMed Central

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten

2013-01-01

A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g., fusiform gyrus), and frontal regions (e.g., ventromedial prefrontal cortex, medial and inferior frontal cortex) in early and again in later time windows. The present data support the view that dynamic facial displays trigger more information reflected in complex neural networks, in particular because of their changing features potentially triggering sustained activation related to a continuing evaluation of those faces. A combined fMRI and EEG approach thus provides an advanced insight to the spatio-temporal characteristics of emotional face processing, by also revealing additional neural generators, not identifiable by the only use of an fMRI approach. PMID:23818974

Temporal and spatial neural dynamics in the perception of basic emotions from complex scenes

PubMed Central

Costa, Tommaso; Cauda, Franco; Crini, Manuella; Tatu, Mona-Karina; Celeghin, Alessia; de Gelder, Beatrice

2014-01-01

The different temporal dynamics of emotions are critical to understand their evolutionary role in the regulation of interactions with the surrounding environment. Here, we investigated the temporal dynamics underlying the perception of four basic emotions from complex scenes varying in valence and arousal (fear, disgust, happiness and sadness) with the millisecond time resolution of Electroencephalography (EEG). Event-related potentials were computed and each emotion showed a specific temporal profile, as revealed by distinct time segments of significant differences from the neutral scenes. Fear perception elicited significant activity at the earliest time segments, followed by disgust, happiness and sadness. Moreover, fear, disgust and happiness were characterized by two time segments of significant activity, whereas sadness showed only one long-latency time segment of activity. Multidimensional scaling was used to assess the correspondence between neural temporal dynamics and the subjective experience elicited by the four emotions in a subsequent behavioral task. We found a high coherence between these two classes of data, indicating that psychological categories defining emotions have a close correspondence at the brain level in terms of neural temporal dynamics. Finally, we localized the brain regions of time-dependent activity for each emotion and time segment with the low-resolution brain electromagnetic tomography. Fear and disgust showed widely distributed activations, predominantly in the right hemisphere. Happiness activated a number of areas mostly in the left hemisphere, whereas sadness showed a limited number of active areas at late latency. The present findings indicate that the neural signature of basic emotions can emerge as the byproduct of dynamic spatiotemporal brain networks as investigated with millisecond-range resolution, rather than in time-independent areas involved uniquely in the processing one specific emotion. PMID:24214921

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

NASA Astrophysics Data System (ADS)

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/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

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

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

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 [(18)F]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/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [(11)C]SCH23390 data, showing promising results.

Localized Spatio-Temporal Constraints for Accelerated CMR Perfusion

PubMed Central

Akçakaya, Mehmet; Basha, Tamer A.; Pflugi, Silvio; Foppa, Murilo; Kissinger, Kraig V.; Hauser, Thomas H.; Nezafat, Reza

2013-01-01

Purpose To develop and evaluate an image reconstruction technique for cardiac MRI (CMR)perfusion that utilizes localized spatio-temporal constraints. Methods CMR perfusion plays an important role in detecting myocardial ischemia in patients with coronary artery disease. Breath-hold k-t based image acceleration techniques are typically used in CMR perfusion for superior spatial/temporal resolution, and improved coverage. In this study, we propose a novel compressed sensing based image reconstruction technique for CMR perfusion, with applicability to free-breathing examinations. This technique uses local spatio-temporal constraints by regularizing image patches across a small number of dynamics. The technique is compared to conventional dynamic-by-dynamic reconstruction, and sparsity regularization using a temporal principal-component (pc) basis, as well as zerofilled data in multi-slice 2D and 3D CMR perfusion. Qualitative image scores are used (1=poor, 4=excellent) to evaluate the technique in 3D perfusion in 10 patients and 5 healthy subjects. On 4 healthy subjects, the proposed technique was also compared to a breath-hold multi-slice 2D acquisition with parallel imaging in terms of signal intensity curves. Results The proposed technique results in images that are superior in terms of spatial and temporal blurring compared to the other techniques, even in free-breathing datasets. The image scores indicate a significant improvement compared to other techniques in 3D perfusion (2.8±0.5 vs. 2.3±0.5 for x-pc regularization, 1.7±0.5 for dynamic-by-dynamic, 1.1±0.2 for zerofilled). Signal intensity curves indicate similar dynamics of uptake between the proposed method with a 3D acquisition and the breath-hold multi-slice 2D acquisition with parallel imaging. Conclusion The proposed reconstruction utilizes sparsity regularization based on localized information in both spatial and temporal domains for highly-accelerated CMR perfusion with potential utility in free-breathing 3D acquisitions. PMID:24123058

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

Mean Normalized Gain: A New Method for the Assessment of the Aerobic System Temporal Dynamics during Randomly Varying Exercise in Humans.

PubMed

Beltrame, Thomas; Hughson, Richard L

2017-01-01

The temporal dynamics of the oxygen uptake ([Formula: see text]) during moderate exercise has classically been related to physical fitness and a slower [Formula: see text] dynamics was associated with deterioration of physical health. However, methods that better characterize the aerobic system temporal dynamics remain challenging. The purpose of this study was to develop a new method (named mean normalized gain, MNG ) to systematically characterize the [Formula: see text] temporal dynamics. Eight healthy, young adults (28 ± 6 years old, 175 ± 7 cm and 79 ± 13 kg) performed multiple pseudorandom binary sequence cycling protocols on different days and time of the day. The MNG was calculated as the normalized amplitude of the [Formula: see text] signal in frequency-domain. The MNG was validated considering the time constant τ obtained from time-domain analysis as reference. The intra-subject consistency of the MNG was checked by testing the same participant on different days and times of the day. The MNG and τ were strongly negatively correlated ( r = -0.86 and p = 0.005). The MNG measured on different days and periods of the day was similar between conditions. Calculations for the MNG have inherent filtering characteristics enhancing reliability for the evaluation of the aerobic system temporal dynamics. In conclusion, the present study successfully validated the use of the MNG for aerobic system analysis and as a potential complementary tool to assess changes in physical fitness.

Temporal variations in a phytoplankton community in a subtropical reservoir: An interplay of extrinsic and intrinsic community effects.

PubMed

Yang, Wen; Zheng, Zhongming; Zheng, Cheng; Lu, Kaihong; Ding, Dewen; Zhu, Jinyong

2018-01-15

The phytoplankton community structure is potentially influenced by both extrinsic effects originating from the surrounding environment and intrinsic effects relying on interspecific interactions between two species. However, few studies have simultaneously considered both types of effects and assessed the relative importance of these factors. In this study, we used data collected over nine months (August 2012-May 2013) from a typical subtropical reservoir in southeast China to analyze the temporal variation of its phytoplankton community structure and develop a quantitative understanding of the extrinsic and intrinsic effects on phytoplankton community dynamics. Significant temporal variations were observed in environmental variables as well as the phytoplankton and zooplankton communities, whereas their variational trajectories and directions were entirely different. Variance partitioning analysis showed that extrinsic factors significantly explained only 31% of the variation in the phytoplankton community, thus suggesting that these factors were incomplete predictors of the community structure. Random forest-based models showed that 48% of qualified responsible phytoplankton species were more accurately predicted by phytoplankton-only models, which revealed clear effects of interspecific species-to-species interactions. Furthermore, we used association networks to model the interactions among phytoplankton, zooplankton and the environment. Network comparisons indicated that interspecific interactions were widely present in the phytoplankton community and dominated the network rather than those between phytoplankton and extrinsic factors. These findings expand the current understanding of the underlying mechanisms that govern phytoplankton community dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

Culicidae Community Composition and Temporal Dynamics in Guapiaçu Ecological Reserve, Cachoeiras de Macacu, Rio de Janeiro, Brazil

PubMed Central

Alencar, Jeronimo; de Mello, Cecilia Ferreira; Guimarães, Anthony Érico; Gil-Santana, Hélcio R.; Silva, Júlia dos Santos; Santos- Mallet, Jacenir R.; Gleiser, Raquel M.

2015-01-01

A temporal observational study was conducted of the Culicidae fauna in a remnant area of Atlantic Forest within a private reserve (Guapiaçu Ecological Reserve-REGUA) presenting typical vegetation cover of dense rain forest, with some patches recovering a floristic composition similar to that of the original community. Research was carried out to analyze the influence of climatic factors (mean monthly temperature, rainfall, and air relative humidity) on the temporal dynamics of the mosquito communities that occur in the reserve. The completeness of the mosquito inventory was assessed with individual-based rarefaction-extrapolation curves. Differences in species composition between sites and months were tested with PERMANOVA. True diversities of orders 0, 1, and 2 (effective numbers) were estimated and compared between sites, months, and years. Multiple stepwise regressions were used to assess relationships between climatic variables, measures of diversity, and abundances of the most common species. There were significant interactive effects between year and site on measures of diversity. However, diversity estimates showed little variation among months, and these were weakly correlated with climatic variables. Abundances of the most common species were significantly related to temperature or relative humidity, but not rainfall. The presence of mosquito species known to be vectors of human diseases combined with an intermittent flow of visitors to the study area suggests there is a risk of disease transmission that warrants further monitoring. PMID:25815724

Temporally coordinated spiking activity of human induced pluripotent stem cell-derived neurons co-cultured with astrocytes.

PubMed

Kayama, Tasuku; Suzuki, Ikuro; Odawara, Aoi; Sasaki, Takuya; Ikegaya, Yuji

2018-01-01

In culture conditions, human induced-pluripotent stem cells (hiPSC)-derived neurons form synaptic connections with other cells and establish neuronal networks, which are expected to be an in vitro model system for drug discovery screening and toxicity testing. While early studies demonstrated effects of co-culture of hiPSC-derived neurons with astroglial cells on survival and maturation of hiPSC-derived neurons, the population spiking patterns of such hiPSC-derived neurons have not been fully characterized. In this study, we analyzed temporal spiking patterns of hiPSC-derived neurons recorded by a multi-electrode array system. We discovered that specific sets of hiPSC-derived neurons co-cultured with astrocytes showed more frequent and highly coherent non-random synchronized spike trains and more dynamic changes in overall spike patterns over time. These temporally coordinated spiking patterns are physiological signs of organized circuits of hiPSC-derived neurons and suggest benefits of co-culture of hiPSC-derived neurons with astrocytes. Copyright © 2017 Elsevier Inc. All rights reserved.

Temporal dynamics of frequency-tunable graphene-based plasmonic grating structures for ultra-broadband terahertz communication

NASA Astrophysics Data System (ADS)

Jornet, Josep Miquel; Thawdar, Ngwe; Woo, Ethan; Andrello, Michael A.

2017-05-01

Terahertz (THz) communication is envisioned as a key wireless technology to satisfy the need for 1000x faster wireless data rates. To date, major progress on both electronic and photonic technologies are finally closing the so-called THz gap. Among others, graphene-based plasmonic nano-devices have been proposed as a way to enable ultra-broadband communications above 1THz. The unique dynamic complex conductivity of graphene enables the propagation of Surface Plasmon Polariton (SPP) waves at THz frequencies. In addition, the conductivity of graphene and, thus, the SPP propagation properties, can be dynamically tuned by means of electrostatic biasing or material doping. This result opens the door to frequency-tunable devices for THz communications. In this paper, the temporal dynamics of graphene-enhanced metallic grating structures used for excitation and detection of SPP waves at THz frequencies are analytically and numerically modeled. More specifically, the response of a metallic grating structure built on top of a graphene-based heterostructure is analyzed by taking into account the grating period and duty cycle and the Fermi energy of the graphene layer. Then, the interfacial charge transfer between a metallic back-gate and the graphene layer in a metal/dielectric/graphene stack is analytically modeled, and the range of achievable Fermi energies is determined. Finally, the rate at which the Fermi energy in graphene can be tuned is estimated starting from the transmission line model of graphene. Extensive numerical and simulation results with COMSOL Multi-physics are provided. The results show that the proposed structure enables dynamic frequency systems with THz bandwidths, thus, enabling resilient communication techniques such as time-hopping THz modulations.

Stratification Pattern of Static and Scale-Invariant Dynamic Measures of Heartbeat Fluctuations Across Sleep Stages in Young and Elderly

PubMed Central

Schmitt, Daniel T.; Stein, Phyllis K.; Ivanov, Plamen Ch.

2010-01-01

Cardiac dynamics exhibit complex variability characterized by scale-invariant and nonlinear temporal organization related to the mechanism of neuroautonomic control, which changes with physiologic states and pathologic conditions. Changes in sleep regulation during sleep stages are also related to fluctuations in autonomic nervous activity. However, the interaction between sleep regulation and cardiac autonomic control remains not well understood. Even less is known how this interaction changes with age, as aspects of both cardiac dynamics and sleep regulation differ in healthy elderly compared to young subjects. We hypothesize that because of the neuroautonomic responsiveness in young subjects, fractal and nonlinear features of cardiac dynamics exhibit a pronounced stratification pattern across sleep stages, while in elderly these features will remain unchanged due to age-related loss of cardiac variability and decline of neuroautonomic responsiveness. We analyze the variability and the temporal fractal organization of heartbeat fluctuations across sleep stages in both young and elderly. We find that independent linear and nonlinear measures of cardiac control consistently exhibit the same ordering in their values across sleep stages, forming a robust stratification pattern. Despite changes in sleep architecture and reduced heart rate variability in elderly subjects, this stratification surprisingly does not break down with advanced age. Moreover, the difference between sleep stages for some linear, fractal, and nonlinear measures exceeds the difference between young and elderly, suggesting that the effect of sleep regulation on cardiac dynamics is significantly stronger than the effect of healthy aging. Quantifying changes in this stratification pattern may provide insights into how alterations in sleep regulation contribute to increased cardiac risk. PMID:19203874

Self-similarity in nature

NASA Astrophysics Data System (ADS)

Timashev, S. F.

2000-02-01

A general phenomenological approach to the analysis of experimental temporal, spatial and energetic series for extracting truly physical non-model parameters ("passport data") is presented, which may be used to characterize and distinguish the evolution as well as the spatial and energetic structure of any open nonlinear dissipative system. This methodology is based on a postulate concerning the crucial information contained in the sequences of non-regularities of the measured dynamic variable (temporal, spatial, energetic). In accordance with this approach, multi-parametric formulas for dynamic variable power spectra as well as for structural functions of different orders are identical for every spatial-temporal-energetic level of the system under consideration. In effect, this entails the introduction of a new kind of self-similarity in Nature. An algorithm has been developed for obtaining as many "passport data" as are necessary for the characterization of a dynamic system. Applications of this approach in the analysis of various experimental series (temporal, spatial, energetic) demonstrate its potential for defining adequate phenomenological parameters of different dynamic processes and structures.

Application of Dynamic Mode Decomposition: Temporal Evolution of Flow Structures in an Aneurysm

NASA Astrophysics Data System (ADS)

Conlin, William; Yu, Paulo; Durgesh, Vibhav

2017-11-01

An aneurysm is an enlargement of a weakened arterial wall that can be fatal or debilitating on rupture. Aneurysm hemodynamics is integral to developing an understanding of aneurysm formation, growth, and rupture. The flow in an aneurysm exhibits complex fluid dynamics behavior due to an inherent unsteady inflow condition and its interactions with large-scale flow structures present in the aneurysm. The objective of this study is to identify the large-scale structures in the aneurysm, study temporal behavior, and quantify their interaction with the inflow condition. For this purpose, detailed Particle Image Velocimetry (PIV) measurements were performed at the center plane of an idealized aneurysm model for a range of inflow conditions. Inflow conditions were precisely controlled using a ViVitro SuperPump system. Dynamic Modal Decomposition (DMD) of the velocity field was used to identify coherent structures and their temporal behavior. DMD was successful in capturing the large-scale flow structures and their temporal behavior. A low dimensional approximation to the flow field was obtained with the most relevant dynamic modes and was used to obtain temporal information about the coherent structures and their interaction with the inflow, formation, evolution, and growth.

Evidence of a Critical Phase Transition in Purely Temporal Dynamics with Long-Delayed Feedback

NASA Astrophysics Data System (ADS)

Faggian, Marco; Ginelli, Francesco; Marino, Francesco; Giacomelli, Giovanni

2018-04-01

Experimental evidence of an absorbing phase transition, so far associated with spatiotemporal dynamics, is provided in a purely temporal optical system. A bistable semiconductor laser, with long-delayed optoelectronic feedback and multiplicative noise, shows the peculiar features of a critical phenomenon belonging to the directed percolation universality class. The numerical study of a simple, effective model provides accurate estimates of the transition critical exponents, in agreement with both theory and our experiment. This result pushes forward a hard equivalence of nontrivial stochastic, long-delayed systems with spatiotemporal ones and opens a new avenue for studying out-of-equilibrium universality classes in purely temporal dynamics.

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

PubMed Central

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 neuronal populations also opens new doors to analyze the joint dynamics of multiple interacting networks. PMID:25520644

Dynamics of Ecosystem Services during Forest Transitions in Reventazón, Costa Rica.

PubMed

Vallet, Améline; Locatelli, Bruno; Levrel, Harold; Brenes Pérez, Christian; Imbach, Pablo; Estrada Carmona, Natalia; Manlay, Raphaël; Oszwald, Johan

2016-01-01

The forest transition framework describes the temporal changes of forest areas with economic development. A first phase of forest contraction is followed by a second phase of expansion once a turning point is reached. This framework does not differentiate forest types or ecosystem services, and describes forests regardless of their contribution to human well-being. For several decades, deforestation in many tropical regions has degraded ecosystem services, such as watershed regulation, while increasing provisioning services from agriculture, for example, food. Forest transitions and expansion have been observed in some countries, but their consequences for ecosystem services are often unclear. We analyzed the implications of forest cover change on ecosystem services in Costa Rica, where a forest transition has been suggested. A review of literature and secondary data on forest and ecosystem services in Costa Rica indicated that forest transition might have led to an ecosystem services transition. We modeled and mapped the changes of selected ecosystem services in the upper part of the Reventazón watershed and analyzed how supply changed over time in order to identify possible transitions in ecosystem services. The modeled changes of ecosystem services is similar to the second phase of a forest transition but no turning point was identified, probably because of the limited temporal scope of the analysis. Trends of provisioning and regulating services and their tradeoffs were opposite in different spatial subunits of our study area, which highlights the importance of scale in the analysis of ecosystem services and forest transitions. The ecosystem services transition framework proposed in this study is useful for analyzing the temporal changes of ecosystem services and linking socio-economic drivers to ecosystem services demand at different scales.

Dynamics of Ecosystem Services during Forest Transitions in Reventazón, Costa Rica

PubMed Central

Vallet, Améline; Locatelli, Bruno; Levrel, Harold; Brenes Pérez, Christian; Imbach, Pablo; Estrada Carmona, Natalia; Manlay, Raphaël; Oszwald, Johan

2016-01-01

The forest transition framework describes the temporal changes of forest areas with economic development. A first phase of forest contraction is followed by a second phase of expansion once a turning point is reached. This framework does not differentiate forest types or ecosystem services, and describes forests regardless of their contribution to human well-being. For several decades, deforestation in many tropical regions has degraded ecosystem services, such as watershed regulation, while increasing provisioning services from agriculture, for example, food. Forest transitions and expansion have been observed in some countries, but their consequences for ecosystem services are often unclear. We analyzed the implications of forest cover change on ecosystem services in Costa Rica, where a forest transition has been suggested. A review of literature and secondary data on forest and ecosystem services in Costa Rica indicated that forest transition might have led to an ecosystem services transition. We modeled and mapped the changes of selected ecosystem services in the upper part of the Reventazón watershed and analyzed how supply changed over time in order to identify possible transitions in ecosystem services. The modeled changes of ecosystem services is similar to the second phase of a forest transition but no turning point was identified, probably because of the limited temporal scope of the analysis. Trends of provisioning and regulating services and their tradeoffs were opposite in different spatial subunits of our study area, which highlights the importance of scale in the analysis of ecosystem services and forest transitions. The ecosystem services transition framework proposed in this study is useful for analyzing the temporal changes of ecosystem services and linking socio-economic drivers to ecosystem services demand at different scales. PMID:27390869

Negative mood and mind wandering increase long-range temporal correlations in attention fluctuations.

PubMed

Irrmischer, Mona; van der Wal, C Natalie; Mansvelder, Huibert D; Linkenkaer-Hansen, Klaus

2018-01-01

There is growing evidence that the intermittent nature of mind wandering episodes and mood have a pronounced influence on trial-to-trial variability in performance. Nevertheless, the temporal dynamics and significance of such lapses in attention remains inadequately understood. Here, we hypothesize that the dynamics of fluctuations in sustained attention between external and internal sources of information obey so-called critical-state dynamics, characterized by trial-to-trial dependencies with long-range temporal correlations. To test this, we performed behavioral investigations measuring reaction times in a visual sustained attention task and cued introspection in probe-caught reports of mind wandering. We show that trial-to-trial variability in reaction times exhibit long-range temporal correlations in agreement with the criticality hypothesis. Interestingly, we observed the fastest responses in subjects with the weakest long-range temporal correlations and show the vital effect of mind wandering and bad mood on this response variability. The implications of these results stress the importance of future research to increase focus on behavioral variability.

Negative mood and mind wandering increase long-range temporal correlations in attention fluctuations

PubMed Central

van der Wal, C. Natalie; Mansvelder, Huibert D.; Linkenkaer-Hansen, Klaus

2018-01-01

There is growing evidence that the intermittent nature of mind wandering episodes and mood have a pronounced influence on trial-to-trial variability in performance. Nevertheless, the temporal dynamics and significance of such lapses in attention remains inadequately understood. Here, we hypothesize that the dynamics of fluctuations in sustained attention between external and internal sources of information obey so-called critical-state dynamics, characterized by trial-to-trial dependencies with long-range temporal correlations. To test this, we performed behavioral investigations measuring reaction times in a visual sustained attention task and cued introspection in probe-caught reports of mind wandering. We show that trial-to-trial variability in reaction times exhibit long-range temporal correlations in agreement with the criticality hypothesis. Interestingly, we observed the fastest responses in subjects with the weakest long-range temporal correlations and show the vital effect of mind wandering and bad mood on this response variability. The implications of these results stress the importance of future research to increase focus on behavioral variability. PMID:29746529

A neural coding scheme reproducing foraging trajectories

NASA Astrophysics Data System (ADS)

Gutiérrez, Esther D.; Cabrera, Juan Luis

2015-12-01

The movement of many animals may follow Lévy patterns. The underlying generating neuronal dynamics of such a behavior is unknown. In this paper we show that a novel discovery of multifractality in winnerless competition (WLC) systems reveals a potential encoding mechanism that is translatable into two dimensional superdiffusive Lévy movements. The validity of our approach is tested on a conductance based neuronal model showing WLC and through the extraction of Lévy flights inducing fractals from recordings of rat hippocampus during open field foraging. Further insights are gained analyzing mice motor cortex neurons and non motor cell signals. The proposed mechanism provides a plausible explanation for the neuro-dynamical fundamentals of spatial searching patterns observed in animals (including humans) and illustrates an until now unknown way to encode information in neuronal temporal series.

The Inner Workings of Magnetic Reconnection: Diffusion Region in the Balance

NASA Technical Reports Server (NTRS)

Hesse, Michael

2010-01-01

The question of whether the micro scale controls the macroscale or vice-versa remains one of the most challenging problems in plasmas. A particular topic of interest within this context is collisionless magnetic reconnection, where both points of views are espoused by different groups of researchers. This presentation will focus on this topic. We will begin by analyzing the properties of electron diffusion region dynamics both for guide field and anti-parallel reconnection, and how they can be scaled to different inflow conditions. As a next step, we will study typical temporal variations of the microscopic dynamics with the objective of understanding the potential for secular changes to the macroscopic system. The research will be based on a combination of analytical theory and numerical modeling.

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

Spatio-Temporal Patterning in Primary Motor Cortex at Movement Onset.

PubMed

Best, Matthew D; Suminski, Aaron J; Takahashi, Kazutaka; Brown, Kevin A; Hatsopoulos, Nicholas G

2017-02-01

Voluntary movement initiation involves the engagement of large populations of motor cortical neurons around movement onset. Despite knowledge of the temporal dynamics that lead to movement, the spatial structure of these dynamics across the cortical surface remains unknown. In data from 4 rhesus macaques, we show that the timing of attenuation of beta frequency local field potential oscillations, a correlate of locally activated cortex, forms a spatial gradient across primary motor cortex (MI). We show that these spatio-temporal dynamics are recapitulated in the engagement order of ensembles of MI neurons. We demonstrate that these patterns are unique to movement onset and suggest that movement initiation requires a precise spatio-temporal sequential activation of neurons in MI. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Temporal Dynamics of the Driving Factors of Urban Landscape Change of Addis Ababa During the Past Three Decades.

PubMed

Zewdie, Meskerem; Worku, Hailu; Bantider, Amare

2018-01-01

Mapping and quantifying urban landscape dynamics and the underlying driving factors are crucial for devising appropriate policies, especially in cities of developing countries where the change is rapid. This study analyzed three decades (1984-2014) of land use land cover change of Addis Ababa using Landsat imagery and examined the underlying factors and their temporal dynamics through expert interview using Analytic Hierarchy Process (AHP). Classification results revealed that urban area increased by 50%, while agricultural land and forest decreased by 34 and 16%, respectively. The driving factors operated differently during the pre and post-1991 period. The year 1991 was chosen because it marked government change in the country resulting in policy change. Policy had the highest influence during the pre-1991 period. Land use change in this period was associated with the housing sector as policies and institutional setups were permissive to this sector. Population growth and in-migration were also important factors. Economic factors played significant role in the post-1991 period. The fact that urban land has a market value, the growth of private investment, and the speculated property market were among the economic factors. Policy reforms since 2003 were also influential to the change. Others such as accessibility, demography, and neighborhood factors were a response to economic factors. All the above-mentioned factors had vital role in shaping the urban pattern of the city. These findings can help planners and policymakers to better understand the dynamic relationship of urban land use and the driving factors to better manage the city.

Temporal Dynamics of the Driving Factors of Urban Landscape Change of Addis Ababa During the Past Three Decades

NASA Astrophysics Data System (ADS)

Zewdie, Meskerem; Worku, Hailu; Bantider, Amare

2018-01-01

Mapping and quantifying urban landscape dynamics and the underlying driving factors are crucial for devising appropriate policies, especially in cities of developing countries where the change is rapid. This study analyzed three decades (1984-2014) of land use land cover change of Addis Ababa using Landsat imagery and examined the underlying factors and their temporal dynamics through expert interview using Analytic Hierarchy Process (AHP). Classification results revealed that urban area increased by 50%, while agricultural land and forest decreased by 34 and 16%, respectively. The driving factors operated differently during the pre and post-1991 period. The year 1991 was chosen because it marked government change in the country resulting in policy change. Policy had the highest influence during the pre-1991 period. Land use change in this period was associated with the housing sector as policies and institutional setups were permissive to this sector. Population growth and in-migration were also important factors. Economic factors played significant role in the post-1991 period. The fact that urban land has a market value, the growth of private investment, and the speculated property market were among the economic factors. Policy reforms since 2003 were also influential to the change. Others such as accessibility, demography, and neighborhood factors were a response to economic factors. All the above-mentioned factors had vital role in shaping the urban pattern of the city. These findings can help planners and policymakers to better understand the dynamic relationship of urban land use and the driving factors to better manage the city.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram

PubMed Central

2010-01-01

Background With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. Results We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Conclusions Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics. PMID:20356411

Potential and limitations of satellite laser altimetry for monitoring water surface dynamics: ICESat for US lakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shu, Liu; Qigang, Jiang; Zhang, Xuesong

Elevation measurements from the Ice, Cloud and Land Elevation Satellite (ICESat) have been applied to monitor dynamics of lakes and other surface water bodies. Despite such potential, the true utility of ICESat--more generally, satellite laser altimetry--for tracking surface water dynamics over time has not been adequately assessed, especially in the continental or global contexts. Here, we analyzed ICESat elevation data for the conterminous United States and examined the potential and limitations of satellite laser altimetry in measuring water-level dynamics. Owing to a lack of spatially-explicit ground-based water-level data, we first resorted to high-fidelity land elevation data acquired by airborne lidarmore » to quantify ICESat’s ranging accuracy. We then performed trend and frequency analyses to evaluate how reliably ICESat could capture water-level dynamics over a range of temporal scales, as compared to in-situ gauge measurements. Our analyses showed that ICESat had a vertical ranging error of 0.16 m at the footprint level—a limit on the detectable range of water-level dynamics. The sparsity of data over time was identified as a major factor limiting the use of ICESat for water dynamics studies. Of all the US lakes, only 361 had quality ICESat measurements for more than two flight passes. Even for those lakes with sufficient temporal coverage, ICESat failed to capture the true interannual water-level dynamics in 68% of the cases. Our frequency analysis suggested that even with a repeat cycle of two months, ICESat could capture only 60% of the variations in water-level dynamics for at most 34 % of the US lakes. To capture 60% of the water-level variation for most of the US lakes, a weekly repeat cycle (e.g., less than 5 days) is needed – a requirement difficult to meet in current designs of spaceborne laser altimetry. Overall, our results highlight that current or near-future satellite laser missions, though with high ranging accuracies, are unlikely to fulfill the general needs in remotely monitoring water surface dynamics for lakes or reservoirs.« less

Parameterizing Coefficients of a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

A method of parameterizing the coefficients of a dynamical system based of a proper orthogonal decomposition (POD) representing the flow dynamics of a viscous fluid has been introduced. (A brief description of POD is presented in the immediately preceding article.) The present parameterization method is intended to enable construction of the dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers. The need for this or a similar method arises as follows: A procedure that includes direct numerical simulation followed by POD, followed by Galerkin projection to a dynamical system has been proven to enable representation of flow dynamics by a low-dimensional model at the Reynolds number of the simulation. However, a more difficult task is to obtain models that are valid over a range of Reynolds numbers. Extrapolation of low-dimensional models by use of straightforward Reynolds-number-based parameter continuation has proven to be inadequate for successful prediction of flows. A key part of the problem of constructing a dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers is the problem of understanding and providing for the variation of the coefficients of the dynamical system with the Reynolds number. Prior methods do not enable capture of temporal dynamics over ranges of Reynolds numbers in low-dimensional models, and are not even satisfactory when large numbers of modes are used. The basic idea of the present method is to solve the problem through a suitable parameterization of the coefficients of the dynamical system. The parameterization computations involve utilization of the transfer of kinetic energy between modes as a function of Reynolds number. The thus-parameterized dynamical system accurately predicts the flow dynamics and is applicable to a range of flow problems in the dynamical regime around the Hopf bifurcation. Parameter-continuation software can be used on the parameterized dynamical system to derive a bifurcation diagram that accurately predicts the temporal flow behavior.

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

PubMed Central

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. PMID:26147887

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

PubMed

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.

Efficient Algorithms for Segmentation of Item-Set Time Series

NASA Astrophysics Data System (ADS)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Spatializing health research: what we know and where we are heading

PubMed Central

Yang, Tse-Chuan; Shoff, Carla; Noah, Aggie J.

2013-01-01

Beyond individual-level factors, researchers have adopted a spatial perspective to explore potentially modifiable environmental determinants of health. A spatial perspective can be integrated into health research by incorporating spatial data into studies or analyzing georeferenced data. Given the rapid changes in data collection methods and the complex dynamics between individuals and environment, we argue that GIS functions have shortcomings with respect to analytical capability and are limited when it comes to visualizing the temporal component in spatio-temporal data. In addition, we maintain that relatively little effort has been made to handle spatial heterogeneity. To that end, health researchers should be persuaded to better justify the theoretical meaning underlying the spatial matrix in analysis, while spatial data collectors, GIS specialists, spatial analysis methodologists, and the different breeds of users should be encouraged to work together making health research move forward through addressing these issues. PMID:23733281

Temporal Fourier analysis applied to equilibrium radionuclide cineangiography. Importance in the study of global and regional left ventricular wall motion.

PubMed

Cardot, J C; Berthout, P; Verdenet, J; Bidet, A; Faivre, R; Bassand, J P; Bidet, R; Maurat, J P

1982-01-01

Regional and global left ventricular wall motion was assessed in 120 patients using radionuclide cineangiography (RCA) and contrast angiography. Functional imaging procedures based on a temporal Fourier analysis of dynamic image sequences were applied to the study of cardiac contractility. Two images were constructed by taking the phase and amplitude values of the first harmonic in the Fourier transform for each pixel. These two images aided in determining the perimeter of the left ventricle to calculate the global ejection fraction. Regional left ventricular wall motion was studied by analyzing the phase value and by examining the distribution histogram of these values. The accuracy of global ejection fraction calculation was improved by the Fourier technique. This technique increased the sensitivity of RCA for determining segmental abnormalities especially in the left anterior oblique view (LAO).

Population Vulnerability to Biannual Cholera Outbreaks and Associated Macro-Scale Drivers in the Bengal Delta

PubMed Central

Akanda, Ali Shafqat; Jutla, Antarpreet S.; Gute, David M.; Sack, R. Bradley; Alam, Munirul; Huq, Anwar; Colwell, Rita R.; Islam, Shafiqul

2013-01-01

The highly populated floodplains of the Bengal Delta have a long history of endemic and epidemic cholera outbreaks, both coastal and inland. Previous studies have not addressed the spatio-temporal dynamics of population vulnerability related to the influence of underlying large-scale processes. We analyzed spatial and temporal variability of cholera incidence across six surveillance sites in the Bengal Delta and their association with regional hydroclimatic and environmental drivers. More specifically, we use salinity and flood inundation modeling across the vulnerable districts of Bangladesh to test earlier proposed hypotheses on the role of these environmental variables. Our results show strong influence of seasonal and interannual variability in estuarine salinity on spring outbreaks and inland flooding on fall outbreaks. A large segment of the population in the Bengal Delta floodplains remain vulnerable to these biannual cholera transmission mechanisms that provide ecologic and environmental conditions for outbreaks over large geographic regions. PMID:24019441

Neural field theory of perceptual echo and implications for estimating brain connectivity

NASA Astrophysics Data System (ADS)

Robinson, P. A.; Pagès, J. C.; Gabay, N. C.; Babaie, T.; Mukta, K. N.

2018-04-01

Neural field theory is used to predict and analyze the phenomenon of perceptual echo in which random input stimuli at one location are correlated with electroencephalographic responses at other locations. It is shown that this echo correlation (EC) yields an estimate of the transfer function from the stimulated point to other locations. Modal analysis then explains the observed spatiotemporal structure of visually driven EC and the dominance of the alpha frequency; two eigenmodes of similar amplitude dominate the response, leading to temporal beating and a line of low correlation that runs from the crown of the head toward the ears. These effects result from mode splitting and symmetry breaking caused by interhemispheric coupling and cortical folding. It is shown how eigenmodes obtained from functional magnetic resonance imaging experiments can be combined with temporal dynamics from EC or other evoked responses to estimate the spatiotemporal transfer function between any two points and hence their effective connectivity.

Spatial and temporal dynamics of the cardiac mitochondrial proteome.

PubMed

Lau, Edward; Huang, Derrick; Cao, Quan; Dincer, T Umut; Black, Caitie M; Lin, Amanda J; Lee, Jessica M; Wang, Ding; Liem, David A; Lam, Maggie P Y; Ping, Peipei

2015-04-01

Mitochondrial proteins alter in their composition and quantity drastically through time and space in correspondence to changing energy demands and cellular signaling events. The integrity and permutations of this dynamism are increasingly recognized to impact the functions of the cardiac proteome in health and disease. This article provides an overview on recent advances in defining the spatial and temporal dynamics of mitochondrial proteins in the heart. Proteomics techniques to characterize dynamics on a proteome scale are reviewed and the physiological consequences of altered mitochondrial protein dynamics are discussed. Lastly, we offer our perspectives on the unmet challenges in translating mitochondrial dynamics markers into the clinic.

Variable-angle epifluorescence microscopy characterizes protein dynamics in the vicinity of plasma membrane in plant cells.

PubMed

Chen, Tong; Ji, Dongchao; Tian, Shiping

2018-03-14

The assembly of protein complexes and compositional lipid patterning act together to endow cells with the plasticity required to maintain compositional heterogeneity with respect to individual proteins. Hence, the applications for imaging protein localization and dynamics require high accuracy, particularly at high spatio-temporal level. We provided experimental data for the applications of Variable-Angle Epifluorescence Microscopy (VAEM) in dissecting protein dynamics in plant cells. The VAEM-based co-localization analysis took penetration depth and incident angle into consideration. Besides direct overlap of dual-color fluorescence signals, the co-localization analysis was carried out quantitatively in combination with the methodology for calculating puncta distance and protein proximity index. Besides, simultaneous VAEM tracking of cytoskeletal dynamics provided more insights into coordinated responses of actin filaments and microtubules. Moreover, lateral motility of membrane proteins was analyzed by calculating diffusion coefficients and kymograph analysis, which represented an alternative method for examining protein motility. The present study presented experimental evidence on illustrating the use of VAEM in tracking and dissecting protein dynamics, dissecting endosomal dynamics, cell structure assembly along with membrane microdomain and protein motility in intact plant cells.

Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model

PubMed Central

Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel

2014-01-01

The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

The temporal distribution of directional gradients under selection for an optimum.

PubMed

Chevin, Luis-Miguel; Haller, Benjamin C

2014-12-01

Temporal variation in phenotypic selection is often attributed to environmental change causing movements of the adaptive surface relating traits to fitness, but this connection is rarely established empirically. Fluctuating phenotypic selection can be measured by the variance and autocorrelation of directional selection gradients through time. However, the dynamics of these gradients depend not only on environmental changes altering the fitness surface, but also on evolution of the phenotypic distribution. Therefore, it is unclear to what extent variability in selection gradients can inform us about the underlying drivers of their fluctuations. To investigate this question, we derive the temporal distribution of directional gradients under selection for a phenotypic optimum that is either constant or fluctuates randomly in various ways in a finite population. Our analytical results, combined with population- and individual-based simulations, show that although some characteristic patterns can be distinguished, very different types of change in the optimum (including a constant optimum) can generate similar temporal distributions of selection gradients, making it difficult to infer the processes underlying apparent fluctuating selection. Analyzing changes in phenotype distributions together with changes in selection gradients should prove more useful for inferring the mechanisms underlying estimated fluctuating selection. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Understanding the Spatio-Temporal Dynamics of Denitrification in an Oregon Salt Marsh

EPA Science Inventory

Salt marshes are highly susceptible to a range of climate change effects (e.g., sea-level rise, salinity changes, storm severity, shifts in vegetation across watershed). It is unclear how these effects will alter the spatial and temporal dynamics of denitrification, a potential p...

Modelling of the nonlinear soliton dynamics in the ring fibre cavity

NASA Astrophysics Data System (ADS)

Razukov, Vadim A.; Melnikov, Leonid A.

2018-04-01

Using the cabaret method numerical realization, long-time spatio-temporal dynamics of the electromagnetic field in a nonlinear ring fibre cavity with dispersion is investigated during the hundreds of round trips. Formation of both the temporal cavity solitons and irregular pulse trains is demonstrated and discussed.

Cortical Spatio-Temporal Dynamics Underlying Phonological Target Detection in Humans

ERIC Educational Resources Information Center

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

2011-01-01

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

Learning Human Actions by Combining Global Dynamics and Local Appearance.

PubMed

Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

Dynamic profiling of different ready-to-drink fermented dairy products: A comparative study using Temporal Check-All-That-Apply (TCATA), Temporal Dominance of Sensations (TDS) and Progressive Profile (PP).

PubMed

Esmerino, Erick A; Castura, John C; Ferraz, Juliana P; Tavares Filho, Elson R; Silva, Ramon; Cruz, Adriano G; Freitas, Mônica Q; Bolini, Helena M A

2017-11-01

Despite the several differences in ingredients, processes and nutritional values, dairy foods as yogurts, fermented milks and milk beverages are widely accepted worldwide, and although they have their sensory profiling normally covered by descriptive analyses, the temporal perception involved during the consumption are rarely considered. In this sense, the present work aimed to assess the dynamic sensory profile of three categories of fermented dairy products using different temporal methodologies: Temporal Dominance of Sensations (TDS), Progressive Profiling (PP), Temporal CATA (TCATA), and compare the results obtained. The findings showed that the different sensory characteristics among the products are basically related to their commercial identity. Regarding the methods, all of them collected the variations between samples with great correlation between data. In addition, to detect differences in intensities, TCATA showed to be the most sensitive method in detecting textural changes. When using PP, a balanced experimental design considering the number of attributes, time intervals, and food matrix must be weighed. The findings are of interest to guide sensory and consumer practitioners involved in the dairy production to formulate/reformulate their products and help them choosing the most suitable dynamic method to temporally evaluate them. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analytical Computation of the Epidemic Threshold on Temporal Networks

NASA Astrophysics Data System (ADS)

Valdano, Eugenio; Ferreri, Luca; Poletto, Chiara; Colizza, Vittoria

2015-04-01

The time variation of contacts in a networked system may fundamentally alter the properties of spreading processes and affect the condition for large-scale propagation, as encoded in the epidemic threshold. Despite the great interest in the problem for the physics, applied mathematics, computer science, and epidemiology communities, a full theoretical understanding is still missing and currently limited to the cases where the time-scale separation holds between spreading and network dynamics or to specific temporal network models. We consider a Markov chain description of the susceptible-infectious-susceptible process on an arbitrary temporal network. By adopting a multilayer perspective, we develop a general analytical derivation of the epidemic threshold in terms of the spectral radius of a matrix that encodes both network structure and disease dynamics. The accuracy of the approach is confirmed on a set of temporal models and empirical networks and against numerical results. In addition, we explore how the threshold changes when varying the overall time of observation of the temporal network, so as to provide insights on the optimal time window for data collection of empirical temporal networked systems. Our framework is of both fundamental and practical interest, as it offers novel understanding of the interplay between temporal networks and spreading dynamics.

Temporal steering and security of quantum key distribution with mutually unbiased bases against individual attacks

NASA Astrophysics Data System (ADS)

Bartkiewicz, Karol; Černoch, Antonín; Lemr, Karel; Miranowicz, Adam; Nori, Franco

2016-06-01

Temporal steering, which is a temporal analog of Einstein-Podolsky-Rosen steering, refers to temporal quantum correlations between the initial and final state of a quantum system. Our analysis of temporal steering inequalities in relation to the average quantum bit error rates reveals the interplay between temporal steering and quantum cloning, which guarantees the security of quantum key distribution based on mutually unbiased bases against individual attacks. The key distributions analyzed here include the Bennett-Brassard 1984 protocol and the six-state 1998 protocol by Bruss. Moreover, we define a temporal steerable weight, which enables us to identify a kind of monogamy of temporal correlation that is essential to quantum cryptography and useful for analyzing various scenarios of quantum causality.

Spatio-temporal dynamics of species richness in coastal fish communities

USGS Publications Warehouse

Lekve, K.; Boulinier, T.; Stenseth, N.C.; Gjøsaeter, J.; Fromentin, J-M.; Hines, J.E.; Nichols, J.D.

2002-01-01

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

Spatial-Temporal Dynamics of Urban Fire Incidents: a Case Study of Nanjing, China

NASA Astrophysics Data System (ADS)

Yao, J.; Zhang, X.

2016-06-01

Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.

Sensitivity analysis of Repast computational ecology models with R/Repast.

PubMed

Prestes García, Antonio; Rodríguez-Patón, Alfonso

2016-12-01

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.

Analyzing the Velocity of Urban Dynamic Over Northeastern China Using Dmsp-Ols Night-Time Lights

NASA Astrophysics Data System (ADS)

Zhou, Y.

2017-09-01

Stable night-time lights (NTL) data from the Defense Meteorological Satellite Program Operational Line-scan System (DMSPOLS) can serve as a good proxy for anthropogenic development. Here DMSP-OLS NTL data was used to detect the urban development status in northeastern China. The spatial and temporal gradients are combined to depict the velocity of urban expanding process. This velocity index represents the instantaneous local velocity along the Earth's surface needed to maintain constant NTL condition, and has a mean of 0.36 km/yr for northeastern China. The velocity change of NTL is lower in the urban center and its near regions, and the suburbs show a relatively high value. The connecting zones between satellite cities and metropolis have also a rapid rate of NTL evolution. The dynamic process of urbanization over the study area is mainly in a manner of spreading from urban cores to edges. The rank size of the velocity for the prefectures is analyzed and a long tail distribution is found. The velocity index can provide insights for the future pattern of urban sprawl.

3D Study of the Morphology and Dynamics of Zeolite Nucleation.

PubMed

Melinte, Georgian; Georgieva, Veselina; Springuel-Huet, Marie-Anne; Nossov, Andreï; Ersen, Ovidiu; Guenneau, Flavien; Gedeon, Antoine; Palčić, Ana; Bozhilov, Krassimir N; Pham-Huu, Cuong; Qiu, Shilun; Mintova, Svetlana; Valtchev, Valentin

2015-12-07

The principle aspects and constraints of the dynamics and kinetics of zeolite nucleation in hydrogel systems are analyzed on the basis of a model Na-rich aluminosilicate system. A detailed time-series EMT-type zeolite crystallization study in the model hydrogel system was performed to elucidate the topological and temporal aspects of zeolite nucleation. A comprehensive set of analytical tools and methods was employed to analyze the gel evolution and complement the primary methods of transmission electron microscopy (TEM) and nuclear magnetic resonance (NMR) spectroscopy. TEM tomography reveals that the initial gel particles exhibit a core-shell structure. Zeolite nucleation is topologically limited to this shell structure and the kinetics of nucleation is controlled by the shell integrity. The induction period extends to the moment when the shell is consumed and the bulk solution can react with the core of the gel particles. These new findings, in particular the importance of the gel particle shell in zeolite nucleation, can be used to control the growth process and properties of zeolites formed in hydrogels. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Spatio-temporal dynamics of fishing effort in a multi-species artisanal diving fishery and its effects on catch variability: insights for sustainable management].

PubMed

Naranjo Madrigall, Helven; Salas Marquez, Silvia

2014-12-01

Artisanal diving fisheries are a source of income, employment and food security of coastal areas in many countries. Understanding the dynamics of these fisheries, including the spatial and temporal dynamics of fishing effort, gears and species can help to address the challenges involved in fisheries management. We aimed to analyze the differences in fishing strategies undertaken by fishers that use two different diving methods (hookah and free diving), the conditions and their potential impacts on catches when adjustments to those strategies are applied over time. For this, detailed information of fishing operations from artisanal boats in the North Pacific coast of Costa Rica was analyzed in two fishing seasons (2007-2008 and 2011-2012). Data were collected by onboard observers (fishing site, fishing time, species composition, depth and visibility). Additionally, interviews with divers were applied to obtain information of price per species, species volume and fishing operations. From the total number of trips during both seasons, hookah diving was represented by a sample size of 69.3%, while free diving, with a sample of 41.9%. More than 15 species were identified in each fishing season. Nevertheless, three categories had substantial contributions in both seasons with differences in the proportions for each case: green lobster (Panulirus gracilis), octopus (Octopus sp.) and parrotfish (Scarus perrico and S. ghobban). It is worth noting that an important proportion of catch was retained by fishers for personal consumption purposes, including species of high commercial value. Additional night diving activity, increased the number of dives from one season to another. Besides, cooperation processes in free diving fishing operations, and changes in fishing effort between seasons, defined important changes in fishing strategies. Potential causes of changes in fishing strategies and the implications for management to ensure the sustainability of these fisheries in the long term are discussed.

Travelling waves and spatial hierarchies in measles epidemics

NASA Astrophysics Data System (ADS)

Grenfell, B. T.; Bjørnstad, O. N.; Kappey, J.

2001-12-01

Spatio-temporal travelling waves are striking manifestations of predator-prey and host-parasite dynamics. However, few systems are well enough documented both to detect repeated waves and to explain their interaction with spatio-temporal variations in population structure and demography. Here, we demonstrate recurrent epidemic travelling waves in an exhaustive spatio-temporal data set for measles in England and Wales. We use wavelet phase analysis, which allows for dynamical non-stationarity-a complication in interpreting spatio-temporal patterns in these and many other ecological time series. In the pre-vaccination era, conspicuous hierarchical waves of infection moved regionally from large cities to small towns; the introduction of measles vaccination restricted but did not eliminate this hierarchical contagion. A mechanistic stochastic model suggests a dynamical explanation for the waves-spread via infective `sparks' from large `core' cities to smaller `satellite' towns. Thus, the spatial hierarchy of host population structure is a prerequisite for these infection waves.

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

PubMed Central

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

Dynamic decomposition of spatiotemporal neural signals

PubMed Central

2017-01-01

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals. PMID:28558039

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, R; Gallagher, B; Neville, J

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 ourmore » 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.« less

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

ERIC Educational Resources Information Center

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…

The Temporal Dynamics of Spoken Word Recognition in Adverse Listening Conditions

ERIC Educational Resources Information Center

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.…

Temporal Dynamics in Auditory Perceptual Learning: Impact of Sequencing and Incidental Learning

ERIC Educational Resources Information Center

Church, Barbara A.; Mercado, Eduardo, III; Wisniewski, Matthew G.; Liu, Estella H.

2013-01-01

Training can improve perceptual sensitivities. We examined whether the temporal dynamics and the incidental versus intentional nature of training are important. Within the context of a birdsong rate discrimination task, we examined whether the sequencing of pretesting exposure to the stimuli mattered. Easy-to-hard (progressive) sequencing of…

Superior Temporal Activation in Response to Dynamic Audio-Visual Emotional Cues

ERIC Educational Resources Information Center

Robins, Diana L.; Hunyadi, Elinora; Schultz, Robert T.

2009-01-01

Perception of emotion is critical for successful social interaction, yet the neural mechanisms underlying the perception of dynamic, audio-visual emotional cues are poorly understood. Evidence from language and sensory paradigms suggests that the superior temporal sulcus and gyrus (STS/STG) play a key role in the integration of auditory and visual…

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

PubMed

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 cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.

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

PubMed

Hansen, Sofie Therese; Hansen, Lars Kai

2017-03-01

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 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 connections exist in the brain than long ranging, arguing for spatially focal sources. Additionally, recent work (Delorme et al., 2012) argues that EEG can be decomposed into components having sparse source distributions. On the temporal side both short and long term stationarity of brain activation are seen. We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

Linking degradation status with ecosystem vulnerability to environmental change

USGS Publications Warehouse

Angeler, David G.; Baho, Didier L.; Allen, Craig R.; Johnson, Richard K.

2015-01-01

Environmental change can cause regime shifts in ecosystems, potentially threatening ecosystem services. It is unclear if the degradation status of ecosystems correlates with their vulnerability to environmental change, and thus the risk of future regime shifts. We assessed resilience in acidified (degraded) and circumneutral (undegraded) lakes with long-term data (1988–2012), using time series modeling. We identified temporal frequencies in invertebrate assemblages, which identifies groups of species whose population dynamics vary at particular temporal scales. We also assessed species with stochastic dynamics, those whose population dynamics vary irregularly and unpredictably over time. We determined the distribution of functional feeding groups of invertebrates within and across the temporal scales identified, and in those species with stochastic dynamics, and assessed attributes hypothesized to contribute to resilience. Three patterns of temporal dynamics, consistent across study lakes, were identified in the invertebrates. The first pattern was one of monotonic change associated with changing abiotic lake conditions. The second and third patterns appeared unrelated to the environmental changes we monitored. Acidified and the circumneutral lakes shared similar levels and patterns of functional richness, evenness, diversity, and redundancy for species within and across the observed temporal scales and for stochastic species groups. These similar resilience characteristics suggest that both lake types did not differ in vulnerability to the environmental changes observed here. Although both lake types appeared equally vulnerable in this study, our approach demonstrates how assessing systemic vulnerability by quantifying ecological resilience can help address uncertainty in predicting ecosystem responses to environmental change across ecosystems.

Flexible retrospective selection of temporal resolution in real-time speech MRI using a golden-ratio spiral view order.

PubMed

Kim, Yoon-Chul; Narayanan, Shrikanth S; Nayak, Krishna S

2011-05-01

In speech production research using real-time magnetic resonance imaging (MRI), the analysis of articulatory dynamics is performed retrospectively. A flexible selection of temporal resolution is highly desirable because of natural variations in speech rate and variations in the speed of different articulators. The purpose of the study is to demonstrate a first application of golden-ratio spiral temporal view order to real-time speech MRI and investigate its performance by comparison with conventional bit-reversed temporal view order. Golden-ratio view order proved to be more effective at capturing the dynamics of rapid tongue tip motion. A method for automated blockwise selection of temporal resolution is presented that enables the synthesis of a single video from multiple temporal resolution videos and potentially facilitates subsequent vocal tract shape analysis. Copyright © 2010 Wiley-Liss, Inc.

Causal relations among events and states in dynamic geographical phenomena

NASA Astrophysics Data System (ADS)

Huang, Zhaoqiang; Feng, Xuezhi; Xuan, Wenling; Chen, Xiuwan

2007-06-01

There is only a static state of the real world to be recorded in conventional geographical information systems. However, there is not only static information but also dynamic information in geographical phenomena. So that how to record the dynamic information and reveal the relations among dynamic information is an important issue in a spatio-temporal information system. From an ontological perspective, we can initially divide the spatio-temporal entities in the world into continuants and occurrents. Continuant entities endure through some extended (although possibly very short) interval of time (e.g., houses, roads, cities, and real-estate). Occurrent entities happen and are then gone (e.g., a house repair job, road construction project, urban expansion, real-estate transition). From an information system perspective, continuants and occurrents that have a unique identity in the system are referred to as objects and events, respectively. And the change is represented implicitly by static snapshots in current spatial temporal information systems. In the previous models, the objects can be considered as the fundamental components of the system, and the change is modeled by considering time-varying attributes of these objects. In the spatio-temporal database, the temporal information that is either interval or instant is involved and the underlying data structures and indexes for temporal are considerable investigated. However, there is the absence of explicit ways of considering events, which affect the attributes of objects or the state. So the research issue of this paper focuses on how to model events in conceptual models of dynamic geographical phenomena and how to represent the causal relations among events and the objects or states. Firstly, the paper reviews the conceptual modeling in a temporal GIS by researchers. Secondly, this paper discusses the spatio-temporal entities: objects and events. Thirdly, this paper investigates the causal relations amongst events and states. The qualitative spatiotemporal change is an important issue in the dynamic geographic-scale phenomena. In real estate transition, the events and states are needed to be represented explicitly. In our modeling the evolution of a dynamic system, it can not avoid fetching in the view of causality. The object's transition is represented by the state of object. Event causes the state of objects changing and causes other events happen. Events connect with objects closely. The basic causal relations are the state-event and event-state relationships. Lastly, the paper concludes with the overview about the causal relations amongst events and states. And this future work is pointed.

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

DOE PAGES

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...

2016-07-25

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Dynamic Network-Based Epistasis Analysis: Boolean Examples

PubMed Central

Azpeitia, Eugenio; Benítez, Mariana; Padilla-Longoria, Pablo; Espinosa-Soto, Carlos; Alvarez-Buylla, Elena R.

2011-01-01

In this article we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the inference of gene regulatory networks. Here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson, epistasis is defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus (herein, classical epistasis). Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct inference of gene interaction topologies is hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our article complements previous accounts, not only by focusing on the implications of the hierarchical and single-path assumption, but also by demonstrating the importance of considering temporal dynamics, and specifically introducing the usefulness of Boolean network models and also reviewing some key properties of network approaches. PMID:22645556

Time-resolved scanning electron microscopy with polarization analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frömter, Robert, E-mail: rfroemte@physik.uni-hamburg.de; Oepen, Hans Peter; The Hamburg Centre for Ultrafast Imaging, Luruper Chaussee 149, 22761 Hamburg

2016-04-04

We demonstrate the feasibility of investigating periodically driven magnetization dynamics in a scanning electron microscope with polarization analysis based on spin-polarized low-energy electron diffraction. With the present setup, analyzing the time structure of the scattering events, we obtain a temporal resolution of 700 ps, which is demonstrated by means of imaging the field-driven 100 MHz gyration of the vortex in a soft-magnetic FeCoSiB square. Owing to the efficient intrinsic timing scheme, high-quality movies, giving two components of the magnetization simultaneously, can be recorded on the time scale of hours.

Surge dynamics coupled to pore-pressure evolution in debris flows

USGS Publications Warehouse

Savage, S.B.; Iverson, R.M.; ,

2003-01-01

Temporally and spatially varying pore-fluid pressures exert strong controls on debris-flow motion by mediating internal and basal friction at grain contacts. We analyze these effects by deriving a one-dimensional model of pore-pressure diffusion explicitly coupled to changes in debris-flow thickness. The new pore-pressure equation is combined with Iverson's (1997) extension of the depth-averaged Savage-Hutter (1989, 1991) granular avalanche equations to predict motion of unsteady debris-flow surges with evolving pore-pressure distributions. Computational results illustrate the profound effects of pore-pressure diffusivities on debris-flow surge depths and velocities. ?? 2003 Millpress,.

Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.

PubMed

Varala, Kranthi; Marshall-Colón, Amy; Cirrone, Jacopo; Brooks, Matthew D; Pasquino, Angelo V; Léran, Sophie; Mittal, Shipra; Rock, Tara M; Edwards, Molly B; Kim, Grace J; Ruffel, Sandrine; McCombie, W Richard; Shasha, Dennis; Coruzzi, Gloria M

2018-06-19

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF "N-specificity" index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs-CRF4, SNZ, CDF1, HHO5/6, and PHL1-validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15 NO 3 - uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal "transcriptional logic" for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine. Copyright © 2018 the Author(s). Published by PNAS.

Temporal dynamics of the gut microbiota in people sharing a confined environment, a 520-day ground-based space simulation, MARS500.

PubMed

Turroni, Silvia; Rampelli, Simone; Biagi, Elena; Consolandi, Clarissa; Severgnini, Marco; Peano, Clelia; Quercia, Sara; Soverini, Matteo; Carbonero, Franck G; Bianconi, Giovanna; Rettberg, Petra; Canganella, Francesco; Brigidi, Patrizia; Candela, Marco

2017-03-24

The intestinal microbial communities and their temporal dynamics are gaining increasing interest due to the significant implications for human health. Recent studies have shown the dynamic behavior of the gut microbiota in free-living, healthy persons. To date, it is not known whether these dynamics are applicable during prolonged life sharing in a confined and controlled environment. The MARS500 project, the longest ground-based space simulation ever, provided us with a unique opportunity to trace the crew microbiota over 520 days of isolated confinement, such as that faced by astronauts in real long-term interplanetary space flights, and after returning to regular life, for a total of 2 years. According to our data, even under the strictly controlled conditions of an enclosed environment, the human gut microbiota is inherently dynamic, capable of shifting between different steady states, typically with rearrangements of autochthonous members. Notwithstanding a strong individuality in the overall gut microbiota trajectory, some key microbial components showed conserved temporal dynamics, with potential implications for the maintenance of a health-promoting, mutualistic microbiota configuration. Sharing life in a confined habitat does not affect the resilience of the individual gut microbial ecosystem, even in the long term. However, the temporal dynamics of certain microbiota components should be monitored when programming future mission simulations and real space flights, to prevent breakdowns in the metabolic and immunological homeostasis of the crewmembers.

Identification of drivers of (dis)liking based on dynamic sensory profiles: Comparison of Temporal Dominance of Sensations and Temporal Check-all-that-apply.

PubMed

Ares, Gastón; Alcaire, Florencia; Antúnez, Lucía; Vidal, Leticia; Giménez, Ana; Castura, John C

2017-02-01

Temporal Dominance of Sensations (TDS) and Temporal Check-all-that-apply (TCATA) are two multi-attribute methods for dynamic sensory characterization. Previous research has shown that both methodologies provide complementary information. However, it remains an open question which of the two approaches better explains consumers' hedonic perception of products. In this context, the aim of the present work was to compare TDS and TCATA in terms of their ability to identify the influence of the dynamic sensory profile of food products on consumer overall liking scores. Two consumer studies were conducted using two different product categories (French bread and vanilla milk desserts). In each study, a between-subjects design was used to obtain dynamic sensory profiles using TDS and TCATA. After the dynamic sensory characterization tasks consumers rated their liking using a 9-point hedonic scale. Across the two studies, both methodologies provided similar information on the main drivers of liking and disliking, particularly when samples showed clear differences in liking. However, in one of the studies attribute applicability from TCATA provided additional insights on the influence of the dynamics of the sensory characteristics of products on consumers' liking. Results of the present work stress the complementarity between TCATA and TDS and highlight the potentiality of TCATA to provide a more detailed description of the dynamics of sensory perception during consumption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms.

PubMed

Cabral, Joana; Kringelbach, Morten L; Deco, Gustavo

2017-10-15

Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity. Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

Label-free nanoscale characterization of red blood cell structure and dynamics using single-shot transport of intensity equation

NASA Astrophysics Data System (ADS)

Poola, Praveen Kumar; John, Renu

2017-10-01

We report the results of characterization of red blood cell (RBC) structure and its dynamics with nanometric sensitivity using transport of intensity equation microscopy (TIEM). Conventional transport of intensity technique requires three intensity images and hence is not suitable for studying real-time dynamics of live biological samples. However, assuming the sample to be homogeneous, phase retrieval using transport of intensity equation has been demonstrated with single defocused measurement with x-rays. We adopt this technique for quantitative phase light microscopy of homogenous cells like RBCs. The main merits of this technique are its simplicity, cost-effectiveness, and ease of implementation on a conventional microscope. The phase information can be easily merged with regular bright-field and fluorescence images to provide multidimensional (three-dimensional spatial and temporal) information without any extra complexity in the setup. The phase measurement from the TIEM has been characterized using polymeric microbeads and the noise stability of the system has been analyzed. We explore the structure and real-time dynamics of RBCs and the subdomain membrane fluctuations using this technique.

Harvesting liquid from unsaturated vapor - nanoflows induced by capillary condensation

NASA Astrophysics Data System (ADS)

Vincent, Olivier; Marguet, Bastien; Stroock, Abraham

2016-11-01

A vapor, even subsaturated, can spontaneously form liquid in nanoscale spaces. This process, known as capillary condensation, plays a fundamental role in various contexts, such as the formation of clouds or the dynamics of hydrocarbons in the geological subsurface. However, large uncertainties remain on the thermodynamics and fluid mechanics of the phenomenon, due to experimental challenges as well as outstanding questions about the validity of macroscale physics at the nanometer scale. We studied experimentally the spatio-temporal dynamics of water condensation in a model nanoporous medium (pore radius 2 nm), taking advantage of the color change of the material upon hydration. We found that at low relative humidities (< 60 % RH), capillary condensation progressed in a diffusive fashion, while it occurred through a well-defined capillary-viscous imbibition front at > 60 % RH, driven by a balance between the pore capillary pressure and the condensation stress given by Kelvin equation. Further analyzing the imbibition dynamics as a function of saturation allowed us to extract detailed information about the physics of nano-confined fluids. Our results suggest excellent extension of macroscale fluid dynamics and thermodynamics even in pores 10 molecules in diameter.

Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.

PubMed

de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca

2018-05-01

Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

NASA Astrophysics Data System (ADS)

Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability and internal climatic fluctuation. The EVI and phenological patterns varied spatially according to climate variations and human management. The overall regional mean EVI value in SEA from 2001 to 2010 has gradually decreased and phenological trends appeared to shift towards a later and slightly longer growing season. Regional vegetation dynamics over SEA exhibited patterns associated with major climate events such as El Nino in 2005. The rainy season tended to start early and end late and the length of rainy season was slightly longer. However, the amount of rainfall has decreased from 2001 to 2010. The relationship between phenology and rainfall varied among different ecosystems. Additionally, the local scale results indicated that rainfall is a dominant force of phenological changes in naturally vegetated areas and rainfed croplands, whereas human management is a key factor in heavily agricultural areas with irrigated systems. The results of estimating GHG emissions from rice fields in Thailand demonstrated that human management, climate variation, and physical geography had a significant influence on the change in GHG emissions. In addition, the complexity of spatio-temporal patterns in phenology and related variables were displayed on the visualization system with effective functions and an interactive interface. The information and knowledge in this research are useful for local and regional environmental management and for identifying mitigation strategies in the context of climate change and ecosystem dynamics in this region.

Dynamic diaschisis: anatomically remote and context-sensitive human brain lesions.

PubMed

Price, C J; Warburton, E A; Moore, C J; Frackowiak, R S; Friston, K J

2001-05-15

Functional neuroimaging was used to investigate how lesions to the Broca's area impair neuronal responses in remote undamaged cortical regions. Four patients with speech output problems, but relatively preserved comprehension, were scanned while viewing words relative to consonant letter strings. In normal subjects, this results in left lateralized activation in the posterior inferior frontal, middle temporal, and posterior inferior temporal cortices. Each patient activated normally in the middle temporal region but abnormally in the damaged posterior inferior frontal cortex and the undamaged posterior inferior temporal cortex. In the damaged frontal region, activity was insensitive to the presence of words but in the undamaged posterior inferior temporal region, activity decreased in the presence of words rather than increasing as it did in the normal individuals. The reversal of responses in the left posterior inferior temporal region illustrate the context-sensitive nature of the abnormality and that failure to activate the left posterior temporal region could not simply be accounted for by insufficient demands on the underlying function. We propose that, in normal individuals, visual word presentation changes the effective connectivity among reading areas and, in patients, posterior temporal responses are abnormal when they depend upon inputs from the damaged inferior frontal cortex. Our results serve to introduce the concept of dynamic diaschisis; the anatomically remote and context-sensitive effects of focal brain lesions. Dynamic diaschisis reveals abnormalities of functional integration that may have profound implications for neuropsychological inference, functional anatomy and, vicariously, cognitive rehabilitation.

Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

NASA Astrophysics Data System (ADS)

Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

2001-12-01

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing.

PubMed

Wu, Desheng; Ning, Shuang

2018-07-01

Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

Diurnal dynamics of the CO2 concentration in water of the coastal zone of lake Baikal in the ice period (testing of the DIEL - CO2 method for assessment of lake metabolic rate)

NASA Astrophysics Data System (ADS)

Panchenko, M. V.; Domysheva, V. M.; Pestunov, D. A.; Sakirko, M. V.; Ivanov, V. G.; Shamrin, A. M.

2017-11-01

Results of three long cycles of 24-hour measurements of the carbon dioxide content in the surface and bottom water in the ice period of 2014-2016 in the Baikal coastal zone are analyzed. The diurnal dynamics of the CO2 concentration in the subglacial water, in which photosynthesis plays the leading role, is described. It is found that, in comparison with the surface subglacial water (that is, directly adjacent to the ice bottom), the more pronounced diurnal rhythm of CO2 is observed in the bottom layer in all realizations. This rhythm is well correlated with pyranometer readings. The data on the diurnal dynamics of CO2 are used to estimate the gross primary production in the bottom water with the DIEL method based on the analysis of temporal variability of the carbon dioxide concentration in water in situ.

Temporal dynamics and developmental memory of 3D chromatin architecture at Hox gene loci

PubMed Central

Noordermeer, Daan; Leleu, Marion; Schorderet, Patrick; Joye, Elisabeth; Chabaud, Fabienne; Duboule, Denis

2014-01-01

Hox genes are essential regulators of embryonic development. Their step-wise transcriptional activation follows their genomic topology and the various states of activation are subsequently memorized into domains of progressively overlapping gene products. We have analyzed the 3D chromatin organization of Hox clusters during their early activation in vivo, using high-resolution circular chromosome conformation capture. Initially, Hox clusters are organized as single chromatin compartments containing all genes and bivalent chromatin marks. Transcriptional activation is associated with a dynamic bi-modal 3D organization, whereby the genes switch autonomously from an inactive to an active compartment. These local 3D dynamics occur within a framework of constitutive interactions within the surrounding Topological Associated Domains, indicating that this regulation process is mostly cluster intrinsic. The step-wise progression in time is fixed at various body levels and thus can account for the chromatin architectures previously described at a later stage for different anterior to posterior levels. DOI: http://dx.doi.org/10.7554/eLife.02557.001 PMID:24843030

Combined Molecular and Spin Dynamics Simulation of Lattice Vacancies in BCC Iron

NASA Astrophysics Data System (ADS)

Mudrick, Mark; Perera, Dilina; Eisenbach, Markus; Landau, David P.

Using an atomistic model that treats translational and spin degrees of freedom equally, combined molecular and spin dynamics simulations have been performed to study dynamic properties of BCC iron at varying levels of defect impurity. Atomic interactions are described by an empirical many-body potential, and spin interactions with a Heisenberg-like Hamiltonian with a coordinate dependent exchange interaction. Equations of motion are solved numerically using the second-order Suzuki-Trotter decomposition for the time evolution operator. We analyze the spatial and temporal correlation functions for atomic displacements and magnetic order to obtain the effect of vacancy defects on the phonon and magnon excitations. We show that vacancy clusters in the material cause splitting of the characteristic transverse spin-wave excitations, indicating the production of additional excitation modes. Additionally, we investigate the coupling of the atomic and magnetic modes. These modes become more distinct with increasing vacancy cluster size. This material is based upon work supported by the U.S. Department of Energy Office of Science Graduate Student Research (SCGSR) program.

Dynamic phosphorylation of Ebola virus VP30 in NP-induced inclusion bodies.

PubMed

Lier, Clemens; Becker, Stephan; Biedenkopf, Nadine

2017-12-01

Zaire Ebolavirus (EBOV) causes a severe feverish disease with high case fatality rates. Transcription of EBOV is dependent on the activity of the nucleocapsid protein VP30 which represents an essential viral transcription factor. Activity of VP30 is regulated via phosphorylation at six N-terminal serine residues. Recent data demonstrated that dynamic phosphorylation and dephosphorylation of serine residue 29 is essential for transcriptional support activity of VP30. To analyze the spatio/temporal dynamics of VP30 phosphorylation, we generated a peptide antibody recognizing specifically VP30 phosphorylated at serine 29. Using this antibody we could demonstrate that (i) the majority of VP30 molecules in EBOV-infected cells is dephosphorylated at the crucial position serine 29, (ii) both, VP30 phosphorylation and dephosphorylation take place in viral inclusion bodies that are induced by the nucleoprotein NP and (iii) NP influences the phosphorylation state of VP30. Copyright © 2017 Elsevier Inc. All rights reserved.

In situ imaging of the dynamics of photo-induced structural phase transition at high pressures by picosecond acoustic interferometry

NASA Astrophysics Data System (ADS)

Kuriakose, Maju; Chigarev, Nikolay; Raetz, Samuel; Bulou, Alain; Tournat, Vincent; Zerr, Andreas; Gusev, Vitalyi E.

2017-05-01

Picosecond acoustic interferometry is used to monitor in time the motion of the phase transition boundary between two water ice phases, VII and VI, coexisting at a pressure of 2.15 GPa when compressed in a diamond anvil cell at room temperature. By analyzing the time-domain Brillouin scattering signals accumulated for a single incidence direction of probe laser pulses, it is possible to access ratios of sound velocity values and of the refractive indices of the involved phases, and to distinguish between the structural phase transition and a recrystallization process. Two-dimensional spatial imaging of the phase transition dynamics indicates that it is initiated by the pump and probe laser pulses, preferentially at the diamond/ice interface. This method should find applications in three-dimensional monitoring with nanometer spatial resolution of the temporal dynamics of low-contrast material inhomogeneities caused by phase transitions or chemical reactions in optically transparent media.

Predictable internal brain dynamics in EEG and its relation to conscious states

PubMed Central

Yoo, Jaewook; Kwon, Jaerock; Choe, Yoonsuck

2014-01-01

Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory), protention (anticipation), and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG) data. Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS). Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics. PMID:24917813

Modal decomposition of turbulent supersonic cavity

NASA Astrophysics Data System (ADS)

Soni, R. K.; Arya, N.; De, A.

2018-06-01

Self-sustained oscillations in a Mach 3 supersonic cavity with a length-to-depth ratio of three are investigated using wall-modeled large eddy simulation methodology for ReD = 3.39× 105 . The unsteady data obtained through computation are utilized to investigate the spatial and temporal evolution of the flow field, especially the second invariant of the velocity tensor, while the phase-averaged data are analyzed over a feedback cycle to study the spatial structures. This analysis is accompanied by the proper orthogonal decomposition (POD) data, which reveals the presence of discrete vortices along the shear layer. The POD analysis is performed in both the spanwise and streamwise planes to extract the coherence in flow structures. Finally, dynamic mode decomposition is performed on the data sequence to obtain the dynamic information and deeper insight into the self-sustained mechanism.

A neural coding scheme reproducing foraging trajectories

PubMed Central

Gutiérrez, Esther D.; Cabrera, Juan Luis

2015-01-01

The movement of many animals may follow Lévy patterns. The underlying generating neuronal dynamics of such a behavior is unknown. In this paper we show that a novel discovery of multifractality in winnerless competition (WLC) systems reveals a potential encoding mechanism that is translatable into two dimensional superdiffusive Lévy movements. The validity of our approach is tested on a conductance based neuronal model showing WLC and through the extraction of Lévy flights inducing fractals from recordings of rat hippocampus during open field foraging. Further insights are gained analyzing mice motor cortex neurons and non motor cell signals. The proposed mechanism provides a plausible explanation for the neuro-dynamical fundamentals of spatial searching patterns observed in animals (including humans) and illustrates an until now unknown way to encode information in neuronal temporal series. PMID:26648311

Development of Four Dimensional Human Model that Enables Deformation of Skin, Organs and Blood Vessel System During Body Movement - Visualizing Movements of the Musculoskeletal System.

PubMed

Suzuki, Naoki; Hattori, Asaki; Hashizume, Makoto

2016-01-01

We constructed a four dimensional human model that is able to visualize the structure of a whole human body, including the inner structures, in real-time to allow us to analyze human dynamic changes in the temporal, spatial and quantitative domains. To verify whether our model was generating changes according to real human body dynamics, we measured a participant's skin expansion and compared it to that of the model conducted under the same body movement. We also made a contribution to the field of orthopedics, as we were able to devise a display method that enables the observer to more easily observe the changes made in the complex skeletal muscle system during body movements, which in the past were difficult to visualize.

Disease elimination and re-emergence in differential-equation models.

PubMed

Greenhalgh, Scott; Galvani, Alison P; Medlock, Jan

2015-12-21

Traditional differential equation models of disease transmission are often used to predict disease trajectories and evaluate the effectiveness of alternative intervention strategies. However, such models cannot account explicitly for probabilistic events, such as those that dominate dynamics when disease prevalence is low during the elimination and re-emergence phases of an outbreak. To account for the dynamics at low prevalence, i.e. the elimination and risk of disease re-emergence, without the added analytical and computational complexity of a stochastic model, we develop a novel application of control theory. We apply our approach to analyze historical data of measles elimination and re-emergence in Iceland from 1923 to 1938, predicting the temporal trajectory of local measles elimination and re-emerge as a result of disease migration from Copenhagen, Denmark. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamics of brain networks in the aesthetic appreciation

PubMed Central

Cela-Conde, Camilo J.; García-Prieto, Juan; Ramasco, José J.; Mirasso, Claudio R.; Bajo, Ricardo; Munar, Enric; Flexas, Albert; del-Pozo, Francisco; Maestú, Fernando

2013-01-01

Neuroimage experiments have been essential for identifying active brain networks. During cognitive tasks as in, e.g., aesthetic appreciation, such networks include regions that belong to the default mode network (DMN). Theoretically, DMN activity should be interrupted during cognitive tasks demanding attention, as is the case for aesthetic appreciation. Analyzing the functional connectivity dynamics along three temporal windows and two conditions, beautiful and not beautiful stimuli, here we report experimental support for the hypothesis that aesthetic appreciation relies on the activation of two different networks, an initial aesthetic network and a delayed aesthetic network, engaged within distinct time frames. Activation of the DMN might correspond mainly to the delayed aesthetic network. We discuss adaptive and evolutionary explanations for the relationships existing between the DMN and aesthetic networks and offer unique inputs to debates on the mind/brain interaction. PMID:23754437

Dynamic conservation for migratory species

PubMed Central

Reynolds, Mark D.; Sullivan, Brian L.; Hallstein, Eric; Matsumoto, Sandra; Kelling, Steve; Merrifield, Matthew; Fink, Daniel; Johnston, Alison; Hochachka, Wesley M.; Bruns, Nicholas E.; Reiter, Matthew E.; Veloz, Sam; Hickey, Catherine; Elliott, Nathan; Martin, Leslie; Fitzpatrick, John W.; Spraycar, Paul; Golet, Gregory H.; McColl, Christopher; Low, Candace; Morrison, Scott A.

2017-01-01

In an era of unprecedented and rapid global change, dynamic conservation strategies that tailor the delivery of habitat to when and where it is most needed can be critical for the persistence of species, especially those with diverse and dispersed habitat requirements. We demonstrate the effectiveness of such a strategy for migratory waterbirds. We analyzed citizen science and satellite data to develop predictive models of bird populations and the availability of wetlands, which we used to determine temporal and spatial gaps in habitat during a vital stage of the annual migration. We then filled those gaps using a reverse auction marketplace to incent qualifying landowners to create temporary wetlands on their properties. This approach is a cost-effective way of adaptively meeting habitat needs for migratory species, optimizes conservation outcomes relative to investment, and can be applied broadly to other conservation challenges. PMID:28845449

Global continental and ocean basin reconstructions since 200 Ma

NASA Astrophysics Data System (ADS)

Seton, M.; Müller, R. D.; Zahirovic, S.; Gaina, C.; Torsvik, T.; Shephard, G.; Talsma, A.; Gurnis, M.; Turner, M.; Maus, S.; Chandler, M.

2012-07-01

Global plate motion models provide a spatial and temporal framework for geological data and have been effective tools for exploring processes occurring at the earth's surface. However, published models either have insufficient temporal coverage or fail to treat tectonic plates in a self-consistent manner. They usually consider the motions of selected features attached to tectonic plates, such as continents, but generally do not explicitly account for the continuous evolution of plate boundaries through time. In order to explore the coupling between the surface and mantle, plate models are required that extend over at least a few hundred million years and treat plates as dynamic features with dynamically evolving plate boundaries. We have constructed a new type of global plate motion model consisting of a set of continuously-closing topological plate polygons with associated plate boundaries and plate velocities since the break-up of the supercontinent Pangea. Our model is underpinned by plate motions derived from reconstructing the seafloor-spreading history of the ocean basins and motions of the continents and utilizes a hybrid absolute reference frame, based on a moving hotspot model for the last 100 Ma, and a true-polar wander corrected paleomagnetic model for 200 to 100 Ma. Detailed regional geological and geophysical observations constrain plate boundary inception or cessation, and time-dependent geometry. Although our plate model is primarily designed as a reference model for a new generation of geodynamic studies by providing the surface boundary conditions for the deep earth, it is also useful for studies in disparate fields when a framework is needed for analyzing and interpreting spatio-temporal data.

Dynamical network of residue–residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation

PubMed Central

Doshi, Urmi; Holliday, Michael J.; Eisenmesser, Elan Z.; Hamelberg, Donald

2016-01-01

Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue–residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general. PMID:27071107

Primitive Auditory Memory Is Correlated with Spatial Unmasking That Is Based on Direct-Reflection Integration

PubMed Central

Li, Huahui; Kong, Lingzhi; Wu, Xihong; Li, Liang

2013-01-01

In reverberant rooms with multiple-people talking, spatial separation between speech sources improves recognition of attended speech, even though both the head-shadowing and interaural-interaction unmasking cues are limited by numerous reflections. It is the perceptual integration between the direct wave and its reflections that bridges the direct-reflection temporal gaps and results in the spatial unmasking under reverberant conditions. This study further investigated (1) the temporal dynamic of the direct-reflection-integration-based spatial unmasking as a function of the reflection delay, and (2) whether this temporal dynamic is correlated with the listeners’ auditory ability to temporally retain raw acoustic signals (i.e., the fast decaying primitive auditory memory, PAM). The results showed that recognition of the target speech against the speech-masker background is a descending exponential function of the delay of the simulated target reflection. In addition, the temporal extent of PAM is frequency dependent and markedly longer than that for perceptual fusion. More importantly, the temporal dynamic of the speech-recognition function is significantly correlated with the temporal extent of the PAM of low-frequency raw signals. Thus, we propose that a chain process, which links the earlier-stage PAM with the later-stage correlation computation, perceptual integration, and attention facilitation, plays a role in spatially unmasking target speech under reverberant conditions. PMID:23658664

Design and implementation of an optimal laser pulse front tilting scheme for ultrafast electron diffraction in reflection geometry with high temporal resolution.

PubMed

Pennacchio, Francesco; Vanacore, Giovanni M; Mancini, Giulia F; Oppermann, Malte; Jayaraman, Rajeswari; Musumeci, Pietro; Baum, Peter; Carbone, Fabrizio

2017-07-01

Ultrafast electron diffraction is a powerful technique to investigate out-of-equilibrium atomic dynamics in solids with high temporal resolution. When diffraction is performed in reflection geometry, the main limitation is the mismatch in group velocity between the overlapping pump light and the electron probe pulses, which affects the overall temporal resolution of the experiment. A solution already available in the literature involved pulse front tilt of the pump beam at the sample, providing a sub-picosecond time resolution. However, in the reported optical scheme, the tilted pulse is characterized by a temporal chirp of about 1 ps at 1 mm away from the centre of the beam, which limits the investigation of surface dynamics in large crystals. In this paper, we propose an optimal tilting scheme designed for a radio-frequency-compressed ultrafast electron diffraction setup working in reflection geometry with 30 keV electron pulses containing up to 10 5 electrons/pulse. To characterize our scheme, we performed optical cross-correlation measurements, obtaining an average temporal width of the tilted pulse lower than 250 fs. The calibration of the electron-laser temporal overlap was obtained by monitoring the spatial profile of the electron beam when interacting with the plasma optically induced at the apex of a copper needle (plasma lensing effect). Finally, we report the first time-resolved results obtained on graphite, where the electron-phonon coupling dynamics is observed, showing an overall temporal resolution in the sub-500 fs regime. The successful implementation of this configuration opens the way to directly probe structural dynamics of low-dimensional systems in the sub-picosecond regime, with pulsed electrons.

Design and implementation of an optimal laser pulse front tilting scheme for ultrafast electron diffraction in reflection geometry with high temporal resolution

PubMed Central

Pennacchio, Francesco; Vanacore, Giovanni M.; Mancini, Giulia F.; Oppermann, Malte; Jayaraman, Rajeswari; Musumeci, Pietro; Baum, Peter; Carbone, Fabrizio

2017-01-01

Ultrafast electron diffraction is a powerful technique to investigate out-of-equilibrium atomic dynamics in solids with high temporal resolution. When diffraction is performed in reflection geometry, the main limitation is the mismatch in group velocity between the overlapping pump light and the electron probe pulses, which affects the overall temporal resolution of the experiment. A solution already available in the literature involved pulse front tilt of the pump beam at the sample, providing a sub-picosecond time resolution. However, in the reported optical scheme, the tilted pulse is characterized by a temporal chirp of about 1 ps at 1 mm away from the centre of the beam, which limits the investigation of surface dynamics in large crystals. In this paper, we propose an optimal tilting scheme designed for a radio-frequency-compressed ultrafast electron diffraction setup working in reflection geometry with 30 keV electron pulses containing up to 105 electrons/pulse. To characterize our scheme, we performed optical cross-correlation measurements, obtaining an average temporal width of the tilted pulse lower than 250 fs. The calibration of the electron-laser temporal overlap was obtained by monitoring the spatial profile of the electron beam when interacting with the plasma optically induced at the apex of a copper needle (plasma lensing effect). Finally, we report the first time-resolved results obtained on graphite, where the electron-phonon coupling dynamics is observed, showing an overall temporal resolution in the sub-500 fs regime. The successful implementation of this configuration opens the way to directly probe structural dynamics of low-dimensional systems in the sub-picosecond regime, with pulsed electrons. PMID:28713841

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

Applicability of optical scanner method for fine root dynamics

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Ohashi, Mizue; Makita, Naoki; Khoon Kho, Lip; Katayama, Ayumi; Matsumoto, Kazuho; Ikeno, Hidetoshi

2016-04-01

Fine root dynamics is one of the important components in forest carbon cycling, as ~60 % of tree photosynthetic production can be allocated to root growth and metabolic activities. Various techniques have been developed for monitoring fine root biomass, production, mortality in order to understand carbon pools and fluxes resulting from fine roots dynamics. The minirhizotron method is now a widely used technique, in which a transparent tube is inserted into the soil and researchers count an increase and decrease of roots along the tube using images taken by a minirhizotron camera or minirhizotron video camera inside the tube. This method allows us to observe root behavior directly without destruction, but has several weaknesses; e.g., the difficulty of scaling up the results to stand level because of the small observation windows. Also, most of the image analysis are performed manually, which may yield insufficient quantitative and objective data. Recently, scanner method has been proposed, which can produce much bigger-size images (A4-size) with lower cost than those of the minirhizotron methods. However, laborious and time-consuming image analysis still limits the applicability of this method. In this study, therefore, we aimed to develop a new protocol for scanner image analysis to extract root behavior in soil. We evaluated applicability of this method in two ways; 1) the impact of different observers including root-study professionals, semi- and non-professionals on the detected results of root dynamics such as abundance, growth, and decomposition, and 2) the impact of window size on the results using a random sampling basis exercise. We applied our new protocol to analyze temporal changes of root behavior from sequential scanner images derived from a Bornean tropical forests. The results detected by the six observers showed considerable concordance in temporal changes in the abundance and the growth of fine roots but less in the decomposition. We also examined potential errors due to window size in the temporal changes in abundance and growth using the detected results, suggesting high applicability of the scanner methods with wide observation windows.

4D Dynamic Required Navigation Performance Final Report

NASA Technical Reports Server (NTRS)

Finkelsztein, Daniel M.; Sturdy, James L.; Alaverdi, Omeed; Hochwarth, Joachim K.

2011-01-01

New advanced four dimensional trajectory (4DT) procedures under consideration for the Next Generation Air Transportation System (NextGen) require an aircraft to precisely navigate relative to a moving reference such as another aircraft. Examples are Self-Separation for enroute operations and Interval Management for in-trail and merging operations. The current construct of Required Navigation Performance (RNP), defined for fixed-reference-frame navigation, is not sufficiently specified to be applicable to defining performance levels of such air-to-air procedures. An extension of RNP to air-to-air navigation would enable these advanced procedures to be implemented with a specified level of performance. The objective of this research effort was to propose new 4D Dynamic RNP constructs that account for the dynamic spatial and temporal nature of Interval Management and Self-Separation, develop mathematical models of the Dynamic RNP constructs, "Required Self-Separation Performance" and "Required Interval Management Performance," and to analyze the performance characteristics of these air-to-air procedures using the newly developed models. This final report summarizes the activities led by Raytheon, in collaboration with GE Aviation and SAIC, and presents the results from this research effort to expand the RNP concept to a dynamic 4D frame of reference.

Rabi-Bloch oscillations in spatially distributed systems: Temporal dynamics and frequency spectra

NASA Astrophysics Data System (ADS)

Levie, Ilay; Kastner, Raphael; Slepyan, Gregory

2017-10-01

We consider one-dimensional chains of two-level quantum systems coupled via tunneling. The chain is driven by the superposition of dc and ac fields in the strong coupling regime. Based on the fundamental principles of electrodynamics and quantum theory, we have developed a generalized model of quantum dynamics for such interactions, free of rotating-wave approximation. The system of equations of motion was studied numerically. We analyzed the dynamics and spectra of the inversion density, dipole current density, and tunneling current density. In the case of resonant interaction with the ac component, the particle dynamics exhibits itself in the oscillatory regime, which may be interpreted as a combination of Rabi and Bloch oscillations with their strong mutual influence. Such scenario for an obliquely incident ac field dramatically differs from the individual picture of both types of oscillations due to the interactions. This effect is counterintuitive because of the existence of markedly different frequency ranges for such two types of oscillations. These dynamics manifest themselves in multiline spectra in different combinations of Rabi and Bloch frequencies. The effect is promising as a framework of a new type of spectroscopy in nanoelectronics and electrical control of nanodevices.

The Temporal and Dynamic Nature of Self-Regulatory Processes during Independent and Externally Assisted Hypermedia Learning

ERIC Educational Resources Information Center

Johnson, Amy M.; Azevedo, Roger; D'Mello, Sidney K.

2011-01-01

This study examined the temporal and dynamic nature of students' self-regulatory processes while learning about the circulatory system with hypermedia. A total of 74 undergraduate students were randomly assigned to 1 of 2 conditions: independent learning or externally assisted learning. Participants in the independent learning condition used a…

GABA[subscript A] Receptors Determine the Temporal Dynamics of Memory Retention

ERIC Educational Resources Information Center

McNally, Gavan P.; Augustyn, Katarzyna A.; Richardson, Rick

2008-01-01

Four experiments studied the role of GABA[subscript A] receptors in the temporal dynamics of memory retention. Memory for an active avoidance response was a nonmonotonic function of the retention interval. When rats were tested shortly (2 min) or some time (24 h) after training, retention was excellent, but when they were tested at intermediate…

Spatio-temporal dynamics of pond use and recruitment in Florida gopher frogs (Rana capito aesopus)

Treesearch

Cathryn H. Greenberg

2001-01-01

This study examines spatio-temporal dynamics of Florida gopher frog (Rang capito aesopus) breeding and juvenile recruitment. Ponds were situated within a hardwood-invaded or a savanna-like longleaf pine-wiregrass upland matrix. Movement (N = 1444) was monitored using intermittent drift fences with pitfall and funnel traps at eight...

Chronic radiation exposure modifies temporal dynamics of cytogenetic but not reproductive indicators in Scots pine populations.

PubMed

Geras'kin, Stanislav; Oudalova, Alla; Kuzmenkov, Alexey; Vasiliyev, Denis

2018-04-18

Over a period of 13 years (2003-2015), reproductive and cytogenetic effects are investigated in Scots pine populations growing in the Bryansk region of Russia radioactively contaminated as a result of the Chernobyl accident. In reference populations, the frequencies of cytogenetic abnormalities are shown to change with time in a cyclic manner. In chronically exposed populations, the cyclic patterns in temporal dynamics of cytogenetic abnormalities appear to be disturbed. In addition, a tendency to decrease in the frequencies of cytogenetic abnormalities with time as well as an increase in their variability with dose rate is revealed. In contrast, no significant impact of chronic radiation exposure on the time dynamics of reproductive indexes is detected. Finally, long-term observations on chronically exposed Scots pine populations revealed qualitative differences in the temporal dynamics of reproductive and cytogenetic indicators. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

USGS Publications Warehouse

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

2005-01-01

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

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics.

PubMed

Hou, Yue; Konen, Jessica; Brat, Daniel J; Marcus, Adam I; Cooper, Lee A D

2018-05-08

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

Anomalous dielectric relaxation with linear reaction dynamics in space-dependent force fields.

PubMed

Hong, Tao; Tang, Zhengming; Zhu, Huacheng

2016-12-28

The anomalous dielectric relaxation of disordered reaction with linear reaction dynamics is studied via the continuous time random walk model in the presence of space-dependent electric field. Two kinds of modified reaction-subdiffusion equations are derived for different linear reaction processes by the master equation, including the instantaneous annihilation reaction and the noninstantaneous annihilation reaction. If a constant proportion of walkers is added or removed instantaneously at the end of each step, there will be a modified reaction-subdiffusion equation with a fractional order temporal derivative operating on both the standard diffusion term and a linear reaction kinetics term. If the walkers are added or removed at a constant per capita rate during the waiting time between steps, there will be a standard linear reaction kinetics term but a fractional order temporal derivative operating on an anomalous diffusion term. The dielectric polarization is analyzed based on the Legendre polynomials and the dielectric properties of both reactions can be expressed by the effective rotational diffusion function and component concentration function, which is similar to the standard reaction-diffusion process. The results show that the effective permittivity can be used to describe the dielectric properties in these reactions if the chemical reaction time is much longer than the relaxation time.

Temporal and Spatial Wildfire Dynamics of Northern Siberia: Larch Forests and Insect Outbreak Areas

NASA Astrophysics Data System (ADS)

Kharuk, Viacheslav; Antamoshkina, Olga; Ponomarev, Eugene

2017-04-01

Wildfire number and burned area temporal dynamics within all of Siberia and along a south-north transect in central Siberia (45 - 73°N) were studied based on NOAA/AVHRR and Terra/MODIS data and field measurements for the period since 1996. In addition, fire return interval along the south-north transect was analyzed. Third, pest outbreak (Siberian silkmoth) impact on the wildfires was studied. Both, number of forest fires and burned area in Siberia increased during recent decades. Significant correlations were found between forest fires, burned areas and air temperature (r = 0.5) and drought index (SPEI) (r = -0.43). Within larch stands along the transect wildfire frequency was strongly correlated with incoming solar radiation (r = 0.91). Fire danger period length decreased linearly from south to north along the transect. Fire return interval increased from 80 years at 62°N to 200 years at the Arctic Circle (66°33'N), and to about 300 years near the northern limit of closed forest stands ( 71+°N). That increase was negatively correlated with incoming solar radiation (r = -0.95). Siberian silkmoth outbreaks leads to an order of magnitude increase in burned area and fire frequency. Multiple fires turns former "dark needle conifer" taiga into grass and bush communities for decades.

EEG dynamical correlates of focal and diffuse causes of coma.

PubMed

Kafashan, MohammadMehdi; Ryu, Shoko; Hargis, Mitchell J; Laurido-Soto, Osvaldo; Roberts, Debra E; Thontakudi, Akshay; Eisenman, Lawrence; Kummer, Terrance T; Ching, ShiNung

2017-11-15

Rapidly determining the causes of a depressed level of consciousness (DLOC) including coma is a common clinical challenge. Quantitative analysis of the electroencephalogram (EEG) has the potential to improve DLOC assessment by providing readily deployable, temporally detailed characterization of brain activity in such patients. While used commonly for seizure detection, EEG-based assessment of DLOC etiology is less well-established. As a first step towards etiological diagnosis, we sought to distinguish focal and diffuse causes of DLOC through assessment of temporal dynamics within EEG signals. We retrospectively analyzed EEG recordings from 40 patients with DLOC with consensus focal or diffuse culprit pathology. For each recording, we performed a suite of time-series analyses, then used a statistical framework to identify which analyses (features) could be used to distinguish between focal and diffuse cases. Using cross-validation approaches, we identified several spectral and non-spectral EEG features that were significantly different between DLOC patients with focal vs. diffuse etiologies, enabling EEG-based classification with an accuracy of 76%. Our findings suggest that DLOC due to focal vs. diffuse injuries differ along several electrophysiological parameters. These results may form the basis of future classification strategies for DLOC and coma that are more etiologically-specific and therefore therapeutically-relevant.

Probing ultrafast proton induced dynamics in transparent dielectrics

NASA Astrophysics Data System (ADS)

Taylor, M.; Coughlan, M.; Nersisyan, G.; Senje, L.; Jung, D.; Currell, F.; Riley, D.; Lewis, C. L. S.; Zepf, M.; Dromey, B.

2018-05-01

A scheme has been developed permitting the spatial and temporal characterisation of ultrafast dynamics induced by laser driven proton bursts in transparent dielectrics. Advantage is taken of the high degree of synchronicity between the proton bursts generated during laser-foil target interactions and the probing laser to provide the basis for streaking of the dynamics. Relaxation times of electrons (<10‑12 s) are measured following swift excitation across the optical band gap for various glass samples. A temporal resolution of <500 fs is achieved demonstrating that these ultrafast dynamics can be characterized on a single-shot basis.

Study on the Characteristics and Impacts of the Spatial-temporal Urban Sprawl in Chinese Coastal Cities using Ocelet

NASA Astrophysics Data System (ADS)

Li, M.; Lo Seen, D.; Zhang, Z.

2015-12-01

The urban population is expected to rise 67% in developing countries and 86% in developed regions by 2050. As the most populous country in the world, China has been experiencing a remarkable urbanization process since the initialization of the reform and opening-up policies in the late 1970s. During the past several decades, the coastal zone undergone the highest urbanization and motst rapid economic development in China. Accurately understanding the characteristics of the spatial-temporal urban sprawl is helpful for urban planning on optimal land use in the future. Ocelet is an interactive visual interpretation and dynamic coding method that has been designed for studying issues related to space, time and multiple scales that are raised when dynamic landscapes are modelled. Using Ocelet, we aim to study the characteristics of the spatial-temporal urban sprawl in thirteen major Chinese coastal cities and how urban sprawl affects the surrounding land changes. Landsat MSS/TM/ETM/OLI, the China-Brazil Earth Resources Satellite (CBERS) and Chinese HJ-1A data are adopted to acquire urban built-up areas and their dynamic changes from 1979 to 2013. The results show that the urban built-up area increased gradually from 1979 to 2002 (~105 km²/yr), then accelerated about four times from 2002 to 2010 (~396 km²/yr) in thirteen major Chinese coastal cities. Although the expansion slowed down since 2010, the urban built-up area still increased at a fairly high rate (~210 km²/yr) from 2010 to 2013. The urban sprawl speed and pattern in each coastal city has also been analyzed, and has been grouped in three costal zones geographically. As a result of urban sprawl, large areas of arable land, rural settlements and forests were lost in these coastal cities. The lost non-urban land types and areas are different in the three costal zones and quantified respectively.

Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000

USGS Publications Warehouse

Giri, C.; Pengra, Bruce; Zhu, Z.; Singh, A.; Tieszen, L.L.

2007-01-01

Mangrove forests in many parts of the world are declining at an alarming rate—possibly even more rapidly than inland tropical forests. The rate and causes of such changes are not known. The forests themselves are dynamic in nature and are undergoing constant changes due to both natural and anthropogenic forces. Our research objective was to monitor deforestation and degradation arising from both natural and anthropogenic forces. We analyzed multi-temporal satellite data from 1970s, 1990s, and 2000s using supervised classification approach. Our spatio-temporal analysis shows that despite having the highest population density in the world in its periphery, areal extent of the mangrove forest of the Sundarbans has not changed significantly (approximately 1.2%) in the last ∼25 years. The forest is however constantly changing due to erosion, aggradation, deforestation and mangrove rehabilitation programs. The net forest area increased by 1.4% from the 1970s to 1990 and decreased by 2.5% from 1990 to 2000. The change is insignificant in the context of classification errors and the dynamic nature of mangrove forests. This is an excellent example of the co-existence of humans with terrestrial and aquatic plant and animal life. The strong commitment of governments under various protection measures such as forest reserves, wildlife sanctuaries, national parks, and international designations, is believed to be responsible for keeping this forest relatively intact (at least in terms of area). While the measured net loss of mangrove forest is not that high, the change matrix shows that turnover due to erosion, aggradation, reforestation and deforestation was much greater than net change. The forest is under threat from natural and anthropogenic forces leading to forest degradation, primarily due to top-dying disease and over-exploitation of forest resources.

Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000

NASA Astrophysics Data System (ADS)

Giri, Chandra; Pengra, Bruce; Zhu, Zhiliang; Singh, Ashbindu; Tieszen, Larry L.

2007-06-01

Mangrove forests in many parts of the world are declining at an alarming rate—possibly even more rapidly than inland tropical forests. The rate and causes of such changes are not known. The forests themselves are dynamic in nature and are undergoing constant changes due to both natural and anthropogenic forces. Our research objective was to monitor deforestation and degradation arising from both natural and anthropogenic forces. We analyzed multi-temporal satellite data from 1970s, 1990s, and 2000s using supervised classification approach. Our spatio-temporal analysis shows that despite having the highest population density in the world in its periphery, areal extent of the mangrove forest of the Sundarbans has not changed significantly (approximately 1.2%) in the last ˜25 years. The forest is however constantly changing due to erosion, aggradation, deforestation and mangrove rehabilitation programs. The net forest area increased by 1.4% from the 1970s to 1990 and decreased by 2.5% from 1990 to 2000. The change is insignificant in the context of classification errors and the dynamic nature of mangrove forests. This is an excellent example of the co-existence of humans with terrestrial and aquatic plant and animal life. The strong commitment of governments under various protection measures such as forest reserves, wildlife sanctuaries, national parks, and international designations, is believed to be responsible for keeping this forest relatively intact (at least in terms of area). While the measured net loss of mangrove forest is not that high, the change matrix shows that turnover due to erosion, aggradation, reforestation and deforestation was much greater than net change. The forest is under threat from natural and anthropogenic forces leading to forest degradation, primarily due to top-dying disease and over-exploitation of forest resources.

Foreshocks and delayed triggering of the 2016 MW7.1 Te Araroa earthquake and dynamic reinvigoration of its aftershock sequence by the MW7.8 Kaikōura earthquake, New Zealand

NASA Astrophysics Data System (ADS)

Warren-Smith, Emily; Fry, Bill; Kaneko, Yoshihiro; Chamberlain, Calum J.

2018-01-01

We analyze the preparatory period of the September 2016 MW7.1 Te Araroa foreshock-mainshock sequence in the Northern Hikurangi margin, New Zealand, and subsequent reinvigoration of Te Araroa aftershocks driven by a large distant earthquake (the November 2016 MW7.8 Kaikōura earthquake). By adopting a matched-filter detection workflow using 582 well-defined template events, we generate an improved foreshock and aftershock catalog for the Te Araroa sequence (>8,000 earthquakes over 66 d). Templates characteristic of the MW7.1 sequence (including the mainshock template) detect several highly correlating events (ML2.5-3.5) starting 12 min after a MW5.7 foreshock. These pre-cursory events occurred within ∼1 km of the mainshock and migrate bilaterally, suggesting precursory slip was triggered by the foreshock on the MW7.1 fault patch prior to mainshock failure. We extend our matched-filter routine to examine the interactions between high dynamic stresses resulting from passing surface waves of the November 2016 MW7.8 Kaikōura earthquake, and the evolution of the Te Araroa aftershock sequence. We observe a sudden spike in moment release of the aftershock sequence immediately following peak dynamic Coulomb stresses of 50-150 kPa on the MW7.1 fault plane. The triggered increase in moment release culminated in a MW5.1 event, immediately followed by a ∼3 h temporal stress shadow. Our observations document the preparatory period of a major subduction margin earthquake following a significant foreshock, and quantify dynamic reinvigoration of a distant on-going major aftershock sequence amid a period of temporal clustering of seismic activity in New Zealand.

Temporal dynamics of European bat Lyssavirus type 1 and survival of Myotis myotis bats in natural colonies.

PubMed

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.

Temporal Dynamics of European Bat Lyssavirus Type 1 and Survival of Myotis myotis Bats in Natural Colonies

PubMed Central

Amengual, Blanca; Bourhy, Hervé; López-Roig, Marc; Serra-Cobo, Jordi

2007-01-01

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 (R0 = 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. PMID:17593965

Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.

PubMed

Cai, Biao; Zille, Pascal; Stephen, Julia M; Wilson, Tony W; Calhoun, Vince D; Wang, Yu Ping

2018-05-01

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) time series, especially during resting state periods, provides a powerful tool to assess human brain functional architecture in health, disease, and developmental states. Recently, the focus of connectivity analysis has shifted toward the subnetworks of the brain, which reveals co-activating patterns over time. Most prior works produced a dense set of high-dimensional vectors, which are hard to interpret. In addition, their estimations to a large extent were based on an implicit assumption of spatial and temporal stationarity throughout the fMRI scanning session. In this paper, we propose an approach called dynamic sparse connectivity patterns (dSCPs), which takes advantage of both matrix factorization and time-varying fMRI time series to improve the estimation power of FC. The feasibility of analyzing dynamic FC with our model is first validated through simulated experiments. Then, we use our framework to measure the difference between young adults and children with real fMRI data set from the Philadelphia Neurodevelopmental Cohort (PNC). The results from the PNC data set showed significant FC differences between young adults and children in four different states. For instance, young adults had reduced connectivity between the default mode network and other subnetworks, as well as hyperconnectivity within the visual system in states 1 and 3, and hypoconnectivity in state 2. Meanwhile, they exhibited temporal correlation patterns that changed over time within functional subnetworks. In addition, the dSCPs model indicated that older people tend to spend more time within a relatively connected FC pattern. Overall, the proposed method provides a valid means to assess dynamic FC, which could facilitate the study of brain networks.

Disentangling the effects of feedback structure and climate on Poaceae annual airborne pollen fluctuations and the possible consequences of climate change.

PubMed

García de León, David; García-Mozo, Herminia; Galán, Carmen; Alcázar, Purificación; Lima, Mauricio; González-Andújar, José L

2015-10-15

Pollen allergies are the most common form of respiratory allergic disease in Europe. Most studies have emphasized the role of environmental processes, as the drivers of airborne pollen fluctuations, implicitly considering pollen production as a random walk. This work shows that internal self-regulating processes of the plants (negative feedback) should be included in pollen dynamic systems in order to give a better explanation of the observed pollen temporal patterns. This article proposes a novel methodological approach based on dynamic systems to investigate the interaction between feedback structure of plant populations and climate in shaping long-term airborne Poaceae pollen fluctuations and to quantify the effects of climate change on future airborne pollen concentrations. Long-term historical airborne Poaceae pollen data (30 years) from Cordoba city (Southern Spain) were analyzed. A set of models, combining feedback structure, temperature and actual evapotranspiration effects on airborne Poaceae pollen were built and compared, using a model selection approach. Our results highlight the importance of first-order negative feedback and mean annual maximum temperature in driving airborne Poaceae pollen dynamics. The best model was used to predict the effects of climate change under two standardized scenarios representing contrasting temporal patterns of economic development and CO2 emissions. Our results predict an increase in pollen levels in southern Spain by 2070 ranging from 28.5% to 44.3%. The findings from this study provide a greater understanding of airborne pollen dynamics and how climate change might impact the future evolution of airborne Poaceae pollen concentrations and thus the future evolution of related pollen allergies. Copyright © 2015 Elsevier B.V. All rights reserved.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

GIS and agent based spatial-temporal simulation modeling for assessing tourism social carrying capacity: a study on Mount Emei scenic area, China

NASA Astrophysics Data System (ADS)

Zhang, Renjun

2007-06-01

Each scenic area can sustain a specific level of acceptance of tourist development and use, beyond which further development can result in socio-cultural deterioration or a decline in the quality of the experience gained by visitors. This specific level is called carrying capacity. Social carrying capacity can be defined as the maximum level of use (in terms of numbers and activities) that can be absorbed by an area without an unacceptable decline in the quality of experience of visitors and without an unacceptable adverse impact on the society of the area. It is difficult to assess the carrying capacity, because the carrying capacity is determined by not only the number of visitors, but also the time, the type of the recreation, the characters of each individual and the physical environment. The objective of this study is to build a spatial-temporal simulation model to simulate the spatial-temporal distribution of tourists. This model is a tourist spatial behaviors simulator (TSBS). Based on TSBS, the changes of each visitor's travel patterns such as location, cost, and other states data are recoded in a state table. By analyzing this table, the intensity of the tourist use in any area can be calculated; the changes of the quality of tourism experience can be quantized and analyzed. So based on this micro simulation method the social carrying capacity can be assessed more accurately, can be monitored proactively and managed adaptively. In this paper, the carrying capacity of Mount Emei scenic area is analyzed as followed: The author selected the intensity of the crowd as the monitoring Indicators. it is regarded that longer waiting time means more crowded. TSBS was used to simulate the spatial-temporal distribution of tourists. the average of waiting time all the visitors is calculated. And then the author assessed the social carrying capacity of Mount Emei scenic area, found the key factors have impacted on social carrying capacity. The results show that the TSBS-aided method for assessing carrying capacity is dynamic, quantifiable and more accurate.

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

PubMed Central

Koorehdavoudi, Hana; Bogdan, Paul

2016-01-01

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

The Spatial and Temporal Transcriptomic Landscapes of Ginseng, Panax ginseng C. A. Meyer.

PubMed

Wang, Kangyu; Jiang, Shicui; Sun, Chunyu; Lin, Yanping; Yin, Rui; Wang, Yi; Zhang, Meiping

2015-12-11

Ginseng, including Asian ginseng (Panax ginseng C. A. Meyer) and American ginseng (P. quinquefolius L.), is one of the most important medicinal herbs in Asia and North America, but significantly understudied. This study sequenced and characterized the transcriptomes and expression profiles of genes expressed in 14 tissues and four different aged roots of Asian ginseng. A total of 265.2 million 100-bp clean reads were generated using the high-throughput sequencing platform HiSeq 2000, representing >8.3x of the 3.2-Gb ginseng genome. From the sequences, 248,993 unigenes were assembled for whole plant, 61,912-113,456 unigenes for each tissue and 54,444-65,412 unigenes for different year-old roots. We comprehensively analyzed the unigene sets and gene expression profiles. We found that the number of genes allocated to each functional category is stable across tissues or developmental stages, while the expression profiles of different genes of a gene family or involved in ginsenoside biosynthesis dramatically diversified spatially and temporally. These results provide an overall insight into the spatial and temporal transcriptome dynamics and landscapes of Asian ginseng, and comprehensive resources for advanced research and breeding of ginseng and related species.

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

NASA Astrophysics Data System (ADS)

Koorehdavoudi, Hana; Bogdan, Paul

2016-06-01

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

Outbreeding and lack of temporal genetic structure in a drone congregation of the neotropical stingless bee Scaptotrigona mexicana

PubMed Central

Mueller, Matthias Y; Moritz, Robin FA; Kraus, F Bernhard

2012-01-01

Drone aggregations are a widespread phenomenon in many stingless bee species (Meliponini), but the ultimate and proximate causes for their formation are still not well understood. One adaptive explanation for this phenomenon is the avoidance of inbreeding, which is especially detrimental for stingless bees due to the combined effects of the complementary sex-determining system and the small effective population size caused by eusociality and monandry. We analyzed the temporal genetic dynamics of a drone aggregation of the stingless bee Scaptotrigona mexicana with microsatellite markers over a time window of four weeks. We estimated the drones of the aggregation to originate from a total of 55 colonies using sibship re-construction. There was no detectable temporal genetic differentiation or sub-structuring in the aggregation. Most important, we could exclude all colonies in close proximity of the aggregation as origin of the drones in the aggregation, implicating that they originate from more distant colonies. We conclude that the diverse genetic composition and the distant origin of the drones of the S. mexicana drone congregation provides an effective mechanism to avoid mating among close relatives. PMID:22833802

Outbreeding and lack of temporal genetic structure in a drone congregation of the neotropical stingless bee Scaptotrigona mexicana.

PubMed

Mueller, Matthias Y; Moritz, Robin Fa; Kraus, F Bernhard

2012-06-01

Drone aggregations are a widespread phenomenon in many stingless bee species (Meliponini), but the ultimate and proximate causes for their formation are still not well understood. One adaptive explanation for this phenomenon is the avoidance of inbreeding, which is especially detrimental for stingless bees due to the combined effects of the complementary sex-determining system and the small effective population size caused by eusociality and monandry. We analyzed the temporal genetic dynamics of a drone aggregation of the stingless bee Scaptotrigona mexicana with microsatellite markers over a time window of four weeks. We estimated the drones of the aggregation to originate from a total of 55 colonies using sibship re-construction. There was no detectable temporal genetic differentiation or sub-structuring in the aggregation. Most important, we could exclude all colonies in close proximity of the aggregation as origin of the drones in the aggregation, implicating that they originate from more distant colonies. We conclude that the diverse genetic composition and the distant origin of the drones of the S. mexicana drone congregation provides an effective mechanism to avoid mating among close relatives.

Achieving Consistent Doppler Measurements from SDO/HMI Vector Field Inversions

NASA Technical Reports Server (NTRS)

Schuck, Peter W.; Antiochos, S. K.; Leka, K. D.; Barnes, Graham

2016-01-01

NASA's Solar Dynamics Observatory is delivering vector magnetic field observations of the full solar disk with unprecedented temporal and spatial resolution; however, the satellite is in a highly inclined geosynchronous orbit. The relative spacecraft-Sun velocity varies by +/-3 kms-1 over a day, which introduces major orbital artifacts in the Helioseismic Magnetic Imager (HMI) data. We demonstrate that the orbital artifacts contaminate all spatial and temporal scales in the data. We describe a newly developed three-stage procedure for mitigating these artifacts in the Doppler data obtained from the Milne-Eddington inversions in the HMI pipeline. The procedure ultimately uses 32 velocity-dependent coefficients to adjust 10 million pixels-a remarkably sparse correction model given the complexity of the orbital artifacts. This procedure was applied to full-disk images of AR 11084 to produce consistent Dopplergrams. The data adjustments reduce the power in the orbital artifacts by 31 dB. Furthermore, we analyze in detail the corrected images and show that our procedure greatly improves the temporal and spectral properties of the data without adding any new artifacts. We conclude that this new procedure makes a dramatic improvement in the consistency of the HMI data and in its usefulness for precision scientific studies.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-07-24

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150-200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300-350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual-motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions

PubMed Central

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-01-01

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150–200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300–350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual–motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions. PMID:26206708

3D undersampled golden-radial phase encoding for DCE-MRA using inherently regularized iterative SENSE.

PubMed

Prieto, Claudia; Uribe, Sergio; Razavi, Reza; Atkinson, David; Schaeffter, Tobias

2010-08-01

One of the current limitations of dynamic contrast-enhanced MR angiography is the requirement of both high spatial and high temporal resolution. Several undersampling techniques have been proposed to overcome this problem. However, in most of these methods the tradeoff between spatial and temporal resolution is constant for all the time frames and needs to be specified prior to data collection. This is not optimal for dynamic contrast-enhanced MR angiography where the dynamics of the process are difficult to predict and the image quality requirements are changing during the bolus passage. Here, we propose a new highly undersampled approach that allows the retrospective adaptation of the spatial and temporal resolution. The method combines a three-dimensional radial phase encoding trajectory with the golden angle profile order and non-Cartesian Sensitivity Encoding (SENSE) reconstruction. Different regularization images, obtained from the same acquired data, are used to stabilize the non-Cartesian SENSE reconstruction for the different phases of the bolus passage. The feasibility of the proposed method was demonstrated on a numerical phantom and in three-dimensional intracranial dynamic contrast-enhanced MR angiography of healthy volunteers. The acquired data were reconstructed retrospectively with temporal resolutions from 1.2 sec to 8.1 sec, providing a good depiction of small vessels, as well as distinction of different temporal phases.

How chemical pollution becomes a social problem. Risk communication and assessment through regional newspapers during the management of PCB pollutions of the Rhône River (France).

PubMed

Comby, Emeline; Le Lay, Yves-François; Piégay, Hervé

2014-06-01

The case study of the polychlorinated biphenyl (PCB) pollutions of the Rhône River (France) offers the possibility of studying criteria for the construction of social problems that result from chemical pollution (2005-2010). We investigated the dynamics of competition that create and define pollution as a social problem and entail its decline. News outlets are crucial for determining how an environmental issue emerges locally or nationally; this study used newspapers to highlight the potential of new outlets as a data source to analyze discourse variability, science-policy-media connections and the hydrosphere. Media coverage was based on a content analysis and textual data analysis of 75 articles. Analytical frameworks such as the Downs Model and the Public Arena Model (Hilgartner and Bosk, 1988) that consider time and stakeholders were tested to determine how human alteration of the hydrosphere can become a social problem and to analyze different communication strategies held by stakeholders. In terms of management, we described the temporal dynamics of the social problem based on the case study and considered an explanation of the selections. We considered the organization of particular stakeholders who define the social problem from its beginning to end by focusing on their discourses, relationships, decision-making and political choices, and scientific studies. Despite some biases, newspapers are useful for retrospectively evaluating the emergence of a social problem in the public arena by describing it through discourse and then understanding the temporal patterns of information. Despite uncertainties and information flow, decisions are made and science is translated to the public. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

Lin, Xueju; McKinley, James; Resch, Charles T; Kaluzny, Rachael; Lauber, Christian L; Fredrickson, James; Knight, Rob; Konopka, Allan

2012-01-01

Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater bacteria and archaea over 10 months within three well clusters separated by ∼30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained three 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 nine 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 with river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper zone in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (for example, 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. PMID:22456444

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

PubMed

Lin, Xueju; McKinley, James; Resch, Charles T; Kaluzny, Rachael; Lauber, Christian L; Fredrickson, James; Knight, Rob; Konopka, Allan

2012-09-01

Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater bacteria and archaea over 10 months within three well clusters separated by ~30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained three 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 nine 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 with river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper zone in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (for example, 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.

Spatial and Temporal Evolution of Earthquake Dynamics: Case Study of the Mw 8.3 Illapel Earthquake, Chile

NASA Astrophysics Data System (ADS)

Yin, Jiuxun; Denolle, Marine A.; Yao, Huajian

2018-01-01

We develop a methodology that combines compressive sensing backprojection (CS-BP) and source spectral analysis of teleseismic P waves to provide metrics relevant to earthquake dynamics of large events. We improve the CS-BP method by an autoadaptive source grid refinement as well as a reference source adjustment technique to gain better spatial and temporal resolution of the locations of the radiated bursts. We also use a two-step source spectral analysis based on (i) simple theoretical Green's functions that include depth phases and water reverberations and on (ii) empirical P wave Green's functions. Furthermore, we propose a source spectrogram methodology that provides the temporal evolution of dynamic parameters such as radiated energy and falloff rates. Bridging backprojection and spectrogram analysis provides a spatial and temporal evolution of these dynamic source parameters. We apply our technique to the recent 2015 Mw 8.3 megathrust Illapel earthquake (Chile). The results from both techniques are consistent and reveal a depth-varying seismic radiation that is also found in other megathrust earthquakes. The low-frequency content of the seismic radiation is located in the shallow part of the megathrust, propagating unilaterally from the hypocenter toward the trench while most of the high-frequency content comes from the downdip part of the fault. Interpretation of multiple rupture stages in the radiation is also supported by the temporal variations of radiated energy and falloff rates. Finally, we discuss the possible mechanisms, either from prestress, fault geometry, and/or frictional properties to explain our observables. Our methodology is an attempt to bridge kinematic observations with earthquake dynamics.

Spatial and temporal dynamics of lake whitefish (Coregonus clupeaformis) health indicators: linking individual-based indicators to a management-relevant endpoint

USGS Publications Warehouse

Wagner, Tyler; Jones, Michael L.; Ebener, Mark P.; Arts, Michael T.; Brenden, Travis O.; Honeyfield, Dale C.; Wright, Gregory M.; Faisal, Mohamed

2010-01-01

We examined the spatial and temporal dynamics of health indicators in four lake whitefish (Coregonus clupeaformis) stocks located in northern lakes Michigan and Huron from 2003 to 2006. The specific objectives were to (1) quantify spatial and temporal variability in health indicators; (2) examine relationships among nutritional indicators and stock-specific spatial and temporal dynamics of pathogen prevalence and intensity of infection; and (3) examine relationships between indicators measured on individual fish and stock-specific estimates of natural mortality. The percent of the total variation attributed to spatial and temporal sources varied greatly depending on the health indicator examined. The most notable pattern was a downward trend in the concentration of highly unsaturated fatty acids (HUFAs), observed in all stocks, in the polar lipid fraction of lake whitefish dorsal muscle tissue over the three study years. Variation among stocks and years for some indicators were correlated with the prevalence and intensity of the swimbladder nematode Cystidicola farionis, suggesting that our measures of fish health were related, at some level, with disease dynamics. We did not find relationships between spatial patterns in fish health indicators and estimates of natural mortality rates for the stocks. Our research highlights the complexity of the interactions between fish nutritional status, disease dynamics, and natural mortality in wild fish populations. Additional research that identifies thresholds of health indicators, below (or above) which survival may be reduced, will greatly help in understanding the relationship between indicators measured on individual fish and potential population-level effects.

A novel approach to assess temporal sensory perception of muscle foods: application of a time-intensity technique to diverse Iberian meat products.

PubMed

Lorido, Laura; Estévez, Mario; Ventanas, Sonia

2014-01-01

Although dynamic sensory techniques such as time-intensity (TI) have been applied to certain meat products, existing knowledge regarding the temporal sensory perception of muscle foods is still limited. The objective of the present study was to apply TI to the flavour and texture perception of three different Iberian meat products: liver pâté, dry-cured sausages ("salchichon") and dry-cured loin. Moreover, the advantages of using dynamic versus static sensory techniques were explored by subjecting the same products to a quantitative descriptive analysis (QDA). TI was a suitable technique to assess the impact of composition and structure of the three meat products on flavour and texture perception from a dynamic perspective. TI parameters extracted from the TI-curves and related to temporal perception enabled the detection of clear differences in sensory temporal perception between the meat products and provided additional insight on sensory perception compared to the conventional static sensory technique (QDA). © 2013.

Exploring the Retrieval Dynamics of Delayed and Final Free Recall: Further Evidence for Temporal-Contextual Search

ERIC Educational Resources Information Center

Unsworth, Nash

2008-01-01

Retrieval dynamics in free recall were explored based on a two-stage search model that relies on temporal-contextual cues. Participants were tested on both delayed and final free recall and correct recalls, errors, and latency measures were examined. In delayed free recall, participants began recall with the first word presented and tended to…

Temporal dynamics of arthropods on six tree species in dry woodlands on the Caribbean Island of Puerto Rico

Treesearch

W. Beltran; Joseph Wunderle Jr.

2014-01-01

The seasonal dynamics of foliage arthropod populations are poorly studied in tropical dry forests despite the importance of these studies for understanding arthropod population responses to environmental change.We monitored the abundance, temporal distributions, and body size of arthropods in five naturalized alien and one native tree species to characterize arthropod...

Reconstructing the temporal and spatial dynamics of emerald ash borer in black ash: a case study of an outlier site in Roscommon County, Michigan

Treesearch

Nathan W. Siegert; Deborah G. McCullough; Andrew M. Liebhold; Frank W. Telewski

2005-01-01

The temporal and spatial dynamics of emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), in an outlier site in Roscommon County, Michigan, were reconstructed using dendrochronological analyses. The site was characterized by pockets of black ash, Fraxinus nigra Marsh., located in swampy areas surrounded...

Temporal Dynamics of Social Exchange and the Development of Solidarity: "Testing the Waters" versus "Taking a Leap of Faith"

ERIC Educational Resources Information Center

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…

Dynamic contrast-enhanced optical imaging of in vivo organ function

NASA Astrophysics Data System (ADS)

Amoozegar, Cyrus B.; Wang, Tracy; Bouchard, Matthew B.; McCaslin, Addason F. H.; Blaner, William S.; Levenson, Richard M.; Hillman, Elizabeth M. C.

2012-09-01

Conventional approaches to optical small animal molecular imaging suffer from poor resolution, limited sensitivity, and unreliable quantitation, often reducing their utility in practice. We previously demonstrated that the in vivo dynamics of an injected contrast agent could be exploited to provide high-contrast anatomical registration, owing to the temporal differences in each organ's response to the circulating fluorophore. This study extends this approach to explore whether dynamic contrast-enhanced optical imaging (DyCE) can allow noninvasive, in vivo assessment of organ function by quantifying the differing cellular uptake or wash-out dynamics of an agent in healthy and damaged organs. Specifically, we used DyCE to visualize and measure the organ-specific uptake dynamics of indocyanine green before and after induction of transient liver damage. DyCE imaging was performed longitudinally over nine days, and blood samples collected at each imaging session were analyzed for alanine aminotransferase (ALT), a liver enzyme assessed clinically as a measure of liver damage. We show that changes in DyCE-derived dynamics of liver and kidney dye uptake caused by liver damage correlate linearly with ALT concentrations, with an r2 value of 0.91. Our results demonstrate that DyCE can provide quantitative, in vivo, longitudinal measures of organ function with inexpensive and simple data acquisition.

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding

NASA Astrophysics Data System (ADS)

Susemihl, Alex; Meir, Ron; Opper, Manfred

2013-03-01

Neurons in the nervous system convey information to higher brain regions by the generation of spike trains. An important question in the field of computational neuroscience is how these sensory neurons encode environmental information in a way which may be simply analyzed by subsequent systems. Many aspects of the form and function of the nervous system have been understood using the concepts of optimal population coding. Most studies, however, have neglected the aspect of temporal coding. Here we address this shortcoming through a filtering theory of inhomogeneous Poisson processes. We derive exact relations for the minimal mean squared error of the optimal Bayesian filter and, by optimizing the encoder, obtain optimal codes for populations of neurons. We also show that a class of non-Markovian, smooth stimuli are amenable to the same treatment, and provide results for the filtering and prediction error which hold for a general class of stochastic processes. This sets a sound mathematical framework for a population coding theory that takes temporal aspects into account. It also formalizes a number of studies which discussed temporal aspects of coding using time-window paradigms, by stating them in terms of correlation times and firing rates. We propose that this kind of analysis allows for a systematic study of temporal coding and will bring further insights into the nature of the neural code.

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

PubMed Central

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

2014-01-01

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

Fitted Fourier-pseudospectral methods for solving a delayed reaction-diffusion partial differential equation in biology

NASA Astrophysics Data System (ADS)

Adam, A. M. A.; Bashier, E. B. M.; Hashim, M. H. A.; Patidar, K. C.

2017-07-01

In this work, we design and analyze a fitted numerical method to solve a reaction-diffusion model with time delay, namely, a delayed version of a population model which is an extension of the logistic growth (LG) equation for a food-limited population proposed by Smith [F.E. Smith, Population dynamics in Daphnia magna and a new model for population growth, Ecology 44 (1963) 651-663]. Seeing that the analytical solution (in closed form) is hard to obtain, we seek for a robust numerical method. The method consists of a Fourier-pseudospectral semi-discretization in space and a fitted operator implicit-explicit scheme in temporal direction. The proposed method is analyzed for convergence and we found that it is unconditionally stable. Illustrative numerical results will be presented at the conference.

Development of a methodology for assessing the safety of embedded software systems

NASA Technical Reports Server (NTRS)

Garrett, C. J.; Guarro, S. B.; Apostolakis, G. E.

1993-01-01

A Dynamic Flowgraph Methodology (DFM) based on an integrated approach to modeling and analyzing the behavior of software-driven embedded systems for assessing and verifying reliability and safety is discussed. DFM is based on an extension of the Logic Flowgraph Methodology to incorporate state transition models. System models which express the logic of the system in terms of causal relationships between physical variables and temporal characteristics of software modules are analyzed to determine how a certain state can be reached. This is done by developing timed fault trees which take the form of logical combinations of static trees relating the system parameters at different point in time. The resulting information concerning the hardware and software states can be used to eliminate unsafe execution paths and identify testing criteria for safety critical software functions.

Cross-language differences in the brain network subserving intelligible speech.

PubMed

Ge, Jianqiao; Peng, Gang; Lyu, Bingjiang; Wang, Yi; Zhuo, Yan; Niu, Zhendong; Tan, Li Hai; Leff, Alexander P; Gao, Jia-Hong

2015-03-10

How is language processed in the brain by native speakers of different languages? Is there one brain system for all languages or are different languages subserved by different brain systems? The first view emphasizes commonality, whereas the second emphasizes specificity. We investigated the cortical dynamics involved in processing two very diverse languages: a tonal language (Chinese) and a nontonal language (English). We used functional MRI and dynamic causal modeling analysis to compute and compare brain network models exhaustively with all possible connections among nodes of language regions in temporal and frontal cortex and found that the information flow from the posterior to anterior portions of the temporal cortex was commonly shared by Chinese and English speakers during speech comprehension, whereas the inferior frontal gyrus received neural signals from the left posterior portion of the temporal cortex in English speakers and from the bilateral anterior portion of the temporal cortex in Chinese speakers. Our results revealed that, although speech processing is largely carried out in the common left hemisphere classical language areas (Broca's and Wernicke's areas) and anterior temporal cortex, speech comprehension across different language groups depends on how these brain regions interact with each other. Moreover, the right anterior temporal cortex, which is crucial for tone processing, is equally important as its left homolog, the left anterior temporal cortex, in modulating the cortical dynamics in tone language comprehension. The current study pinpoints the importance of the bilateral anterior temporal cortex in language comprehension that is downplayed or even ignored by popular contemporary models of speech comprehension.

Cross-language differences in the brain network subserving intelligible speech

PubMed Central

Ge, Jianqiao; Peng, Gang; Lyu, Bingjiang; Wang, Yi; Zhuo, Yan; Niu, Zhendong; Tan, Li Hai; Leff, Alexander P.; Gao, Jia-Hong

2015-01-01

How is language processed in the brain by native speakers of different languages? Is there one brain system for all languages or are different languages subserved by different brain systems? The first view emphasizes commonality, whereas the second emphasizes specificity. We investigated the cortical dynamics involved in processing two very diverse languages: a tonal language (Chinese) and a nontonal language (English). We used functional MRI and dynamic causal modeling analysis to compute and compare brain network models exhaustively with all possible connections among nodes of language regions in temporal and frontal cortex and found that the information flow from the posterior to anterior portions of the temporal cortex was commonly shared by Chinese and English speakers during speech comprehension, whereas the inferior frontal gyrus received neural signals from the left posterior portion of the temporal cortex in English speakers and from the bilateral anterior portion of the temporal cortex in Chinese speakers. Our results revealed that, although speech processing is largely carried out in the common left hemisphere classical language areas (Broca’s and Wernicke’s areas) and anterior temporal cortex, speech comprehension across different language groups depends on how these brain regions interact with each other. Moreover, the right anterior temporal cortex, which is crucial for tone processing, is equally important as its left homolog, the left anterior temporal cortex, in modulating the cortical dynamics in tone language comprehension. The current study pinpoints the importance of the bilateral anterior temporal cortex in language comprehension that is downplayed or even ignored by popular contemporary models of speech comprehension. PMID:25713366

Impact of fitting algorithms on errors of parameter estimates in dynamic contrast-enhanced MRI

NASA Astrophysics Data System (ADS)

Debus, C.; Floca, R.; Nörenberg, D.; Abdollahi, A.; Ingrisch, M.

2017-12-01

Parameter estimation in dynamic contrast-enhanced MRI (DCE MRI) is usually performed by non-linear least square (NLLS) fitting of a pharmacokinetic model to a measured concentration-time curve. The two-compartment exchange model (2CXM) describes the compartments ‘plasma’ and ‘interstitial volume’ and their exchange in terms of plasma flow and capillary permeability. The model function can be defined by either a system of two coupled differential equations or a closed-form analytical solution. The aim of this study was to compare these two representations in terms of accuracy, robustness and computation speed, depending on parameter combination and temporal sampling. The impact on parameter estimation errors was investigated by fitting the 2CXM to simulated concentration-time curves. Parameter combinations representing five tissue types were used, together with two arterial input functions, a measured and a theoretical population based one, to generate 4D concentration images at three different temporal resolutions. Images were fitted by NLLS techniques, where the sum of squared residuals was calculated by either numeric integration with the Runge-Kutta method or convolution. Furthermore two example cases, a prostate carcinoma and a glioblastoma multiforme patient, were analyzed in order to investigate the validity of our findings in real patient data. The convolution approach yields improved results in precision and robustness of determined parameters. Precision and stability are limited in curves with low blood flow. The model parameter ve shows great instability and little reliability in all cases. Decreased temporal resolution results in significant errors for the differential equation approach in several curve types. The convolution excelled in computational speed by three orders of magnitude. Uncertainties in parameter estimation at low temporal resolution cannot be compensated by usage of the differential equations. Fitting with the convolution approach is superior in computational time, with better stability and accuracy at the same time.

Potential effects of climate change on the risk of accidents with poisonous species of the genus Tityus (Scorpiones, Buthidae) in Argentina.

PubMed

Martinez, Pablo Ariel; Andrade, Mayane Alves; Bidau, Claudio Juan

2018-06-01

The temporal pattern of co-occurrence of human beings and venomous species (scorpions, spiders, snakes) is changing. Thus, the temporal pattern of areas with risk of accidents with such species tends to become dynamic in time. We analyze the areas of occurrence of species of Tityus in Argentina and assess the impact of global climate change on their area of distribution by the construction of risk maps. Using data of occurrence of the species and climatic variables, we constructed models of species distribution (SMDs) under current and future climatic conditions. We also created maps that allow the detection of temporal shifts in the distribution patterns of each Tityus species. Finally, we developed risk maps for the analyzed species. Our results predict that climate change will have an impact on the distribution of Tityus species which will clearly expand to more southern latitudes, with the exception of T. argentinus. T. bahiensis, widely distributed in Brazil, showed a considerable increase of its potential area (ca. 37%) with future climate change. The species T. confluens and T. trivittatus that cause the highest number of accidents in Argentina are expected to show significant changes of their distributions in future scenarios. The former fact is worrying because Buenos Aires province is the more densely populated district in Argentina thus iable to become the most affected by T. trivittatus. These alterations of distributional patterns can lead to amplify the accident risk zones of venomous species, becoming an important subject of concern for public health policies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Graph distance for complex networks

NASA Astrophysics Data System (ADS)

Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

2016-10-01

Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

Beyond Group-Threat: Temporal Dynamics of International Migration and Linkages to Anti-Foreigner Sentiment.

PubMed

DeWaard, Jack

2015-07-01

Prior research on the association between country-level patterns of international migration and anti-foreigner sentiment shows that larger foreign-born concentrations increase perceptions of threat among native-born individuals in receiving countries, which, in turn, give rise to exclusionary preferences. While recent work has assembled a list of limiting conditions that shape the strength of this association, I argue that these efforts are premature because they are based on a narrow way of conceptualising and measuring international migration. In contrast to concepts and measures privileging the size of the foreign-born population in receiving countries, I draw from other literatures highlighting the temporal dynamics of migration. In considering the role of the temporal dynamics of international migration in explaining variation in anti-foreigner sentiment, the question is whether and how the temporal stability of the foreign-born population in receiving countries matters. My results suggest that it does. The size and temporal stability of the foreign-born population play opposing roles in aggravating and ameliorating anti-foreigner sentiment, respectively, with each operating via different pathways at the individual level. My work thus breaks new ground by challenging existing theoretical constructs and operationalisations in the group-threat literature.

Beyond Group-Threat: Temporal Dynamics of International Migration and Linkages to Anti-Foreigner Sentiment

PubMed Central

DeWaard, Jack

2014-01-01

Prior research on the association between country-level patterns of international migration and anti-foreigner sentiment shows that larger foreign-born concentrations increase perceptions of threat among native-born individuals in receiving countries, which, in turn, give rise to exclusionary preferences. While recent work has assembled a list of limiting conditions that shape the strength of this association, I argue that these efforts are premature because they are based on a narrow way of conceptualising and measuring international migration. In contrast to concepts and measures privileging the size of the foreign-born population in receiving countries, I draw from other literatures highlighting the temporal dynamics of migration. In considering the role of the temporal dynamics of international migration in explaining variation in anti-foreigner sentiment, the question is whether and how the temporal stability of the foreign-born population in receiving countries matters. My results suggest that it does. The size and temporal stability of the foreign-born population play opposing roles in aggravating and ameliorating anti-foreigner sentiment, respectively, with each operating via different pathways at the individual level. My work thus breaks new ground by challenging existing theoretical constructs and operationalisations in the group-threat literature. PMID:26146481

Temporal Causality Analysis of Sentiment Change in a Cancer Survivor Network.

PubMed

Bui, Ngot; Yen, John; Honavar, Vasant

2016-06-01

Online health communities constitute a useful source of information and social support for patients. American Cancer Society's Cancer Survivor Network (CSN), a 173,000-member community, is the largest online network for cancer patients, survivors, and caregivers. A discussion thread in CSN is often initiated by a cancer survivor seeking support from other members of CSN. Discussion threads are multi-party conversations that often provide a source of social support e.g., by bringing about a change of sentiment from negative to positive on the part of the thread originator. While previous studies regarding cancer survivors have shown that members of an online health community derive benefits from their participation in such communities, causal accounts of the factors that contribute to the observed benefits have been lacking. We introduce a novel framework to examine the temporal causality of sentiment dynamics in the CSN. We construct a Probabilistic Computation Tree Logic representation and a corresponding probabilistic Kripke structure to represent and reason about the changes in sentiments of posts in a thread over time. We use a sentiment classifier trained using machine learning on a set of posts manually tagged with sentiment labels to classify posts as expressing either positive or negative sentiment. We analyze the probabilistic Kripke structure to identify the prima facie causes of sentiment change on the part of the thread originators in the CSN forum and their significance. We find that the sentiment of replies appears to causally influence the sentiment of the thread originator. Our experiments also show that the conclusions are robust with respect to the choice of the (i) classification threshold of the sentiment classifier; (ii) and the choice of the specific sentiment classifier used. We also extend the basic framework for temporal causality analysis to incorporate the uncertainty in the states of the probabilistic Kripke structure resulting from the use of an imperfect state transducer (in our case, the sentiment classifier). Our analysis of temporal causality of CSN sentiment dynamics offers new insights that the designers, managers and moderators of an online community such as CSN can utilize to facilitate and enhance the interactions so as to better meet the social support needs of the CSN participants. The proposed methodology for analysis of temporal causality has broad applicability in a variety of settings where the dynamics of the underlying system can be modeled in terms of state variables that change in response to internal or external inputs.

Temporal Causality Analysis of Sentiment Change in a Cancer Survivor Network

PubMed Central

Bui, Ngot; Yen, John; Honavar, Vasant

2017-01-01

Online health communities constitute a useful source of information and social support for patients. American Cancer Society’s Cancer Survivor Network (CSN), a 173,000-member community, is the largest online network for cancer patients, survivors, and caregivers. A discussion thread in CSN is often initiated by a cancer survivor seeking support from other members of CSN. Discussion threads are multi-party conversations that often provide a source of social support e.g., by bringing about a change of sentiment from negative to positive on the part of the thread originator. While previous studies regarding cancer survivors have shown that members of an online health community derive benefits from their participation in such communities, causal accounts of the factors that contribute to the observed benefits have been lacking. We introduce a novel framework to examine the temporal causality of sentiment dynamics in the CSN. We construct a Probabilistic Computation Tree Logic representation and a corresponding probabilistic Kripke structure to represent and reason about the changes in sentiments of posts in a thread over time. We use a sentiment classifier trained using machine learning on a set of posts manually tagged with sentiment labels to classify posts as expressing either positive or negative sentiment. We analyze the probabilistic Kripke structure to identify the prima facie causes of sentiment change on the part of the thread originators in the CSN forum and their significance. We find that the sentiment of replies appears to causally influence the sentiment of the thread originator. Our experiments also show that the conclusions are robust with respect to the choice of the (i) classification threshold of the sentiment classifier; (ii) and the choice of the specific sentiment classifier used. We also extend the basic framework for temporal causality analysis to incorporate the uncertainty in the states of the probabilistic Kripke structure resulting from the use of an imperfect state transducer (in our case, the sentiment classifier). Our analysis of temporal causality of CSN sentiment dynamics offers new insights that the designers, managers and moderators of an online community such as CSN can utilize to facilitate and enhance the interactions so as to better meet the social support needs of the CSN participants. The proposed methodology for analysis of temporal causality has broad applicability in a variety of settings where the dynamics of the underlying system can be modeled in terms of state variables that change in response to internal or external inputs. PMID:29399599

"One-Stop Shop": Free-Breathing Dynamic Contrast-Enhanced Magnetic Resonance Imaging of the Kidney Using Iterative Reconstruction and Continuous Golden-Angle Radial Sampling.

PubMed

Riffel, Philipp; Zoellner, Frank G; Budjan, Johannes; Grimm, Robert; Block, Tobias K; Schoenberg, Stefan O; Hausmann, Daniel

2016-11-01

The purpose of the present study was to evaluate a recently introduced technique for free-breathing dynamic contrast-enhanced renal magnetic resonance imaging (MRI) applying a combination of radial k-space sampling, parallel imaging, and compressed sensing. The technique allows retrospective reconstruction of 2 motion-suppressed sets of images from the same acquisition: one with lower temporal resolution but improved image quality for subjective image analysis, and one with high temporal resolution for quantitative perfusion analysis. In this study, 25 patients underwent a kidney examination, including a prototypical fat-suppressed, golden-angle radial stack-of-stars T1-weighted 3-dimensional spoiled gradient-echo examination (GRASP) performed after contrast agent administration during free breathing. Images were reconstructed at temporal resolutions of 55 spokes per frame (6.2 seconds) and 13 spokes per frame (1.5 seconds). The GRASP images were evaluated by 2 blinded radiologists. First, the reconstructions with low temporal resolution underwent subjective image analysis: the radiologists assessed the best arterial phase and the best renal phase and rated image quality score for each patient on a 5-point Likert-type scale.In addition, the diagnostic confidence was rated according to a 3-point Likert-type scale. Similarly, respiratory motion artifacts and streak artifacts were rated according to a 3-point Likert-type scale.Then, the reconstructions with high temporal resolution were analyzed with a voxel-by-voxel deconvolution approach to determine the renal plasma flow, and the results were compared with values reported in previous literature. Reader 1 and reader 2 rated the overall image quality score for the best arterial phase and the best renal phase with a median image quality score of 4 (good image quality) for both phases, respectively. A high diagnostic confidence (median score of 3) was observed. There were no respiratory motion artifacts in any of the patients. Streak artifacts were present in all of the patients, but did not compromise diagnostic image quality.The estimated renal plasma flow was slightly higher (295 ± 78 mL/100 mL per minute) than reported in previous MRI-based studies, but also closer to the physiologically expected value. Dynamic, motion-suppressed contrast-enhanced renal MRI can be performed in high diagnostic quality during free breathing using a combination of golden-angle radial sampling, parallel imaging, and compressed sensing. Both morphologic and quantitative functional information can be acquired within a single acquisition.

Separating temporal and topological effects in walk-based network centrality.

PubMed

Colman, Ewan R; Charlton, Nathaniel

2016-07-01

The recently introduced concept of dynamic communicability is a valuable tool for ranking the importance of nodes in a temporal network. Two metrics, broadcast score and receive score, were introduced to measure the centrality of a node with respect to a model of contagion based on time-respecting walks. This article examines the temporal and structural factors influencing these metrics by considering a versatile stochastic temporal network model. We analytically derive formulas to accurately predict the expectation of the broadcast and receive scores when one or more columns in a temporal edge-list are shuffled. These methods are then applied to two publicly available data sets and we quantify how much the centrality of each individual depends on structural or temporal influences. From our analysis, we highlight two practical contributions: a way to control for temporal variation when computing dynamic communicability and the conclusion that the broadcast and receive scores can, under a range of circumstances, be replaced by the row and column sums of the matrix exponential of a weighted adjacency matrix given by the data.

Separating temporal and topological effects in walk-based network centrality

NASA Astrophysics Data System (ADS)

Colman, Ewan R.; Charlton, Nathaniel

2016-07-01

The recently introduced concept of dynamic communicability is a valuable tool for ranking the importance of nodes in a temporal network. Two metrics, broadcast score and receive score, were introduced to measure the centrality of a node with respect to a model of contagion based on time-respecting walks. This article examines the temporal and structural factors influencing these metrics by considering a versatile stochastic temporal network model. We analytically derive formulas to accurately predict the expectation of the broadcast and receive scores when one or more columns in a temporal edge-list are shuffled. These methods are then applied to two publicly available data sets and we quantify how much the centrality of each individual depends on structural or temporal influences. From our analysis, we highlight two practical contributions: a way to control for temporal variation when computing dynamic communicability and the conclusion that the broadcast and receive scores can, under a range of circumstances, be replaced by the row and column sums of the matrix exponential of a weighted adjacency matrix given by the data.

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

NASA Astrophysics Data System (ADS)

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 four reoccurring patterns of typical model performance, which can be related to different phases of the hydrograph. Overall, the baseflow cluster has the lowest performance. By combining the periods with poor model performance with the dominant model components during these phases, the groundwater module was detected as the model part with the highest potential for model improvements. The detection of dominant processes in periods of poor model performance enhances the understanding of the SWAT model. Based on this, concepts how to improve the SWAT model structure for the application in German lowland catchment are derived.

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

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

Temporal bird community dynamics are strongly affected by landscape fragmentation in a Central American tropical forest region

USGS Publications Warehouse

Blandón, A.C.; Perelman, S.B.; Ramírez, M.; López, A.; Javier, O.; Robbins, Chandler S.

2016-01-01

Habitat loss and fragmentation are considered the main causes of species extinctions, particularly in tropical ecosystems. The objective of this work was to evaluate the temporal dynamics of tropical bird communities in landscapes with different levels of fragmentation in eastern Guatemala. We evaluated five bird community dynamic parameters for forest specialists and generalists: (1) species extinction, (2) species turnover, (3) number of colonizing species, (4) relative species richness, and (5) a homogeneity index. For each of 24 landscapes, community dynamic parameters were estimated from bird point count data, for the 1998–1999 and 2008–2009 periods, accounting for species’ detection probability. Forest specialists had higher extinction rates and a smaller number of colonizing species in landscapes with higher fragmentation, thus having lower species richness in both time periods. Alternatively, forest generalists elicited a completely different pattern, showing a curvilinear association to forest fragmentation for most parameters. Thus, greater community dynamism for forest generalists was shown in landscapes with intermediate levels of fragmentation. Our study supports general theory regarding the expected negative effects of habitat loss and fragmentation on the temporal dynamics of biotic communities, particularly for forest specialists, providing strong evidence from understudied tropical bird communities.

Apparatus for characterizing the temporo-spatial properties of a dynamic fluid front and method thereof

DOEpatents

Battiste, Richard L.

2007-12-25

Methods and apparatus are described for characterizing the temporal-spatial properties of a dynamic fluid front within a mold space while the mold space is being filled with fluid. A method includes providing a mold defining a mold space and having one or more openings into the mold space; heating a plurality of temperature sensors that extend into the mold space; injecting a fluid into the mold space through the openings, the fluid experiencing a dynamic fluid front while filling the mold space with the fluid; and characterizing temporal-spatial properties of the dynamic fluid front by monitoring a temperature of each of the plurality of heated temperature sensors while the mold space is being filled with the fluid. An apparatus includes a mold defining a mold space; one or more openings for introducing a fluid into the mold space and filling the mold space with the fluid, the fluid experiencing a dynamic fluid front while filling the mold space; a plurality of heated temperature sensors extending into the mold space; and a computer coupled to the plurality of heated temperature sensors for characterizing the temporal-spatial properties of the dynamic fluid front.

Apparatus for characterizing the temporo-spatial properties of a dynamic fluid front and method thereof

DOEpatents

Battiste, Richard L

2013-12-31

Methods and apparatus are described for characterizing the temporal-spatial properties of a dynamic fluid front within a mold space while the mold space is being filled with fluid. A method includes providing a mold defining a mold space and having one or more openings into the mold space; heating a plurality of temperature sensors that extend into the mold space; injecting a fluid into th emold space through the openings, the fluid experiencing a dynamic fluid front while filling the mold space with a fluid; and characterizing temporal-spatial properties of the dynamic fluid front by monitoring a termperature of each of the plurality of heated temperature sensors while the mold space is being filled with the fluid. An apparatus includes a mold defining a mold space; one or more openings for introducing a fluid into th emold space and filling the mold space with the fluid, the fluid experiencing a dynamic fluid front while filling the mold space; a plurality of heated temperature sensors extending into the mold space; and a computer coupled to the plurality of heated temperature sensors for characterizing the temporal-spatial properties of the dynamic fluid front.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Dynamic recruitment of resting state sub-networks

PubMed Central

O'Neill, George C.; Bauer, Markus; Woolrich, Mark W.; Morris, Peter G.; Barnes, Gareth R.; Brookes, Matthew J.

2015-01-01

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease. PMID:25899137

Individual Sensitivity to Spectral and Temporal Cues in Listeners With Hearing Impairment

PubMed Central

Wright, Richard A.; Blackburn, Michael C.; Tatman, Rachael; Gallun, Frederick J.

2015-01-01

Purpose The present study was designed to evaluate use of spectral and temporal cues under conditions in which both types of cues were available. Method Participants included adults with normal hearing and hearing loss. We focused on 3 categories of speech cues: static spectral (spectral shape), dynamic spectral (formant change), and temporal (amplitude envelope). Spectral and/or temporal dimensions of synthetic speech were systematically manipulated along a continuum, and recognition was measured using the manipulated stimuli. Level was controlled to ensure cue audibility. Discriminant function analysis was used to determine to what degree spectral and temporal information contributed to the identification of each stimulus. Results Listeners with normal hearing were influenced to a greater extent by spectral cues for all stimuli. Listeners with hearing impairment generally utilized spectral cues when the information was static (spectral shape) but used temporal cues when the information was dynamic (formant transition). The relative use of spectral and temporal dimensions varied among individuals, especially among listeners with hearing loss. Conclusion Information about spectral and temporal cue use may aid in identifying listeners who rely to a greater extent on particular acoustic cues and applying that information toward therapeutic interventions. PMID:25629388

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

PubMed

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

2016-08-15

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

Atomistic observation and simulation analysis of spatio-temporal fluctuations during radiation-induced amorphization.

PubMed

Watanabe, Seiichi; Hoshino, Misaki; Koike, Takuto; Suda, Takanori; Ohnuki, Soumei; Takahashi, Heishichirou; Lam, Nighi Q

2003-01-01

We performed a dynamical-atomistic study of radiation-induced amorphization in the NiTi intermetallic compound using in situ high-resolution high-voltage electron microscopy and molecular dynamics simulations in connection with image simulation. Spatio-temporal fluctuations as non-equilibrium fluctuations in an energy-dissipative system, due to transient atom-cluster formation during amorphization, were revealed by the present spatial autocorrelation analysis.

The role of the global phase in the spatio-temporal evolution of strong-coupling Brillouin scattering

NASA Astrophysics Data System (ADS)

Amiranoff, F.; Riconda, C.; Chiaramello, M.; Lancia, L.; Marquès, J. R.; Weber, S.

2018-01-01

The role of the global phase in the spatio-temporal evolution of the 3-wave coupled equations for backscattering is analyzed in the strong-coupling regime of Brillouin scattering. This is of particular interest for controlled backscattering in the case of plasma-based amplification to produce short and intense laser pulses. It is shown that the analysis of the envelope equations of the three waves involved, pump, seed, and ion wave, in terms of phase and amplitude fully describes the coupling dynamics. In particular, it helps understanding the role of the chirp of the laser beams and of the plasma density profile. The results can be used to optimize or quench the coupling mechanism. It is found that the directionality of the energy transfer is imposed by the phase relation at the leading edge of the pulse. This actually ensures continued energy transfer even if the intensity of the seed pulse is already higher than the pump pulse intensity.

Time-resolved photoluminescence study of CdSe/CdMnS/CdS core/multi-shell nanoplatelets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, J. R.; Department of Physics, State University of New York, University at Buffalo, Buffalo, New York 14260; Delikanli, S.

2016-06-13

We used photoluminescence spectroscopy to resolve two emission features in CdSe/CdMnS/CdS and CdSe/CdS core/multi-shell nanoplatelet heterostructures. The photoluminescence from the magnetic sample has a positive circular polarization with a maximum centered at the position of the lower energy feature. The higher energy feature has a corresponding signature in the absorption spectrum; this is not the case for the low-energy feature. We have also studied the temporal evolution of these features using a pulsed-excitation/time-resolved photoluminescence technique to investigate their corresponding recombination channels. A model was used to analyze the temporal dynamics of the photoluminescence which yielded two distinct timescales associated withmore » these recombination channels. The above results indicate that the low-energy feature is associated with recombination of electrons with holes localized at the core/shell interfaces; the high-energy feature, on the other hand, is excitonic in nature with the holes confined within the CdSe cores.« less

Diatom diversity in chronically versus episodically acidified adirondack streams

USGS Publications Warehouse

Passy, S.I.; Ciugulea, I.; Lawrence, G.B.

2006-01-01

The relationship between algal species richness and diversity, and pH is controversial. Furthermore, it is still unknown how episodic stream acidification following atmospheric deposition affects species richness and diversity. Here we analyzed water chemistry and diatom epiphyton dynamics and showed their contrasting behavior in chronically vs. episodically acidic streams in the Adirondack region. Species richness and diversity were significantly higher in the chronically acidic brown water stream, where organic acidity was significantly higher and the ratio of inorganic to organic monomeric aluminum significantly lower. Conversely, in the episodically acidic clear water stream, the inorganic acidity and pH were significantly higher and the diatom communities were very species-poor. This suggests that episodic acidification in the Adirondacks may be more stressful for stream biota than chronic acidity. Strong negative linear relationships between species diversity, Eunotia exigua, and dissolved organic carbon against pH were revealed after the influence of non-linear temporal trends was partialled out using a novel way of temporal modeling. ?? 2006 WILEY-VCH Verlag GmbH & Co. KGaA.

Evaluation and correction for optical scattering variations in laser speckle rheology of biological fluids.

PubMed

Hajjarian, Zeinab; Nadkarni, Seemantini K

2013-01-01

Biological fluids fulfill key functionalities such as hydrating, protecting, and nourishing cells and tissues in various organ systems. They are capable of these versatile tasks owing to their distinct structural and viscoelastic properties. Characterizing the viscoelastic properties of bio-fluids is of pivotal importance for monitoring the development of certain pathologies as well as engineering synthetic replacements. Laser Speckle Rheology (LSR) is a novel optical technology that enables mechanical evaluation of tissue. In LSR, a coherent laser beam illuminates the tissue and temporal speckle intensity fluctuations are analyzed to evaluate mechanical properties. The rate of temporal speckle fluctuations is, however, influenced by both optical and mechanical properties of tissue. Therefore, in this paper, we develop and validate an approach to estimate and compensate for the contributions of light scattering to speckle dynamics and demonstrate the capability of LSR for the accurate extraction of viscoelastic moduli in phantom samples and biological fluids of varying optical and mechanical properties.

Observational constraints on relativistic electron dynamics: temporal evolution of electron spectra and flux isotropization

NASA Astrophysics Data System (ADS)

Kanekal, S. G.; Selesnick, R. S.; Baker, D. N.; Blake, J. B.

2007-05-01

Models of energization of electrons in the Earth's outer radiation belts invoke two classes of processes, radial transport and in-situ wave-particle interactions. Temporal evolution of electron spectra and flux isotropization during energization events provide useful observational constraints on models of electron energization. Events dominated by radial diffusion result in pancake type pitch angle distributions whereas some in-situ wave-particle energization mechanisms include pitch angle scattering leading to rapid flux isotropization. We present a survey of flux isotrpization time scales and electron spectra during relativstic electron enhancement events. We will use data collected by detectors onboard SAMPEX in low earth orbit and Polar which measures electron fluxes at higher altitude to measure flux isotropization. Electron spectra are obtained by pulse height analyzed data from the PET detector onboard SAMPEX.SAMPEX measurements cover the entire outer zone for more than a decade from mid 1992 to mid 2004 and Polar covers the time period from mid 1996 to the present.

Evaluation and Correction for Optical Scattering Variations in Laser Speckle Rheology of Biological Fluids

PubMed Central

Hajjarian, Zeinab; Nadkarni, Seemantini K.

2013-01-01

Biological fluids fulfill key functionalities such as hydrating, protecting, and nourishing cells and tissues in various organ systems. They are capable of these versatile tasks owing to their distinct structural and viscoelastic properties. Characterizing the viscoelastic properties of bio-fluids is of pivotal importance for monitoring the development of certain pathologies as well as engineering synthetic replacements. Laser Speckle Rheology (LSR) is a novel optical technology that enables mechanical evaluation of tissue. In LSR, a coherent laser beam illuminates the tissue and temporal speckle intensity fluctuations are analyzed to evaluate mechanical properties. The rate of temporal speckle fluctuations is, however, influenced by both optical and mechanical properties of tissue. Therefore, in this paper, we develop and validate an approach to estimate and compensate for the contributions of light scattering to speckle dynamics and demonstrate the capability of LSR for the accurate extraction of viscoelastic moduli in phantom samples and biological fluids of varying optical and mechanical properties. PMID:23705028

Polyphasic Temporal Behavior of Finger-Tapping Performance: A Measure of Motor Skills and Fatigue.

PubMed

Aydin, Leyla; Kiziltan, Erhan; Gundogan, Nimet Unay

2016-01-01

Successive voluntary motor movement involves a number of physiological mechanisms and may reflect motor skill development and neuromuscular fatigue. In this study, the temporal behavior of finger tapping was investigated in relation to motor skills and fatigue by using a long-term computer-based test. The finger-tapping performances of 29 healthy male volunteers were analyzed using linear and nonlinear regression models established for inter-tapping interval. The results suggest that finger-tapping performance exhibits a polyphasic nature, and has several characteristic time points, which may be directly related to muscle dynamics and energy consumption. In conclusion, we believe that future studies evaluating the polyphasic nature of the maximal voluntary movement will lead to the definition of objective scales that can be used in the follow up of some neuromuscular diseases, as well as, the determination of motor skills, individual ability, and peripheral fatigue through the use of a low cost, easy-to-use computer-based finger-tapping test.

Time-Hierarchical Clustering and Visualization of Weather Forecast Ensembles.

PubMed

Ferstl, Florian; Kanzler, Mathias; Rautenhaus, Marc; Westermann, Rudiger

2017-01-01

We propose a new approach for analyzing the temporal growth of the uncertainty in ensembles of weather forecasts which are started from perturbed but similar initial conditions. As an alternative to traditional approaches in meteorology, which use juxtaposition and animation of spaghetti plots of iso-contours, we make use of contour clustering and provide means to encode forecast dynamics and spread in one single visualization. Based on a given ensemble clustering in a specified time window, we merge clusters in time-reversed order to indicate when and where forecast trajectories start to diverge. We present and compare different visualizations of the resulting time-hierarchical grouping, including space-time surfaces built by connecting cluster representatives over time, and stacked contour variability plots. We demonstrate the effectiveness of our visual encodings with forecast examples of the European Centre for Medium-Range Weather Forecasts, which convey the evolution of specific features in the data as well as the temporally increasing spatial variability.

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

NASA Astrophysics Data System (ADS)

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 temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

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

PubMed

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

2018-02-13

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 temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Brownian motion of a circle swimmer in a harmonic trap

NASA Astrophysics Data System (ADS)

Jahanshahi, Soudeh; Löwen, Hartmut; ten Hagen, Borge

2017-02-01

We study the dynamics of a Brownian circle swimmer with a time-dependent self-propulsion velocity in an external temporally varying harmonic potential. For several situations, the noise-free swimming paths, the noise-averaged mean trajectories, and the mean-square displacements are calculated analytically or by computer simulation. Based on our results, we discuss optimal swimming strategies in order to explore a maximum spatial range around the trap center. In particular, we find a resonance situation for the maximum escape distance as a function of the various frequencies in the system. Moreover, the influence of the Brownian noise is analyzed by comparing noise-free trajectories at zero temperature with the corresponding noise-averaged trajectories at finite temperature. The latter reveal various complex self-similar spiral or rosette-like patterns. Our predictions can be tested in experiments on artificial and biological microswimmers under dynamical external confinement.

Strain and thermally induced magnetic dynamics and spin current in magnetic insulators subject to transient optical grating

NASA Astrophysics Data System (ADS)

Wang, Xi-Guang; Chotorlishvili, Levan; Berakdar, Jamal

2017-07-01

We analyze the magnetic dynamics and particularlythe spin current in an open-circuit ferromagnetic insulator irradiated by two intense, phase-locked laser pulses. The interference of the laser beams generates a transient optical grating and a transient spatio-temporal temperature distribution. Both effects lead to elastic and heat waves at the surface and into the bulk of the sample. The strain induced spin current as well as the thermally induced magnonic spin current are evaluated numerically on the basis of micromagnetic simulations using solutions of the heat equation. We observe that the thermo-elastically induced magnonic spin current propagates on a distance larger than the characteristic size of thermal profile, an effect useful for applications in remote detection of spin caloritronics phenomena. Our findings point out that exploiting strain adds a new twist to heat-assisted magnetic switching and spin-current generation for spintronic applications.

[Age structure and dynamics of Quercus wutaishanica population in Lingkong Mountain of Shanxi Province, China].

PubMed

Zhang, Jie; Shangguan, Tie-Liang; Duan, Yi-Hao; Guo, Wei; Liu, Wei-Hua; Guo, Dong-Gang

2014-11-01

Using the plant survivorship theory, the age structure, and the relationship between tree height and diameter (DBH) of Quercus wutaishanica population in Lingkong Mountain were analyzed, and the static life table was compiled and the survival curve plotted. The shuttle shape in age structure of Q. wutaishanica population suggested its temporal stability. The linear regression significantly fitted the positive correlation between tree height and DBH. The maximal life expectancy was observed among the trees beyond the age of the highest mortality and coincided with the lowest point of mortality density, suggesting the strong vitality of the seedlings and young trees that survived in the natural selection and intraspecific competition. The population stability of the Q. wutaishanica population was characterized by the Deevey-II of the survival curve. The dynamic pattern was characterized by the recession in the early phase, growth in the intermediate phase, and stability in the latter phase.

Multifractal Fluctuations of Jiuzhaigou Tourists Before and after Wenchuan Earthquake

NASA Astrophysics Data System (ADS)

Shi, Kai; Li, Wen-Yong; Liu, Chun-Qiong; Huang, Zheng-Wen

2013-03-01

In this work, multifractal methods have been successfully used to characterize the temporal fluctuations of daily Jiuzhai Valley domestic and foreign tourists before and after Wenchuan earthquake in China. We used multifractal detrending moving average method (MF-DMA). It showed that Jiuzhai Valley tourism markets are characterized by long-term memory and multifractal nature in. Moreover, the major sources of multifractality are studied. Based on the concept of sliding window, the time evolutions of the multifractal behavior of domestic and foreign tourists were analyzed and the influence of Wenchuan earthquake on Jiuzhai Valley tourism system dynamics were evaluated quantitatively. The study indicates that the inherent dynamical mechanism of Jiuzhai Valley tourism system has not been fundamentally changed from long views, although Jiuzhai Valley tourism system was seriously affected by the Wenchuan earthquake. Jiuzhai Valley tourism system has the ability to restore to its previous state in the short term.

Topographic Cues Reveal Two Distinct Spreading Mechanisms in Blood Platelets

PubMed Central

Sandmann, Rabea; Köster, Sarah

2016-01-01

Blood platelets are instrumental in blood clotting and are thus heavily involved in early wound closure. After adhering to a substrate they spread by forming protrusions like lamellipodia and filopodia. However, the interaction of these protrusions with the physical environment of platelets while spreading is not fully understood. Here we dynamically image platelets during this spreading process and compare their behavior on smooth and on structured substrates. In particular we analyze the temporal evolution of the spread area, the cell morphology and the dynamics of individual filopodia. Interestingly, the topographic cues enable us to distinguish two spreading mechanisms, one that is based on numerous persistent filopodia and one that rather involves lamellipodia. Filopodia-driven spreading coincides with a strong response of platelet morphology to the substrate topography during spreading, whereas lamellipodia-driven spreading does not. Thus, we quantify different degrees of filopodia formation in platelets and the influence of filopodia in spreading on structured substrates. PMID:26934830

Role of the noise on the transient dynamics of an ecosystem of interacting species

NASA Astrophysics Data System (ADS)

Spagnolo, B.; La Barbera, A.

2002-11-01

We analyze the transient dynamics of an ecosystem described by generalized Lotka-Volterra equations in the presence of a multiplicative noise and a random interaction parameter between the species. We consider specifically three cases: (i) two competing species, (ii) three interacting species (one predator-two preys), (iii) n-interacting species. The interaction parameter in case (i) is a stochastic process which obeys a stochastic differential equation. We find noise delayed extinction of one of two species, which is akin to the noise-enhanced stability phenomenon. Other two noise-induced effects found are temporal oscillations and spatial patterns of the two competing species. In case (ii) the noise induces correlated spatial patterns of the predator and of the two preys concentrations. Finally, in case (iii) we find the asymptotic behavior of the time average of the ith population when the ecosystem is composed of a great number of interacting species.

The Role of Helium Metastable States in Radio-Frequency Helium-Oxygen Atmospheric Pressure Plasma Jets: Measurement and Numerical Simulation

NASA Astrophysics Data System (ADS)

Niemi, Kari; Waskoenig, Jochen; Sadeghi, Nader; Gans, Timo; O'Connell, Deborah

2011-10-01

Absolute densities of metastable He atoms were measured line-of sight integrated along the plasma channel of a capacitively-coupled radio-frequency driven atmospheric pressure plasma jet operated in helium oxygen mixtures by tunable diode-laser absorption spectroscopy. Dependencies of the He metastable density with oxygen admixtures up to 1 percent were investigated. Results are compared to a 1-d numerical simulation, which includes a semi-kinetical treatment of the electron dynamics and the complex plasma chemistry (20 species, 184 reactions), and very good agreement is found. The main formation mechanisms for the helium metastables are identified and analyzed, including their pronounced spatio-temporal dynamics. Penning ionization through helium metastables is found to be significant for plasma sustainment, while it is revealed that helium metastables are not an important energy carrying species into the jet effluent and therefore will not play a direct role in remote surface treatments.

Analysis of the Spatiotemporal Characteristics of Hemorrhagic Fever with Renal Syndrome in Hubei Province, China

NASA Astrophysics Data System (ADS)

Fan, H.; Ge, L.; Song, L.; Zhao, Q.

2015-07-01

Hemorrhagic fever with renal syndrome(HFRS) is a worldwide fulminant infectious disease. Since the first HFRS cases in Hubei Province were reported in 1957, the disease has spread across the province and Hubei has become one of seriously affected areas in China. However, the epidemic characteristics of HFRS are still not entirely clear. Therefore, a systematic investigation of spatial and temporal distribution pattern of HFRS system is needed. In order to facilitate better prevention and control of HFRS in Hubei Province, in this paper, a GIS spatiotemporal analysis and modeling tool was developed to analyze the spatiotemporal dynamics of the HFRS epidemic, as well as providinga comprehensive examination the dynamic pattern of HFRS in Hubei over the past 30 years (1980-2009), to determine spatiotemporal change trends and the causes of HFRS. This paper describes the experiments and their results.

From retinal waves to activity-dependent retinogeniculate map development.

PubMed

Markowitz, Jeffrey; Cao, Yongqiang; Grossberg, Stephen

2012-01-01

A neural model is described of how spontaneous retinal waves are formed in infant mammals, and how these waves organize activity-dependent development of a topographic map in the lateral geniculate nucleus, with connections from each eye segregated into separate anatomical layers. The model simulates the spontaneous behavior of starburst amacrine cells and retinal ganglion cells during the production of retinal waves during the first few weeks of mammalian postnatal development. It proposes how excitatory and inhibitory mechanisms within individual cells, such as Ca(2+)-activated K(+) channels, and cAMP currents and signaling cascades, can modulate the spatiotemporal dynamics of waves, notably by controlling the after-hyperpolarization currents of starburst amacrine cells. Given the critical role of the geniculate map in the development of visual cortex, these results provide a foundation for analyzing the temporal dynamics whereby the visual cortex itself develops.

Spatial and Temporal Patterns of Throughfall Amounts and Solutes in a Tropical Montane Forest - Comparisons with Findings From Lowland Rain Forests

NASA Astrophysics Data System (ADS)

Zimmermann, A.

2007-05-01

The diverse tree species composition, irregular shaped tree crowns and a multi-layered forest structure affect the redistribution of rainfall in lower montane rain forests. In addition, abundant epiphyte biomass and associated canopy humus influence spatial patterns of throughfall. The spatial variability of throughfall amounts controls spatial patterns of solute concentrations and deposition. Moreover, the living and dead biomass interacts with the rainwater during the passage through the canopy and creates a chemical variability of its own. Since spatial and temporal patterns are intimately linked, the analysis of temporal solute concentration dynamics is an important step to understand the emerging spatial patterns. I hypothesized that: (1) the spatial variability of volumes and chemical composition of throughfall is particularly high compared with other forests because of the high biodiversity and epiphytism, (2) the temporal stability of the spatial pattern is high because of stable structures in the canopy (e.g. large epiphytes) that show only minor changes during the short term observation period, and (3) the element concentrations decrease with increasing rainfall because of exhausting element pools in the canopy. The study area at 1950 m above sea level is located in the south Ecuadorian Andes far away from anthropogenic emission sources and marine influences. Rain and throughfall were collected from August to October 2005 on an event and within-event basis for five precipitation periods and analyzed for pH, K, Na, Ca, Mg, NH4+, Cl-, NO3-, PO43-, TN, TP and TOC. Throughfall amounts and most of the solutes showed a high spatial variability, thereby the variability of H+, K, Ca, Mg, Cl- and NO3- exceeded those from a Brazilian tropical rain forest. The temporal persistence of the spatial patterns was high for throughfall amounts and varied depending on the solute. Highly persistent time stability patterns were detected for K, Mg and TOC concentrations. Time stability patterns of solute deposition were somewhat weaker than for concentrations for most of the solutes. Epiphytes strongly affected time stability patterns in that collectors situated below thick moss mats or arboreal bromeliads were in large part responsible for the extreme persistence with low throughfall amounts and high ion concentrations (H+ showed low concentrations). Rainfall solute concentrations were low compared with a variety of other tropical lowland and montane forest sites and showed a small temporal variability during the study period for both between and within-event dynamics, respectively. Throughfall solute concentrations were more within the range when compared with other sites and showed highly variable within-event dynamics. For most of the solutes, within-event concentrations did not reach low, constant concentrations in later event stages, rather concentrations fluctuated (e.g. Cl-) or increased (e.g. K and TOC). The within-event throughfall solute concentration dynamics in this lower montane rain forest contrast to recent observations from lowland tropical rain forests in Panama and Brazil. The observed within-event patterns are attributed (1) to the influence of epiphytes and associated canopy humus, and (2) to low rainfall intensities.

Chimera states in complex networks: interplay of fractal topology and delay

NASA Astrophysics Data System (ADS)

Sawicki, Jakub; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2017-06-01

Chimera states are an example of intriguing partial synchronization patterns emerging in networks of identical oscillators. They consist of spatially coexisting domains of coherent (synchronized) and incoherent (desynchronized) dynamics. We analyze chimera states in networks of Van der Pol oscillators with hierarchical connectivities, and elaborate the role of time delay introduced in the coupling term. In the parameter plane of coupling strength and delay time we find tongue-like regions of existence of chimera states alternating with regions of existence of coherent travelling waves. We demonstrate that by varying the time delay one can deliberately stabilize desired spatio-temporal patterns in the system.

Association of spring-summer hydrology and meteorology with human West Nile virus infection in West Texas, USA, 2002-2016.

PubMed

Ukawuba, Israel; Shaman, Jeffrey

2018-04-04

The emergence of West Nile virus (WNV) in the Western Hemisphere has motivated research into the processes contributing to the incidence and persistence of the disease in the region. Meteorology and hydrology are fundamental determinants of vector-borne disease transmission dynamics of a region. The availability of water influences the population dynamics of vector and host, while temperature impacts vector growth rates, feeding habits, and disease transmission potential. Characterization of the temporal pattern of environmental factors influencing WNV risk is crucial to broaden our understanding of local transmission dynamics and to inform efforts of control and surveillance. We used hydrologic, meteorological and WNV data from west Texas (2002-2016) to analyze the relationship between environmental conditions and annual human WNV infection. A Bayesian model averaging framework was used to evaluate the association of monthly environmental conditions with WNV infection. Findings indicate that wet conditions in the spring combined with dry and cool conditions in the summer are associated with increased annual WNV cases. Bayesian multi-model inference reveals monthly means of soil moisture, specific humidity and temperature to be the most important variables among predictors tested. Environmental conditions in March, June, July and August were the leading predictors in the best-fitting models. The results significantly link soil moisture and temperature in the spring and summer to WNV transmission risk. Wet spring in association with dry and cool summer was the temporal pattern best-describing WNV, regardless of year. Our findings also highlight that soil moisture may be a stronger predictor of annual WNV transmission than rainfall.

Introduction to the Focus Issue: Chemo-Hydrodynamic Patterns and Instabilities

NASA Astrophysics Data System (ADS)

De Wit, A.; Eckert, K.; Kalliadasis, S.

2012-09-01

Pattern forming instabilities are often encountered in a wide variety of natural phenomena and technological applications, from self-organization in biological and chemical systems to oceanic or atmospheric circulation and heat and mass transport processes in engineering systems. Spatio-temporal structures are ubiquitous in hydrodynamics where numerous different convective instabilities generate pattern formation and complex spatiotemporal dynamics, which have been much studied both theoretically and experimentally. In parallel, reaction-diffusion processes provide another large family of pattern forming instabilities and spatio-temporal structures which have been analyzed for several decades. At the intersection of these two fields, "chemo-hydrodynamic patterns and instabilities" resulting from the coupling of hydrodynamic and reaction-diffusion processes have been less studied. The exploration of the new instability and symmetry-breaking scenarios emerging from the interplay between chemical reactions, diffusion and convective motions is a burgeoning field in which numerous exciting problems have emerged during the last few years. These problems range from fingering instabilities of chemical fronts and reactive fluid-fluid interfaces to the dynamics of reaction-diffusion systems in the presence of chaotic mixing. The questions to be addressed are at the interface of hydrodynamics, chemistry, engineering or environmental sciences to name a few and, as a consequence, they have started to draw the attention of several communities including both the nonlinear chemical dynamics and hydrodynamics communities. The collection of papers gathered in this Focus Issue sheds new light on a wide range of phenomena in the general area of chemo-hydrodynamic patterns and instabilities. It also serves as an overview of the current research and state-of-the-art in the field.

Temporal dynamics in dominant runoff sources and flow paths in the Andean Páramo

NASA Astrophysics Data System (ADS)

Correa, Alicia; Windhorst, David; Tetzlaff, Doerthe; Crespo, Patricio; Célleri, Rolando; Feyen, Jan; Breuer, Lutz

2017-07-01

The relative importance of catchment's water provenance and flow paths varies in space and time, complicating the conceptualization of the rainfall-runoff responses. We assessed the temporal dynamics in source areas, flow paths, and age by End Member Mixing Analysis (EMMA), hydrograph separation, and Inverse Transit Time Proxies (ITTPs) estimation within a headwater catchment in the Ecuadorian Andes. Twenty-two solutes, stable isotopes, pH, and electrical conductivity from a stream and 12 potential sources were analyzed. Four end-members were required to satisfactorily represent the hydrological system, i.e., rainfall, spring water, and water from the bottom layers of Histosols and Andosols. Water from Histosols in and near the riparian zone was the highest source contributor to runoff throughout the year (39% for the drier season, 45% for the wetter season), highlighting the importance of the water that is stored in the riparian zone. Spring water contributions to streamflow tripled during the drier season, as evidenced by geochemical signatures that are consistent with deeper flow paths rather than shallow interflow through Andosols. Rainfall exhibited low seasonal variation in this contribution. Hydrograph separation revealed that 94% and 84% is preevent water in the drier and wetter seasons, respectively. From low-flow to high-flow conditions, all the sources increased their contribution except spring water. The relative age of stream water decreased during wetter periods, when the contributing area of the riparian zone expands. The multimethod and multitracer approach enabled to closely study the interchanging importance of flow processes and water source dynamics from an interannual perspective.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina).

PubMed

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-05-01

Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control.