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Sample records for multivariate event time

  1. Two-stage estimation for multivariate recurrent event data with a dependent terminal event.

    PubMed

    Chen, Chyong-Mei; Chuang, Ya-Wen; Shen, Pao-Sheng

    2015-03-01

    Recurrent event data arise in longitudinal follow-up studies, where each subject may experience the same type of events repeatedly. The work in this article is motivated by the data from a study of repeated peritonitis for patients on peritoneal dialysis. Due to the aspects of medicine and cost, the peritonitis cases were classified into two types: Gram-positive and non-Gram-positive peritonitis. Further, since the death and hemodialysis therapy preclude the occurrence of recurrent events, we face multivariate recurrent event data with a dependent terminal event. We propose a flexible marginal model, which has three characteristics: first, we assume marginal proportional hazard and proportional rates models for terminal event time and recurrent event processes, respectively; second, the inter-recurrences dependence and the correlation between the multivariate recurrent event processes and terminal event time are modeled through three multiplicative frailties corresponding to the specified marginal models; third, the rate model with frailties for recurrent events is specified only on the time before the terminal event. We propose a two-stage estimation procedure for estimating unknown parameters. We also establish the consistency of the two-stage estimator. Simulation studies show that the proposed approach is appropriate for practical use. The methodology is applied to the peritonitis cohort data that motivated this study.

  2. Multivariate Voronoi Outlier Detection for Time Series.

    PubMed

    Zwilling, Chris E; Wang, Michelle Yongmei

    2014-10-01

    Outlier detection is a primary step in many data mining and analysis applications, including healthcare and medical research. This paper presents a general method to identify outliers in multivariate time series based on a Voronoi diagram, which we call Multivariate Voronoi Outlier Detection (MVOD). The approach copes with outliers in a multivariate framework, via designing and extracting effective attributes or features from the data that can take parametric or nonparametric forms. Voronoi diagrams allow for automatic configuration of the neighborhood relationship of the data points, which facilitates the differentiation of outliers and non-outliers. Experimental evaluation demonstrates that our MVOD is an accurate, sensitive, and robust method for detecting outliers in multivariate time series data.

  3. Multivariate cluster analysis of forest fire events in Portugal

    NASA Astrophysics Data System (ADS)

    Tonini, Marj; Pereira, Mario; Vega Orozco, Carmen; Parente, Joana

    2015-04-01

    Portugal is one of the major fire-prone European countries, mainly due to its favourable climatic, topographic and vegetation conditions. Compared to the other Mediterranean countries, the number of events registered here from 1980 up to nowadays is the highest one; likewise, with respect to the burnt area, Portugal is the third most affected country. Portuguese mapped burnt areas are available from the website of the Institute for the Conservation of Nature and Forests (ICNF). This official geodatabase is the result of satellite measurements starting from the year 1990. The spatial information, delivered in shapefile format, provides a detailed description of the shape and the size of area burnt by each fire, while the date/time information relate to the ignition fire is restricted to the year of occurrence. In terms of a statistical formalism wildfires can be associated to a stochastic point process, where events are analysed as a set of geographical coordinates corresponding, for example, to the centroid of each burnt area. The spatio/temporal pattern of stochastic point processes, including the cluster analysis, is a basic procedure to discover predisposing factorsas well as for prevention and forecasting purposes. These kinds of studies are primarily focused on investigating the spatial cluster behaviour of environmental data sequences and/or mapping their distribution at different times. To include both the two dimensions (space and time) a comprehensive spatio-temporal analysis is needful. In the present study authors attempt to verify if, in the case of wildfires in Portugal, space and time act independently or if, conversely, neighbouring events are also closer in time. We present an application of the spatio-temporal K-function to a long dataset (1990-2012) of mapped burnt areas. Moreover, the multivariate K-function allowed checking for an eventual different distribution between small and large fires. The final objective is to elaborate a 3D

  4. Multivariate Statistical Modelling of Drought and Heat Wave Events

    NASA Astrophysics Data System (ADS)

    Manning, Colin; Widmann, Martin; Vrac, Mathieu; Maraun, Douglas; Bevaqua, Emanuele

    2016-04-01

    Multivariate Statistical Modelling of Drought and Heat Wave Events C. Manning1,2, M. Widmann1, M. Vrac2, D. Maraun3, E. Bevaqua2,3 1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK 2. Laboratoire des Sciences du Climat et de l'Environnement, (LSCE-IPSL), Centre d'Etudes de Saclay, Gif-sur-Yvette, France 3. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010 Graz, Austria Compound extreme events are a combination of two or more contributing events which in themselves may not be extreme but through their joint occurrence produce an extreme impact. Compound events are noted in the latest IPCC report as an important type of extreme event that have been given little attention so far. As part of the CE:LLO project (Compound Events: muLtivariate statisticaL mOdelling) we are developing a multivariate statistical model to gain an understanding of the dependence structure of certain compound events. One focus of this project is on the interaction between drought and heat wave events. Soil moisture has both a local and non-local effect on the occurrence of heat waves where it strongly controls the latent heat flux affecting the transfer of sensible heat to the atmosphere. These processes can create a feedback whereby a heat wave maybe amplified or suppressed by the soil moisture preconditioning, and vice versa, the heat wave may in turn have an effect on soil conditions. An aim of this project is to capture this dependence in order to correctly describe the joint probabilities of these conditions and the resulting probability of their compound impact. We will show an application of Pair Copula Constructions (PCCs) to study the aforementioned compound event. PCCs allow in theory for the formulation of multivariate dependence structures in any dimension where the PCC is a decomposition of a multivariate distribution into a product of bivariate components modelled using copulas. A

  5. Network structure of multivariate time series

    PubMed Central

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-01-01

    Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail. PMID:26487040

  6. Network structure of multivariate time series.

    PubMed

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-10-21

    Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

  7. Time varying, multivariate volume data reduction

    SciTech Connect

    Ahrens, James P; Fout, Nathaniel; Ma, Kwan - Liu

    2010-01-01

    Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the

  8. Visualizing frequent patterns in large multivariate time series

    NASA Astrophysics Data System (ADS)

    Hao, M.; Marwah, M.; Janetzko, H.; Sharma, R.; Keim, D. A.; Dayal, U.; Patnaik, D.; Ramakrishnan, N.

    2011-01-01

    The detection of previously unknown, frequently occurring patterns in time series, often called motifs, has been recognized as an important task. However, it is difficult to discover and visualize these motifs as their numbers increase, especially in large multivariate time series. To find frequent motifs, we use several temporal data mining and event encoding techniques to cluster and convert a multivariate time series to a sequence of events. Then we quantify the efficiency of the discovered motifs by linking them with a performance metric. To visualize frequent patterns in a large time series with potentially hundreds of nested motifs on a single display, we introduce three novel visual analytics methods: (1) motif layout, using colored rectangles for visualizing the occurrences and hierarchical relationships of motifs in a multivariate time series, (2) motif distortion, for enlarging or shrinking motifs as appropriate for easy analysis and (3) motif merging, to combine a number of identical adjacent motif instances without cluttering the display. Analysts can interactively optimize the degree of distortion and merging to get the best possible view. A specific motif (e.g., the most efficient or least efficient motif) can be quickly detected from a large time series for further investigation. We have applied these methods to two real-world data sets: data center cooling and oil well production. The results provide important new insights into the recurring patterns.

  9. Detrended fluctuation analysis of multivariate time series

    NASA Astrophysics Data System (ADS)

    Xiong, Hui; Shang, P.

    2017-01-01

    In this work, we generalize the detrended fluctuation analysis (DFA) to the multivariate case, named multivariate DFA (MVDFA). The validity of the proposed MVDFA is illustrated by numerical simulations on synthetic multivariate processes, where the cases that initial data are generated independently from the same system and from different systems as well as the correlated variate from one system are considered. Moreover, the proposed MVDFA works well when applied to the multi-scale analysis of the returns of stock indices in Chinese and US stock markets. Generally, connections between the multivariate system and the individual variate are uncovered, showing the solid performances of MVDFA and the multi-scale MVDFA.

  10. Segmentation of biological multivariate time-series data

    NASA Astrophysics Data System (ADS)

    Omranian, Nooshin; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2015-03-01

    Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana.

  11. An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data.

    PubMed

    Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

    2016-01-01

    This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems.

  12. An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

    PubMed Central

    Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

    2015-01-01

    This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

  13. Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

    ERIC Educational Resources Information Center

    Price, Larry R.

    2012-01-01

    The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

  14. Interpretable Early Classification of Multivariate Time Series

    ERIC Educational Resources Information Center

    Ghalwash, Mohamed F.

    2013-01-01

    Recent advances in technology have led to an explosion in data collection over time rather than in a single snapshot. For example, microarray technology allows us to measure gene expression levels in different conditions over time. Such temporal data grants the opportunity for data miners to develop algorithms to address domain-related problems,…

  15. Distance measure with improved lower bound for multivariate time series

    NASA Astrophysics Data System (ADS)

    Li, Hailin

    2017-02-01

    Lower bound function is one of the important techniques used to fast search and index time series data. Multivariate time series has two aspects of high dimensionality including the time-based dimension and the variable-based dimension. Due to the influence of variable-based dimension, a novel method is proposed to deal with the lower bound distance computation for multivariate time series. The proposed method like the traditional ones also reduces the dimensionality of time series in its first step and thus does not directly apply the lower bound function on the multivariate time series. The dimensionality reduction is that multivariate time series is reduced to univariate time series denoted as center sequences according to the principle of piecewise aggregate approximation. In addition, an extended lower bound function is designed to obtain good tightness and fast measure the distance between any two center sequences. The experimental results demonstrate that the proposed lower bound function has better tightness and improves the performance of similarity search in multivariate time series datasets.

  16. Estimating the ratio of multivariate recurrent event rates with application to a blood transfusion study.

    PubMed

    Ning, Jing; Rahbar, Mohammad H; Choi, Sangbum; Piao, Jin; Hong, Chuan; Del Junco, Deborah J; Rahbar, Elaheh; Fox, Erin E; Holcomb, John B; Wang, Mei-Cheng

    2015-07-09

    In comparative effectiveness studies of multicomponent, sequential interventions like blood product transfusion (plasma, platelets, red blood cells) for trauma and critical care patients, the timing and dynamics of treatment relative to the fragility of a patient's condition is often overlooked and underappreciated. While many hospitals have established massive transfusion protocols to ensure that physiologically optimal combinations of blood products are rapidly available, the period of time required to achieve a specified massive transfusion standard (e.g. a 1:1 or 1:2 ratio of plasma or platelets:red blood cells) has been ignored. To account for the time-varying characteristics of transfusions, we use semiparametric rate models for multivariate recurrent events to estimate blood product ratios. We use latent variables to account for multiple sources of informative censoring (early surgical or endovascular hemorrhage control procedures or death). The major advantage is that the distributions of latent variables and the dependence structure between the multivariate recurrent events and informative censoring need not be specified. Thus, our approach is robust to complex model assumptions. We establish asymptotic properties and evaluate finite sample performance through simulations, and apply the method to data from the PRospective Observational Multicenter Major Trauma Transfusion study.

  17. A multivariate heuristic model for fuzzy time-series forecasting.

    PubMed

    Huarng, Kun-Huang; Yu, Tiffany Hui-Kuang; Hsu, Yu Wei

    2007-08-01

    Fuzzy time-series models have been widely applied due to their ability to handle nonlinear data directly and because no rigid assumptions for the data are needed. In addition, many such models have been shown to provide better forecasting results than their conventional counterparts. However, since most of these models require complicated matrix computations, this paper proposes the adoption of a multivariate heuristic function that can be integrated with univariate fuzzy time-series models into multivariate models. Such a multivariate heuristic function can easily be extended and integrated with various univariate models. Furthermore, the integrated model can handle multiple variables to improve forecasting results and, at the same time, avoid complicated computations due to the inclusion of multiple variables.

  18. Regularly timed events amid chaos

    NASA Astrophysics Data System (ADS)

    Blakely, Jonathan N.; Cooper, Roy M.; Corron, Ned J.

    2015-11-01

    We show rigorously that the solutions of a class of chaotic oscillators are characterized by regularly timed events in which the derivative of the solution is instantaneously zero. The perfect regularity of these events is in stark contrast with the well-known unpredictability of chaos. We explore some consequences of these regularly timed events through experiments using chaotic electronic circuits. First, we show that a feedback loop can be implemented to phase lock the regularly timed events to a periodic external signal. In this arrangement the external signal regulates the timing of the chaotic signal but does not strictly lock its phase. That is, phase slips of the chaotic oscillation persist without disturbing timing of the regular events. Second, we couple the regularly timed events of one chaotic oscillator to those of another. A state of synchronization is observed where the oscillators exhibit synchronized regular events while their chaotic amplitudes and phases evolve independently. Finally, we add additional coupling to synchronize the amplitudes, as well, however in the opposite direction illustrating the independence of the amplitudes from the regularly timed events.

  19. [Anomaly Detection of Multivariate Time Series Based on Riemannian Manifolds].

    PubMed

    Xu, Yonghong; Hou, Xiaoying; Li Shuting; Cui, Jie

    2015-06-01

    Multivariate time series problems widely exist in production and life in the society. Anomaly detection has provided people with a lot of valuable information in financial, hydrological, meteorological fields, and the research areas of earthquake, video surveillance, medicine and others. In order to quickly and efficiently find exceptions in time sequence so that it can be presented in front of people in an intuitive way, we in this study combined the Riemannian manifold with statistical process control charts, based on sliding window, with a description of the covariance matrix as the time sequence, to achieve the multivariate time series of anomaly detection and its visualization. We made MA analog data flow and abnormal electrocardiogram data from MIT-BIH as experimental objects, and verified the anomaly detection method. The results showed that the method was reasonable and effective.

  20. A multivariate time-series approach to marital interaction

    PubMed Central

    Kupfer, Jörg; Brosig, Burkhard; Brähler, Elmar

    2005-01-01

    Time-series analysis (TSA) is frequently used in order to clarify complex structures of mutually interacting panel data. The method helps in understanding how the course of a dependent variable is predicted by independent time-series with no time lag, as well as by previous observations of that dependent variable (autocorrelation) and of independent variables (cross-correlation). The study analyzes the marital interaction of a married couple under clinical conditions over a period of 144 days by means of TSA. The data were collected within a course of couple therapy. The male partner was affected by a severe condition of atopic dermatitis and the woman suffered from bulimia nervosa. Each of the partners completed a mood questionnaire and a body symptom checklist. After the determination of auto- and cross-correlations between and within the parallel data sets, multivariate time-series models were specified. Mutual and individual patterns of emotional reactions explained 14% (skin) and 33% (bulimia) of the total variance in both dependent variables (adj. R², p<0.0001 for the multivariate models). The question was discussed whether multivariate TSA-models represent a suitable approach to the empirical exploration of clinical marital interaction. PMID:19742066

  1. A multivariate time-series approach to marital interaction.

    PubMed

    Kupfer, Jörg; Brosig, Burkhard; Brähler, Elmar

    2005-08-02

    Time-series analysis (TSA) is frequently used in order to clarify complex structures of mutually interacting panel data. The method helps in understanding how the course of a dependent variable is predicted by independent time-series with no time lag, as well as by previous observations of that dependent variable (autocorrelation) and of independent variables (cross-correlation).The study analyzes the marital interaction of a married couple under clinical conditions over a period of 144 days by means of TSA. The data were collected within a course of couple therapy. The male partner was affected by a severe condition of atopic dermatitis and the woman suffered from bulimia nervosa.Each of the partners completed a mood questionnaire and a body symptom checklist. After the determination of auto- and cross-correlations between and within the parallel data sets, multivariate time-series models were specified. Mutual and individual patterns of emotional reactions explained 14% (skin) and 33% (bulimia) of the total variance in both dependent variables (adj. R(2), p<0.0001 for the multivariate models).The question was discussed whether multivariate TSA-models represent a suitable approach to the empirical exploration of clinical marital interaction.

  2. Phylogenetic proximity revealed by neurodevelopmental event timings.

    PubMed

    Nagarajan, Radhakrishnan; Clancy, Barbara

    2008-01-01

    Statistical properties such as distribution and correlation signatures were investigated using a temporal database of common neurodevelopmental events in the three species most frequently used in experimental studies, rat, mouse, and macaque. There was a fine nexus between phylogenetic proximity and empirically derived dates of the occurrences of 40 common events including the neurogenesis of cortical layers and outgrowth milestones of developing axonal projections. Exponential and power-law approximations to the distribution of the events reveal strikingly similar decay patterns in rats and mice when compared to macaques. Subsequent hierarchical clustering of the common event timings also captures phylogenetic proximity, an association further supported by multivariate linear regression data. These preliminary results suggest that statistical analyses of the timing of developmental milestones may offer a novel measure of phylogenetic classifications. This may have added pragmatic value in the specific support it offers for the reliability of rat/mouse comparative modeling, as well as in the broader implications for the potential of meta-analyses using databases assembled from the extensive empirical literature.

  3. The LCLS Timing Event System

    SciTech Connect

    Dusatko, John; Allison, S.; Browne, M.; Krejcik, P.; /SLAC

    2012-07-23

    The Linac Coherent Light Source requires precision timing trigger signals for various accelerator diagnostics and controls at SLAC-NAL. A new timing system has been developed that meets these requirements. This system is based on COTS hardware with a mixture of custom-designed units. An added challenge has been the requirement that the LCLS Timing System must co-exist and 'know' about the existing SLC Timing System. This paper describes the architecture, construction and performance of the LCLS timing event system.

  4. Nonlinear independent component analysis and multivariate time series analysis

    NASA Astrophysics Data System (ADS)

    Storck, Jan; Deco, Gustavo

    1997-02-01

    We derive an information-theory-based unsupervised learning paradigm for nonlinear independent component analysis (NICA) with neural networks. We demonstrate that under the constraint of bounded and invertible output transfer functions the two main goals of unsupervised learning, redundancy reduction and maximization of the transmitted information between input and output (Infomax-principle), are equivalent. No assumptions are made concerning the kind of input and output distributions, i.e. the kind of nonlinearity of correlations. An adapted version of the general NICA network is used for the modeling of multivariate time series by unsupervised learning. Given time series of various observables of a dynamical system, our net learns their evolution in time by extracting statistical dependencies between past and present elements of the time series. Multivariate modeling is obtained by making present value of each time series statistically independent not only from their own past but also from the past of the other series. Therefore, in contrast to univariate methods, the information lying in the couplings between the observables is also used and a detection of higher-order cross correlations is possible. We apply our method to time series of the two-dimensional Hénon map and to experimental time series obtained from the measurements of axial velocities in different locations in weakly turbulent Taylor-Couette flow.

  5. A Method for Comparing Multivariate Time Series with Different Dimensions

    PubMed Central

    Tapinos, Avraam; Mendes, Pedro

    2013-01-01

    In many situations it is desirable to compare dynamical systems based on their behavior. Similarity of behavior often implies similarity of internal mechanisms or dependency on common extrinsic factors. While there are widely used methods for comparing univariate time series, most dynamical systems are characterized by multivariate time series. Yet, comparison of multivariate time series has been limited to cases where they share a common dimensionality. A semi-metric is a distance function that has the properties of non-negativity, symmetry and reflexivity, but not sub-additivity. Here we develop a semi-metric – SMETS – that can be used for comparing groups of time series that may have different dimensions. To demonstrate its utility, the method is applied to dynamic models of biochemical networks and to portfolios of shares. The former is an example of a case where the dependencies between system variables are known, while in the latter the system is treated (and behaves) as a black box. PMID:23393554

  6. Multivariate Bayesian modeling of known and unknown causes of events--an application to biosurveillance.

    PubMed

    Shen, Yanna; Cooper, Gregory F

    2012-09-01

    This paper investigates Bayesian modeling of known and unknown causes of events in the context of disease-outbreak detection. We introduce a multivariate Bayesian approach that models multiple evidential features of every person in the population. This approach models and detects (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A contribution of this paper is that it introduces a multivariate Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has general applicability in domains where the space of known causes is incomplete.

  7. Optimal model-free prediction from multivariate time series

    NASA Astrophysics Data System (ADS)

    Runge, Jakob; Donner, Reik V.; Kurths, Jürgen

    2015-05-01

    Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal preselection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used suboptimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Niño Southern Oscillation.

  8. Optimal model-free prediction from multivariate time series.

    PubMed

    Runge, Jakob; Donner, Reik V; Kurths, Jürgen

    2015-05-01

    Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal preselection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used suboptimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Niño Southern Oscillation.

  9. Fast and Flexible Multivariate Time Series Subsequence Search

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Oza, Nikunj C.; Zhu, Qiang; Srivastava, Ashok N.

    2010-01-01

    Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which often contain several gigabytes of data. Surprisingly, research on MTS search is very limited. Most of the existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two algorithms to solve this problem (1) a List Based Search (LBS) algorithm which uses sorted lists for indexing, and (2) a R*-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences. Both algorithms guarantee that all matching patterns within the specified thresholds will be returned (no false dismissals). The very few false alarms can be removed by a post-processing step. Since our framework is also capable of Univariate Time-Series (UTS) subsequence search, we first demonstrate the efficiency of our algorithms on several UTS datasets previously used in the literature. We follow this up with experiments using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>99%) thus needing actual disk access for only less than 1% of the observations. To the best of our knowledge, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

  10. Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

    PubMed

    Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

    2013-05-01

    Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

  11. F100 multivariable control synthesis program: Evaluation of a multivariable control using a real-time engine simulation

    NASA Technical Reports Server (NTRS)

    Szuch, J. R.; Soeder, J. F.; Seldner, K.; Cwynar, D. S.

    1977-01-01

    The design, evaluation, and testing of a practical, multivariable, linear quadratic regulator control for the F100 turbofan engine were accomplished. NASA evaluation of the multivariable control logic and implementation are covered. The evaluation utilized a real time, hybrid computer simulation of the engine. Results of the evaluation are presented, and recommendations concerning future engine testing of the control are made. Results indicated that the engine testing of the control should be conducted as planned.

  12. Gaining Efficiency via Weighted Estimators for Multivariate Failure Time Data*

    PubMed

    Fan, Jianqing; Zhou, Yong; Cai, Jianwen; Chen, Min

    2009-06-01

    Multivariate failure time data arise frequently in survival analysis. A commonly used technique is the working independence estimator for marginal hazard models. Two natural questions are how to improve the efficiency of the working independence estimator and how to identify the situations under which such an estimator has high statistical efficiency. In this paper, three weighted estimators are proposed based on three different optimal criteria in terms of the asymptotic covariance of weighted estimators. Simplified close-form solutions are found, which always outperform the working independence estimator. We also prove that the working independence estimator has high statistical efficiency, when asymptotic covariance of derivatives of partial log-likelihood functions is nearly exchangeable or diagonal. Simulations are conducted to compare the performance of the weighted estimator and working independence estimator. A data set from Busselton population health surveys is analyzed using the proposed estimators.

  13. Optimizing functional network representation of multivariate time series.

    PubMed

    Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; del Pozo, Francisco; Menasalvas, Ernestina; Boccaletti, Stefano

    2012-01-01

    By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

  14. Optimizing Functional Network Representation of Multivariate Time Series

    NASA Astrophysics Data System (ADS)

    Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco Del; Menasalvas, Ernestina; Boccaletti, Stefano

    2012-09-01

    By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

  15. Algorithms for the analysis of ensemble neural spiking activity using simultaneous-event multivariate point-process models.

    PubMed

    Ba, Demba; Temereanca, Simona; Brown, Emery N

    2014-01-01

    Understanding how ensembles of neurons represent and transmit information in the patterns of their joint spiking activity is a fundamental question in computational neuroscience. At present, analyses of spiking activity from neuronal ensembles are limited because multivariate point process (MPP) models cannot represent simultaneous occurrences of spike events at an arbitrarily small time resolution. Solo recently reported a simultaneous-event multivariate point process (SEMPP) model to correct this key limitation. In this paper, we show how Solo's discrete-time formulation of the SEMPP model can be efficiently fit to ensemble neural spiking activity using a multinomial generalized linear model (mGLM). Unlike existing approximate procedures for fitting the discrete-time SEMPP model, the mGLM is an exact algorithm. The MPP time-rescaling theorem can be used to assess model goodness-of-fit. We also derive a new marked point-process (MkPP) representation of the SEMPP model that leads to new thinning and time-rescaling algorithms for simulating an SEMPP stochastic process. These algorithms are much simpler than multivariate extensions of algorithms for simulating a univariate point process, and could not be arrived at without the MkPP representation. We illustrate the versatility of the SEMPP model by analyzing neural spiking activity from pairs of simultaneously-recorded rat thalamic neurons stimulated by periodic whisker deflections, and by simulating SEMPP data. In the data analysis example, the SEMPP model demonstrates that whisker motion significantly modulates simultaneous spiking activity at the 1 ms time scale and that the stimulus effect is more than one order of magnitude greater for simultaneous activity compared with non-simultaneous activity. Together, the mGLM, the MPP time-rescaling theorem and the MkPP representation of the SEMPP model offer a theoretically sound, practical tool for measuring joint spiking propensity in a neuronal ensemble.

  16. A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series

    PubMed Central

    Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M.; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

    2015-01-01

    Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in

  17. A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series.

    PubMed

    Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

    2015-01-01

    Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in

  18. A Bayesian approach to joint analysis of multivariate longitudinal data and parametric accelerated failure time.

    PubMed

    Luo, Sheng

    2014-02-20

    Impairment caused by Parkinson's disease (PD) is multidimensional (e.g., sensoria, functions, and cognition) and progressive. Its multidimensional nature precludes a single outcome to measure disease progression. Clinical trials of PD use multiple categorical and continuous longitudinal outcomes to assess the treatment effects on overall improvement. A terminal event such as death or dropout can stop the follow-up process. Moreover, the time to the terminal event may be dependent on the multivariate longitudinal measurements. In this article, we consider a joint random-effects model for the correlated outcomes. A multilevel item response theory model is used for the multivariate longitudinal outcomes and a parametric accelerated failure time model is used for the failure time because of the violation of proportional hazard assumption. These two models are linked via random effects. The Bayesian inference via MCMC is implemented in 'BUGS' language. Our proposed method is evaluated by a simulation study and is applied to DATATOP study, a motivating clinical trial to determine if deprenyl slows the progression of PD.

  19. A Framework and Algorithms for Multivariate Time Series Analytics (MTSA): Learning, Monitoring, and Recommendation

    ERIC Educational Resources Information Center

    Ngan, Chun-Kit

    2013-01-01

    Making decisions over multivariate time series is an important topic which has gained significant interest in the past decade. A time series is a sequence of data points which are measured and ordered over uniform time intervals. A multivariate time series is a set of multiple, related time series in a particular domain in which domain experts…

  20. Narrative event boundaries, reading times, and expectation.

    PubMed

    Pettijohn, Kyle A; Radvansky, Gabriel A

    2016-10-01

    During text comprehension, readers create mental representations of the described events, called situation models. When new information is encountered, these models must be updated or new ones created. Consistent with the event indexing model, previous studies have shown that when readers encounter an event shift, reading times often increase. However, such increases are not consistently observed. This paper addresses this inconsistency by examining the extent to which reading-time differences observed at event shifts reflect an unexpectedness in the narrative rather than processes involved in model updating. In two reassessments of prior work, event shifts known to increase reading time were rated as less expected, and expectedness ratings significantly predicted reading time. In three new experiments, participants read stories in which an event shift was or was not foreshadowed, thereby influencing expectedness of the shift. Experiment 1 revealed that readers do not expect event shifts, but foreshadowing eliminates this. Experiment 2 showed that foreshadowing does not affect identification of event shifts. Finally, Experiment 3 found that, although reading times increased when an event shift was not foreshadowed, they were not different from controls when it was. Moreover, responses to memory probes were slower following an event shift regardless of foreshadowing, suggesting that situation model updating had taken place. Overall, the results support the idea that previously observed reading time increases at event shifts reflect, at least in part, a reader's unexpected encounter with a shift rather than an increase in processing effort required to update a situation model.

  1. Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials

    PubMed Central

    Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

    2013-01-01

    Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials. PMID:23853700

  2. Multivariate space - time analysis of PRE-STORM precipitation

    NASA Technical Reports Server (NTRS)

    Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

    1994-01-01

    This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

  3. Multivariate real-time assessment of droughts via copula-based multi-site Hazard Trajectories and Fans

    NASA Astrophysics Data System (ADS)

    Salvadori, G.; De Michele, C.

    2015-07-01

    Droughts, like floods, represent the most dangerous, and costly, water cycle expressions, with huge impacts on society and built environment. Droughts are events occurring over a certain region, lasting several weeks or months, and involving multiple variables: thus, a multivariate, multi-site, approach is most appropriate for their statistical characterization. In this methodological work, hydrological droughts are considered, and a multivariate approach is proposed, by regarding as relevant variables the duration and the average intensity. A multivariate, multi-site, frequency analysis is presented, based on the Theory of Copulas and the joint Survival Kendall's Return Periods, by investigating the historical drought episodes occurred at five main river sections of the Po river (Northern Italy), the most important Italian basin. The tool of Dynamic Return Period is used, and the new concepts of Hazard Trajectories and Fans are introduced, in order to provide useful indications for a valuable multi-site real-time assessment of droughts.

  4. Visual pattern discovery in timed event data

    NASA Astrophysics Data System (ADS)

    Schaefer, Matthias; Wanner, Franz; Mansmann, Florian; Scheible, Christian; Stennett, Verity; Hasselrot, Anders T.; Keim, Daniel A.

    2011-01-01

    Business processes have tremendously changed the way large companies conduct their business: The integration of information systems into the workflows of their employees ensures a high service level and thus high customer satisfaction. One core aspect of business process engineering are events that steer the workflows and trigger internal processes. Strict requirements on interval-scaled temporal patterns, which are common in time series, are thereby released through the ordinal character of such events. It is this additional degree of freedom that opens unexplored possibilities for visualizing event data. In this paper, we present a flexible and novel system to find significant events, event clusters and event patterns. Each event is represented as a small rectangle, which is colored according to categorical, ordinal or intervalscaled metadata. Depending on the analysis task, different layout functions are used to highlight either the ordinal character of the data or temporal correlations. The system has built-in features for ordering customers or event groups according to the similarity of their event sequences, temporal gap alignment and stacking of co-occurring events. Two characteristically different case studies dealing with business process events and news articles demonstrate the capabilities of our system to explore event data.

  5. Detecting unitary events without discretization of time.

    PubMed

    Grün, S; Diesmann, M; Grammont, F; Riehle, A; Aertsen, A

    1999-12-15

    In earlier studies we developed the 'Unitary Events' analysis (Grün S. Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance and Interpretation. Reihe Physik, Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.) to detect the presence of conspicuous spike coincidences in multiple single unit recordings and to evaluate their statistical significance. The method enabled us to study the relation between spike synchronization and behavioral events (Riehle A, Grün S, Diesmann M, Aertsen A. Spike synchronization and rate modulation differentially involved in motor cortical function. Science 1997;278:1950-1953.). There is recent experimental evidence that the timing accuracy of coincident spiking events, which might be relevant for higher brain function, may be in the range of 1-5 ms. To detect coincidences on that time scale, we sectioned the observation interval into short disjunct time slices ('bins'). Unitary Events analysis of this discretized process demonstrated that coincident events can indeed be reliably detected. However, the method looses sensitivity for higher temporal jitter of the events constituting the coincidences (Grün S. Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance and Interpretation. Reihe Physik, Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.). Here we present a new approach, the 'multiple shift' method (MS), which overcomes the need for binning and treats the data in their (original) high time resolution (typically 1 ms, or better). Technically, coincidences are detected by shifting the spike trains against each other over the range of allowed coincidence width and integrating the number of exact coincidences (on the time resolution of the data) over all shifts. We found that the new method enhances the sensitivity for coincidences with temporal jitter. Both methods are outlined and compared on the basis of their analytical description and their application on

  6. Decoupling in linear time-varying multivariable systems

    NASA Technical Reports Server (NTRS)

    Sankaran, V.

    1973-01-01

    The necessary and sufficient conditions for the decoupling of an m-input, m-output, linear time varying dynamical system by state variable feedback is described. The class of feedback matrices which decouple the system are illustrated. Systems which do not satisfy these results are described and systems with disturbances are considered. Some examples are illustrated to clarify the results.

  7. Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

    ERIC Educational Resources Information Center

    Molenaar, Peter C. M.; And Others

    1992-01-01

    The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)

  8. It's T time: A study on the return period of multivariate problems

    NASA Astrophysics Data System (ADS)

    Michailidi, Eleni Maria; Balistrocchi, Matteo; Bacchi, Baldassare

    2016-04-01

    variables: hydrograph's peak flow, volume and shape. Consequently, a multivariate framework is needed for a more realistic view of the matter at hand. In recent years, the application of copula functions has facilitated overcoming the inadequacies of multivariate distributions as the problem is handled from two non-interwinding aspects: the dependence structure of the pair of variables and the marginal distributions. The main objective of this study is to investigate whether it is possible to find, in a multivariate space, a region where all the multivariate events produce 'risk' lower or greater than a fixed mean inter-occurrence of failures of one time every T-years. Preliminary results seem to confirm that it is impossible to obtain uniqueness in the definition.

  9. Tidal Disruption Events Across Cosmic Time

    NASA Astrophysics Data System (ADS)

    Fialkov, Anastasia; Loeb, Abraham

    2017-01-01

    Tidal disruption events (TDEs) of stars by single or binary super-massive black holes illuminate the environment around quiescent black holes in galactic nuclei allowing to probe dorment black holes. We predict the TDE rates expected to be detected by next-generation X-ray surveys. We include events sourced by both single and binary super-massive black holes assuming that 10% of TDEs lead to the formation of relativistic jets and are therefore observable to higher redshifts. Assigning the Eddington luminosity to each event, we show that if the occupation fraction of intermediate black holes is high, more than 90% of the brightest TDE might be associated with merging black holes which are potential sources for eLISA. Next generation telescopes with improved sensitivities should probe dim local TDE events as well as bright events at high redshifts. We show that an instrument which is 50 times more sensitive than the Swift Burst Alert Telescope (BAT) is expected to trigger ~10 times more events than BAT. Majority of these events originate at low redshifts (z<0.5) if the occupation fraction of IMBHs is high and at high-redshift (z>2) if it is low.

  10. Discrete Events as Units of Perceived Time

    ERIC Educational Resources Information Center

    Liverence, Brandon M.; Scholl, Brian J.

    2012-01-01

    In visual images, we perceive both space (as a continuous visual medium) and objects (that inhabit space). Similarly, in dynamic visual experience, we perceive both continuous time and discrete events. What is the relationship between these units of experience? The most intuitive answer may be similar to the spatial case: time is perceived as an…

  11. Globally disruptive events show predictable timing patterns

    NASA Astrophysics Data System (ADS)

    Gillman, Michael P.; Erenler, Hilary E.

    2017-01-01

    Globally disruptive events include asteroid/comet impacts, large igneous provinces and glaciations, all of which have been considered as contributors to mass extinctions. Understanding the overall relationship between the timings of the largest extinctions and their potential proximal causes remains one of science's great unsolved mysteries. Cycles of about 60 Myr in both fossil diversity and environmental data suggest external drivers such as the passage of the Solar System through the galactic plane. While cyclic phenomena are recognized statistically, a lack of coherent mechanisms and a failure to link key events has hampered wider acceptance of multi-million year periodicity and its relevance to earth science and evolution. The generation of a robust predictive model of timings, with a clear plausible primary mechanism, would signal a paradigm shift. Here, we present a model of the timings of globally disruptive events and a possible explanation of their ultimate cause. The proposed model is a symmetrical pattern of 63 Myr sequences around a central value, interpreted as the occurrence of events along, and parallel to, the galactic midplane. The symmetry is consistent with multiple dark matter disks, aligned parallel to the midplane. One implication of the precise pattern of timings and the underlying physical model is the ability to predict future events, such as a major extinction in 1-2 Myr.

  12. Granger Causality in Multivariate Time Series Using a Time-Ordered Restricted Vector Autoregressive Model

    NASA Astrophysics Data System (ADS)

    Siggiridou, Elsa; Kugiumtzis, Dimitris

    2016-04-01

    Granger causality has been used for the investigation of the inter-dependence structure of the underlying systems of multi-variate time series. In particular, the direct causal effects are commonly estimated by the conditional Granger causality index (CGCI). In the presence of many observed variables and relatively short time series, CGCI may fail because it is based on vector autoregressive models (VAR) involving a large number of coefficients to be estimated. In this work, the VAR is restricted by a scheme that modifies the recently developed method of backward-in-time selection (BTS) of the lagged variables and the CGCI is combined with BTS. Further, the proposed approach is compared favorably to other restricted VAR representations, such as the top-down strategy, the bottom-up strategy, and the least absolute shrinkage and selection operator (LASSO), in terms of sensitivity and specificity of CGCI. This is shown by using simulations of linear and nonlinear, low and high-dimensional systems and different time series lengths. For nonlinear systems, CGCI from the restricted VAR representations are compared with analogous nonlinear causality indices. Further, CGCI in conjunction with BTS and other restricted VAR representations is applied to multi-channel scalp electroencephalogram (EEG) recordings of epileptic patients containing epileptiform discharges. CGCI on the restricted VAR, and BTS in particular, could track the changes in brain connectivity before, during and after epileptiform discharges, which was not possible using the full VAR representation.

  13. A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series

    ERIC Educational Resources Information Center

    Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.

    2011-01-01

    Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…

  14. A Multivariate Model for the Meta-Analysis of Study Level Survival Data at Multiple Times

    ERIC Educational Resources Information Center

    Jackson, Dan; Rollins, Katie; Coughlin, Patrick

    2014-01-01

    Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

  15. Learning a Mahalanobis Distance-Based Dynamic Time Warping Measure for Multivariate Time Series Classification.

    PubMed

    Mei, Jiangyuan; Liu, Meizhu; Wang, Yuan-Fang; Gao, Huijun

    2016-06-01

    Multivariate time series (MTS) datasets broadly exist in numerous fields, including health care, multimedia, finance, and biometrics. How to classify MTS accurately has become a hot research topic since it is an important element in many computer vision and pattern recognition applications. In this paper, we propose a Mahalanobis distance-based dynamic time warping (DTW) measure for MTS classification. The Mahalanobis distance builds an accurate relationship between each variable and its corresponding category. It is utilized to calculate the local distance between vectors in MTS. Then we use DTW to align those MTS which are out of synchronization or with different lengths. After that, how to learn an accurate Mahalanobis distance function becomes another key problem. This paper establishes a LogDet divergence-based metric learning with triplet constraint model which can learn Mahalanobis matrix with high precision and robustness. Furthermore, the proposed method is applied on nine MTS datasets selected from the University of California, Irvine machine learning repository and Robert T. Olszewski's homepage, and the results demonstrate the improved performance of the proposed approach.

  16. Reinforcement genetic approach to coefficient estimation for multivariable nonlinear discrete-time dynamical systems

    NASA Astrophysics Data System (ADS)

    Chang, Wei-Der; Yan, Jun-Juh

    2006-10-01

    In this paper, we propose a novel genetic algorithm (GA) with a multi-crossover fashion to estimate the associated coefficients for a class of nonlinear discrete-time multivariable dynamical systems. Unlike the traditional crossover method of using two chromosomes, the proposed method uses three chromosomes to achieve a crossover. According to the adjusting direction by crossing three chromosomes, more excellent offspring can be produced. To solve the identification problem of multivariable nonlinear discrete-time systems, each of estimated system coefficients represents a gene, and a collection of genes is referred to as a chromosome in the view of GA. The chromosomes in the population are then evolved using the proposed multi-crossover method. An illustrative example of multivariable nonlinear systems is given to demonstrate the effectiveness, as compared with the traditional crossover method, of the proposed method.

  17. NavyTime: Event and Time Ordering from Raw Text

    DTIC Science & Technology

    2013-06-01

    completely labeled graph of events and times, it is not about true extraction, but matching human la- beling decisions that were constrained by time and...relation ID and la- beling . Results are shown in Table 3. Our system ranked 2nd of 4 systems. Our best performing setup uses trained classi- fiers for

  18. Multivariable Model for Time to First Treatment in Patients With Chronic Lymphocytic Leukemia

    PubMed Central

    Wierda, William G.; O'Brien, Susan; Wang, Xuemei; Faderl, Stefan; Ferrajoli, Alessandra; Do, Kim-Anh; Garcia-Manero, Guillermo; Cortes, Jorge; Thomas, Deborah; Koller, Charles A.; Burger, Jan A.; Lerner, Susan; Schlette, Ellen; Abruzzo, Lynne; Kantarjian, Hagop M.; Keating, Michael J.

    2011-01-01

    Purpose The clinical course for patients with chronic lymphocytic leukemia (CLL) is diverse; some patients have indolent disease, never needing treatment, whereas others have aggressive disease requiring early treatment. We continue to use criteria for active disease to initiate therapy. Multivariable analysis was performed to identify prognostic factors independently associated with time to first treatment for patients with CLL. Patients and Methods Traditional laboratory, clinical prognostic, and newer prognostic factors such as fluorescent in situ hybridization (FISH), IGHV mutation status, and ZAP-70 expression evaluated at first patient visit to MD Anderson Cancer Center were correlated by multivariable analysis with time to first treatment. This multivariable model was used to develop a nomogram—a weighted tool to calculate 2- and 4-year probability of treatment and estimate median time to first treatment. Results There were 930 previously untreated patients who had traditional and new prognostic factors evaluated; they did not have active CLL requiring initiation of treatment within 3 months of first visit and were observed for time to first treatment. The following were independently associated with shorter time to first treatment: three involved lymph node sites, increased size of cervical lymph nodes, presence of 17p deletion or 11q deletion by FISH, increased serum lactate dehydrogenase, and unmutated IGHV mutation status. Conclusion We developed a multivariable model that incorporates traditional and newer prognostic factors to identify patients at high risk for progression to treatment. This model may be useful to identify patients for early interventional trials. PMID:21969505

  19. Analyzing Multiple Multivariate Time Series Data Using Multilevel Dynamic Factor Models.

    PubMed

    Song, Hairong; Zhang, Zhiyong

    2014-01-01

    Multivariate time series data offer researchers opportunities to study dynamics of various systems in social and behavioral sciences. Dynamic factor model (DFM), as an idiographic approach for studying intraindividual variability and dynamics, has typically been applied to time series data obtained from a single unit. When multivariate time series data are collected from multiple units, how to synchronize dynamical information becomes a silent issue. To address this issue, the current study presented a multilevel dynamic factor model (MDFM) that analyzes multiple multivariate time series in multilevel SEM frameworks. MDFM not only disentangles within- and between-person variability but also models dynamics of the intraindividual processes. To illustrate the uses of MDFMs, we applied lag0, lag1, and lag2 MDFMs to empirical data on affect collected from 205 dating couples who had at least 50 consecutive days of observations. We also considered a model extension where the dynamical coefficients were allowed to be randomly varying in the population. The empirical analysis yielded interesting findings regarding affect regulation and coregulation within couples, demonstrating promising uses of MDFMs in analyzing multiple multivariate time series. In the end, we discussed a number of methodological issues in the applications of MDFMs and pointed out possible directions for future research.

  20. Comparison of procedures to assess non-linear and time-varying effects in multivariable models for survival data.

    PubMed

    Buchholz, Anika; Sauerbrei, Willi

    2011-03-01

    The focus of many medical applications is to model the impact of several factors on time to an event. A standard approach for such analyses is the Cox proportional hazards model. It assumes that the factors act linearly on the log hazard function (linearity assumption) and that their effects are constant over time (proportional hazards (PH) assumption). Variable selection is often required to specify a more parsimonious model aiming to include only variables with an influence on the outcome. As follow-up increases the effect of a variable often gets weaker, which means that it varies in time. However, spurious time-varying effects may also be introduced by mismodelling other parts of the multivariable model, such as omission of an important covariate or an incorrect functional form of a continuous covariate. These issues interact. To check whether the effect of a variable varies in time several tests for non-PH have been proposed. However, they are not sufficient to derive a model, as appropriate modelling of the shape of time-varying effects is required. In three examples we will compare five recently published strategies to assess whether and how the effects of covariates from a multivariable model vary in time. For practical use we will give some recommendations.

  1. Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

    ERIC Educational Resources Information Center

    Molenaar, Peter C. M.; Nesselroade, John R.

    2001-01-01

    Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

  2. An Investigation of Multivariate Adaptive Regression Splines for Modeling and Analysis of Univariate and Semi-Multivariate Time Series Systems

    DTIC Science & Technology

    1991-09-01

    GRAFSTAT from IBM Research; I am grateful to Dr . Peter Welch for supplying GRAFSTAT. To P.A.W. Lewis, Thank you for your support, confidence and...34Multivariate Adaptive Regression Splines", Annals of Statistics, v. 19, no. 2, pp. 1-142, 1991. Geib , A., Applied Optimal Estimation, M.I.T. Press, Cambridge

  3. Non-parametric estimation of gap time survival functions for ordered multivariate failure time data.

    PubMed

    Schaubel, Douglas E; Cai, Jianwen

    2004-06-30

    Times between sequentially ordered events (gap times) are often of interest in biomedical studies. For example, in a cancer study, the gap times from incidence-to-remission and remission-to-recurrence may be examined. Such data are usually subject to right censoring, and within-subject failure times are generally not independent. Statistical challenges in the analysis of the second and subsequent gap times include induced dependent censoring and non-identifiability of the marginal distributions. We propose a non-parametric method for constructing one-sample estimators of conditional gap-time specific survival functions. The estimators are uniformly consistent and, upon standardization, converge weakly to a zero-mean Gaussian process, with a covariance function which can be consistently estimated. Simulation studies reveal that the asymptotic approximations are appropriate for finite samples. Methods for confidence bands are provided. The proposed methods are illustrated on a renal failure data set, where the probabilities of transplant wait-listing and kidney transplantation are of interest.

  4. Multivariate prediction of major adverse cardiac events after 9914 percutaneous coronary interventions in the north west of England

    PubMed Central

    Grayson, A D; Moore, R K; Jackson, M; Rathore, S; Sastry, S; Gray, T P; Schofield, I; Chauhan, A; Ordoubadi, F F; Prendergast, B; Stables, R H

    2006-01-01

    Objective To develop a multivariate prediction model for major adverse cardiac events (MACE) after percutaneous coronary interventions (PCIs) by using the North West Quality Improvement Programme in Cardiac Interventions (NWQIP) PCI Registry. Setting All NHS centres undertaking adult PCIs in north west England. Methods Retrospective analysis of prospectively collected data on 9914 consecutive patients undergoing adult PCI between 1 August 2001 and 31 December 2003. A multivariate logistic regression analysis was undertaken, with the forward stepwise technique, to identify independent risk factors for MACE. The area under the receiver operating characteristic (ROC) curve and the Hosmer‐Lemeshow goodness of fit statistic were calculated to assess the performance and calibration of the model, respectively. The statistical model was internally validated by using the technique of bootstrap resampling. Main outcome measures MACE, which were in‐hospital mortality, Q wave myocardial infarction, emergency coronary artery bypass graft surgery, and cerebrovascular accidents. Results Independent variables identified with an increased risk of developing MACE were advanced age, female sex, cerebrovascular disease, cardiogenic shock, priority, and treatment of the left main stem or graft lesions during PCI. The ROC curve for the predicted probability of MACE was 0.76, indicating a good discrimination power. The prediction equation was well calibrated, predicting well at all levels of risk. Bootstrapping showed that estimates were stable. Conclusions A contemporaneous multivariate prediction model for MACE after PCI was developed. The NWQIP tool allows calculation of the risk of MACE permitting meaningful risk adjusted comparisons of performance between hospitals and operators. PMID:16159983

  5. Multivariate spatial analysis of a heavy rain event in a densely populated delta city

    NASA Astrophysics Data System (ADS)

    Gaitan, Santiago; ten Veldhuis, Marie-claire; Bruni, Guenda; van de Giesen, Nick

    2014-05-01

    Delta cities account for half of the world's population and host key infrastructure and services for the global economic growth. Due to the characteristic geography of delta areas, these cities face high vulnerability to extreme weather and pluvial flooding risks, that are expected to increase as climate change drives heavier rain events. Besides, delta cities are subjected to fast urban densification processes that progressively make them more vulnerable to pluvial flooding. Delta cities need to be adapted to better cope with this threat. The mechanism leading to damage after heavy rains is not completely understood. For instance, current research has shown that rain intensities and volumes can only partially explain the occurrence and localization of rain-related insurance claims (Spekkers et al., 2013). The goal of this paper is to provide further insights into spatial characteristics of the urban environment that can significantly be linked to pluvial-related flooding impacts. To that end, a study-case has been selected: on October 12 to 14 2013, a heavy rain event triggered pluvial floods in Rotterdam, a densely populated city which is undergoing multiple climate adaptation efforts and is located in the Meuse river Delta. While the average yearly precipitation in this city is around 800 mm, local rain gauge measurements ranged from aprox. 60 to 130 mm just during these three days. More than 600 citizens' telephonic complaints reported impacts related to rainfall. The registry of those complaints, which comprises around 300 calls made to the municipality and another 300 to the fire brigade, was made available for research. Other accessible information about this city includes a series of rainfall measurements with up to 1 min time-step at 7 different locations around the city, ground-based radar rainfall data (1 Km^2 spatial resolution and 5 min time-step), a digital elevation model (50 cm of horizontal resolution), a model of overland-flow paths, cadastral

  6. Multivariate time series modeling of short-term system scale irrigation demand

    NASA Astrophysics Data System (ADS)

    Perera, Kushan C.; Western, Andrew W.; George, Biju; Nawarathna, Bandara

    2015-12-01

    Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi, OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1-5 days ahead daily IDCGi, ASP and IDCGi, OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi, OTR across 5 command areas were ranged 0.98-0.78. These models were capable of generating skillful forecasts (MSSS ⩾ 0.5 and ACC ⩾ 0.6) of IDCGi, ASP and IDCGi, OTR for all 5 lead days and IDCGi, ASP and IDCGi, OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi, OTR forecasts have improved the operators' ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers' face, such as

  7. Development and validation of multivariable predictive model for thromboembolic events in lymphoma patients.

    PubMed

    Antic, Darko; Milic, Natasa; Nikolovski, Srdjan; Todorovic, Milena; Bila, Jelena; Djurdjevic, Predrag; Andjelic, Bosko; Djurasinovic, Vladislava; Sretenovic, Aleksandra; Vukovic, Vojin; Jelicic, Jelena; Hayman, Suzanne; Mihaljevic, Biljana

    2016-10-01

    Lymphoma patients are at increased risk of thromboembolic events but thromboprophylaxis in these patients is largely underused. We sought to develop and validate a simple model, based on individual clinical and laboratory patient characteristics that would designate lymphoma patients at risk for thromboembolic event. The study population included 1,820 lymphoma patients who were treated in the Lymphoma Departments at the Clinics of Hematology, Clinical Center of Serbia and Clinical Center Kragujevac. The model was developed using data from a derivation cohort (n = 1,236), and further assessed in the validation cohort (n = 584). Sixty-five patients (5.3%) in the derivation cohort and 34 (5.8%) patients in the validation cohort developed thromboembolic events. The variables independently associated with risk for thromboembolism were: previous venous and/or arterial events, mediastinal involvement, BMI>30 kg/m(2) , reduced mobility, extranodal localization, development of neutropenia and hemoglobin level < 100g/L. Based on the risk model score, the population was divided into the following risk categories: low (score 0-1), intermediate (score 2-3), and high (score >3). For patients classified at risk (intermediate and high-risk scores), the model produced negative predictive value of 98.5%, positive predictive value of 25.1%, sensitivity of 75.4%, and specificity of 87.5%. A high-risk score had positive predictive value of 65.2%. The diagnostic performance measures retained similar values in the validation cohort. Developed prognostic Thrombosis Lymphoma - ThroLy score is more specific for lymphoma patients than any other available score targeting thrombosis in cancer patients. Am. J. Hematol. 91:1014-1019, 2016. © 2016 Wiley Periodicals, Inc.

  8. Applying the multivariate time-rescaling theorem to neural population models

    PubMed Central

    Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

    2011-01-01

    Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

  9. A multivariate based event detection method and performance comparison with two baseline methods.

    PubMed

    Liu, Shuming; Smith, Kate; Che, Han

    2015-09-01

    Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate.

  10. Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

    NASA Astrophysics Data System (ADS)

    zhang, L.

    2011-12-01

    Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be

  11. Supporting the Process of Exploring and Interpreting Space–Time Multivariate Patterns: The Visual Inquiry Toolkit

    PubMed Central

    Chen, Jin; MacEachren, Alan M.; Guo, Diansheng

    2009-01-01

    While many data sets carry geographic and temporal references, our ability to analyze these datasets lags behind our ability to collect them because of the challenges posed by both data complexity and tool scalability issues. This study develops a visual analytics approach that leverages human expertise with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate data sets. We develop and apply a variety of methods for data clustering, pattern searching, information visualization, and synthesis. By combining both human and machine strengths, this approach has a better chance to discover novel, relevant, and potentially useful information that is difficult to detect by any of the methods used in isolation. We demonstrate the effectiveness of the approach by applying the Visual Inquiry Toolkit we developed to analyze a data set containing geographically referenced, time-varying and multivariate data for U.S. technology industries. PMID:19960096

  12. Constructing networks from a dynamical system perspective for multivariate nonlinear time series.

    PubMed

    Nakamura, Tomomichi; Tanizawa, Toshihiro; Small, Michael

    2016-03-01

    We describe a method for constructing networks for multivariate nonlinear time series. We approach the interaction between the various scalar time series from a deterministic dynamical system perspective and provide a generic and algorithmic test for whether the interaction between two measured time series is statistically significant. The method can be applied even when the data exhibit no obvious qualitative similarity: a situation in which the naive method utilizing the cross correlation function directly cannot correctly identify connectivity. To establish the connectivity between nodes we apply the previously proposed small-shuffle surrogate (SSS) method, which can investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) between two data sets from the viewpoint of deterministic dynamical systems. The procedure to construct networks based on this idea is composed of three steps: (i) each time series is considered as a basic node of a network, (ii) the SSS method is applied to verify the connectivity between each pair of time series taken from the whole multivariate time series, and (iii) the pair of nodes is connected with an undirected edge when the null hypothesis cannot be rejected. The network constructed by the proposed method indicates the intrinsic (essential) connectivity of the elements included in the system or the underlying (assumed) system. The method is demonstrated for numerical data sets generated by known systems and applied to several experimental time series.

  13. A Visualization System for Space-Time and Multivariate Patterns (VIS-STAMP)

    PubMed Central

    Guo, Diansheng; Chen, Jin; MacEachren, Alan M.; Liao, Ke

    2011-01-01

    The research reported here integrates computational, visual, and cartographic methods to develop a geovisual analytic approach for exploring and understanding spatio-temporal and multivariate patterns. The developed methodology and tools can help analysts investigate complex patterns across multivariate, spatial, and temporal dimensions via clustering, sorting, and visualization. Specifically, the approach involves a self-organizing map, a parallel coordinate plot, several forms of reorderable matrices (including several ordering methods), a geographic small multiple display, and a 2-dimensional cartographic color design method. The coupling among these methods leverages their independent strengths and facilitates a visual exploration of patterns that are difficult to discover otherwise. The visualization system we developed supports overview of complex patterns and, through a variety of interactions, enables users to focus on specific patterns and examine detailed views. We demonstrate the system with an application to the IEEE InfoVis 2005 Contest data set, which contains time-varying, geographically referenced, and multivariate data for technology companies in the US. PMID:17073369

  14. Evaluation of an F100 multivariable control using a real-time engine simulation

    NASA Technical Reports Server (NTRS)

    Szuch, J. R.; Soeder, J. F.; Skira, C.

    1977-01-01

    The control evaluated has been designed for the F100-PW-100 turbofan engine. The F100 engine represents the current state-of-the-art in aircraft gas turbine technology. The control makes use of a multivariable, linear quadratic regulator. The evaluation procedure employed utilized a real-time hybrid computer simulation of the F100 engine and an implementation of the control logic on the NASA LeRC digital computer/controller. The results of the evaluation indicated that the control logic and its implementation will be capable of controlling the engine throughout its operating range.

  15. A multivariate model for the meta-analysis of study level survival data at multiple times.

    PubMed

    Jackson, Dan; Rollins, Katie; Coughlin, Patrick

    2014-09-01

    Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and we compare the results to those obtained from standard methodologies. Our method uses exact binomial within-study distributions and enforces the constraints that both the study specific and the overall mortality rates must not decrease over time. We directly model the probabilities of mortality at each time point, which are the quantities of primary clinical interest. We also present I(2) statistics that quantify the impact of the between-study heterogeneity, which is very considerable in our data set.

  16. Multivariable time series prediction for the icing process on overhead power transmission line.

    PubMed

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

  17. Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

    PubMed Central

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  18. [Psychosocial predictors of metabolic instability in brittle diabetes--a multivariate time series analysis].

    PubMed

    Brosig, B; Leweke, F; Milch, W; Eckhard, M; Reimer, C

    2001-06-01

    The term "brittle diabetes" denotes the unstable course of an insulin-dependent diabetes characterised by frequent hypo- or hyperglycaemic crises. The aim of this study is to demonstrate empirically how psychosocial parameters interact with metabolic instability in a paradigmatic case of juvenile brittle diabetes. By means of a structured diary study, blood sugar values, moods (SAM), body symptoms (GBB), the daily hustle and hassle, helping therapeutic alliance (HAQ) and the aspects of setting were registered. Resulting time series (112 days each) were ARIMA-analysed by a multivariate approach. It could be shown that the mean variance of daily blood sugar values as an indicator of brittleness was predicted by moods, body complaints and by a family session as setting factor (p < 0.05, for corresponding predictors). Feelings of dominance preceded an increase of blood sugar variance, whereas depressive moods, anger and body symptoms were associated with metabolic instability. A family therapy session also resulted in an increase of the mean blood sugar variance. The model accounted for almost 30% of the total variance of the dependent variable (R-square-adjusted, p < 0.0001). The potential of multivariate time-series as a means to demonstrate psychosomatic interrelations is discussed. We believe that the results may also contribute to an empirically rooted understanding of psychodynamic processes in psychosomatoses.

  19. Discrimination of coupling structures using causality networks from multivariate time series

    NASA Astrophysics Data System (ADS)

    Koutlis, Christos; Kugiumtzis, Dimitris

    2016-09-01

    Measures of Granger causality on multivariate time series have been used to form the so-called causality networks. A causality network represents the interdependence structure of the underlying dynamical system or coupled dynamical systems, and its properties are quantified by network indices. In this work, it is investigated whether network indices on networks generated by an appropriate Granger causality measure can discriminate different coupling structures. The information based Granger causality measure of partial mutual information from mixed embedding (PMIME) is used to form causality networks, and a large number of network indices are ranked according to their ability to discriminate the different coupling structures. The evaluation of the network indices is done with a simulation study based on two dynamical systems, the coupled Mackey-Glass delay differential equations and the neural mass model, both of 25 variables, and three prototypes of coupling structures, i.e., random, small-world, and scale-free. It is concluded that the setting of PMIME combined with a network index attains high level of discrimination of the coupling structures solely on the basis of the observed multivariate time series. This approach is demonstrated to identify epileptic seizures emerging during electroencephalogram recordings.

  20. Investigation of time and weather effects on crash types using full Bayesian multivariate Poisson lognormal models.

    PubMed

    El-Basyouny, Karim; Barua, Sudip; Islam, Md Tazul

    2014-12-01

    Previous research shows that various weather elements have significant effects on crash occurrence and risk; however, little is known about how these elements affect different crash types. Consequently, this study investigates the impact of weather elements and sudden extreme snow or rain weather changes on crash type. Multivariate models were used for seven crash types using five years of daily weather and crash data collected for the entire City of Edmonton. In addition, the yearly trend and random variation of parameters across the years were analyzed by using four different modeling formulations. The proposed models were estimated in a full Bayesian context via Markov Chain Monte Carlo simulation. The multivariate Poisson lognormal model with yearly varying coefficients provided the best fit for the data according to Deviance Information Criteria. Overall, results showed that temperature and snowfall were statistically significant with intuitive signs (crashes decrease with increasing temperature; crashes increase as snowfall intensity increases) for all crash types, while rainfall was mostly insignificant. Previous snow showed mixed results, being statistically significant and positively related to certain crash types, while negatively related or insignificant in other cases. Maximum wind gust speed was found mostly insignificant with a few exceptions that were positively related to crash type. Major snow or rain events following a dry weather condition were highly significant and positively related to three crash types: Follow-Too-Close, Stop-Sign-Violation, and Ran-Off-Road crashes. The day-of-the-week dummy variables were statistically significant, indicating a possible weekly variation in exposure. Transportation authorities might use the above results to improve road safety by providing drivers with information regarding the risk of certain crash types for a particular weather condition.

  1. Multivariate weather regimes in the Mediterranean, a perspective to increase Heavy Precipitating Events predictability using medium range ensemble forecasting?

    NASA Astrophysics Data System (ADS)

    Joly, B.; Arbogast, P.; Descamps, L.; Labadie, C.

    2009-09-01

    South-eastern France is a region subject to very Heavy Precipitating Events (HPEs). They have been identified to often occur in some Large Scale recurrent Circulations (LSCs) which may play a significant role in triggering or maintaining the extreme convective processes (Nuissier et al., 2007). A previous study (within the French national CYPRIM Project, ACI-INSU) based on the classification of the geopotential height for a thousand rainy days extracted from the French southeastern regional raingauges network showed the existence of two different patterns associated with the HPEs and the importance of the coincidence of low-level ingredients. However, by design these patterns cannot be considered as objective features describing the whole large scale variability as weather regimes methods can do. Then, we intend to generalize these results by investigating a classification based on a multivariate atmospheric state vector rather than on a single parameter (the geopotential height at 500 hPa). This is also motivated by previous studies (Vautard et al. 1988, Vautard 1990) which have shown that weather regimes are linked with the low frequency variability sources and then could set up a framework to explain nonlinear transitions from low frequency to high variability events. We build a pseudo-state vector as a 25 parameters vector, the parameters being selected as the most correlated with daily rainfall. The number of classes is chosen using an hybrid method combining dynamical and hierarchical clustering. It leads to a 8-classes classification. Then the connections between the clusters and the HPEs shows that two clusters concentrate more than 70% of the HPEs. The composite analysis at different levels shows a good agreement with the CYPRIM patterns. Furthermore, a simple correlation analysis to the centroids of these two clusters shows they significantly discriminate the HPEs compared to the non-HPEs part of the data. Thus we explore the opportunity to determine

  2. Ecological prediction with nonlinear multivariate time-frequency functional data models

    USGS Publications Warehouse

    Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

    2013-01-01

    Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

  3. Reconstructing causal pathways and optimal prediction from multivariate time series using the Tigramite package

    NASA Astrophysics Data System (ADS)

    Runge, Jakob

    2016-04-01

    Causal reconstruction techniques from multivariate time series have become a popular approach to analyze interactions in complex systems such as the Earth. These approaches allow to exclude effects of common drivers and indirect influences. Practical applications are, however, especially challenging if nonlinear interactions are taken into account and for typically strongly autocorrelated climate time series. Here we discuss a new reconstruction approach with accompanying software package (Tigramite) and focus on two applications: (1) Information or perturbation transfer along causal pathways. This method allows to detect and quantify which intermediate nodes are important mediators of an interaction mechanism and is illustrated to disentangle pathways of atmospheric flow over Europe and for the ENSO - Indian Monsoon interaction mechanism. (2) A nonlinear model-free prediction technique that efficiently utilizes causal drivers and can be shown to yield information-theoretically optimal predictors avoiding over-fitting. The performance of this framework is illustrated on a climatological index of El Nino Southern Oscillation. References: Runge, J. (2015). Quantifying information transfer and mediation along causal pathways in complex systems. Phys. Rev. E, 92(6), 062829. doi:10.1103/PhysRevE.92.062829 Runge, J., Donner, R. V., & Kurths, J. (2015). Optimal model-free prediction from multivariate time series. Phys. Rev. E, 91(5), 052909. doi:10.1103/PhysRevE.91.052909 Runge, J., Petoukhov, V., Donges, J. F., Hlinka, J., Jajcay, N., Vejmelka, M., … Kurths, J. (2015). Identifying causal gateways and mediators in complex spatio-temporal systems. Nature Communications, 6, 8502. doi:10.1038/ncomms9502

  4. Reconstructing the times of past and future personal events.

    PubMed

    Ben Malek, Hédi; Berna, Fabrice; D'Argembeau, Arnaud

    2017-04-11

    Humans have the remarkable ability to mentally travel through past and future times. However, while memory for the times of past events has been much investigated, little is known about how imagined future events are temporally located. Using a think-aloud protocol, we found that the temporal location of past and future events is rarely directly accessed, but instead mostly relies on reconstructive and inferential strategies. References to lifetime periods and factual knowledge (about the self, others, and the world) were most frequently used to determine the temporal location of both past and future events. Event details (e.g., places, persons, or weather conditions) were also used, but mainly for past events. Finally, the results showed that events whose temporal location was directly accessed were judged more important for personal goals. Together, these findings shed new light on the mechanisms involved in locating personal events in past and future times.

  5. Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

    NASA Astrophysics Data System (ADS)

    Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

    2016-03-01

    A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

  6. Circuit for measuring time differences among events

    DOEpatents

    Romrell, Delwin M.

    1977-01-01

    An electronic circuit has a plurality of input terminals. Application of a first input signal to any one of the terminals initiates a timing sequence. Later inputs to the same terminal are ignored but a later input to any other terminal of the plurality generates a signal which can be used to measure the time difference between the later input and the first input signal. Also, such time differences may be measured between the first input signal and an input signal to any other terminal of the plurality or the circuit may be reset at any time by an external reset signal.

  7. Denoising and Multivariate Analysis of Time-Of-Flight SIMS Images

    SciTech Connect

    Wickes, Bronwyn; Kim, Y.; Castner, David G.

    2003-08-30

    Time-of-flight SIMS (ToF-SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF-SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF-SIMS image data. Three established denoising algorithms down-binning, boxcar and wavelet filtering were applied to ToF-SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component

  8. Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

    NASA Astrophysics Data System (ADS)

    Gu, Huaying; Liu, Zhixue; Weng, Yingliang

    2017-04-01

    The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

  9. Multivariate Analyses of Small Theropod Dinosaur Teeth and Implications for Paleoecological Turnover through Time

    PubMed Central

    Larson, Derek W.; Currie, Philip J.

    2013-01-01

    Isolated small theropod teeth are abundant in vertebrate microfossil assemblages, and are frequently used in studies of species diversity in ancient ecosystems. However, determining the taxonomic affinities of these teeth is problematic due to an absence of associated diagnostic skeletal material. Species such as Dromaeosaurus albertensis, Richardoestesia gilmorei, and Saurornitholestes langstoni are known from skeletal remains that have been recovered exclusively from the Dinosaur Park Formation (Campanian). It is therefore likely that teeth from different formations widely disparate in age or geographic position are not referable to these species. Tooth taxa without any associated skeletal material, such as Paronychodon lacustris and Richardoestesia isosceles, have also been identified from multiple localities of disparate ages throughout the Late Cretaceous. To address this problem, a dataset of measurements of 1183 small theropod teeth (the most specimen-rich theropod tooth dataset ever constructed) from North America ranging in age from Santonian through Maastrichtian were analyzed using multivariate statistical methods: canonical variate analysis, pairwise discriminant function analysis, and multivariate analysis of variance. The results indicate that teeth referred to the same taxon from different formations are often quantitatively distinct. In contrast, isolated teeth found in time equivalent formations are not quantitatively distinguishable from each other. These results support the hypothesis that small theropod taxa, like other dinosaurs in the Late Cretaceous, tend to be exclusive to discrete host formations. The methods outlined have great potential for future studies of isolated teeth worldwide, and may be the most useful non-destructive technique known of extracting the most data possible from isolated and fragmentary specimens. The ability to accurately assess species diversity and turnover through time based on isolated teeth will help illuminate

  10. [Near infrared spectroscopy and multivariate statistical process analysis for real-time monitoring of production process].

    PubMed

    Wang, Yi; Ma, Xiang; Wen, Ya-Dong; Zou, Quan; Wang, Jun; Tu, Jia-Run; Cai, Wen-Sheng; Shao, Xue-Guang

    2013-05-01

    Near infrared diffusive reflectance spectroscopy has been applied in on-site or on-line analysis due to its characteristics of fastness, non-destruction and the feasibility for real complex sample analysis. The present work reported a real-time monitoring method for industrial production by using near infrared spectroscopic technique and multivariate statistical process analysis. In the method, the real-time near infrared spectra of the materials are collected on the production line, and then the evaluation of the production process can be achieved by a statistic Hotelling T2 calculated with the established model. In this work, principal component analysis (PCA) is adopted for building the model, and the statistic is calculated by projecting the real-time spectra onto the PCA model. With an application of the method in a practical production, it was demonstrated that a real-time evaluation of the variations in the production can be realized by investigating the changes in the statistic, and the comparison of the products in different batches can be achieved by further statistics of the statistic. Therefore, the proposed method may provide a practical way for quality insurance of production processes.

  11. A simple ergonomic measure reduces fluoroscopy time during ERCP: A multivariate analysis

    PubMed Central

    Jowhari, Fahd; Hopman, Wilma M.; Hookey, Lawrence

    2017-01-01

    Background and study aims Endoscopic retrograde cholangiopancreatgraphy (ERCP) carries a radiation risk to patients undergoing the procedure and the team performing it. Fluoroscopy time (FT) has been shown to have a linear relationship with radiation exposure during ERCP. Recent modifications to our ERCP suite design were felt to impact fluoroscopy time and ergonomics. This multivariate analysis was therefore undertaken to investigate these effects, and to identify and validate various clinical, procedural and ergonomic factors influencing the total fluoroscopy time during ERCP. This would better assist clinicians with predicting prolonged fluoroscopic durations and to undertake relevant precautions accordingly. Patients and methods A retrospective analysis of 299 ERCPs performed by 4 endoscopists over an 18-month period, at a single tertiary care center was conducted. All inpatients/outpatients (121 males, 178 females) undergoing ERCP for any clinical indication from January 2012 to June 2013 in the chosen ERCP suite were included in the study. Various predetermined clinical, procedural and ergonomic factors were obtained via chart review. Univariate analyses identified factors to be included in the multivariate regression model with FT as the dependent variable. Results Bringing the endoscopy and fluoroscopy screens next to each other was associated with a significantly lesser FT than when the screens were separated further (–1.4 min, P = 0.026). Other significant factors associated with a prolonged FT included having a prior ERCP (+ 1.4 min, P = 0.031), and more difficult procedures (+ 4.2 min for each level of difficulty, P < 0.001). ERCPs performed by high-volume endoscopists used lesser FT vs. low-volume endoscopists (–1.82, P = 0.015). Conclusions Our study has identified and validated various factors that affect the total fluoroscopy time during ERCP. This is the first study to show that decreasing the distance between

  12. A simple ergonomic measure reduces fluoroscopy time during ERCP: A multivariate analysis.

    PubMed

    Jowhari, Fahd; Hopman, Wilma M; Hookey, Lawrence

    2017-03-01

    Background and study aims Endoscopic retrograde cholangiopancreatgraphy (ERCP) carries a radiation risk to patients undergoing the procedure and the team performing it. Fluoroscopy time (FT) has been shown to have a linear relationship with radiation exposure during ERCP. Recent modifications to our ERCP suite design were felt to impact fluoroscopy time and ergonomics. This multivariate analysis was therefore undertaken to investigate these effects, and to identify and validate various clinical, procedural and ergonomic factors influencing the total fluoroscopy time during ERCP. This would better assist clinicians with predicting prolonged fluoroscopic durations and to undertake relevant precautions accordingly. Patients and methods A retrospective analysis of 299 ERCPs performed by 4 endoscopists over an 18-month period, at a single tertiary care center was conducted. All inpatients/outpatients (121 males, 178 females) undergoing ERCP for any clinical indication from January 2012 to June 2013 in the chosen ERCP suite were included in the study. Various predetermined clinical, procedural and ergonomic factors were obtained via chart review. Univariate analyses identified factors to be included in the multivariate regression model with FT as the dependent variable. Results Bringing the endoscopy and fluoroscopy screens next to each other was associated with a significantly lesser FT than when the screens were separated further (-1.4 min, P = 0.026). Other significant factors associated with a prolonged FT included having a prior ERCP (+ 1.4 min, P = 0.031), and more difficult procedures (+ 4.2 min for each level of difficulty, P < 0.001). ERCPs performed by high-volume endoscopists used lesser FT vs. low-volume endoscopists (-1.82, P = 0.015). Conclusions Our study has identified and validated various factors that affect the total fluoroscopy time during ERCP. This is the first study to show that decreasing the distance between the

  13. A Hydraulic Tomographic Approach: Coupling of Travel Time and Amplitude Inversion Using Multivariate Statistics

    NASA Astrophysics Data System (ADS)

    Brauchler, R.; Cheng, J.; Dietrich, P.; Everett, M.; Johnson, B.; Sauter, M.

    2005-12-01

    Knowledge about the spatial variations in hydraulic properties plays an important role controlling solute movement in saturated flow systems. Traditional hydrogeological approaches appear to have difficulties providing high resolution parameter estimates. Thus, we have decided to develop an approach coupling the two existing hydraulic tomographic approaches: a) Inversion of the drawdown as a function of time (amplitude inversion) and b) the inversion of travel times of the pressure disturbance. The advantages of hydraulic travel time tomography are its high structural resolution and computational efficiency. However, travel times are primarily controlled by the aquifer diffusivity making it difficult to determine hydraulically conductivity and storage. Amplitude inversion on the other hand is able to determine hydraulic conductivity and storage separately, but the heavy computational burden of the amplitude inversion is often a shortcoming, especially for larger data sets. Our coupled inversion approach was developed and tested using synthetic data sets. The data base of the inversion comprises simulated slug tests, in which the position of the sources (injection ports) isolated with packers, are varied between the tests. The first step was the inversion of several characteristic travel times (e.g. early, intermediate and late travel times) in order to determine the diffusivity distribution. Secondly, the resulting diffusivity distributions were classified into homogeneous groups in order to differentiate between hydrogeological units characterized by a significant diffusivity contrast. The classification was performed by using multivariate statistics. With a numerical flow model and an automatic parameter estimator the amplitude inversion was performed in a final step. The classified diffusivity distribution is an excellent starting model for the amplitude inversion and allows to reduce strongly the calculation time. The final amplitude inversion overcomes

  14. Environmental Events and the Timing of Death.

    ERIC Educational Resources Information Center

    Marriott, Cindy

    There is some evidence that the timing of death may not be random. Taking into consideration some of the variables which possibly affect death, this paper reviews intervention techniques with the possible goal of saving lives. Knowing that the elderly respond to the environment, society should accept as its responsibility the provision of support…

  15. A distributed computing system for multivariate time series analyses of multichannel neurophysiological data.

    PubMed

    Müller, Andy; Osterhage, Hannes; Sowa, Robert; Andrzejak, Ralph G; Mormann, Florian; Lehnertz, Klaus

    2006-04-15

    We present a client-server application for the distributed multivariate analysis of time series using standard PCs. We here concentrate on analyses of multichannel EEG/MEG data, but our method can easily be adapted to other time series. Due to the rapid development of new analysis techniques, the focus in the design of our application was not only on computational performance, but also on high flexibility and expandability of both the client and the server programs. For this purpose, the communication between the server and the clients as well as the building of the computational tasks has been realized via the Extensible Markup Language (XML). Running our newly developed method in an asynchronous distributed environment with random availability of remote and heterogeneous resources, we tested the system's performance for a number of different univariate and bivariate analysis techniques. Results indicate that for most of the currently available analysis techniques, calculations can be performed in real time, which, in principle, allows on-line analyses at relatively low cost.

  16. Young Children's Memory for the Times of Personal Past Events

    PubMed Central

    Pathman, Thanujeni; Larkina, Marina; Burch, Melissa; Bauer, Patricia J.

    2012-01-01

    Remembering the temporal information associated with personal past events is critical for autobiographical memory, yet we know relatively little about the development of this capacity. In the present research, we investigated temporal memory for naturally occurring personal events in 4-, 6-, and 8-year-old children. Parents recorded unique events in which their children participated during a 4-month period. At test, children made relative recency judgments and estimated the time of each event using conventional time-scales (time of day, day of week, month of year, and season). Children also were asked to provide justifications for their time-scale judgments. Six- and 8-year-olds, but not 4-year-olds, accurately judged the order of two distinct events. There were age-related improvements in children's estimation of the time of events using conventional time-scales. Older children provided more justifications for their time-scale judgments compared to younger children. Relations between correct responding on the time-scale judgments and provision of meaningful justifications suggest that children may use that information to reconstruct the times associated with past events. The findings can be used to chart a developmental trajectory of performance in temporal memory for personal past events, and have implications for our understanding of autobiographical memory development. PMID:23687467

  17. ETARA - EVENT TIME AVAILABILITY, RELIABILITY ANALYSIS

    NASA Technical Reports Server (NTRS)

    Viterna, L. A.

    1994-01-01

    The ETARA system was written to evaluate the performance of the Space Station Freedom Electrical Power System, but the methodology and software can be modified to simulate any system that can be represented by a block diagram. ETARA is an interactive, menu-driven reliability, availability, and maintainability (RAM) simulation program. Given a Reliability Block Diagram representation of a system, the program simulates the behavior of the system over a specified period of time using Monte Carlo methods to generate block failure and repair times as a function of exponential and/or Weibull distributions. ETARA can calculate availability parameters such as equivalent availability, state availability (percentage of time at a particular output state capability), continuous state duration and number of state occurrences. The program can simulate initial spares allotment and spares replenishment for a resupply cycle. The number of block failures are tabulated both individually and by block type. ETARA also records total downtime, repair time, and time waiting for spares. Maintenance man-hours per year and system reliability, with or without repair, at or above a particular output capability can also be calculated. The key to using ETARA is the development of a reliability or availability block diagram. The block diagram is a logical graphical illustration depicting the block configuration necessary for a function to be successfully accomplished. Each block can represent a component, a subsystem, or a system. The function attributed to each block is considered for modeling purposes to be either available or unavailable; there are no degraded modes of block performance. A block does not have to represent physically connected hardware in the actual system to be connected in the block diagram. The block needs only to have a role in contributing to an available system function. ETARA can model the RAM characteristics of systems represented by multilayered, nesting block diagrams

  18. A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2015-01-01

    Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS’s hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs’ spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets. PMID:25905027

  19. Bicomponent Trend Maps: A Multivariate Approach to Visualizing Geographic Time Series

    PubMed Central

    Schroeder, Jonathan P.

    2012-01-01

    The most straightforward approaches to temporal mapping cannot effectively illustrate all potentially significant aspects of spatio-temporal patterns across many regions and times. This paper introduces an alternative approach, bicomponent trend mapping, which employs a combination of principal component analysis and bivariate choropleth mapping to illustrate two distinct dimensions of long-term trend variations. The approach also employs a bicomponent trend matrix, a graphic that illustrates an array of typical trend types corresponding to different combinations of scores on two principal components. This matrix is useful not only as a legend for bicomponent trend maps but also as a general means of visualizing principal components. To demonstrate and assess the new approach, the paper focuses on the task of illustrating population trends from 1950 to 2000 in census tracts throughout major U.S. urban cores. In a single static display, bicomponent trend mapping is not able to depict as wide a variety of trend properties as some other multivariate mapping approaches, but it can make relationships among trend classes easier to interpret, and it offers some unique flexibility in classification that could be particularly useful in an interactive data exploration environment. PMID:23504193

  20. Analysis of heterogeneous dengue transmission in Guangdong in 2014 with multivariate time series model

    PubMed Central

    Cheng, Qing; Lu, Xin; Wu, Joseph T.; Liu, Zhong; Huang, Jincai

    2016-01-01

    Guangdong experienced the largest dengue epidemic in recent history. In 2014, the number of dengue cases was the highest in the previous 10 years and comprised more than 90% of all cases. In order to analyze heterogeneous transmission of dengue, a multivariate time series model decomposing dengue risk additively into endemic, autoregressive and spatiotemporal components was used to model dengue transmission. Moreover, random effects were introduced in the model to deal with heterogeneous dengue transmission and incidence levels and power law approach was embedded into the model to account for spatial interaction. There was little spatial variation in the autoregressive component. In contrast, for the endemic component, there was a pronounced heterogeneity between the Pearl River Delta area and the remaining districts. For the spatiotemporal component, there was considerable heterogeneity across districts with highest values in some western and eastern department. The results showed that the patterns driving dengue transmission were found by using clustering analysis. And endemic component contribution seems to be important in the Pearl River Delta area, where the incidence is high (95 per 100,000), while areas with relatively low incidence (4 per 100,000) are highly dependent on spatiotemporal spread and local autoregression. PMID:27666657

  1. Nuclear event zero-time calculation and uncertainty evaluation.

    PubMed

    Pan, Pujing; Ungar, R Kurt

    2012-04-01

    It is important to know the initial time, or zero-time, of a nuclear event such as a nuclear weapon's test, a nuclear power plant accident or a nuclear terrorist attack (e.g. with an improvised nuclear device, IND). Together with relevant meteorological information, the calculated zero-time is used to help locate the origin of a nuclear event. The zero-time of a nuclear event can be derived from measured activity ratios of two nuclides. The calculated zero-time of a nuclear event would not be complete without an appropriately evaluated uncertainty term. In this paper, analytical equations for zero-time and the associated uncertainty calculations are derived using a measured activity ratio of two nuclides. Application of the derived equations is illustrated in a realistic example using data from the last Chinese thermonuclear test in 1980.

  2. Multivariate analysis of GPS position time series of JPL second reprocessing campaign

    NASA Astrophysics Data System (ADS)

    Amiri-Simkooei, A. R.; Mohammadloo, T. H.; Argus, D. F.

    2017-01-01

    The second reprocessing of all GPS data gathered by the Analysis Centers of IGS was conducted in late 2013 using the latest models and methodologies. Improved models of antenna phase center variations and solar radiation pressure in JPL's reanalysis are expected to significantly reduce errors. In an earlier work, JPL estimates of position time series, termed first reprocessing campaign, were examined in terms of their spatial and temporal correlation, power spectra, and draconitic signal. Similar analyses are applied to GPS time series at 89 and 66 sites of the second reanalysis with the time span of 7 and 21 years, respectively, to study possible improvements. Our results indicate that the spatial correlations are reduced on average by a factor of 1.25. While the white and flicker noise amplitudes for all components are reduced by 29-56 %, the random walk amplitude is enlarged. The white, flicker, and random walk noise amount to rate errors of, respectively, 0.01, 0.12, and 0.09 mm/yr in the horizontal and 0.04, 0.41 and 0.3 mm/yr in the vertical. Signals reported previously, such as those with periods of 13.63, 14.76, 5.5, and 351.4 / n for n=1,2,ldots,8 days, are identified in multivariate spectra of both data sets. The oscillation of the draconitic signal is reduced by factors of 1.87, 1.87, and 1.68 in the east, north and up components, respectively. Two other signals with Chandlerian period and a period of 380 days can also be detected.

  3. Family Events and the Timing of Intergenerational Transfers

    ERIC Educational Resources Information Center

    Leopold, Thomas; Schneider, Thorsten

    2011-01-01

    This research investigates how family events in adult children's lives influence the timing of their parents' financial transfers. We draw on retrospective data collected by the German Socio-Economic Panel Study and use event history models to study the effects of marriage, divorce and childbirth on the receipt of large gifts from parents. We find…

  4. Sensor-Generated Time Series Events: A Definition Language

    PubMed Central

    Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

    2012-01-01

    There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

  5. Balance characteristics of multivariate background error covariance for rainy and dry seasons and their impact on precipitation forecasts of two rainfall events

    NASA Astrophysics Data System (ADS)

    Chen, Yaodeng; Xia, Xue; Min, Jinzhong; Huang, Xiang-Yu; Rizvi, Syed R. H.

    2016-10-01

    Atmospheric moisture content or humidity is an important analysis variable of any meteorological data assimilation system. The humidity analysis can be univariate, using humidity background (normally short-range numerical forecasts) and humidity observations. However, more and more data assimilation systems are multivariate, analyzing humidity together with wind, temperature and pressure. Background error covariances, with unbalanced velocity potential and humidity in the multivariate formulation, are generated from weather research and forecasting model forecasts, collected over a summer rainy season and a winter dry season. The unbalanced velocity potential and humidity related correlations are shown to be significantly larger, indicating more important roles unbalanced velocity potential and humidity play, in the rainy season than that in the dry season. Three cycling data assimilation experiments of two rainfall events in the middle and lower reaches of the Yangtze River are carried out. The experiments differ in the formulation of the background error covariances. Results indicate that only including unbalanced velocity potential in the multivariate background error covariance improves wind analyses, but has little impact on temperature and humidity analyses. In contrast, further including humidity in the multivariate background error covariance although has a slight negative effect on wind analyses and a neutral effect on temperature analyses, but significantly improves humidity analyses, leading to precipitation forecasts more consistent with China Hourly Merged Precipitation Analysis.

  6. Intraoperative imaging of cortical cerebral perfusion by time-resolved thermography and multivariate data analysis.

    PubMed

    Steiner, Gerald; Sobottka, Stephan B; Koch, Edmund; Schackert, Gabriele; Kirsch, Matthias

    2011-01-01

    A new approach to cortical perfusion imaging is demonstrated using high-sensitivity thermography in conjunction with multivariate statistical data analysis. Local temperature changes caused by a cold bolus are imaged and transferred to a false color image. A cold bolus of 10 ml saline at ice temperature is injected systemically via a central venous access. During the injection, a sequence of 735 thermographic images are recorded within 2 min. The recorded data cube is subjected to a principal component analysis (PCA) to select slight changes of the cortical temperature caused by the cold bolus. PCA reveals that 11 s after injection the temperature of blood vessels is shortly decreased followed by an increase to the temperature before the cold bolus is injected. We demonstrate the potential of intraoperative thermography in combination with multivariate data analysis to image cortical cerebral perfusion without any markers. We provide the first in vivo application of multivariate thermographic imaging.

  7. Semiparametric time-to-event modeling in the presence of a latent progression event.

    PubMed

    Rice, John D; Tsodikov, Alex

    2016-08-24

    In cancer research, interest frequently centers on factors influencing a latent event that must precede a terminal event. In practice it is often impossible to observe the latent event precisely, making inference about this process difficult. To address this problem, we propose a joint model for the unobserved time to the latent and terminal events, with the two events linked by the baseline hazard. Covariates enter the model parametrically as linear combinations that multiply, respectively, the hazard for the latent event and the hazard for the terminal event conditional on the latent one. We derive the partial likelihood estimators for this problem assuming the latent event is observed, and propose a profile likelihood-based method for estimation when the latent event is unobserved. The baseline hazard in this case is estimated nonparametrically using the EM algorithm, which allows for closed-form Breslow-type estimators at each iteration, bringing improved computational efficiency and stability compared with maximizing the marginal likelihood directly. We present simulation studies to illustrate the finite-sample properties of the method; its use in practice is demonstrated in the analysis of a prostate cancer data set.

  8. Analysing adverse events by time-to-event models: the CLEOPATRA study.

    PubMed

    Proctor, Tanja; Schumacher, Martin

    2016-07-01

    When analysing primary and secondary endpoints in a clinical trial with patients suffering from a chronic disease, statistical models for time-to-event data are commonly used and accepted. This is in contrast to the analysis of data on adverse events where often only a table with observed frequencies and corresponding test statistics is reported. An example is the recently published CLEOPATRA study where a three-drug regimen is compared with a two-drug regimen in patients with HER2-positive first-line metastatic breast cancer. Here, as described earlier, primary and secondary endpoints (progression-free and overall survival) are analysed using time-to-event models, whereas adverse events are summarized in a simple frequency table, although the duration of study treatment differs substantially. In this paper, we demonstrate the application of time-to-event models to first serious adverse events using the data of the CLEOPATRA study. This will cover the broad range between a simple incidence rate approach over survival and competing risks models (with death as a competing event) to multi-state models. We illustrate all approaches by means of graphical displays highlighting the temporal dynamics and compare the obtained results. For the CLEOPATRA study, the resulting hazard ratios are all in the same order of magnitude. But the use of time-to-event models provides valuable and additional information that would potentially be overlooked by only presenting incidence proportions. These models adequately address the temporal dynamics of serious adverse events as well as death of patients. Copyright © 2016 John Wiley & Sons, Ltd.

  9. Reciprocal Benefits of Mass-Univariate and Multivariate Modeling in Brain Mapping: Applications to Event-Related Functional MRI, H2 15O-, and FDG-PET

    PubMed Central

    Habeck, Christian G.

    2006-01-01

    In brain mapping studies of sensory, cognitive, and motor operations, specific waveforms of dynamic neural activity are predicted based on theoretical models of human information processing. For example in event-related functional MRI (fMRI), the general linear model (GLM) is employed in mass-univariate analyses to identify the regions whose dynamic activity closely matches the expected waveforms. By comparison multivariate analyses based on PCA or ICA provide greater flexibility in detecting spatiotemporal properties of experimental data that may strongly support alternative neuroscientific explanations. We investigated conjoint multivariate and mass-univariate analyses that combine the capabilities to (1) verify activation of neural machinery we already understand and (2) discover reliable signatures of new neural machinery. We examined combinations of GLM and PCA that recover latent neural signals (waveforms and footprints) with greater accuracy than either method alone. Comparative results are illustrated with analyses of real fMRI data, adding to Monte Carlo simulation support. PMID:23165047

  10. Real-time measurements, rare events and photon economics

    NASA Astrophysics Data System (ADS)

    Jalali, B.; Solli, D. R.; Goda, K.; Tsia, K.; Ropers, C.

    2010-07-01

    Rogue events otherwise known as outliers and black swans are singular, rare, events that carry dramatic impact. They appear in seemingly unconnected systems in the form of oceanic rogue waves, stock market crashes, evolution, and communication systems. Attempts to understand the underlying dynamics of such complex systems that lead to spectacular and often cataclysmic outcomes have been frustrated by the scarcity of events, resulting in insufficient statistical data, and by the inability to perform experiments under controlled conditions. Extreme rare events also occur in ultrafast physical sciences where it is possible to collect large data sets, even for rare events, in a short time period. The knowledge gained from observing rare events in ultrafast systems may provide valuable insight into extreme value phenomena that occur over a much slower timescale and that have a closer connection with human experience. One solution is a real-time ultrafast instrument that is capable of capturing singular and randomly occurring non-repetitive events. The time stretch technology developed during the past 13 years is providing a powerful tool box for reaching this goal. This paper reviews this technology and discusses its use in capturing rogue events in electronic signals, spectroscopy, and imaging. We show an example in nonlinear optics where it was possible to capture rare and random solitons whose unusual statistical distribution resemble those observed in financial markets. The ability to observe the true spectrum of each event in real time has led to important insight in understanding the underlying process, which in turn has made it possible to control soliton generation leading to improvement in the coherence of supercontinuum light. We also show a new class of fast imagers which are being considered for early detection of cancer because of their potential ability to detect rare diseased cells (so called rogue cells) in a large population of healthy cells.

  11. Moving Events in Time: Time-Referent Hand-Arm Movements Influence Perceived Temporal Distance to Past Events

    ERIC Educational Resources Information Center

    Blom, Stephanie S. A. H.; Semin, Gun R.

    2013-01-01

    We examine and find support for the hypothesis that time-referent hand-arm movements influence temporal judgments. In line with the concept of "left is associated with earlier times, and right is associated with later times," we show that performing left (right) hand-arm movements while thinking about a past event increases (decreases) the…

  12. Effects of alcohol intake on time-based event expectations.

    PubMed

    Kunchulia, Marina; Thomaschke, Roland

    2016-04-01

    Previous evidence suggests that alcohol affects various forms of temporal cognition. However, there are presently no studies investigating whether and how alcohol affects on time-based event expectations. Here, we investigated the effects of alcohol on time-based event expectations. Seventeen healthy volunteers, aged between 19 and 36 years, participated. We employed a variable foreperiod paradigm with temporally predictable events, mimicking a computer game. Error rate and reaction time were analyzed in placebo (0 g/kg), low dose (0.2 g/kg) and high dose (0.6 g/kg) conditions. We found that alcohol intake did not eliminate, but substantially reduced, the formation of time-based expectancy. This effect was stronger for high doses, than for low doses, of alcohol. As a result of our studies, we have evidence that alcohol intake impairs time-based event expectations. The mechanism by which the level of alcohol impairs time-based event expectations needs to be clarified by future research.

  13. Asynchronous visual event-based time-to-contact.

    PubMed

    Clady, Xavier; Clercq, Charles; Ieng, Sio-Hoi; Houseini, Fouzhan; Randazzo, Marco; Natale, Lorenzo; Bartolozzi, Chiara; Benosman, Ryad

    2014-01-01

    Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing.

  14. Asynchronous visual event-based time-to-contact

    PubMed Central

    Clady, Xavier; Clercq, Charles; Ieng, Sio-Hoi; Houseini, Fouzhan; Randazzo, Marco; Natale, Lorenzo; Bartolozzi, Chiara; Benosman, Ryad

    2014-01-01

    Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing. PMID:24570652

  15. Sharing Time: A Student-Run Speech Event.

    ERIC Educational Resources Information Center

    Foster, Michele

    An ethnographic study was made of a student-led speech event in an ethnically mixed combined first- and second-grade classroom. In an activity called "Sharing Time," general rules governed appropriate ways of behaving, but no teacher rules governed ways of speaking, topic, or amount of time at talk. Collected over a 5-month period, data…

  16. New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares.

    PubMed

    Fadel, Maya Abou; de Juan, Anna; Vezin, Hervé; Duponchel, Ludovic

    2016-12-01

    Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra.

  17. Inferring direct directed-information flow from multivariate nonlinear time series

    NASA Astrophysics Data System (ADS)

    Jachan, Michael; Henschel, Kathrin; Nawrath, Jakob; Schad, Ariane; Timmer, Jens; Schelter, Björn

    2009-07-01

    Estimating the functional topology of a network from multivariate observations is an important task in nonlinear dynamics. We introduce the nonparametric partial directed coherence that allows disentanglement of direct and indirect connections and their directions. We illustrate the performance of the nonparametric partial directed coherence by means of a simulation with data from synchronized nonlinear oscillators and apply it to real-world data from a patient suffering from essential tremor.

  18. Time Separation Between Events in a Sequence: a Regional Property?

    NASA Astrophysics Data System (ADS)

    Muirwood, R.; Fitzenz, D. D.

    2013-12-01

    Earthquake sequences are loosely defined as events occurring too closely in time and space to appear unrelated. Depending on the declustering method, several, all, or no event(s) after the first large event might be recognized as independent mainshocks. It can therefore be argued that a probabilistic seismic hazard assessment (PSHA, traditionally dealing with mainshocks only) might already include the ground shaking effects of such sequences. Alternatively all but the largest event could be classified as an ';aftershock' and removed from the earthquake catalog. While in PSHA the question is only whether to keep or remove the events from the catalog, for Risk Management purposes, the community response to the earthquakes, as well as insurance risk transfer mechanisms, can be profoundly affected by the actual timing of events in such a sequence. In particular the repetition of damaging earthquakes over a period of weeks to months can lead to businesses closing and families evacuating from the region (as happened in Christchurch, New Zealand in 2011). Buildings that are damaged in the first earthquake may go on to be damaged again, even while they are being repaired. Insurance also functions around a set of critical timeframes - including the definition of a single 'event loss' for reinsurance recoveries within the 192 hour ';hours clause', the 6-18 month pace at which insurance claims are settled, and the annual renewal of insurance and reinsurance contracts. We show how temporal aspects of earthquake sequences need to be taken into account within models for Risk Management, and what time separation between events are most sensitive, both in terms of the modeled disruptions to lifelines and business activity as well as in the losses to different parties (such as insureds, insurers and reinsurers). We also explore the time separation between all events and between loss causing events for a collection of sequences from across the world and we point to the need to

  19. Does time really slow down during a frightening event?

    PubMed

    Stetson, Chess; Fiesta, Matthew P; Eagleman, David M

    2007-12-12

    Observers commonly report that time seems to have moved in slow motion during a life-threatening event. It is unknown whether this is a function of increased time resolution during the event, or instead an illusion of remembering an emotionally salient event. Using a hand-held device to measure speed of visual perception, participants experienced free fall for 31 m before landing safely in a net. We found no evidence of increased temporal resolution, in apparent conflict with the fact that participants retrospectively estimated their own fall to last 36% longer than others' falls. The duration dilation during a frightening event, and the lack of concomitant increase in temporal resolution, indicate that subjective time is not a single entity that speeds or slows, but instead is composed of separable subcomponents. Our findings suggest that time-slowing is a function of recollection, not perception: a richer encoding of memory may cause a salient event to appear, retrospectively, as though it lasted longer.

  20. A real-time assessment of factors influencing medication events.

    PubMed

    Dollarhide, Adrian W; Rutledge, Thomas; Weinger, Matthew B; Fisher, Erin Stucky; Jain, Sonia; Wolfson, Tanya; Dresselhaus, Timothy R

    2014-01-01

    Reducing medical error is critical to improving the safety and quality of healthcare. Physician stress, fatigue, and excessive workload are performance-shaping factors (PSFs) that may influence medical events (actual administration errors and near misses), but direct relationships between these factors and patient safety have not been clearly defined. This study assessed the real-time influence of emotional stress, workload, and sleep deprivation on self-reported medication events by physicians in academic hospitals. During an 18-month study period, 185 physician participants working at four university-affiliated teaching hospitals reported medication events using a confidential reporting application on handheld computers. Emotional stress scores, perceived workload, patient case volume, clinical experience, total sleep, and demographic variables were also captured via the handheld computers. Medication event reports (n = 11) were then correlated with these demographic and PSFs. Medication events were associated with 36.1% higher perceived workload (p < .05), 38.6% higher inpatient caseloads (p < .01), and 55.9% higher emotional stress scores (p < .01). There was a trend for reported events to also be associated with less sleep (p = .10). These results confirm the effect of factors influencing medication events, and support attention to both provider and hospital environmental characteristics for improving patient safety.

  1. The sensitivity and specificity of markers for event times.

    PubMed

    Cai, Tianxi; Pepe, Margaret Sullivan; Zheng, Yingye; Lumley, Thomas; Jenny, Nancy Swords

    2006-04-01

    The statistical literature on assessing the accuracy of risk factors or disease markers as diagnostic tests deals almost exclusively with settings where the test, Y, is measured concurrently with disease status D. In practice, however, disease status may vary over time and there is often a time lag between when the marker is measured and the occurrence of disease. One example concerns the Framingham risk score (FR-score) as a marker for the future risk of cardiovascular events, events that occur after the score is ascertained. To evaluate such a marker, one needs to take the time lag into account since the predictive accuracy may be higher when the marker is measured closer to the time of disease occurrence. We therefore consider inference for sensitivity and specificity functions that are defined as functions of time. Semiparametric regression models are proposed. Data from a cohort study are used to estimate model parameters. One issue that arises in practice is that event times may be censored. In this research, we extend in several respects the work by Leisenring et al. (1997) that dealt only with parametric models for binary tests and uncensored data. We propose semiparametric models that accommodate continuous tests and censoring. Asymptotic distribution theory for parameter estimates is developed and procedures for making statistical inference are evaluated with simulation studies. We illustrate our methods with data from the Cardiovascular Health Study, relating the FR-score measured at enrollment to subsequent risk of cardiovascular events.

  2. Events in time: Basic analysis of Poisson data

    SciTech Connect

    Engelhardt, M.E.

    1994-09-01

    The report presents basic statistical methods for analyzing Poisson data, such as the member of events in some period of time. It gives point estimates, confidence intervals, and Bayesian intervals for the rate of occurrence per unit of time. It shows how to compare subsets of the data, both graphically and by statistical tests, and how to look for trends in time. It presents a compound model when the rate of occurrence varies randomly. Examples and SAS programs are given.

  3. Estimating differences and ratios in median times to event

    PubMed Central

    Rogawski, Elizabeth T.; Westreich, Daniel J.; Kang, Gagandeep; Ward, Honorine D.; Cole, Stephen R.

    2016-01-01

    Time differences and time ratios are often more interpretable estimates of effect than hazard ratios for time-to-event data, especially for common outcomes. We developed a SAS macro for estimating time differences and time ratios between baseline-fixed binary exposure groups based on inverse probability weighted Kaplan-Meier curves. The macro uses pooled logistic regression to calculate inverse probability of censoring and exposure weights, draws Kaplan-Meier curves based on the weighted data, and estimates the time difference and time ratio at a user-defined survival proportion. The macro also calculates the risk difference and risk ratio at a user-specified time. Confidence intervals are constructed by bootstrap. We provide an example assessing the effect of exclusive breastfeeding during diarrhea on the incidence of subsequent diarrhea in children followed from birth to 3 years in Vellore, India. The SAS macro provided here should facilitate the wider reporting of time differences and time ratios. PMID:27465526

  4. A multivariate time-warping based classifier for gesture recognition with wearable strain sensors.

    PubMed

    Giorgino, Toni; Tormene, Paolo; Quaglini, Silvana

    2007-01-01

    Conductive elastomer elements can be industrially embedded into garments to form unobtrusive strain sensing stripes. The present article outlines the structure of a strain-sensor based gesture detection algorithm. Current sensing prototypes include several dozens of sensors; their redundancy with respect to the limb's degrees of freedom, and other artifacts implied by this measurement technique, call for the development of novel robust multivariate pattern-matching techniques. The algorithm's construction is explained, and its performances are evaluated in the context of motor rehabilitation exercises for both two-class and multi-class tasks.

  5. Space-Time Event Sparse Penalization for Magneto-/Electroencephalography

    PubMed Central

    Bolstad, Andrew; Van Veen, Barry; Nowak, Robert

    2009-01-01

    This article presents a new spatio-temporal method for M/EEG source reconstruction based on the assumption that only a small number of events, localized in space and/or time, are responsible for the measured signal. Each space-time event is represented using a basis function expansion which reflects the most relevant (or measurable) features of the signal. This model of neural activity leads naturally to a Bayesian likelihood function which balances the model fit to the data with the complexity of the model, where the complexity is related to the number of included events. A novel Expectation-Maximization algorithm which maximizes the likelihood function is presented. The new method is shown to be effective on several MEG simulations of neurological activity as well as data from a self-paced finger tapping experiment. PMID:19457366

  6. Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

    PubMed

    Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

    2016-01-01

    Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms

  7. Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects

    PubMed Central

    Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

    2017-01-01

    Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms

  8. Hearing flashes and seeing beeps: Timing audiovisual events

    PubMed Central

    2017-01-01

    Many events from daily life are audiovisual (AV). Handclaps produce both visual and acoustic signals that are transmitted in air and processed by our sensory systems at different speeds, reaching the brain multisensory integration areas at different moments. Signals must somehow be associated in time to correctly perceive synchrony. This project aims at quantifying the mutual temporal attraction between senses and characterizing the different interaction modes depending on the offset. In every trial participants saw four beep-flash pairs regularly spaced in time, followed after a variable delay by a fifth event in the test modality (auditory or visual). A large range of AV offsets was tested. The task was to judge whether the last event came before/after what was expected given the perceived rhythm, while attending only to the test modality. Flashes were perceptually shifted in time toward beeps, the attraction being stronger for lagging than leading beeps. Conversely, beeps were not shifted toward flashes, indicating a nearly total auditory capture. The subjective timing of the visual component resulting from the AV interaction could easily be forward but not backward in time, an intuitive constraint stemming from minimum visual processing delays. Finally, matching auditory and visual time-sensitivity with beeps embedded in pink noise produced very similar mutual attractions of beeps and flashes. Breaking the natural auditory preference for timing allowed vision to take over as well, showing that this preference is not hardwired. PMID:28207786

  9. Time Evolution of Elemental Ratios in Solar Energetic Particle Events

    NASA Astrophysics Data System (ADS)

    Zelina, P.; Dalla, S.; Cohen, C. M. S.; Mewaldt, R. A.

    2017-01-01

    Heavy ion ratio abundances in solar energetic particle (SEP) events, e.g., Fe/O, often exhibit decreases over time. Using particle instruments on the Advanced Composition Explorer, Solar and Heliospheric Observatory and Solar Terrestrial Relations Observatory spacecraft, we analyzed heavy ion data from 4 SEP events taking place between 2006 December and 2014 December. We constructed 36 different ionic pairs and studied their time evolution in each event. We quantified the temporal behavior of abundant SEP ratios by fitting the data to derive a decay time constant B. We also considered the ratio of ionic mass-to-charge for each pair, the S value given, e.g., for Fe/O by {S}{Fe/{{O}}}={(M/Q)}{Fe}/{(M/Q)}{{O}}. We found that the temporal behavior of SEP ratios is ordered by the value of S: ratios with S> 1 showed decreases over time (i.e., B< 0) and those with S< 1 showed increases (B> 0). We plotted B as a function of S and observed a clear monotonic dependence: ratios with a large S decayed at a higher rate. A prominent discontinuity at S = 2.0 (corresponding to He/H) was found in three of the four events, suggesting anomalous behavior of protons. The X/H ratios often show an initial increase followed by a decrease, and decay at a slower rate. We discuss possible causes of the observed B versus S trends within current understanding of SEP propagation.

  10. Making Story Time a Literacy Event for the Young Child.

    ERIC Educational Resources Information Center

    Weir, Beth

    1989-01-01

    Reviews research and anecdotal accounts which present instructional techniques and which suggest that the quality of instruction, quality of time, and quality of books are significant factors in ensuring that story reading is a true literacy event. Argues that consistent story readings facilitate the acquisition of the reading process. (RS)

  11. Established time series measure occurrence and frequency of episodic events.

    NASA Astrophysics Data System (ADS)

    Pebody, Corinne; Lampitt, Richard

    2015-04-01

    Established time series measure occurrence and frequency of episodic events. Episodic flux events occur in open oceans. Time series making measurements over significant time scales are one of the few methods that can capture these events and compare their impact with 'normal' flux. Seemingly rare events may be significant on local scales, but without the ability to measure the extent of flux on spatial and temporal scales and combine with the frequency of occurrence, it is difficult to constrain their impact. The Porcupine Abyssal Plain Sustained Observatory (PAP-SO) in the Northeast Atlantic (49 °N 16 °W, 5000m water depth) has measured particle flux since 1989 and zooplankton swimmers since 2000. Sediment traps at 3000m and 100 metres above bottom, collect material year round and we have identified close links between zooplankton and particle flux. Some of these larger animals, for example Diacria trispinosa, make a significant contribution to carbon flux through episodic flux events. D. trispinosa is a euthecosome mollusc which occurs in the Northeast Atlantic, though the PAP-SO is towards the northern limit of its distribution. Pteropods are comprised of aragonite shell, containing soft body parts excepting the muscular foot which extends beyond the mouth of the living animal. Pteropods, both live-on-entry animals and the empty shells are found year round in the 3000m trap. Generally the abundance varies with particle flux, but within that general pattern there are episodic events where significant numbers of these animals containing both organic and inorganic carbon are captured at depth and therefore could be defined as contributing to export flux. Whether the pulse of animals is as a result of the life cycle of D. trispinosa or the effects of the physics of the water column is unclear, but the complexity of the PAP-SO enables us not only to collect these animals but to examine them in parallel to the biogeochemical and physical elements measured by the

  12. Initial Time Dependence of Abundances in Solar Energetic Particle Events

    NASA Technical Reports Server (NTRS)

    Reames, Donald V.; Ny, C. K.; Tylka, A. J.

    1999-01-01

    We compare the initial behavior of Fe/O and He/H abundance ratios and their relationship to the evolution of the proton energy spectra in "small" and "large" gradual solar energetic particle (SEP) events. The results are qualitatively consistent with the behavior predicted by the theory of Ng et al. (1999a, b). He/H ratios that initially rise with time are a signature of scattering by non-Kolmogorov Alfven wave spectra generated by intense beams of shock-accelerated protons streaming outward in large gradual SEP events.

  13. The Time of Our Lives: Life Span Development of Timing and Event Tracking

    ERIC Educational Resources Information Center

    McAuley, J. Devin; Jones, Mari Riess; Holub, Shayla; Johnston, Heather M.; Miller, Nathaniel S.

    2006-01-01

    Life span developmental profiles were constructed for 305 participants (ages 4-95) for a battery of paced and unpaced perceptual-motor timing tasks that included synchronize-continue tapping at a wide range of target event rates. Two life span hypotheses, derived from an entrainment theory of timing and event tracking, were tested. A preferred…

  14. [Multivariate Adaptive Regression Splines (MARS), an alternative for the analysis of time series].

    PubMed

    Vanegas, Jairo; Vásquez, Fabián

    2016-12-19

    Multivariate Adaptive Regression Splines (MARS) is a non-parametric modelling method that extends the linear model, incorporating nonlinearities and interactions between variables. It is a flexible tool that automates the construction of predictive models: selecting relevant variables, transforming the predictor variables, processing missing values and preventing overshooting using a self-test. It is also able to predict, taking into account structural factors that might influence the outcome variable, thereby generating hypothetical models. The end result could identify relevant cut-off points in data series. It is rarely used in health, so it is proposed as a tool for the evaluation of relevant public health indicators. For demonstrative purposes, data series regarding the mortality of children under 5 years of age in Costa Rica were used, comprising the period 1978-2008.

  15. Prediction problem for target events based on the inter-event waiting time

    NASA Astrophysics Data System (ADS)

    Shapoval, A.

    2010-11-01

    In this paper we address the problem of forecasting the target events of a time series given the distribution ξ of time gaps between target events. Strong earthquakes and stock market crashes are the two types of such events that we are focusing on. In the series of earthquakes, as McCann et al. show [W.R. Mc Cann, S.P. Nishenko, L.R. Sykes, J. Krause, Seismic gaps and plate tectonics: seismic potential for major boundaries, Pure and Applied Geophysics 117 (1979) 1082-1147], there are well-defined gaps (called seismic gaps) between strong earthquakes. On the other hand, usually there are no regular gaps in the series of stock market crashes [M. Raberto, E. Scalas, F. Mainardi, Waiting-times and returns in high-frequency financial data: an empirical study, Physica A 314 (2002) 749-755]. For the case of seismic gaps, we analytically derive an upper bound of prediction efficiency given the coefficient of variation of the distribution ξ. For the case of stock market crashes, we develop an algorithm that predicts the next crash within a certain time interval after the previous one. We show that this algorithm outperforms random prediction. The efficiency of our algorithm sets up a lower bound of efficiency for effective prediction of stock market crashes.

  16. Return time statistic of wind power ramp events

    NASA Astrophysics Data System (ADS)

    Calif, Rudy; Schmitt, François G.

    2015-04-01

    Detection and forecasting of wind power ramp events is a critical issue for the management of power generated by wind turbine and a cluster of wind turbines. The wind power ramp events occur suddenly with larges changes (increases or decreases) of wind power output. In this work, the statistic and the dynamic of wind power ramp events are examined. For that, we analyze several datasets of wind power output with different sampling rate and duration. The data considered are delivered by five wind farms and two single turbines, located at different geographic locations. From these datasets, the return time series τr of wind power ramp events, i.e., the time between two successive ramps above a given threshold Δ p. The return time statistic is investigated plotting the complementary cumulative distribution C(τ_r) in log-log representation. Using a robust method developed by Clauset et al., combining maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov Smirnov statistic, we show a scaling behavior of the return time statistic, of the form: C(τ_r)˜ kτ_r-α where k is a positive constant and the exponent α called the tail exponent of the distribution. In this study, the value of α ranges from 1.68 to 2.20. This result is a potential information for the estimation risk of wind power generation based on the return time series. Clauset A, Shalizi CR, Newman MEJ. Power-Law distributions in empirical data. SIAM Review 2009;51(4):661-703.

  17. Life Events and Depressive Symptoms in African American Adolescents: Do Ecological Domains and Timing of Life Events Matter?

    ERIC Educational Resources Information Center

    Sanchez, Yadira M.; Lambert, Sharon F.; Ialongo, Nicholas S.

    2012-01-01

    Considerable research has documented associations between adverse life events and internalizing symptoms in adolescents, but much of this research has focused on the number of events experienced, with less attention to the ecological context or timing of events. This study examined life events in three ecological domains relevant to adolescents…

  18. Time-quefrency analysis of overlapping similar microseismic events

    NASA Astrophysics Data System (ADS)

    Nagano, Koji

    2016-05-01

    In this paper, I describe a new technique to determine the interval between P-waves in similar, overlapping microseismic events. The similar microseismic events that occur with overlapping waveforms are called `proximate microseismic doublets' herein. Proximate microseismic doublets had been discarded in previous studies because we had not noticed their usefulness. Analysis of similar events can show relative locations of sources between them. Analysis of proximate microseismic doublets can provide more precise relative source locations because variation in the velocity structure has little influence on their relative travel times. It is necessary to measure the interval between the P-waves in the proximate microseismic doublets to determine their relative source locations. A `proximate microseismic doublet' is a pair of microseismic events in which the second event arrives before the attenuation of the first event. Cepstrum analysis can provide the interval even though the second event overlaps the first event. However, a cepstrum of a proximate microseismic doublet generally has two peaks, one representing the interval between the arrivals of the two P-waves, and the other representing the interval between the arrivals of the two S-waves. It is therefore difficult to determine the peak that represents the P-wave interval from the cepstrum alone. I used window functions in cepstrum analysis to isolate the first and second P-waves and to suppress the second S-wave. I change the length of the window function and calculate the cepstrum for each window length. The result is represented in a three-dimensional contour plot of length-quefrency-cepstrum data. The contour plot allows me to identify the cepstrum peak that represents the P-wave interval. The precise quefrency can be determined from a two-dimensional quefrency-cepstrum graph, provided that the length of the window is appropriately chosen. I have used both synthetic and field data to demonstrate that this

  19. Real-Time Multimission Event Notification System for Mars Relay

    NASA Technical Reports Server (NTRS)

    Wallick, Michael N.; Allard, Daniel A.; Gladden, Roy E.; Wang, Paul; Hy, Franklin H.

    2013-01-01

    As the Mars Relay Network is in constant flux (missions and teams going through their daily workflow), it is imperative that users are aware of such state changes. For example, a change by an orbiter team can affect operations on a lander team. This software provides an ambient view of the real-time status of the Mars network. The Mars Relay Operations Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay Network. As part of MaROS, a feature set was developed that operates on several levels of the software architecture. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. The result is a real-time event notification and management system, so mission teams can track and act upon events on a moment-by-moment basis. This software retrieves events from MaROS and displays them to the end user. Updates happen in real time, i.e., messages are pushed to the user while logged into the system, and queued when the user is not online for later viewing. The software does not do away with the email notifications, but augments them with in-line notifications. Further, this software expands the events that can generate a notification, and allows user-generated notifications. Existing software sends a smaller subset of mission-generated notifications via email. A common complaint of users was that the system-generated e-mails often "get lost" with other e-mail that comes in. This software allows for an expanded set (including user-generated) of notifications displayed in-line of the program. By separating notifications, this can improve a user's workflow.

  20. Model predictive control of P-time event graphs

    NASA Astrophysics Data System (ADS)

    Hamri, H.; Kara, R.; Amari, S.

    2016-12-01

    This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

  1. Investigating Progression in Substance Use Initiation Using a Discrete-Time Multiple Event Process Survival Mixture (MEPSUM) Approach

    PubMed Central

    Richmond-Rakerd, Leah S.; Fleming, Kimberly A.; Slutske, Wendy S.

    2015-01-01

    The order and timing of substance initiation has significant implications for later problematic patterns of use. Despite the need to study initiation from a multivariate framework, survival analytic methods typically cannot accommodate more than two substances in one model. The Discrete-Time Multiple Event Process Survival Mixture (MEPSUM; Dean, Bauer, & Shanahan, 2014) model represents an advance by incorporating more than two outcomes and enabling establishment of latent classes within a multivariate hazard distribution. Employing a MEPSUM approach, we evaluated patterns of tobacco, alcohol, and cannabis initiation in the National Longitudinal Study of Adolescent to Adult Health (N=18,923). We found four classes that differed in their ages and ordering of peak initiation risk. Demographics, externalizing psychopathology, and personality significantly predicted class membership. Sex differences in the association between delinquency and initiation patterns also emerged. Findings support the utility of the MEPSUM approach in elucidating developmental pathways underlying clinically relevant phenomena. PMID:27127730

  2. A rank test for bivariate time-to-event outcomes when one event is a surrogate.

    PubMed

    Shaw, Pamela A; Fay, Michael P

    2016-08-30

    In many clinical settings, improving patient survival is of interest but a practical surrogate, such as time to disease progression, is instead used as a clinical trial's primary endpoint. A time-to-first endpoint (e.g., death or disease progression) is commonly analyzed but may not be adequate to summarize patient outcomes if a subsequent event contains important additional information. We consider a surrogate outcome very generally as one correlated with the true endpoint of interest. Settings of interest include those where the surrogate indicates a beneficial outcome so that the usual time-to-first endpoint of death or surrogate event is nonsensical. We present a new two-sample test for bivariate, interval-censored time-to-event data, where one endpoint is a surrogate for the second, less frequently observed endpoint of true interest. This test examines whether patient groups have equal clinical severity. If the true endpoint rarely occurs, the proposed test acts like a weighted logrank test on the surrogate; if it occurs for most individuals, then our test acts like a weighted logrank test on the true endpoint. If the surrogate is a useful statistical surrogate, our test can have better power than tests based on the surrogate that naively handles the true endpoint. In settings where the surrogate is not valid (treatment affects the surrogate but not the true endpoint), our test incorporates the information regarding the lack of treatment effect from the observed true endpoints and hence is expected to have a dampened treatment effect compared with tests based on the surrogate alone. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

  3. Interpreting the estimated timing of migration events between hybridizing species.

    PubMed

    Strasburg, Jared L; Rieseberg, Loren H

    2011-06-01

    The question of whether speciation can occur in the presence of gene flow has long been a contentious one. However, measuring the amount and timing of gene flow remains challenging. The computer program IMa2 allows researchers to estimate the timing of migration events for each locus during analyses, and these estimates have been used to infer the timing of introgression and mode of speciation. We use simulated data sets to examine the degree to which gene-flow timing estimates can be used for these purposes, and what demographic conditions and data sets may be most amenable to gene-flow timing estimation. We find that the 90% highest posterior density (HPD) interval of gene-flow timing is almost always substantially wider than the actual window of gene flow, and increasing the information content of the data set in terms of number of loci, number of sequences sampled or locus length (and thus number of variable sites) has little impact on the posterior distribution over the range of values we tested. Even when simulated gene flow only occurred over the most recent 0.01% of the species' history, the HPD interval usually encompasses the inferred divergence time. Our results indicate that gene-flow timing estimates made using the method currently implemented in IMa2 cannot reliably be used to make inferences about the timing of introgression between diverged species or to distinguish between speciation with gene flow and allopatric speciation followed by one or more episodes of gene flow.

  4. Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

    PubMed

    Hwang, Chih-Lyang; Jan, Chau

    2016-02-01

    At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

  5. Detecting and characterising ramp events in wind power time series

    NASA Astrophysics Data System (ADS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-12-01

    In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain.

  6. Empirical reconstruction of storm-time steady magnetospheric convection events

    NASA Astrophysics Data System (ADS)

    Stephens, G. K.; Sitnov, M. I.; Kissinger, J.; Tsyganenko, N. A.; McPherron, R. L.; Korth, H.; Anderson, B. J.

    2013-12-01

    We investigate the storm-scale morphology of the magnetospheric magnetic field as well as underlying distributions of electric currents, equatorial plasma pressure and entropy for four Steady Magnetospheric Convection (SMC) events that occurred during the May 2000 and October 2011 magnetic storms. The analysis is made using the empirical geomagnetic field model TS07D, in which the structure of equatorial currents is not predefined and it is dictated by data. The model also combines the strengths of statistical and event-oriented approaches in mining data for the reconstruction of the magnetic field. The formation of a near-Earth minimum of the equatorial magnetic field in the midnight sector is inferred from data without ad hoc assumptions of a special current system postulated in earlier empirical reconstructions. In addition, a new SMC class is discovered where the minimum equatorial field is substantially larger and located closer to Earth. The magnetic field tailward of the minimum is also much larger, and the corresponding region of accumulated magnetic flux may occupy a very short tail region. The equatorial current and plasma pressure are found to be strongly enhanced far beyond geosynchronous orbit and in a broad local time interval covering the whole nightside region. This picture is consistent with independent recent statistical studies of the SMC pressure distributions, global MHD and kinetic RCM-E simulations. Distributions of the flux tube volume and entropy inferred from data reveal different mechanisms of the magnetotail convection crisis resolution for two classes of SMC events.

  7. Timing and tempo of the Great Oxidation Event

    PubMed Central

    Chamberlain, Kevin R.; Bleeker, Wouter; Söderlund, Ulf; de Kock, Michiel O.; Larsson, Emilie R.; Bekker, Andrey

    2017-01-01

    The first significant buildup in atmospheric oxygen, the Great Oxidation Event (GOE), began in the early Paleoproterozoic in association with global glaciations and continued until the end of the Lomagundi carbon isotope excursion ca. 2,060 Ma. The exact timing of and relationships among these events are debated because of poor age constraints and contradictory stratigraphic correlations. Here, we show that the first Paleoproterozoic global glaciation and the onset of the GOE occurred between ca. 2,460 and 2,426 Ma, ∼100 My earlier than previously estimated, based on an age of 2,426 ± 3 Ma for Ongeluk Formation magmatism from the Kaapvaal Craton of southern Africa. This age helps define a key paleomagnetic pole that positions the Kaapvaal Craton at equatorial latitudes of 11° ± 6° at this time. Furthermore, the rise of atmospheric oxygen was not monotonic, but was instead characterized by oscillations, which together with climatic instabilities may have continued over the next ∼200 My until ≤2,250–2,240 Ma. Ongeluk Formation volcanism at ca. 2,426 Ma was part of a large igneous province (LIP) and represents a waning stage in the emplacement of several temporally discrete LIPs across a large low-latitude continental landmass. These LIPs played critical, albeit complex, roles in the rise of oxygen and in both initiating and terminating global glaciations. This series of events invites comparison with the Neoproterozoic oxygen increase and Sturtian Snowball Earth glaciation, which accompanied emplacement of LIPs across supercontinent Rodinia, also positioned at low latitude. PMID:28167763

  8. What controls the local time extent of flux transfer events?

    NASA Astrophysics Data System (ADS)

    Milan, S. E.; Imber, S. M.; Carter, J. A.; Walach, M.-T.; Hubert, B.

    2016-02-01

    Flux transfer events (FTEs) are the manifestation of bursty and/or patchy magnetic reconnection at the magnetopause. We compare two sequences of the ionospheric signatures of flux transfer events observed in global auroral imagery and coherent ionospheric radar measurements. Both sequences were observed during very similar seasonal and interplanetary magnetic field (IMF) conditions, though with differing solar wind speed. A key observation is that the signatures differed considerably in their local time extent. The two periods are 26 August 1998, when the IMF had components BZ≈-10 nT and BY≈9 nT and the solar wind speed was VX≈650 km s-1, and 31 August 2005, IMF BZ≈-7 nT, BY≈17 nT, and VX≈380 km s-1. In the first case, the reconnection rate was estimated to be near 160 kV, and the FTE signatures extended across at least 7 h of magnetic local time (MLT) of the dayside polar cap boundary. In the second, a reconnection rate close to 80 kV was estimated, and the FTEs had a MLT extent of roughly 2 h. We discuss the ramifications of these differences for solar wind-magnetosphere coupling.

  9. Intelligent fuzzy controller for event-driven real time systems

    NASA Technical Reports Server (NTRS)

    Grantner, Janos; Patyra, Marek; Stachowicz, Marian S.

    1992-01-01

    Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.

  10. An introduction to real-time graphical techniques for analyzing multivariate data

    NASA Astrophysics Data System (ADS)

    Friedman, Jerome H.; McDonald, John Alan; Stuetzle, Werner

    1987-08-01

    Orion I is a graphics system used to study applications of computer graphics - especially interactive motion graphics - in statistics. Orion I is the newest of a family of "Prim" systems, whose most striking common feature is the use of real-time motion graphics to display three dimensional scatterplots. Orion I differs from earlier Prim systems through the use of modern and relatively inexpensive raster graphics and microprocessor technology. It also delivers more computing power to its user; Orion I can perform more sophisticated real-time computations than were possible on previous such systems. We demonstrate some of Orion I's capabilities in our film: "Exploring data with Orion I".

  11. Detection of intermittent events in atmospheric time series

    NASA Astrophysics Data System (ADS)

    Paradisi, P.; Cesari, R.; Palatella, L.; Contini, D.; Donateo, A.

    2009-04-01

    The modeling approach in atmospheric sciences is based on the assumption that local fluxes of mass, momentum, heat, etc... can be described as linear functions of the local gradient of some intensive property (concentration, flow strain, temperature,...). This is essentially associated with Gaussian statistics and short range (exponential) correlations. However, the atmosphere is a complex dynamical system displaying a wide range of spatial and temporal scales. A global description of the atmospheric dynamics should include a great number of degrees of freedom, strongly interacting on several temporal and spatial scales, thus generating long range (power-law) correlations and non-Gaussian distribution of fluctuations (Lévy flights, Lévy walks, Continuous Time Random Walks) [1]. This is typically associated with anomalous diffusion and scaling, non-trivial memory features and correlation decays and, especially, with the emergence of flux-gradient relationships that are non-linear and/or non-local in time and/or space. Actually, the local flux-gradient relationship is greatly preferred due to a more clear physical meaning, allowing to perform direct comparisons with experimental data, and, especially, to smaller computational costs in numerical models. In particular, the linearity of this relationship allows to define a transport coefficient (e.g., turbulent diffusivity) and the modeling effort is usually focused on this coefficient. However, the validity of the local (and linear) flux-gradient model is strongly dependent on the range of spatial and temporal scales represented by the model and, consequently, by the sub-grid processes included in the flux-gradient relationship. In this work, in order to check the validity of local and linear flux-gradient relationships, an approach based on the concept of renewal critical events [2] is introduced. In fact, in renewal theory [2], the dynamical origin of anomalous behaviour and non-local flux-gradient relation is

  12. Time use choices and healthy body weight: A multivariate analysis of data from the American Time use Survey

    PubMed Central

    2011-01-01

    Background We examine the relationship between time use choices and healthy body weight as measured by survey respondents' body mass index (BMI). Using data from the 2006 and 2007 American Time Use Surveys, we expand upon earlier research by including more detailed measures of time spent eating as well as measures of physical activity time and sedentary time. We also estimate three alternative models that relate time use to BMI. Results Our results suggest that time use and BMI are simultaneously determined. The preferred empirical model reveals evidence of an inverse relationship between time spent eating and BMI for women and men. In contrast, time spent drinking beverages while simultaneously doing other things and time spent watching television/videos are positively linked to BMI. For women only, time spent in food preparation and clean-up is inversely related to BMI while for men only, time spent sleeping is inversely related to BMI. Models that include grocery prices, opportunity costs of time, and nonwage income reveal that as these economic variables increase, BMI declines. Conclusions In this large, nationally representative data set, our analyses that correct for time use endogeneity reveal that the Americans' time use decisions have implications for their BMI. The analyses suggest that both eating time and context (i.e., while doing other tasks simultaneously) matters as does time spent in food preparation, and time spent in sedentary activities. Reduced form models suggest that shifts in grocery prices, opportunity costs of time, and nonwage income may be contributing to alterations in time use patterns and food choices that have implications for BMI. PMID:21810246

  13. Higher Dimensional Clayton–Oakes Models for Multivariate Failure Time Data

    PubMed Central

    Prentice, R. L.

    2016-01-01

    Summary The Clayton–Oakes bivariate failure time model is extended to dimensions m > 2 in a manner that allows unspecified marginal survivor functions for all dimensions less than m. Special cases that allow unspecified marginal survivor functions of dimension q with q < m, while making some provisions for dependencies of dimension greater than q, are also described. PMID:27738350

  14. MULTIVARIATE STATISTICAL MODELS FOR EFFECTS OF PM AND COPOLLUTANTS IN A DAILY TIME SERIES EPIDEMIOLOGY STUDY

    EPA Science Inventory

    Most analyses of daily time series epidemiology data relate mortality or morbidity counts to PM and other air pollutants by means of single-outcome regression models using multiple predictors, without taking into account the complex statistical structure of the predictor variable...

  15. Classification of broiler breast filets according to deboning time using near infrared spectroscopy and multivariate analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Chicken breast filets were deboned and NIR spectra were collected after 2, 4, and 24 hours. The deboning was performed on pairs of filets to minimize differences due only to the meat and not the deboning time (i.e. right at 2 hours, left at 24; right at 2, left at 4; right at 4, left at 24 hrs). The...

  16. Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

    DOE PAGES

    Steed, Chad A.; Halsey, William; Dehoff, Ryan; ...

    2017-02-16

    Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

  17. Event coincidence analysis for quantifying statistical interrelationships between event time series. On the role of flood events as triggers of epidemic outbreaks

    NASA Astrophysics Data System (ADS)

    Donges, J. F.; Schleussner, C.-F.; Siegmund, J. F.; Donner, R. V.

    2016-05-01

    Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.

  18. Putting Predictive Models to Use: Scoring of Unseen Streaming Data using a Multivariate Time Series Classification Tool

    NASA Astrophysics Data System (ADS)

    Sipes, T.; Karimabadi, H.; Imber, S. M.; Slavin, J. A.; Pothier, N. M.; Coeli, R.

    2013-12-01

    Advances in data collection and data storage technologies have made the assembly of multivariate time series data more common. Data analysis and extraction of knowledge from such massive and complex datasets encountered in space physics today present a major obstacle to fully utilizing our vast data repositories and to scientific progress. In the previous years we introduced a time series classification tool MineTool-TS [Karimabadi et al, 2009] and its extension to simulation and streaming data [Sipes& Karimabadi, 2012, 2013]. In this work we demonstrate the applicability and real world utility of the predictive models created using the tool to scoring and labeling of a large dataset of unseen, streaming data. Predictive models that are created are based on the assumption that the training data used to create them is a true representative of the population. Multivariate time series datasets are also characterized by large amounts of variability and potential background noise. Moreover, there are multiple issues being raised by the streaming nature of the data. In this work we illustrate how we dealt with these challenges and demonstrate the results in a study of flux ropes in the plasma sheet. We have used an iterative process of building a predictive model using the original labeled training set, tested it on a week worth of streaming data, had the results checked by a scientific expert in the domain, and fed the results and the labels back into the training set, creating a large training set and using it to produce the final model. This final model was then put to use to predict a very large, unseen, six month period of streaming data. In this work we present the results of our machine learning approach to automatically detect flux ropes in spacecraft data.

  19. Real-time performance analysis of wireless multimedia networks based on partially observed multivariate point processes

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2000-07-01

    Third-generation (3G) wireless networks will support integrated multimedia services based on a cellular extension of a packet-switched architecture using variants of the Internet protocol (IP). Services can be categorized as real- time and delay-sensitive, or non-real-time and delay- insensitive. Each call, arriving to or active within the network, carries demand for one or more services in parallel; each service type with a guaranteed quality of service (QoS). Admission of new calls to the wireless IP network (WIN) from the gateway of a wired network or from a mobile subscriber (MS) is allowed by call admission control procedures. Roaming of the MSs among the nodes of the WIN is controlled by handoff procedures between base stations (BSs), or BS controllers, and the MSs. Metrics such as the probabilities of call blocking and dropping, handoff transition time, processing latency of a call, throughput, and capacity are used to evaluate the performance of network control procedures. The metrics are directly related to the network resources required to provide the QoS for the integrated services.

  20. DeCon: A tool to detect emotional concordance in multivariate time series data of emotional responding

    PubMed Central

    Bulteel, Kirsten; Ceulemans, Eva; Thompson, Renee J.; Waugh, Christian E.; Gotlib, Ian H.; Tuerlinckx, Francis; Kuppens, Peter

    2013-01-01

    The occurrence of concordance among different response components during an emotional episode is a key feature of several contemporary accounts and definitions of emotion. Yet, capturing such response concordance in empirical data has proven to be elusive, in large part because of a lack of appropriate statistical tools that are tailored to measure the intricacies of response concordance in the context of data on emotional responding. In this article, we present a tool we developed to detect two different forms of response concordance—response patterning and synchronization—in multivariate time series data of emotional responding, and apply this tool to data concerning physiological responding to emotional stimuli. While the findings provide partial evidence for both response patterning and synchronization, they also show that the presence and nature of such patterning and synchronization is strongly person-dependent. PMID:24220647

  1. A new proposal for multivariable modelling of time-varying effects in survival data based on fractional polynomial time-transformation.

    PubMed

    Sauerbrei, Willi; Royston, Patrick; Look, Maxime

    2007-06-01

    The Cox proportional hazards model has become the standard for the analysis of survival time data in cancer and other chronic diseases. In most studies, proportional hazards (PH) are assumed for covariate effects. With long-term follow-up, the PH assumption may be violated, leading to poor model fit. To accommodate non-PH effects, we introduce a new procedure, MFPT, an extension of the multivariable fractional polynomial (MFP) approach, to do the following: (1) select influential variables; (2) determine a sensible dose-response function for continuous variables; (3) investigate time-varying effects; (4) model such time-varying effects on a continuous scale. Assuming PH initially, we start with a detailed model-building step, including a search for possible non-linear functions for continuous covariates. Sometimes a variable with a strong short-term effect may appear weak or non-influential if 'averaged' over time under the PH assumption. To protect against omitting such variables, we repeat the analysis over a restricted time-interval. Any additional prognostic variables identified by this second analysis are added to create our final time-fixed multivariable model. Using a forward-selection algorithm we search for possible improvements in fit by adding time-varying covariates. The first part to create a final time-fixed model does not require the use of MFP. A model may be given from 'outside' or a different strategy may be preferred for this part. This broadens the scope of the time-varying part. To motivate and illustrate the methodology, we create prognostic models from a large database of patients with primary breast cancer. Non-linear time-fixed effects are found for progesterone receptor status and number of positive lymph nodes. Highly statistically significant time-varying effects are present for progesterone receptor status and tumour size.

  2. UNCERTAINTY IN PHASE ARRIVAL TIME PICKS FOR REGIONAL SEISMIC EVENTS: AN EXPERIMENTAL DESIGN

    SciTech Connect

    A. VELASCO; ET AL

    2001-02-01

    The detection and timing of seismic arrivals play a critical role in the ability to locate seismic events, especially at low magnitude. Errors can occur with the determination of the timing of the arrivals, whether these errors are made by automated processing or by an analyst. One of the major obstacles encountered in properly estimating travel-time picking error is the lack of a clear and comprehensive discussion of all of the factors that influence phase picks. This report discusses possible factors that need to be modeled to properly study phase arrival time picking errors. We have developed a multivariate statistical model, experimental design, and analysis strategy that can be used in this study. We have embedded a general form of the International Data Center(IDC)/U.S. National Data Center (USNDC) phase pick measurement error model into our statistical model. We can use this statistical model to optimally calibrate a picking error model to regional data. A follow-on report will present the results of this analysis plan applied to an implementation of an experiment/data-gathering task.

  3. Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data.

    PubMed

    Grootswagers, Tijl; Wardle, Susan G; Carlson, Thomas A

    2017-04-01

    Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

  4. Time course of salinity adaptation in a strongly euryhaline estuarine teleost, fundulus heteroclitus: A multivariable approach

    USGS Publications Warehouse

    Marshall, W.S.; Emberley, T.R.; Singer, T.D.; Bryson, S.E.; McCormick, S.D.

    1999-01-01

    Freshwater-adapted killifish (Fundulus heteroclitus) were transferred directly from soft fresh water to full-strength sea water for periods of 1h, 3h, 8h and 1, 2, 7, 14 and 30 days. Controls were transferred to fresh water for 24 h. Measured variables included: blood [Na+], osmolality, glucose and cortisol levels, basal and stimulated rates of ion transport and permeability of in vitro opercular epithelium, gill Na+/K+-ATPase and citrate synthase activity and chloride cell ultrastructure. These data were compared with previously published killifish cystic fibrosis transmembrane conductance regulator (kfCFTR) expression in the gills measured over a similar time course. Plasma cortisol levels peaked at 1 h, coincident with a rise in plasma [Na+]. At 8 h after transfer to sea water, a time at which previous work has shown kfCFTR expression to be elevated, blood osmolality and [Na+] were high, and cortisol levels and opercular membrane short-circuit current (I(SC); a measure of Cl- secretion rate) were low. The 24h group, which showed the highest level of kfCFTR expression, had the highest plasma [Na+] and osmolality, elevated plasma cortisol levels, significantly lower opercular membrane resistance, an increased opercular membrane ion secretion rate and collapsed tubule inclusions in mitochondria-rich cells, but no change in gill Na+/K+-ATPase and citrate synthase activity or plasma glucose levels. Apparently, killifish have a rapid (<1h) cortisol response to salinity coupled to subsequent (8-48 h) expression of kfCFTR anion channel proteins in existing mitochondria-rich cells that convert transport from ion uptake to ion secretion.

  5. Relative timing of deglacial climate events in Antarctica and Greenland.

    PubMed

    Morgan, Vin; Delmotte, Marc; van Ommen, Tas; Jouzel, Jean; Chappellaz, Jérôme; Woon, Suenor; Masson-Delmotte, Valérie; Raynaud, Dominique

    2002-09-13

    The last deglaciation was marked by large, hemispheric, millennial-scale climate variations: the Bølling-Allerød and Younger Dryas periods in the north, and the Antarctic Cold Reversal in the south. A chronology from the high-accumulation Law Dome East Antarctic ice core constrains the relative timing of these two events and provides strong evidence that the cooling at the start of the Antarctic Cold Reversal did not follow the abrupt warming during the northern Bølling transition around 14,500 years ago. This result suggests that southern changes are not a direct response to abrupt changes in North Atlantic thermohaline circulation, as is assumed in the conventional picture of a hemispheric temperature seesaw.

  6. Detecting Rare Events in the Time-Domain

    SciTech Connect

    Rest, A; Garg, A

    2008-10-31

    One of the biggest challenges in current and future time-domain surveys is to extract the objects of interest from the immense data stream. There are two aspects to achieving this goal: detecting variable sources and classifying them. Difference imaging provides an elegant technique for identifying new transients or changes in source brightness. Much progress has been made in recent years toward refining the process. We discuss a selection of pitfalls that can afflict an automated difference imagine pipeline and describe some solutions. After identifying true astrophysical variables, we are faced with the challenge of classifying them. For rare events, such as supernovae and microlensing, this challenge is magnified because we must balance having selection criteria that select for the largest number of objects of interest against a high contamination rate. We discuss considerations and techniques for developing classification schemes.

  7. Simplifying Facility and Event Scheduling: Saving Time and Money.

    ERIC Educational Resources Information Center

    Raasch, Kevin

    2003-01-01

    Describes a product called the Event Management System (EMS), a computer software program to manage facility and event scheduling. Provides example of the school district and university uses of EMS. Describes steps in selecting a scheduling-management system. (PKP)

  8. Frey syndrome: factors influencing the time to event.

    PubMed

    Lafont, M; Whyte, A; Whyte, J; Saura, E; Tejedor, M T

    2015-07-01

    Frey syndrome is a common complication after parotidectomy. The time from surgery to disease onset may be quite long; therefore, a time-to-event analysis was performed for the occurrence of this syndrome post-parotidectomy. Three hundred and thirty-four patients who underwent a parotidectomy between January 2002 and November 2012 were identified (retrospective study). Of these patients, 102 developed Frey syndrome post-surgery and 232 did not. The time-to-onset analysis enabled us to estimate the risk ratio associated with different types of parotid gland tumours, various parotidectomy procedures, and repeat parotidectomy, which is useful for predicting preoperative and surgical risk. The risk of developing Frey syndrome was lower in patients with malignant tumours than in those with benign tumours (risk ratio 0.351, 95% confidence interval (CI) 0.155-0.594). Risk ratios for lumpectomy PA (pre-auricular area), superficial parotidectomy, and total parotidectomy with respect to lumpectomy T (tail) were 4.378 (95% CI 1.168-16.410), 8.040 (95% CI 3.286-19.670), and 8.174 (95% CI 3.076-21.723), respectively. Repeat parotidectomy also increased the risk of developing Frey syndrome (risk ratio 3.214, 95% CI 1.547-6.678). No effect of the use of a superficial muscular aponeurotic system (SMAS) flap on the risk of developing Frey syndrome was detected (P=0.888).

  9. Two step transfer entropy - An estimator of delayed directional couplings between multivariate EEG time series.

    PubMed

    Songhorzadeh, Maryam; Ansari-Asl, Karim; Mahmoudi, Alimorad

    2016-12-01

    Quantifying delayed directional couplings between electroencephalographic (EEG) time series requires an efficient method of causal network inference. This is especially due to the limited knowledge about the underlying dynamics of the brain activity. Recent methods based on information theoretic measures such as Transfer Entropy (TE) made significant progress on this issue by providing a model-free framework for causality detection. However, TE estimation from observed data is not a trivial task, especially when the number of variables is large which is the case in a highly complex system like human brain. Here we propose a computationally efficient procedure for TE estimation based on using sets of the Most Informative Variables that effectively contribute to resolving the uncertainty of the destination. In the first step of this method, some conditioning sets are determined through a nonlinear state space reconstruction; then in the second step, optimal estimation of TE is done based on these sets. Validation of the proposed method using synthetic data and neurophysiological signals demonstrates computational efficiency in quantifying delayed directional couplings compared with the common TE analysis.

  10. Time in Language: Event Duration in Language Comprehension

    ERIC Educational Resources Information Center

    Coll-Florit, Marta; Gennari, Silvia P.

    2011-01-01

    This work investigates how we process and represent event duration in on-line language comprehension. Specifically, it examines how events of different duration are processed and what type of knowledge underlies their representations. Studies 1-4 examined verbs and phrases in different contexts. They showed that durative events took longer to…

  11. Life events and depressive symptoms in African American adolescents: do ecological domains and timing of life events matter?

    PubMed

    Sanchez, Yadira M; Lambert, Sharon F; Ialongo, Nicholas S

    2012-04-01

    Considerable research has documented associations between adverse life events and internalizing symptoms in adolescents, but much of this research has focused on the number of events experienced, with less attention to the ecological context or timing of events. This study examined life events in three ecological domains relevant to adolescents (i.e., family, peers, themselves) as predictors of the course of depressive symptoms among a community epidemiologically defined sample of 419 (47.2% females) urban African American adolescents. Given that youth depressive symptoms change over time, grade level was examined as a moderator. For males, the strength of associations between life events happening to participants, family life events, and peer life events and depressive symptoms did not change from grades 6-9. For females, the strength of the association between peer life events and depressive symptoms did not change over time, but the strength of associations between life events happening to participants and family life events and females' depressive symptoms decreased over time. Implications of the findings and directions for future research are discussed.

  12. Time to tenure in Spanish universities: an event history analysis.

    PubMed

    Sanz-Menéndez, Luis; Cruz-Castro, Laura; Alva, Kenedy

    2013-01-01

    Understanding how institutional incentives and mechanisms for assigning recognition shape access to a permanent job is important. This study, based on data from questionnaire survey responses and publications of 1,257 university science, biomedical and engineering faculty in Spain, attempts to understand the timing of getting a permanent position and the relevant factors that account for this transition, in the context of dilemmas between mobility and permanence faced by organizations. Using event history analysis, the paper looks at the time to promotion and the effects of some relevant covariates associated to academic performance, social embeddedness and mobility. We find that research productivity contributes to career acceleration, but that other variables are also significantly associated to a faster transition. Factors associated to the social elements of academic life also play a role in reducing the time from PhD graduation to tenure. However, mobility significantly increases the duration of the non-tenure stage. In contrast with previous findings, the role of sex is minor. The variations in the length of time to promotion across different scientific domains is confirmed, with faster career advancement for those in the Engineering and Technological Sciences compared with academics in the Biological and Biomedical Sciences. Results show clear effects of seniority, and rewards to loyalty, in addition to some measurements of performance and quality of the university granting the PhD, as key elements speeding up career advancement. Findings suggest the existence of a system based on granting early permanent jobs to those that combine social embeddedness and team integration with some good credentials regarding past and potential future performance, rather than high levels of mobility.

  13. Time to Tenure in Spanish Universities: An Event History Analysis

    PubMed Central

    Sanz-Menéndez, Luis; Cruz-Castro, Laura; Alva, Kenedy

    2013-01-01

    Understanding how institutional incentives and mechanisms for assigning recognition shape access to a permanent job is important. This study, based on data from questionnaire survey responses and publications of 1,257 university science, biomedical and engineering faculty in Spain, attempts to understand the timing of getting a permanent position and the relevant factors that account for this transition, in the context of dilemmas between mobility and permanence faced by organizations. Using event history analysis, the paper looks at the time to promotion and the effects of some relevant covariates associated to academic performance, social embeddedness and mobility. We find that research productivity contributes to career acceleration, but that other variables are also significantly associated to a faster transition. Factors associated to the social elements of academic life also play a role in reducing the time from PhD graduation to tenure. However, mobility significantly increases the duration of the non-tenure stage. In contrast with previous findings, the role of sex is minor. The variations in the length of time to promotion across different scientific domains is confirmed, with faster career advancement for those in the Engineering and Technological Sciences compared with academics in the Biological and Biomedical Sciences. Results show clear effects of seniority, and rewards to loyalty, in addition to some measurements of performance and quality of the university granting the PhD, as key elements speeding up career advancement. Findings suggest the existence of a system based on granting early permanent jobs to those that combine social embeddedness and team integration with some good credentials regarding past and potential future performance, rather than high levels of mobility. PMID:24116199

  14. Time warp: authorship shapes the perceived timing of actions and events.

    PubMed

    Ebert, Jeffrey P; Wegner, Daniel M

    2010-03-01

    It has been proposed that inferring personal authorship for an event gives rise to intentional binding, a perceptual illusion in which one's action and inferred effect seem closer in time than they otherwise would (Haggard, Clark, & Kalogeras, 2002). Using a novel, naturalistic paradigm, we conducted two experiments to test this hypothesis and examine the relationship between binding and self-reported authorship. In both experiments, an important authorship indicator - consistency between one's action and a subsequent event - was manipulated, and its effects on binding and self-reported authorship were measured. Results showed that action-event consistency enhanced both binding and self-reported authorship, supporting the hypothesis that binding arises from an inference of authorship. At the same time, evidence for a dissociation emerged, with consistency having a more robust effect on self-reports than on binding. Taken together, these results suggest that binding and self-reports reveal different aspects of the sense of authorship.

  15. Prediction of beef color using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate analyses.

    PubMed

    Moreira, Luiz Felipe Pompeu Prado; Ferrari, Adriana Cristina; Moraes, Tiago Bueno; Reis, Ricardo Andrade; Colnago, Luiz Alberto; Pereira, Fabíola Manhas Verbi

    2016-05-19

    Time-domain nuclear magnetic resonance and chemometrics were used to predict color parameters, such as lightness (L*), redness (a*), and yellowness (b*) of beef (Longissimus dorsi muscle) samples. Analyzing the relaxation decays with multivariate models performed with partial least-squares regression, color quality parameters were predicted. The partial least-squares models showed low errors independent of the sample size, indicating the potentiality of the method. Minced procedure and weighing were not necessary to improve the predictive performance of the models. The reduction of transverse relaxation time (T2 ) measured by Carr-Purcell-Meiboom-Gill pulse sequence in darker beef in comparison with lighter ones can be explained by the lower relaxivity Fe(2+) present in deoxymyoglobin and oxymyoglobin (red beef) to the higher relaxivity of Fe(3+) present in metmyoglobin (brown beef). These results point that time-domain nuclear magnetic resonance spectroscopy can become a useful tool for quality assessment of beef cattle on bulk of the sample and through-packages, because this technique is also widely applied to measure sensorial parameters, such as flavor, juiciness and tenderness, and physicochemical parameters, cooking loss, fat and moisture content, and instrumental tenderness using Warner Bratzler shear force. Copyright © 2016 John Wiley & Sons, Ltd.

  16. Generalization of the mechanisms of cross-correlation analysis in the case of a multivariate time series

    NASA Astrophysics Data System (ADS)

    Kravets, O. Ja; Abramov, G. V.; Beletskaja, S. Ju

    2017-02-01

    The article describes a generalization of the mechanisms of cross-correlation analysis in the case of a multivariate time series and how this allows the optimal lags to be identified for each of the independent variables (IV) using a number of algorithms. The use of generalized mechanisms will allow variables to be analysed and predicted based on the retrospective analysis of multidimensional data. In the available literature, cross-correlation has been defined only for pairs of time series. However, the study of dependent variable (DV) dependencies on multidimensional independent variables that takes into account the vector of specially selected time lags will significantly improve the quality of models based on multiple regression. The idea of multiple cross-correlation lies in the sequential forward shift of each IV row with respect to DV (it transpires that DV is delayed relative to IV) until we obtain a minimum error or the best test of multiple regression. After the completion of all stages of multiple cross-correlation, the synthesis of the model is not a difficult process.

  17. Time since discharge of 9mm cartridges by headspace analysis, part 2: Ageing study and estimation of the time since discharge using multivariate regression.

    PubMed

    Gallidabino, M; Romolo, F S; Weyermann, C

    2017-03-01

    Estimating the time since discharge of spent cartridges can be a valuable tool in the forensic investigation of firearm-related crimes. To reach this aim, it was previously proposed that the decrease of volatile organic compounds released during discharge is monitored over time using non-destructive headspace extraction techniques. While promising results were obtained for large-calibre cartridges (e.g., shotgun shells), handgun calibres yielded unsatisfying results. In addition to the natural complexity of the specimen itself, these can also be attributed to some selective choices in the methods development. Thus, the present series of papers aimed to systematically evaluate the potential of headspace analysis to estimate the time since discharge of cartridges through the use of more comprehensive analytical and interpretative techniques. Following the comprehensive optimisation and validation of an exhaustive headspace sorptive extraction (HSSE) method in the first part of this work, the present paper addresses the application of chemometric tools in order to systematically evaluate the potential of applying headspace analysis to estimate the time since discharge of 9mm Geco cartridges. Several multivariate regression and pre-treatment methods were tested and compared to univariate models based on non-linear regression. Random forests (RF) and partial least squares (PLS) proceeded by pairwise log-ratios normalisation (PLR) showed the best results, and allowed to estimate time since discharge up to 48h of ageing and to differentiate recently fired from older cartridges (e.g., less than 5h compared to more than 1-2 days). The proposed multivariate approaches showed significant improvement compared to univariate models. The effects of storage conditions were also tested and results demonstrated that temperature, humidity and cartridge position should be taken into account when estimating the time since discharge.

  18. Multivariate time series analysis on the dynamic relationship between Class B notifiable diseases and gross domestic product (GDP) in China.

    PubMed

    Zhang, Tao; Yin, Fei; Zhou, Ting; Zhang, Xing-Yu; Li, Xiao-Song

    2016-12-01

    The surveillance of infectious diseases is of great importance for disease control and prevention, and more attention should be paid to the Class B notifiable diseases in China. Meanwhile, according to the International Monetary Fund (IMF), the annual growth of Chinese gross domestic product (GDP) would decelerate below 7% after many years of soaring. Under such circumstances, this study aimed to answer what will happen to the incidence rates of infectious diseases in China if Chinese GDP growth remained below 7% in the next five years. Firstly, time plots and cross-correlation matrices were presented to illustrate the characteristics of data. Then, the multivariate time series (MTS) models were proposed to explore the dynamic relationship between incidence rates and GDP. Three kinds of MTS models, i.e., vector auto-regressive (VAR) model for original series, VAR model for differenced series and error-correction model (ECM), were considered in this study. The rank of error-correction term was taken as an indicator for model selection. Finally, our results suggested that four kinds of infectious diseases (epidemic hemorrhagic fever, pertussis, scarlet fever and syphilis) might need attention in China because their incidence rates have increased since the year 2010.

  19. Predictive modeling in Clostridium acetobutylicum fermentations employing Raman spectroscopy and multivariate data analysis for real-time culture monitoring

    NASA Astrophysics Data System (ADS)

    Zu, Theresah N. K.; Liu, Sanchao; Germane, Katherine L.; Servinsky, Matthew D.; Gerlach, Elliot S.; Mackie, David M.; Sund, Christian J.

    2016-05-01

    The coupling of optical fibers with Raman instrumentation has proven to be effective for real-time monitoring of chemical reactions and fermentations when combined with multivariate statistical data analysis. Raman spectroscopy is relatively fast, with little interference from the water peak present in fermentation media. Medical research has explored this technique for analysis of mammalian cultures for potential diagnosis of some cancers. Other organisms studied via this route include Escherichia coli, Saccharomyces cerevisiae, and some Bacillus sp., though very little work has been performed on Clostridium acetobutylicum cultures. C. acetobutylicum is a gram-positive anaerobic bacterium, which is highly sought after due to its ability to use a broad spectrum of substrates and produce useful byproducts through the well-known Acetone-Butanol-Ethanol (ABE) fermentation. In this work, real-time Raman data was acquired from C. acetobutylicum cultures grown on glucose. Samples were collected concurrently for comparative off-line product analysis. Partial-least squares (PLS) models were built both for agitated cultures and for static cultures from both datasets. Media components and metabolites monitored include glucose, butyric acid, acetic acid, and butanol. Models were cross-validated with independent datasets. Experiments with agitation were more favorable for modeling with goodness of fit (QY) values of 0.99 and goodness of prediction (Q2Y) values of 0.98. Static experiments did not model as well as agitated experiments. Raman results showed the static experiments were chaotic, especially during and shortly after manual sampling.

  20. Young Children's Memory for the Times of Personal Past Events

    ERIC Educational Resources Information Center

    Pathman, Thanujeni; Larkina, Marina; Burch, Melissa M.; Bauer, Patricia J.

    2013-01-01

    Remembering the temporal information associated with personal past events is critical for autobiographical memory, yet we know relatively little about the development of this capacity. In the present research, we investigated temporal memory for naturally occurring personal events in 4-, 6-, and 8-year-old children. Parents recorded unique events…

  1. Large Time Projection Chambers for Rare Event Detection

    SciTech Connect

    Heffner, M

    2009-11-03

    The Time Projection Chamber (TPC) concept [add ref to TPC section] has been applied to many projects outside of particle physics and the accelerator based experiments where it was initially developed. TPCs in non-accelerator particle physics experiments are principally focused on rare event detection (e.g. neutrino and darkmater experiments) and the physics of these experiments can place dramatically different constraints on the TPC design (only extensions to the traditional TPCs are discussed here). The drift gas, or liquid, is usually the target or matter under observation and due to very low signal rates a TPC with the largest active mass is desired. The large mass complicates particle tracking of short and sometimes very low energy particles. Other special design issues include, efficient light collection, background rejection, internal triggering and optimal energy resolution. Backgrounds from gamma-rays and neutrons are significant design issues in the construction of these TPCs. They are generally placed deep underground to shield from cosmogenic particles and surrounded with shielding to reduce radiation from the local surroundings. The construction materials have to be carefully screened for radiopurity as they are in close contact with the active mass and can be a signification source of background events. The TPC excels in reducing this internal background because the mass inside the fieldcage forms one monolithic volume from which fiducial cuts can be made ex post facto to isolate quiet drift mass, and can be circulated and purified to a very high level. Self shielding in these large mass systems can be significant and the effect improves with density. The liquid phase TPC can obtain a high density at low pressure which results in very good self-shielding and compact installation with a lightweight containment. The down sides are the need for cryogenics, slower charge drift, tracks shorter than the typical electron diffusion, lower energy resolution (e

  2. Events and children’s sense of time: a perspective on the origins of everyday time-keeping

    PubMed Central

    Forman, Helen

    2015-01-01

    In this article I discuss abstract or pure time versus the content of time, (i.e., events, activities, and other goings-on). Or, more specifically, the utility of these two sorts of time in time-keeping or temporal organization. It is often assumed that abstract, uniform, and objective time is a universal physical entity out there, which humans may perceive of. However, this sort of evenly flowing time was only recently introduced to the human community, together with the mechanical clock. Before the introduction of mechanical clock-time, there were only events available to denote the extent of time. Events defined time, unlike the way time may define events in our present day culture. It is therefore conceivable that our primeval or natural mode of time-keeping involves the perception, estimation, and coordination of events. I find it likely that events continues to subserve our sense of time and time-keeping efforts, especially for children who have not yet mastered the use of clock-time. Instead of seeing events as a distraction to our perception of time, I suggest that our experience and understanding of time emerges from our perception of events. PMID:25814969

  3. Validation of cross-sectional time series and multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents using doubly labeled water

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate, nonintrusive, and inexpensive techniques are needed to measure energy expenditure (EE) in free-living populations. Our primary aim in this study was to validate cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on observable participant cha...

  4. Off-Time Events and Life Quality of Older Adults.

    ERIC Educational Resources Information Center

    Goodhart, Darlene; Zautra, Alex

    Many previous studies have found that daily life events influence community residents' perceived quality of life, which refers to the relative goodness of life as evaluated subjectively. A subsample population of 539 older residents, aged 55 and over, were interviewed in their homes. A 60-item scale was devised to measure the effects of…

  5. Quantifying causal coupling strength: A lag-specific measure for multivariate time series related to transfer entropy

    NASA Astrophysics Data System (ADS)

    Runge, Jakob; Heitzig, Jobst; Marwan, Norbert; Kurths, Jürgen

    2012-12-01

    While it is an important problem to identify the existence of causal associations between two components of a multivariate time series, a topic addressed in Runge, Heitzig, Petoukhov, and Kurths [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.108.258701 108, 258701 (2012)], it is even more important to assess the strength of their association in a meaningful way. In the present article we focus on the problem of defining a meaningful coupling strength using information-theoretic measures and demonstrate the shortcomings of the well-known mutual information and transfer entropy. Instead, we propose a certain time-delayed conditional mutual information, the momentary information transfer (MIT), as a lag-specific measure of association that is general, causal, reflects a well interpretable notion of coupling strength, and is practically computable. Rooted in information theory, MIT is general in that it does not assume a certain model class underlying the process that generates the time series. As discussed in a previous paper [Runge, Heitzig, Petoukhov, and Kurths, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.108.258701 108, 258701 (2012)], the general framework of graphical models makes MIT causal in that it gives a nonzero value only to lagged components that are not independent conditional on the remaining process. Further, graphical models admit a low-dimensional formulation of conditions, which is important for a reliable estimation of conditional mutual information and, thus, makes MIT practically computable. MIT is based on the fundamental concept of source entropy, which we utilize to yield a notion of coupling strength that is, compared to mutual information and transfer entropy, well interpretable in that, for many cases, it solely depends on the interaction of the two components at a certain lag. In particular, MIT is, thus, in many cases able to exclude the misleading influence of autodependency within a process in an information-theoretic way

  6. Can Granger causality delineate natural versus anthropogenic drivers of climate change from global-average multivariate time series?

    NASA Astrophysics Data System (ADS)

    Kodra, E. A.; Chatterjee, S.; Ganguly, A. R.

    2009-12-01

    The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) notes with a high degree of certainty that global warming can be attributed to anthropogenic emissions. Detection and attribution studies, which attempt to delineate human influences on regional- and decadal-scale climate change or its impacts, use a variety of techniques, including Granger causality. Recently, Granger causality was used as a tool for detection and attribution in climate based on a spatio-temporal data mining approach. However, the degree to which Granger causality may be able to delineate natural versus anthropogenic drivers of change in these situations needs to be thoroughly investigated. As a first step, we use multivariate global-average time series of observations to test the performance of Granger causality. We apply the popular Granger F-tests to Radiative Forcing (RF), which is a transformation of carbon dioxide (CO2), and Global land surface Temperature anomalies (GT). Our preliminary results with observations appear to suggest that RF Granger-causes GT, which seem to become more apparent with more data. However, carefully designed simulations indicate that these results are not reliable and may, in fact, be misleading. On the other hand, the same observation- and simulation-driven methodologies, when applied to the El Niño Southern Oscillation (ENSO) index, clearly show reliable Granger-causality from ENSO to GT. We develop and test several hypotheses to explain why the Granger causality tests between RF and GT are not reliable. We conclude that the form of Granger causality used in this study, and in past studies reported in the literature, is sensitive to data availability, random variability, and especially whether the variables arise from a deterministic or stochastic process. Simulations indicate that Granger causality in this form performs poorly, even in simple linear effect cases, when applied to one deterministic and one stochastic time

  7. Near-real-time attribution of extreme weather events

    NASA Astrophysics Data System (ADS)

    Allen, M. R.; Pall, P.; Stone, D.; Stott, P.; Lohmann, D.

    2007-12-01

    As the impacts of global climate change become increasingly evident, there is growing demand for a quantitative and objective answer the the question of what is "to blame" for observed extreme weather phenomena. In addition to considerable public interest, understanding how external drivers, particularly secular trends such as anthropogenic greenhouse gas forcing, is important for the correct quantification of current weather-related risks for the insurance industry. We propose a method of quantifying the contribution of external drivers to weather-related risks based on a twinned ensemble design. Under this approach, a large ensemble of simulations with a forecast-resolution atmospheric model is driven with observed sea surface temperatures and atmospheric composition over the period of interest. A second ensemble is then generated with the influence of a particular external agent, such as anthropogenic greenhouse gases, removed through modification of composition and surface temperatures. Conventional detection and attribution techniques are used to allow for uncertainty in the magnitude and pattern of the signal removed. The frequency of occurrence of the weather event in question can then be compared between the two ensembles. For the exploration of changing risks of the most extreme events, very large ensembles (thousands of members, unprecedented for a model of this resolution) are needed, requiring a novel distributed computing approach, relying on computing resources donated by the general public: see http://attribution.cpdn.org. We focus as an example on the events of Autumn 2000 which brought widespread flooding to many regions of the UK. Precipitation from the twin ensembles is used to force an empirical run-off model to provide an estimate of its contribution to flood risk. Results are summarized in the form of an estimated fraction attributable risk for the anthropogenic contribution to the flooding events of that year.

  8. Handling time misalignment and rank deficiency in liquid chromatography by multivariate curve resolution: Quantitation of five biogenic amines in fish.

    PubMed

    Pinto, Licarion; Díaz Nieto, César Horacio; Zón, María Alicia; Fernández, Héctor; de Araujo, Mario Cesar Ugulino

    2016-01-01

    Biogenic amines (BAs) are used for identifying spoilage in food. The most common are tryptamine (TRY), 2-phenylethylamine (PHE), putrescine (PUT), cadaverine (CAD) and histamine (HIS). Due to lack of chromophores, chemical derivatization with dansyl was employed to analyze these BAs using high performance liquid chromatography with a diode array detector (HPLC-DAD). However, the derivatization reaction occurs with any primary or secondary amine, leading to co-elution of analytes and interferents with identical spectral profiles, and thus causing rank deficiency. When the spectral profile is the same and peak misalignment is present on the chromatographic runs, it is not possible to handle the data only with Multivariate Curve Resolution and Alternative Least Square (MCR-ALS), by augmenting the time, or the spectral mode. A way to circumvent this drawback is to receive information from another detector that leads to a selective profile for the analyte. To overcome both problems, (tri-linearity break in time, and spectral mode), this paper proposes a new analytical methodology for fast quantitation of these BAs in fish with HPLC-DAD by using the icoshift algorithm for temporal misalignment correction before MCR-ALS spectral mode augmented treatment. Limits of detection, relative errors of prediction (REP) and average recoveries, ranging from 0.14 to 0.50 µg mL(-1), 3.5-8.8% and 88.08%-99.68%, respectively. These are outstanding results obtained, reaching quantification limits for the five BAs much lower than those established by the Food and Agriculture Organization of the United Nations and World Health Organization (FAO/WHO), and the European Food Safety Authority (EFSA), all without any pre-concentration steps. The concentrations of BAs in fish samples ranged from 7.82 to 29.41 µg g(-1), 8.68-25.95 µg g(-1), 4.76-28.54 µg g(-1), 5.18-39.95 µg g(-1) and 1.45-52.62 µg g(-1) for TRY, PHE, PUT, CAD, and HIS, respectively. In addition, the proposed method spends

  9. Geological Time, Biological Events and the Learning Transfer Problem

    ERIC Educational Resources Information Center

    Johnson, Claudia C.; Middendorf, Joan; Rehrey, George; Dalkilic, Mehmet M.; Cassidy, Keely

    2014-01-01

    Comprehension of geologic time does not come easily, especially for students who are studying the earth sciences for the first time. This project investigated the potential success of two teaching interventions that were designed to help non-science majors enrolled in an introductory geology class gain a richer conceptual understanding of the…

  10. Reporting of Life Events Over Time: Methodological Issues in a Longitudinal Sample of Women

    ERIC Educational Resources Information Center

    Pachana, Nancy A.; Brilleman, Sam L.; Dobson, Annette J.

    2011-01-01

    The number of life events reported by study participants is sensitive to the method of data collection and time intervals under consideration. Individual characteristics also influence reporting; respondents with poor mental health report more life events. Much current research on life events is cross-sectional. Data from a longitudinal study of…

  11. Travel time classification of extreme solar events: Two families and an outlier

    NASA Astrophysics Data System (ADS)

    Freed, A. J.; Russell, C. T.

    2014-10-01

    Extreme solar events are of great interest because of the extensive damage that could be experienced by technological systems such as electrical transformers during such periods. In studying geophysical phenomena, it is helpful to have a quantitative measure of event strength so that similar events can be intercompared. Such a measure also allows the calculation of the occurrence rates of events with varying strength. We use historical fast travel time solar events to develop a measure of strength based on the Sun-Earth trip time. We find that these fast events can be grouped into two distinct families with one even faster outlier. That outlier is not the Carrington event of 1859 but the extremely intense solar particle event of August 1972.

  12. Reliability of travel time data computed from interpreted migrated events

    NASA Astrophysics Data System (ADS)

    Jannaud, L. R.

    1995-02-01

    In the Sequential Migration Aided Reflection Tomography (SMART) method, travel times used by reflection tomography are computed by tracing rays which propagate with the migration velocity and reflect from reflectors picked on migrated images. Because of limits of migration resolution, this picking involves inaccuracies, to which computed travel times are unfortunately very sensitive. The objective of this paper is to predict a priori the confidence we can have in emergence data, i.e., emergence point location and travel time, from the statistical information that describes the uncertainties of the reflectors. (These reflectors can be obtained by picking on migrated images as explained above or by any other method). The proposed method relies on a linearization of each step of the ray computation, allowing one to deduce, from the statistical properties of reflector fluctuations, the statistical properties of ray-tracing outputs. The computed confidences and correlations give access to a more realistic analysis of emergence data. Moreover, they can be used as inputs for reflection tomography to compute models that match travel times according to the confidence we have in the reflector. Applications on real data show that the uncertainties are generally large and, what is much more interesting, strongly varying from one ray to another. Taking them into account is therefore very important for both a better understanding of the kinematic information in the data and the computation of a model that matches these travel times.

  13. Parent–offspring similarity in the timing of developmental events: an origin of heterochrony?

    PubMed Central

    Tills, Oliver; Rundle, Simon D.; Spicer, John I.

    2013-01-01

    Understanding the link between ontogeny (development) and phylogeny (evolution) remains a key aim of biology. Heterochrony, the altered timing of developmental events between ancestors and descendants, could be such a link although the processes responsible for producing heterochrony, widely viewed as an interspecific phenomenon, are still unclear. However, intraspecific variation in developmental event timing, if heritable, could provide the raw material from which heterochronies originate. To date, however, heritable developmental event timing has not been demonstrated, although recent work did suggest a genetic basis for intraspecific differences in event timing in the embryonic development of the pond snail, Radix balthica. Consequently, here we used high-resolution (temporal and spatial) imaging of the entire embryonic development of R. balthica to perform a parent–offspring comparison of the timing of twelve, physiological and morphological developmental events. Between-parent differences in the timing of all events were good predictors of such timing differences between their offspring, and heritability was demonstrated for two of these events (foot attachment and crawling). Such heritable intraspecific variation in developmental event timing could be the raw material for speciation events, providing a fundamental link between ontogeny and phylogeny, via heterochrony. PMID:23966639

  14. Causal Context Presented in Subsequent Event Modifies the Perceived Timing of Cause and Effect

    PubMed Central

    Umemura, Hiroyuki

    2017-01-01

    The effect of perceived causality on other aspects of perception, such as temporal or spatial perception, has interested many researchers. Previous studies have shown that the perceived timing of two events is modulated when the events are intentionally produced or the causal link between the two events was known in advance. However, little research has directly supported the idea that causality alone can modulate the perceived timing of two events without having knowledge about causal links in advance. In this study, I used novel causal displays in which various types of causal contexts could be presented in subsequent events (movement or color change of objects). In these displays, the preceding events were the same (ball falling from above), so observers could not predict which subsequent events displayed. The results showed that the perceived causal context modulated the temporal relationship of two serial events so as to be consistent with the causal order implied by the subsequent event; ball hit the floor, then objects moved. These modulations were smaller when the movements implied preceding effect of the falling ball (e.g., wind pressure). These results are well-suited to the Bayesian framework in which the perceived timing of events is reconstructed through the observers' prior experiences, and suggest that multiple prior experiences would competitively contribute to the estimation of the timing of events. PMID:28326051

  15. Causal Context Presented in Subsequent Event Modifies the Perceived Timing of Cause and Effect.

    PubMed

    Umemura, Hiroyuki

    2017-01-01

    The effect of perceived causality on other aspects of perception, such as temporal or spatial perception, has interested many researchers. Previous studies have shown that the perceived timing of two events is modulated when the events are intentionally produced or the causal link between the two events was known in advance. However, little research has directly supported the idea that causality alone can modulate the perceived timing of two events without having knowledge about causal links in advance. In this study, I used novel causal displays in which various types of causal contexts could be presented in subsequent events (movement or color change of objects). In these displays, the preceding events were the same (ball falling from above), so observers could not predict which subsequent events displayed. The results showed that the perceived causal context modulated the temporal relationship of two serial events so as to be consistent with the causal order implied by the subsequent event; ball hit the floor, then objects moved. These modulations were smaller when the movements implied preceding effect of the falling ball (e.g., wind pressure). These results are well-suited to the Bayesian framework in which the perceived timing of events is reconstructed through the observers' prior experiences, and suggest that multiple prior experiences would competitively contribute to the estimation of the timing of events.

  16. Pipeline Implementation of Real Time Event Cross Correlation for Nuclear Treaty Monitoring

    NASA Astrophysics Data System (ADS)

    Junek, W. N.; Wehlen, J. A., III

    2014-12-01

    The United States National Data Center (US NDC) is responsible for monitoring international compliance to nuclear test ban treaties. This mission is performed through real time acquisition, processing, and evaluation of data acquired by a global network of seismic, hydroacoustic, and infrasonic sensors. Automatic and human reviewed event solutions are stored in a data warehouse which contains over 15 years of alphanumeric information and waveform data. A significant effort is underway to employ the data warehouse in real time processing to improve the quality of automatic event solutions, reduce analyst burden, and supply decision makers with information regarding relevant historic events. To this end, the US NDC processing pipeline has been modified to automatically recognize events built in the past. Event similarity information and the most relevant historic solution are passed to the human analyst to assist their evaluation of automatically formed events. This is achieved through real time cross correlation of selected seismograms from automatically formed events against those stored in the data warehouse. Historic events used in correlation analysis are selected based on a set of user defined parameters, which are tuned to maintain pipeline timeliness requirements. Software architecture and database infrastructure were modified using a multithreaded design for increased processing speed, database connection pools for parallel queries, and Oracle spatial indexing to enhance query efficiency. This functionality allows the human analyst to spend more time studying anomalous events and less time rebuilding routine events.

  17. Developmental and Cognitive Perspectives on Humans' Sense of the Times of Past and Future Events

    ERIC Educational Resources Information Center

    Friedman, W.J.

    2005-01-01

    Mental time travel in human adults includes a sense of when past events occurred and future events are expected to occur. Studies with adults and children reveal that a number of distinct psychological processes contribute to a temporally differentiated sense of the past and future. Adults possess representations of multiple time patterns, and…

  18. The Roles of Prior Experience and the Timing of Misinformation Presentation on Young Children's Event Memories

    ERIC Educational Resources Information Center

    Roberts, Kim P.; Powell, Martine B.

    2007-01-01

    The current study addressed how the timing of interviews affected children's memories of unique and repeated events. Five- to six-year-olds (N = 125) participated in activities 1 or 4 times and were misinformed either 3 or 21 days after the only or last event. Although single-experience children were subsequently less accurate in the 21- versus…

  19. Multivariate time-dependent comparison of the impact of lenalidomide in lower-risk myelodysplastic syndromes with chromosome 5q deletion.

    PubMed

    Sánchez-García, Joaquín; Del Cañizo, Consuelo; Lorenzo, Ignacio; Nomdedeu, Benet; Luño, Elisa; de Paz, Raquel; Xicoy, Blanca; Valcárcel, David; Brunet, Salut; Marco-Betes, Victor; García-Pintos, Marta; Osorio, Santiago; Tormo, Mar; Bailén, Alicia; Cerveró, Carlos; Ramos, Fernando; Diez-Campelo, María; Such, Esperanza; Arrizabalaga, Beatriz; Azaceta, Gemma; Bargay, Joan; Arilla, María J; Falantes, José; Serrano-López, Josefina; Sanz, Guillermo F

    2014-07-01

    The impact of lenalidomide treatment on long-term outcomes of patients with lower risk myelodysplastic syndromes (MDS) and chromosome 5q deletion (del(5q)) is unclear. This study used time-dependent multivariate methodology to analyse the influence of lenalidomide therapy on overall survival (OS) and acute myeloblastic leukaemia (AML) progression in 215 patients with International Prognostic Scoring System (IPSS) low or intermediate-1 risk and del(5q). There were significant differences in several relevant characteristics at presentation between patients receiving (n = 86) or not receiving lenalidomide (n = 129). The 5-year time-dependent probabilities of OS and progression to AML were 62% and 31% for patients receiving lenalidomide and 42% and 25% for patients not receiving lenalidomide; differences were not statistically significant in multivariate analysis that included all variables independently associated with those outcomes (OS, P = 0·45; risk of AML, P = 0·31, respectively). Achievement of RBC transfusion independency (P = 0·069) or cytogenetic response (P = 0·021) after lenalidomide was associated with longer OS in multivariate analysis. These data clearly show that response to lenalidomide results in a substantial clinical benefit in lower risk MDS patients with del(5q). Lenalidomide treatment does not appear to increase AML risk in this population of patients.

  20. Human error and time of occurrence in hazardous material events in mining and manufacturing.

    PubMed

    Ruckart, Perri Zeitz; Burgess, Paula A

    2007-04-11

    Human error has played a role in several large-scale hazardous materials events. To assess how human error and time of occurrence may have contributed to acute chemical releases, data from the Hazardous Substances Emergency Events Surveillance (HSEES) system for 1996-2003 were analyzed. Analyses were restricted to events in mining or manufacturing where human error was a contributing factor. The temporal distribution of releases was also evaluated to determine if the night shift impacted releases due to human error. Human error-related events in mining and manufacturing resulted in almost four times as many events with victims and almost three times as many events with evacuations compared with events in these industries where human error was not a contributing factor (10.3% versus 2.7% and 11.8% versus 4.5%, respectively). Time of occurrence of events attributable to human error in mining and manufacturing showed a widespread distribution for number of events, events with victims and evacuations, and hospitalizations and deaths, without apparent increased occurrence during the night shift. Utilizing human factor engineering in both front-end ergonomic design and retrospective incident investigation provides one potential systematic approach that may help minimize human error in workplace-related acute chemical releases and their resulting injuries.

  1. Predicting dose-time profiles of solar energetic particle events using Bayesian forecasting methods.

    PubMed

    Neal, J S; Townsend, L W

    2001-12-01

    Bayesian inference techniques, coupled with Markov chain Monte Carlo sampling methods, are used to predict dose-time profiles for energetic solar particle events. Inputs into the predictive methodology are dose and dose-rate measurements obtained early in the event. Surrogate dose values are grouped in hierarchical models to express relationships among similar solar particle events. Models assume nonlinear, sigmoidal growth for dose throughout an event. Markov chain Monte Carlo methods are used to sample from Bayesian posterior predictive distributions for dose and dose rate. Example predictions are provided for the November 8, 2000, and August 12, 1989, solar particle events.

  2. Time-varying exposure and the impact of stressful life events on onset of affective disorder.

    PubMed

    Wainwright, Nicholas W J; Surtees, Paul G

    2002-07-30

    Stressful life events are now established as risk factors for the onset of affective disorder but few studies have investigated time-varying exposure effects. Discrete (grouped) time survival methods provide a flexible framework for evaluating multiple time-dependent covariates and time-varying covariate effects. Here, we use these methods to investigate the time-varying influence of life events on the onset of affective disorder. Various straightforward time-varying exposure models are compared, involving one or more (stepped) time-dependent covariates and time-dependent covariates constructed or estimated according to exponential decay. These models are applied to data from two quite different studies. The first, a small scale interviewer-based longitudinal study (n = 180) concerned with affective disorder onset following loss (or threat of loss) event experiences. The second, a questionnaire assessment as part of an ongoing population study (n = 3353), provides a history of marital loss events and of depressive disorder onset. From the first study the initial impact of loss events was found to decay with a half-life of 5 weeks. Psychological coping strategy was found to modify vulnerability to the adverse effects of these events. The second study revealed that while men had a lower immediate risk of disorder onset following loss event experience their risk period was greater than for women. Time-varying exposure effects were well described by the appropriate use of simple time-dependent covariates.

  3. Time sequence of events leading to chromosomal aberration formation

    SciTech Connect

    Moore, R.C. ); Bender, M.A. )

    1993-01-01

    Investigations have been carried out on the influence of the repair polymerases on the yield of different types of chromosomal aberrations. The studies were mainly concerned with the effect of inhibiting the polymerases on the yield of aberrations. The polymerases fill in single-strand regions, and the fact that their inhibition affects the yield of aberrations suggests that single-strand lesions are influential in aberration formation. The results indicate that there are two actions of polymerases in clastogenesis. One is in their involvement in a G[sub 2] repair system, in which either of the two chromatids is concerned, and which does not yield aberrations unless the inhibition is still operating when the cells enter mitosis. The second is such that when repair is inhibited, further damage accrues. The second action is affected by inhibiting polymerase repair, but also operates even when the repair enzymes are active. The production of chromosomal exchanges involves a series of reactions, some of which are reversible. The time span over which the reactions occur is much longer than has been envisaged previously.

  4. Time sequence of events leading to chromosomal aberration formation

    SciTech Connect

    Moore, R.C.; Bender, M.A.

    1993-05-01

    Investigations have been carried out on the influence of the repair polymerases on the yield of different types of chromosomal aberrations. The studies were mainly concerned with the effect of inhibiting the polymerases on the yield of aberrations. The polymerases fill in single-strand regions, and the fact that their inhibition affects the yield of aberrations suggests that single-strand lesions are influential in aberration formation. The results indicate that there are two actions of polymerases in clastogenesis. One is in their involvement in a G{sub 2} repair system, in which either of the two chromatids is concerned, and which does not yield aberrations unless the inhibition is still operating when the cells enter mitosis. The second is such that when repair is inhibited, further damage accrues. The second action is affected by inhibiting polymerase repair, but also operates even when the repair enzymes are active. The production of chromosomal exchanges involves a series of reactions, some of which are reversible. The time span over which the reactions occur is much longer than has been envisaged previously.

  5. Angles of multivariable root loci

    NASA Technical Reports Server (NTRS)

    Thompson, P. M.; Stein, G.; Laub, A. J.

    1982-01-01

    A generalized eigenvalue problem is demonstrated to be useful for computing the multivariable root locus, particularly when obtaining the arrival angles to finite transmission zeros. The multivariable root loci are found for a linear, time-invariant output feedback problem. The problem is then employed to compute a closed-loop eigenstructure. The method of computing angles on the root locus is demonstrated, and the method is extended to a multivariable optimal root locus.

  6. Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture.

    PubMed

    Sweeting, Michael J; Thompson, Simon G

    2011-09-01

    Shared random effects joint models are becoming increasingly popular for investigating the relationship between longitudinal and time-to-event data. Although appealing, such complex models are computationally intensive, and quick, approximate methods may provide a reasonable alternative. In this paper, we first compare the shared random effects model with two approximate approaches: a naïve proportional hazards model with time-dependent covariate and a two-stage joint model, which uses plug-in estimates of the fitted values from a longitudinal analysis as covariates in a survival model. We show that the approximate approaches should be avoided since they can severely underestimate any association between the current underlying longitudinal value and the event hazard. We present classical and Bayesian implementations of the shared random effects model and highlight the advantages of the latter for making predictions. We then apply the models described to a study of abdominal aortic aneurysms (AAA) to investigate the association between AAA diameter and the hazard of AAA rupture. Out-of-sample predictions of future AAA growth and hazard of rupture are derived from Bayesian posterior predictive distributions, which are easily calculated within an MCMC framework. Finally, using a multivariate survival sub-model we show that underlying diameter rather than the rate of growth is the most important predictor of AAA rupture.

  7. A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

    NASA Astrophysics Data System (ADS)

    Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

    2002-12-01

    The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

  8. Multivariate normality

    NASA Technical Reports Server (NTRS)

    Crutcher, H. L.; Falls, L. W.

    1976-01-01

    Sets of experimentally determined or routinely observed data provide information about the past, present and, hopefully, future sets of similarly produced data. An infinite set of statistical models exists which may be used to describe the data sets. The normal distribution is one model. If it serves at all, it serves well. If a data set, or a transformation of the set, representative of a larger population can be described by the normal distribution, then valid statistical inferences can be drawn. There are several tests which may be applied to a data set to determine whether the univariate normal model adequately describes the set. The chi-square test based on Pearson's work in the late nineteenth and early twentieth centuries is often used. Like all tests, it has some weaknesses which are discussed in elementary texts. Extension of the chi-square test to the multivariate normal model is provided. Tables and graphs permit easier application of the test in the higher dimensions. Several examples, using recorded data, illustrate the procedures. Tests of maximum absolute differences, mean sum of squares of residuals, runs and changes of sign are included in these tests. Dimensions one through five with selected sample sizes 11 to 101 are used to illustrate the statistical tests developed.

  9. Cognitive tasks in information analysis: Use of event dwell time to characterize component activities

    SciTech Connect

    Sanquist, Thomas F.; Greitzer, Frank L.; Slavich, Antoinette L.; Littlefield, Rik J.; Littlefield, Janis S.; Cowley, Paula J.

    2004-09-28

    Technology-based enhancement of information analysis requires a detailed understanding of the cognitive tasks involved in the process. The information search and report production tasks of the information analysis process were investigated through evaluation of time-stamped workstation data gathered with custom software. Model tasks simulated the search and production activities, and a sample of actual analyst data were also evaluated. Task event durations were calculated on the basis of millisecond-level time stamps, and distributions were plotted for analysis. The data indicate that task event time shows a cyclic pattern of variation, with shorter event durations (< 2 sec) reflecting information search and filtering, and longer event durations (> 10 sec) reflecting information evaluation. Application of cognitive principles to the interpretation of task event time data provides a basis for developing “cognitive signatures” of complex activities, and can facilitate the development of technology aids for information intensive tasks.

  10. Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach.

    PubMed

    Lie, Octavian V; van Mierlo, Pieter

    2017-01-01

    The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (<60). The aim of this study was to test two Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

  11. Time, space, and events in language and cognition: a comparative view.

    PubMed

    Sinha, Chris; Gärdenfors, Peter

    2014-10-01

    We propose an event-based account of the cognitive and linguistic representation of time and temporal relations. Human beings differ from nonhuman animals in entertaining and communicating elaborate detached (as opposed to cued) event representations and temporal relational schemas. We distinguish deictically based (D-time) from sequentially based (S-time) representations, identifying these with the philosophical categories of A-series and B-series time. On the basis of cross-linguistic data, we claim that all cultures employ both D-time and S-time representations. We outline a cognitive model of event structure, emphasizing that this does not entail an explicit, separate representation of a time dimension. We propose that the notion of an event-independent, metric "time as such" is not universal, but a cultural and historical construction based on cognitive technologies for measuring time intervals. We critically examine claims that time is universally conceptualized in terms of spatial metaphors, and hypothesize that systematic space-time metaphor is only found in languages and cultures that have constructed the notion of time as a separate dimension. We emphasize the importance of distinguishing what is universal from what is variable in cultural and linguistic representations of time, and speculate on the general implications of an event-based understanding of time.

  12. Monitoring Natural Events Globally in Near Real-Time Using NASA's Open Web Services and Tools

    NASA Technical Reports Server (NTRS)

    Boller, Ryan A.; Ward, Kevin Alan; Murphy, Kevin J.

    2015-01-01

    Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based missions, many of which can be useful for monitoring natural events. In recent years, these measurements have been made available in near real-time, making it possible to use them to also aid in managing the response to natural events. We present the challenges and ongoing solutions to using NASA satellite data for monitoring and managing these events.

  13. Neural Network-Based Event-Triggered State Feedback Control of Nonlinear Continuous-Time Systems.

    PubMed

    Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

    2016-03-01

    This paper presents a novel approximation-based event-triggered control of multi-input multi-output uncertain nonlinear continuous-time systems in affine form. The controller is approximated using a linearly parameterized neural network (NN) in the context of event-based sampling. After revisiting the NN approximation property in the context of event-based sampling, an event-triggered condition is proposed using the Lyapunov technique to reduce the network resource utilization and to generate the required number of events for the NN approximation. In addition, a novel weight update law for aperiodic tuning of the NN weights at triggered instants is proposed to relax the knowledge of complete system dynamics and to reduce the computation when compared with the traditional NN-based control. Nonetheless, a nonzero positive lower bound for the inter-event times is guaranteed to avoid the accumulation of events or Zeno behavior. For analyzing the stability, the event-triggered system is modeled as a nonlinear impulsive dynamical system and the Lyapunov technique is used to show local ultimate boundedness of all signals. Furthermore, in order to overcome the unnecessary triggered events when the system states are inside the ultimate bound, a dead-zone operator is used to reset the event-trigger errors to zero. Finally, the analytical design is substantiated with numerical results.

  14. L/superscript-p/ stability /p ranging from 1 to infinity/ of multivariable non-linear time-varying feedback systems that are open-loop unstable

    NASA Technical Reports Server (NTRS)

    Callier, F. M.; Desoer, C. A.

    1974-01-01

    The loop transformation technique (Sandberg, 1965; Zames, 1966, Willems, 1971), and the fixed point theorem (Schwartz, 1970) are used to derive the L(superscript-p) stability for a class of multivariable nonlinear time-varying feedback systems which are open-loop unstable. The application of the fixed point theorem in L(superscript-p) shows that the nonlinear feedback system has one and only one solution for any pair of inputs in L(superscript-p), that the solutions are continuously dependent on the inputs, and that the closed loop system is L(superscript-p)-stable for any p ranging from 1 to infinity.

  15. Schizophrenia Spectrum Disorders Show Reduced Specificity and Less Positive Events in Mental Time Travel.

    PubMed

    Chen, Xing-Jie; Liu, Lu-Lu; Cui, Ji-Fang; Wang, Ya; Chen, An-Tao; Li, Feng-Hua; Wang, Wei-Hong; Zheng, Han-Feng; Gan, Ming-Yuan; Li, Chun-Qiu; Shum, David H K; Chan, Raymond C K

    2016-01-01

    Mental time travel refers to the ability to recall past events and to imagine possible future events. Schizophrenia (SCZ) patients have problems in remembering specific personal experiences in the past and imagining what will happen in the future. This study aimed to examine episodic past and future thinking in SCZ spectrum disorders including SCZ patients and individuals with schizotypal personality disorder (SPD) proneness who are at risk for developing SCZ. Thirty-two SCZ patients, 30 SPD proneness individuals, and 33 healthy controls participated in the study. The Sentence Completion for Events from the Past Test (SCEPT) and the Sentence Completion for Events in the Future Test were used to measure past and future thinking abilities. Results showed that SCZ patients showed significantly reduced specificity in recalling past and imagining future events, they generated less proportion of specific and extended events compared to healthy controls. SPD proneness individuals only generated less extended events compared to healthy controls. The reduced specificity was mainly manifested in imagining future events. Both SCZ patients and SPD proneness individuals generated less positive events than controls. These results suggest that mental time travel impairments in SCZ spectrum disorders and have implications for understanding their cognitive and emotional deficits.

  16. The Time-Scaling Issue in the Frequency Analysis of Multidimensional Extreme Events

    NASA Astrophysics Data System (ADS)

    Gonzalez, J.; Valdes, J. B.

    2004-05-01

    Extreme events, such as droughts, appear as a period of time where water availability differ exceptionally from normal condition. Several characteristic of this departure from the normality are important in analyzing droughts recurrence frequency (e.g. magnitude, maximum intensity, duration, severity,.). In this kind of problems, the time scale applied in the analyses may become an issue when applying conventional frequency analysis approaches, generally based on the run theory. Usually few (one or two) main event-characteristics may be used, and when the time-scale changes in orders of magnitude, the derived frequency significantly changes, so poor characterization is achieved. For example, sort time-scale empathies characteristic such as intensity, but long time scale does magnitude. That variability may be overcome using a new approach, where events are threatened as in-time-multidimensional. This is studied in this work by comparing analysis applying conventional approach and the new multidimensional approach, and using from daily to decadal time scale. The improve in the performance of applying multidimensional technique, whit which frequency remains characterized even using different time-scale order of magnitude, results the main outcome of the study. The ability of implicitly incorporate all event feature in the time distribution, made possible characterize the events, independently of the time-scale, if the scale does not hide the extreme features.

  17. Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor

    PubMed Central

    Simon Chane, Camille; Ieng, Sio-Hoi; Posch, Christoph; Benosman, Ryad B.

    2016-01-01

    The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (>143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time. PMID:27642275

  18. Asynchronous Periodic Edge-Event Triggered Control for Double-Integrator Networks With Communication Time Delays.

    PubMed

    Duan, Gaopeng; Xiao, Feng; Wang, Long

    2017-01-23

    This paper focuses on the average consensus of double-integrator networked systems based on the asynchronous periodic edge-event triggered control. The asynchronous property lies in the edge event-detecting procedure. For different edges, their event detections are performed at different times and the corresponding events occur independently of each other. When an event is activated, the two adjacent agents connected by the corresponding link sample their relative state information and update their controllers. The application of incidence matrix facilitates the transformation of control objects from the agent-based to the edge-based. Practically, due to the constraints of network bandwidth and communication distance, agents usually cannot receive the instantaneous information of some others, which has an impact on the system performance. Hence, it is necessary to investigate the presence of communication time delays. For double-integrator multiagent systems with and without communication time delays, the average state consensus can be asynchronously achieved by designing appropriate parameters under the proposed event-detecting rules. The presented results specify the relationship among the maximum allowable time delays, interaction topologies, and event-detecting periods. Furthermore, the proposed protocols have the advantages of reduced communication costs and controller-updating costs. Simulation examples are given to illustrate the proposed theoretical results.

  19. On the estimation of intracluster correlation for time-to-event outcomes in cluster randomized trials.

    PubMed

    Kalia, Sumeet; Klar, Neil; Donner, Allan

    2016-12-30

    Cluster randomized trials (CRTs) involve the random assignment of intact social units rather than independent subjects to intervention groups. Time-to-event outcomes often are endpoints in CRTs. Analyses of such data need to account for the correlation among cluster members. The intracluster correlation coefficient (ICC) is used to assess the similarity among binary and continuous outcomes that belong to the same cluster. However, estimating the ICC in CRTs with time-to-event outcomes is a challenge because of the presence of censored observations. The literature suggests that the ICC may be estimated using either censoring indicators or observed event times. A simulation study explores the effect of administrative censoring on estimating the ICC. Results show that ICC estimators derived from censoring indicators or observed event times are negatively biased. Analytic work further supports these results. Observed event times are preferred to estimate the ICC under minimum frequency of administrative censoring. To our knowledge, the existing literature provides no practical guidance on the estimation of ICC when substantial amount of administrative censoring is present. The results from this study corroborate the need for further methodological research on estimating the ICC for correlated time-to-event outcomes. Copyright © 2016 John Wiley & Sons, Ltd.

  20. WAITING TIME DISTRIBUTION OF SOLAR ENERGETIC PARTICLE EVENTS MODELED WITH A NON-STATIONARY POISSON PROCESS

    SciTech Connect

    Li, C.; Su, W.; Fang, C.; Zhong, S. J.; Wang, L.

    2014-09-10

    We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ∼Δt {sup –γ}. The SEEs display a broken power-law WTD. The power-law index is γ{sub 1} = 0.99 for the short waiting times (<70 hr) and γ{sub 2} = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, γ ∼ 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate λ = 1/Δt varies as the time distribution of event rate f(λ) = Aλ{sup –α}exp (– βλ), the time-dependent Poisson distribution can produce a power-law tail WTD of ∼Δt {sup α} {sup –3}, where 0 ≤ α < 2.

  1. Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm

    PubMed Central

    Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

    2016-01-01

    Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses. PMID:27706086

  2. Spatial Cueing in Time-Space Synesthetes: An Event-Related Brain Potential Study

    ERIC Educational Resources Information Center

    Teuscher, Ursina; Brang, David; Ramachandran, Vilayanur S.; Coulson, Seana

    2010-01-01

    Some people report that they consistently and involuntarily associate time events, such as months of the year, with specific spatial locations; a condition referred to as time-space synesthesia. The present study investigated the manner in which such synesthetic time-space associations affect visuo-spatial attention via an endogenous cuing…

  3. Stochastic Generation of Drought Events using Reconstructed Annual Streamflow Time Series from Tree Ring Analysis

    NASA Astrophysics Data System (ADS)

    Lopes, A.; Dracup, J. A.

    2011-12-01

    The statistical analysis of multiyear drought events in streamflow records is often restricted by the size of samples since only a few number of droughts events can be extracted from common river flow time series data. An alternative to those conventional datasets is the use of paleo hydrologic data such as streamflow time series reconstructed from tree ring analysis. In this study, we analyze the statistical characteristics of drought events present in a 1439 year long time series of reconstructed annual streamflow records at the Feather river inflow to the Oreville reservoir, California. Also, probabilistic distributions were used to describe duration and severity of drought events and the results were compared with previous studies that used only the observed streamflow data. Finally, a stochastic simulation model was developed to synthetically generate sequences of drought and high-flow events with the same characteristics of the paleo hydrologic record. The long term mean flow was used as the single truncation level to define 248 drought events and 248 high flow events with specific duration and severity. The longest drought and high flow events had 13 years (1471 to 1483) and 9 years of duration (1903 to 1911), respectively. A strong relationship between event duration and severity in both drought and high flow events were found so the longest droughts also corresponded to the more severe ones. Therefore, the events were classified by duration (in years) and probability distributions were fitted to the frequency distribution of drought and high flow severity for each duration. As a result, it was found that the gamma distribution describes well the frequency distribution of drought severities for all durations. For high flow events, the exponential distribution is more adequate for one year events while the gamma distribution is better suited for the longer events. Those distributions can be used to estimate the recurrence time of drought events according to

  4. Improving linear accelerator service response with a real-time electronic event reporting system.

    PubMed

    Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

    2014-09-01

    To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations. PACS

  5. Improving linear accelerator service response with a real- time electronic event reporting system.

    PubMed

    Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

    2014-09-08

    To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations.

  6. Multicomponent seismic noise attenuation with multivariate order statistic filters

    NASA Astrophysics Data System (ADS)

    Wang, Chao; Wang, Yun; Wang, Xiaokai; Xun, Chao

    2016-10-01

    The vector relationship between multicomponent seismic data is highly important for multicomponent processing and interpretation, but this vector relationship could be damaged when each component is processed individually. To overcome the drawback of standard component-by-component filtering, multivariate order statistic filters are introduced and extended to attenuate the noise of multicomponent seismic data by treating such dataset as a vector wavefield rather than a set of scalar fields. According to the characteristics of seismic signals, we implement this type of multivariate filtering along local events. First, the optimal local events are recognized according to the similarity between the vector signals which are windowed from neighbouring seismic traces with a sliding time window along each trial trajectory. An efficient strategy is used to reduce the computational cost of similarity measurement for vector signals. Next, one vector sample each from the neighbouring traces are extracted along the optimal local event as the input data for a multivariate filter. Different multivariate filters are optimal for different noise. The multichannel modified trimmed mean (MTM) filter, as one of the multivariate order statistic filters, is applied to synthetic and field multicomponent seismic data to test its performance for attenuating white Gaussian noise. The results indicate that the multichannel MTM filter can attenuate noise while preserving the relative amplitude information of multicomponent seismic data more effectively than a single-channel filter.

  7. Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming.

    PubMed

    Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

    2016-09-01

    This paper presents an event-triggered near optimal control of uncertain nonlinear discrete-time systems. Event-driven neurodynamic programming (NDP) is utilized to design the control policy. A neural network (NN)-based identifier, with event-based state and input vectors, is utilized to learn the system dynamics. An actor-critic framework is used to learn the cost function and the optimal control input. The NN weights of the identifier, the critic, and the actor NNs are tuned aperiodically once every triggered instant. An adaptive event-trigger condition to decide the trigger instants is derived. Thus, a suitable number of events are generated to ensure a desired accuracy of approximation. A near optimal performance is achieved without using value and/or policy iterations. A detailed analysis of nontrivial inter-event times with an explicit formula to show the reduction in computation is also derived. The Lyapunov technique is used in conjunction with the event-trigger condition to guarantee the ultimate boundedness of the closed-loop system. The simulation results are included to verify the performance of the controller. The net result is the development of event-driven NDP.

  8. Are Time- and Event-based Prospective Memory Comparably Affected in HIV Infection?†

    PubMed Central

    Zogg, Jennifer B.; Woods, Steven Paul; Weber, Erica; Doyle, Katie; Grant, Igor; Atkinson, J. Hampton; Ellis, Ronald J.; McCutchan, J. Allen; Marcotte, Thomas D.; Hale, Braden R.; Ellis, Ronald J.; McCutchan, J. Allen; Letendre, Scott; Capparelli, Edmund; Schrier, Rachel; Heaton, Robert K.; Cherner, Mariana; Moore, David J.; Jernigan, Terry; Fennema-Notestine, Christine; Archibald, Sarah L.; Hesselink, John; Annese, Jacopo; Taylor, Michael J.; Masliah, Eliezer; Everall, Ian; Langford, T. Dianne; Richman, Douglas; Smith, David M.; McCutchan, J. Allen; Everall, Ian; Lipton, Stuart; McCutchan, J. Allen; Atkinson, J. Hampton; Ellis, Ronald J.; Letendre, Scott; Atkinson, J. Hampton; von Jaeger, Rodney; Gamst, Anthony C.; Cushman, Clint; Masys, Daniel R.; Abramson, Ian; Ake, Christopher; Vaida, Florin

    2011-01-01

    According to the multi-process theory of prospective memory (ProM), time-based tasks rely more heavily on strategic processes dependent on prefrontal systems than do event-based tasks. Given the prominent frontostriatal pathophysiology of HIV infection, one would expect HIV-infected individuals to demonstrate greater deficits in time-based versus event-based ProM. However, the two prior studies examining this question have produced variable results. We evaluated this hypothesis in 143 individuals with HIV infection and 43 demographically similar seronegative adults (HIV−) who completed the research version of the Memory for Intentions Screening Test, which yields parallel subscales of time- and event-based ProM. Results showed main effects of HIV serostatus and cue type, but no interaction between serostatus and cue. Planned pair-wise comparisons showed a significant effect of HIV on time-based ProM and a trend-level effect on event-based ProM that was driven primarily by the subset of participants with HIV-associated neurocognitive disorders. Nevertheless, time-based ProM was more strongly correlated with measures of executive functions, attention/working memory, and verbal fluency in HIV-infected persons. Although HIV-associated deficits in time- and event-based ProM appear to be of comparable severity, the cognitive architecture of time-based ProM may be more strongly influenced by strategic monitoring and retrieval processes. PMID:21459901

  9. Case-based damage assessment of storm events in near real-time

    NASA Astrophysics Data System (ADS)

    Möhrle, Stella; Mühr, Bernhard

    2015-04-01

    Damage assessment in times of crisis is complex due to a highly dynamic environment and uncertainty in respect of available information. In order to assess the extent of a disaster in near real-time, historic events and their consequences may facilitate first estimations. Events of the past, which are in the same category or which have similar frame conditions like imminent or just occurring storms, might give preliminary information about possible damages. The challenge here is to identify useful historic events based on little information regarding the current event. This work investigates the potential of drawing conclusions about a current event based on similar historic disasters, exemplarily for storm events in Germany. Predicted wind speed and area affected can be used for roughly classifying a storm event. For this purpose, a grid of equidistant points can be used to split up the area of Germany. In combination with predicted wind speed at these points and the predicted number of points affected, respectively, a storm can be categorized in a fast manner. In contrast to investigate only data taken by the observation network, the grid approach is more objective, since stations are not equally distributed. Based on model data, the determined storm class provides one key factor for identifying similar historic events. Further aspects, such as region or specific event characteristics, complete knowledge about the potential storm scale and result in a similarity function, which automatically identifies useful events from the past. This work presents a case-based approach to estimate damages in the event of an extreme storm event in Germany. The focus in on the similarity function, which is based on model storm classes, particularly wind speed and area affected. In order to determine possible damages more precisely, event specific characteristics and region will be included. In the frame of determining similar storm events, neighboring storm classes will be

  10. A LORETA study of mental time travel: similar and distinct electrophysiological correlates of re-experiencing past events and pre-experiencing future events.

    PubMed

    Lavallee, Christina F; Persinger, Michael A

    2010-12-01

    Previous studies exploring mental time travel paradigms with functional neuroimaging techniques have uncovered both common and distinct neural correlates of re-experiencing past events or pre-experiencing future events. A gap in the mental time travel literature exists, as paradigms have not explored the affective component of re-experiencing past episodic events; this study explored this sparsely researched area. The present study employed standardized low resolution electromagnetic tomography (sLORETA) to identify electrophysiological correlates of re-experience affect-laden and non-affective past events, as well as pre-experiencing a future anticipated event. Our results confirm previous research and are also novel in that we illustrate common and distinct electrophysiological correlates of re-experiencing affective episodic events. Furthermore, research from this experiment yields results outlining a pattern of activation in the frontal and temporal regions is correlated with the time frame of past or future events subjects imagined.

  11. A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

    NASA Astrophysics Data System (ADS)

    Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

    2016-06-01

    In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865–1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.

  12. A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

    PubMed Central

    Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

    2016-01-01

    In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865–1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields. PMID:27293028

  13. Unbiased metabolite profiling by liquid chromatography-quadrupole time-of-flight mass spectrometry and multivariate data analysis for herbal authentication: classification of seven Lonicera species flower buds.

    PubMed

    Gao, Wen; Yang, Hua; Qi, Lian-Wen; Liu, E-Hu; Ren, Mei-Ting; Yan, Yu-Ting; Chen, Jun; Li, Ping

    2012-07-06

    Plant-based medicines become increasingly popular over the world. Authentication of herbal raw materials is important to ensure their safety and efficacy. Some herbs belonging to closely related species but differing in medicinal properties are difficult to be identified because of similar morphological and microscopic characteristics. Chromatographic fingerprinting is an alternative method to distinguish them. Existing approaches do not allow a comprehensive analysis for herbal authentication. We have now developed a strategy consisting of (1) full metabolic profiling of herbal medicines by rapid resolution liquid chromatography (RRLC) combined with quadrupole time-of-flight mass spectrometry (QTOF MS), (2) global analysis of non-targeted compounds by molecular feature extraction algorithm, (3) multivariate statistical analysis for classification and prediction, and (4) marker compounds characterization. This approach has provided a fast and unbiased comparative multivariate analysis of the metabolite composition of 33-batch samples covering seven Lonicera species. Individual metabolic profiles are performed at the level of molecular fragments without prior structural assignment. In the entire set, the obtained classifier for seven Lonicera species flower buds showed good prediction performance and a total of 82 statistically different components were rapidly obtained by the strategy. The elemental compositions of discriminative metabolites were characterized by the accurate mass measurement of the pseudomolecular ions and their chemical types were assigned by the MS/MS spectra. The high-resolution, comprehensive and unbiased strategy for metabolite data analysis presented here is powerful and opens the new direction of authentication in herbal analysis.

  14. Gunbarrel mafic magmatic event: A key 780 Ma time marker for Rodinia plate reconstructions

    USGS Publications Warehouse

    Harlan, S.S.; Heaman, L.; LeCheminant, A.N.; Premo, W.R.

    2003-01-01

    Precise U-Pb baddeleyite dating of mafic igneous rocks provides evidence for a widespread and synchronous magmatic event that extended for >2400 km along the western margin of the Neoproterozoic Laurentian craton. U-Pb baddeleyite analyses for eight intrusions from seven localities ranging from the northern Canadian Shield to northwestern Wyoming-southwestern Montana are statistically indistinguishable and yield a composite U-Pb concordia age for this event of 780.3 ?? 1.4 Ma (95% confidence level). This 780 Ma event is herein termed the Gunbarrel magmatic event. The mafic magmatism of the Gunbarrel event represents the largest mafic dike swarm yet identified along the Neoproterozoic margin of Laurentia. The origin of the mafic magmatism is not clear, but may be related to mantle-plume activity or upwelling asthenosphere leading to crustal extension accompanying initial breakup of the supercontinent Rodinia and development of the proto-Pacific Ocean. The mafic magmatism of the Gunbarrel magmatic event at 780 Ma predates the voluminous magmatism of the 723 Ma Franklin igneous event of the northwestern Canadian Shield by ???60 m.y. The precise dating of the extensive Neoproterozoic Gunbarrel and Franklin magmatic events provides unique time markers that can ultimately be used for robust testing of Neoproterozoic continental reconstructions.

  15. Timing of the most recent surface rupture event on the Ohariu Fault near Paraparaumu, New Zealand

    USGS Publications Warehouse

    Litchfield, N.; Van Dissen, R.; Langridge, Rob; Heron, D.; Prentice, C.

    2004-01-01

    Thirteen radiocarbon ages from three trenches across the Ohariu Fault tightly constrain the timing of the most recent surface rupture event at Muaupoko Stream valley, c. 2 km east of Paraparaumu, to between 930 and 1050 cal. yr BP. This age overlaps with previously published ages of the most recent event on the Ohariu Fault and together they further constrain the event to 1000-1050 cal. yr BP. Two trenches provide loose constraints on the maximum recurrence interval at 3-7000 yr. Tephra, most probably the Kawakawa Tephra, was found within alluvial fan deposits in two of the trenches. ?? The Royal Society of New Zealand 2004.

  16. Diagnosis of Discrete Event System with Linear-Time Temporal Logic Proposition

    NASA Astrophysics Data System (ADS)

    Zanma, Tadanao; Aoyama, Shigeru; Ishida, Muneaki

    Diagnosis for discrete event systems has been investigated. In this paper, authors examine a state estimation problem of a system modeled by a finite state automaton in which each state has its corresponding logical formulas. We formalize a diagnosis problem of truth values of atomic propositions which constitute the logical formulas. Our approach to the problem is based on the discrete event system theory by use of linear-time temporal logic.

  17. Development of a time-oriented data warehouse based on a medical information event model.

    PubMed

    Yamamoto, Yuichiro; Namikawa, Hirokazu; Inamura, Kiyonari

    2002-01-01

    We designed a new medical information event model and developed a time-oriented data warehouse based on the model. Here, the medical information event in a basic data unit is handled by a medical information system. The timing of decision making and treatment for a patient in the processing of his medical information is sometimes very critical. The time-oriented data warehouse was developed, to provide a search feature on the time axis. Our medical information event model has a unique simple data structure. PC-ORDERING2000 developed by NEC, which used Oracle, had about 600 pages of tables. However, we reduced these 600 complicated data structures to one unique and simple event model. By means of shifting clinical data from the old type order entry system into the new order entry system of the medical information event model, we produced a simple and flexible system, and the easy secondary use of clinical data of patients was realized. Evaluation of our system revealed heightened data retrieval efficiency and shortened response time 1:600 at a terminal, owing to the 1:600 reduction of the number of tables as mentioned above.

  18. November 2004 space weather events: Real-time observations and forecasts

    NASA Astrophysics Data System (ADS)

    Trichtchenko, L.; Zhukov, A.; van der Linden, R.; Stankov, S. M.; Jakowski, N.; StanisłAwska, I.; Juchnikowski, G.; Wilkinson, P.; Patterson, G.; Thomson, A. W. P.

    2007-06-01

    Space weather events with their solar origin and their distribution through the heliosphere affect the whole magnetosphere-ionosphere-Earth system. Their real-time monitoring and forecasting are important for science and technology. Here we discuss one of the largest space weather events of Solar Cycle 23, in November 2004, which was also one of the most difficult periods to forecast. Nine halo coronal mass ejections (CMEs), interacting on their way through the interplanetary medium and forming two geoeffective interplanetary structures, exemplify the complexity of the event. Real-time and quasi-real-time observations of the ground geomagnetic field show rapid and extensive expansion of the auroral oval to 55° in geomagnetic latitude accompanied by great variability of the ionosphere. Geomagnetically induced currents (GICs) seen in ground networks, such as power grids and pipelines, were significant during the event, although no problems were reported. Forecasts of the CME propagation, global and local ground geomagnetic activity, and ionospheric parameters, issued by several regional warning centers, revealed certain deficiencies in predictions of the interplanetary characteristics of the CME, size of the geomagnetic disturbances, and complexity of the ionospheric variations produced by this event. This paper is a collective report based on the materials presented at the splinter session on November 2004 events during the first European Space Weather Week.

  19. A multivariate time-frequency method to characterize the influence of respiration over heart period and arterial pressure

    NASA Astrophysics Data System (ADS)

    Orini, Michele; Bailón, Raquel; Laguna, Pablo; Mainardi, Luca T.; Barbieri, Riccardo

    2012-12-01

    Respiratory activity introduces oscillations both in arterial pressure and heart period, through mechanical and autonomic mechanisms. Respiration, arterial pressure, and heart period are, generally, non-stationary processes and the interactions between them are dynamic. In this study we present a methodology to robustly estimate the time course of cross spectral indices to characterize dynamic interactions between respiratory oscillations of heart period and blood pressure, as well as their interactions with respiratory activity. Time-frequency distributions belonging to Cohen's class are used to estimate time-frequency (TF) representations of coherence, partial coherence and phase difference. The characterization is based on the estimation of the time course of cross spectral indices estimated in specific TF regions around the respiratory frequency. We used this methodology to describe the interactions between respiration, heart period variability (HPV) and systolic arterial pressure variability (SAPV) during tilt table test with both spontaneous and controlled respiratory patterns. The effect of selective autonomic blockade was also studied. Results suggest the presence of common underling mechanisms of regulation between cardiovascular signals, whose interactions are time-varying. SAPV changes followed respiratory flow both in supine and standing positions and even after selective autonomic blockade. During head-up tilt, phase differences between respiration and SAPV increased. Phase differences between respiration and HPV were comparable to those between respiration and SAPV during supine position, and significantly increased during standing. As a result, respiratory oscillations in SAPV preceded respiratory oscillations in HPV during standing. Partial coherence was the most sensitive index to orthostatic stress. Phase difference estimates were consistent among spontaneous and controlled breathing patterns, whereas coherence was higher in spontaneous breathing

  20. Relaxation times in single event electrospraying controlled by nozzle front surface modification.

    PubMed

    Stachewicz, Urszula; Dijksman, J Frits; Burdinski, Dirk; Yurteri, Caner U; Marijnissen, Jan C M

    2009-02-17

    Single event electrospraying (SEE) is a method for on-demand deposition of femtoliter to picoliter volumes of fluids. To determine the influence of the size of the meniscus on the characteristics of the single event electrospraying process, glass capillaries were used with and without an antiwetting coating comprising a self-assembled 1H,1H,2H,2H-perfluorodecyltrichlorosilane-based monolayer to control the meniscus size. A large difference was found in driving single event electrospraying from a small meniscus compared to what is needed to generate a single event electrospraying from a large meniscus. Furthermore, after studying the different time constants related to the electrical and the hydrodynamic phenomena, we are able to explain the timing limitations of the deposition process from both a small and a large meniscus. The hydrodynamic relaxation time is significantly reduced in the case of the modified capillary, and the timing of SEE, which determines the deposition time, is limited by the resistor-capacitor RC time of the electrical circuit needed to drive the SEE. We have built a model that describes the almost one-dimensional motion of the liquid in the capillary during pulsing. The model has been used to estimate the hydrodynamic relaxation times related to the meniscus-to-cone and cone-to-meniscus transitions during SEE. By confining the meniscus to the inner diameter of the nozzle, we are able to deposit a volume smaller than 5 pL per SEE.

  1. Estimation of intervention effects using recurrent event time data in the presence of event dependence and a cured fraction.

    PubMed

    Xu, Ying; Lam, K F; Cheung, Yin Bun

    2014-06-15

    Recurrent event data with a fraction of subjects having zero event are often seen in randomized clinical trials. Those with zero event may belong to a cured (or non-susceptible) fraction. Event dependence refers to the situation that a person's past event history affects his future event occurrences. In the presence of event dependence, an intervention may have an impact on the event rate in the non-cured through two pathways-a primary effect directly on the outcome event and a secondary effect mediated through event dependence. The primary effect combined with the secondary effect is the total effect. We propose a frailty mixture model and a two-step estimation procedure for the estimation of the effect of an intervention on the probability of cure and the total effect on event rate in the non-cured. A summary measure of intervention effects is derived. The performance of the proposed model is evaluated by simulation. Data on respiratory exacerbations from a randomized, placebo-controlled trial are re-analyzed for illustration.

  2. BACKWARD ESTIMATION OF STOCHASTIC PROCESSES WITH FAILURE EVENTS AS TIME ORIGINS1

    PubMed Central

    Gary Chan, Kwun Chuen; Wang, Mei-Cheng

    2011-01-01

    Stochastic processes often exhibit sudden systematic changes in pattern a short time before certain failure events. Examples include increase in medical costs before death and decrease in CD4 counts before AIDS diagnosis. To study such terminal behavior of stochastic processes, a natural and direct way is to align the processes using failure events as time origins. This paper studies backward stochastic processes counting time backward from failure events, and proposes one-sample nonparametric estimation of the mean of backward processes when follow-up is subject to left truncation and right censoring. We will discuss benefits of including prevalent cohort data to enlarge the identifiable region and large sample properties of the proposed estimator with related extensions. A SEER–Medicare linked data set is used to illustrate the proposed methodologies. PMID:21359167

  3. From sensation to perception: Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time.

    PubMed

    Hogendoorn, Hinze

    2015-01-01

    An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness. Here, I argue that the application of multivariate pattern classification techniques to neuroimaging data acquired while observers experience perceptual illusions provides a unique way to dissociate sensory mechanisms from mechanisms underlying conscious awareness. Using this approach, it is possible to directly compare patterns of neural activity that correspond to the contents of awareness, independent from changes in sensory input, and to track these neural representations over time at high temporal resolution. I highlight five recent studies using this approach, and provide practical considerations and limitations for future implementations.

  4. Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic.

    PubMed

    Hopke, P K; Liu, C; Rubin, D B

    2001-03-01

    Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.

  5. Visual and Real-Time Event-Specific Loop-Mediated Isothermal Amplification Based Detection Assays for Bt Cotton Events MON531 and MON15985.

    PubMed

    Randhawa, Gurinder Jit; Chhabra, Rashmi; Bhoge, Rajesh K; Singh, Monika

    2015-01-01

    Bt cotton events MON531 and MON15985 are authorized for commercial cultivation in more than 18 countries. In India, four Bt cotton events have been commercialized; more than 95% of total area under genetically modified (GM) cotton cultivation comprises events MON531 and MON15985. The present study reports on the development of efficient event-specific visual and real-time loop-mediated isothermal amplification (LAMP) assays for detection and identification of cotton events MON531 and MON15985. Efficiency of LAMP assays was compared with conventional and real-time PCR assays. Real-time LAMP assay was found time-efficient and most sensitive, detecting up to two target copies within 35 min. The developed real-time LAMP assays, when combined with efficient DNA extraction kit/protocol, may facilitate onsite GM detection to check authenticity of Bt cotton seeds.

  6. Time difference of arrival to blast localization of potential chemical/biological event on the move

    NASA Astrophysics Data System (ADS)

    Morcos, Amir; Desai, Sachi; Peltzer, Brian; Hohil, Myron E.

    2007-10-01

    Integrating a sensor suite with ability to discriminate potential Chemical/Biological (CB) events from high-explosive (HE) events employing a standalone acoustic sensor with a Time Difference of Arrival (TDOA) algorithm we developed a cueing mechanism for more power intensive and range limited sensing techniques. Enabling the event detection algorithm to locate to a blast event using TDOA we then provide further information of the event as either Launch/Impact and if CB/HE. The added information is provided to a range limited chemical sensing system that exploits spectroscopy to determine the contents of the chemical event. The main innovation within this sensor suite is the system will provide this information on the move while the chemical sensor will have adequate time to determine the contents of the event from a safe stand-off distance. The CB/HE discrimination algorithm exploits acoustic sensors to provide early detection and identification of CB attacks. Distinct characteristics arise within the different airburst signatures because HE warheads emphasize concussive and shrapnel effects, while CB warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. Differences characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. The discrete wavelet transform (DWT) is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 3km. Highly reliable discrimination is achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition. The development of an adaptive noise

  7. Effective target binarization method for linear timed address-event vision system

    NASA Astrophysics Data System (ADS)

    Xu, Jiangtao; Zou, Jiawei; Yan, Shi; Gao, Zhiyuan

    2016-06-01

    This paper presents an effective target binarization method for a linear timed address-event (TAE) vision system. In the preprocessing phase, TAE data are processed by denoising, thinning, and edge connection methods sequentially to obtain the denoised- and clear-event contours. Then, the object region will be confirmed by an event-pair matching method. Finally, the image open and close operations of morphology methods are introduced to remove the artifacts generated by event-pair mismatching. Several degraded images were processed by our method and some traditional binarization methods, and the experimental results are provided. As compared with other methods, the proposed method performs efficiently on extracting the target region and gets satisfactory binarization results from object images with low-contrast and nonuniform illumination.

  8. Markov chains and semi-Markov models in time-to-event analysis

    PubMed Central

    Abner, Erin L.; Charnigo, Richard J.; Kryscio, Richard J.

    2014-01-01

    A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields. PMID:24818062

  9. Neural Correlates of the Time Marker for the Perception of Event Timing

    PubMed Central

    Qi, Liang; Terada, Yoshikazu; Nishida, Shin’ya

    2016-01-01

    While sensory processing latency, inferred from the manual reaction time (RT), is substantially affected by diverse stimulus parameters, subjective temporal judgments are relatively accurate. The neural mechanisms underlying this timing perception remain obscure. Here, we measured human neural activity by magnetoencephalography while participants performed a simultaneity judgment task between the onset of random-dot coherent motion and a beep. In a separate session, participants performed an RT task for the same stimuli. We analyzed the relationship between neural activity evoked by motion onset and point of subjective simultaneity (PSS) or RT. The effect of motion coherence was smaller for PSS than RT, but changes in RT and PSS could both be predicted by the time at which an integrated sensory response crossed a threshold. The task differences could be ascribed to the lower threshold for PSS than for RT. In agreement with the psychophysical threshold difference, the participants reported longer delays in their motor response from the subjective motion onset for weaker stimuli. However, they could not judge the timing of stimuli weaker than the detection threshold. A possible interpretation of the present findings is that the brain assigns the time marker for timing perception prior to stimulus detection, but the time marker is available only after stimulus detection. PMID:27679810

  10. Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test

    PubMed Central

    Vervoort, Danique; Vuillerme, Nicolas; Kosse, Nienke; Hortobágyi, Tibor; Lamoth, Claudine J. C.

    2016-01-01

    Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG) test includes several elements that people use in daily life. The test has different transition phases: rise from a chair, walk, 180° turn, walk back, turn, and sit-down on a chair. For this reason the TUG is an often used test to evaluate in a standardized way possible decline in balance and walking ability due to age and or pathology. Using inertial sensors, qualitative information about the performance of the sub-phases can provide more specific information about a decline in balance and walking ability. The first aim of our study was to identify variables extracted from the instrumented timed-up-and-go (iTUG) that most effectively distinguished performance differences across age (age 18–75). Second, we determined the discriminative ability of those identified variables to classify a younger (age 18–45) and older age group (age 46–75). From healthy adults (n = 59), trunk accelerations and angular velocities were recorded during iTUG performance. iTUG phases were detected with wavelet-analysis. Using a Partial Least Square (PLS) model, from the 72-iTUG variables calculated across phases, those that explained most of the covariance between variables and age were extracted. Subsequently, a PLS-discriminant analysis (DA) assessed classification power of the identified iTUG variables to discriminate the age groups. 27 variables, related to turning, walking and the stand-to-sit movement explained 71% of the variation in age. The PLS-DA with these 27 variables showed a sensitivity and specificity of 90% and 85%. Based on this model, the iTUG can accurately distinguish young and older adults. Such data can serve as a reference for pathological aging with respect to a widely used mobility test. Mobility tests like the TUG supplemented with smart technology could be used in clinical

  11. Database for temporal events and spatial object features in time-lapse images

    NASA Astrophysics Data System (ADS)

    Eggers, Charles E.; Trivedi, Mohan M.

    2000-04-01

    We present an image database system with the capability to locate specified object-level merge and separation events in a sequence of time-lapse images. Specifically, the objects of interest are live cells in phase contrast images acquired by scanning cytometry. The system is named TERSIS and it resides on a workstation accessing time lapse images on CD- ROM. The cell objects are segmented and the resulting data are processed to extract a time series and its time derivative series for each spatial feature. Cell objects are tracked through the image sequence by applying similarity metrics to the cell object feature vectors, and cell merge and separation events are located using global image statistics. Multiple hypotheses are generated and scored to determine participating cell objects in merge/separation events. The cell association and time-varying spatial data re stored in a database. A graphical suer interface provides the user with tools to specify queries for specific cellular states and events for recall and display. Primary limitation include the need for an automatic front-end segmenter and increased cell tracking volume. The design of this system is extensible to other object types and forms of sequential image input, including video.

  12. Discrete-event requirements model for sensor fusion to provide real-time diagnostic feedback

    NASA Astrophysics Data System (ADS)

    Rokonuzzaman, Mohd; Gosine, Raymond G.

    1998-06-01

    Minimally-invasive surgical techniques reduce the size of the access corridor and affected zones resulting in limited real-time perceptual information available to the practitioners. A real-time feedback system is required to offset deficiencies in perceptual information. This feedback system acquires data from multiple sensors and fuses these data to extract pertinent information within defined time windows. To perform this task, a set of computing components interact with each other resulting in a discrete event dynamic system. In this work, a new discrete event requirements model for sensor fusion has been proposed to ensure logical and temporal correctness of the operation of the real-time diagnostic feedback system. This proposed scheme models system requirements as a Petri net based discrete event dynamic machine. The graphical representation and quantitative analysis of this model has been developed. Having a natural graphical property, this Petri net based model enables the requirements engineer to communicate intuitively with the client to avoid faults in the early phase of the development process. The quantitative analysis helps justify the logical and temporal correctness of the operation of the system. It has been shown that this model can be analyzed to check the presence of deadlock, reachability, and repetitiveness of the operation of the sensor fusion system. This proposed novel technique to model the requirements of sensor fusion as a discrete event dynamic system has the potential to realize highly reliable real-time diagnostic feedback system for many applications, such as minimally invasive instrumentation.

  13. Ants Can Expect the Time of an Event on Basis of Previous Experiences

    PubMed Central

    Cammaerts, Roger

    2016-01-01

    Working on three ant species of the genus Myrmica, M. ruginodis, M. rubra, and M. sabuleti, we showed that foragers can expect the subsequent time at which food will be available on the basis of the previous times at which food was present. The ants acquired this expectative ability right after having experienced two time shifts of food delivery. Moreover, the ants' learning score appeared to be a logarithmic function of time (i.e., of the number of training days). This ability to expect subsequent times at which an event will occur may be an advantageous ethological trait. PMID:27403457

  14. Multi-variable X-band radar observation and tracking of ash plume from Mt. Etna volcano on November 23, 2013 event

    NASA Astrophysics Data System (ADS)

    Montopoli, Mario; Vulpiani, Gianfranco; Riccci, Matteo; Corradini, Stefano; Merucci, Luca; Marzano, Frank S.

    2015-04-01

    Ground based weather radar observations of volcanic ash clouds are gaining momentum after recent works which demonstrated their potential use either as stand alone tool or in combination with satellite retrievals. From an operational standpoint, radar data have been mainly exploited to derive the height of ash plume and its temporal-spatial development, taking into account the radar limitation of detecting coarse ash particles (from approximately 20 microns to 10 millimeters and above in terms of particle's radius). More sophisticated radar retrievals can include airborne ash concentration, ash fall rate and out-flux rate. Marzano et al. developed several volcanic ash radar retrieval (VARR) schemes, even though their practical use is still subject to a robust validation activity. The latter is made particularly difficult due to the lack of field campaigns with multiple observations and the scarce repetition of volcanic events. The radar variable, often used to infer the physical features of actual ash clouds, is the radar reflectivity named ZHH. It is related to ash particle size distribution and it shows a nice power law relationship with ash concentration. This makes ZHH largely used in radar-volcanology studies. However, weather radars are often able to detect Doppler frequency shifts and, more and more, they have a polarization-diversity capability. The former means that wind speed spectrum of the ash cloud is potentially inferable, whereas the latter implies that variables other than ZHH are available. Theoretically, these additional radar variables are linked to the degree of eccentricity of ash particles, their orientation and density as well as the presence of strong turbulence effects. Thus, the opportunity to refine the ash radar estimates so far developed can benefit from the thorough analysis of radar Doppler and polarization diversity. In this work we show a detailed analysis of Doppler shifts and polarization variables measured by the X band radar

  15. Time-Frequency Characteristics of Tsunami Magnetic Signals from Four Pacific Ocean Events

    NASA Astrophysics Data System (ADS)

    Schnepf, N. R.; Manoj, C.; An, C.; Sugioka, H.; Toh, H.

    2016-12-01

    The recent deployment of highly sensitive seafloor magnetometers coinciding with the deep solar minimum has provided excellent opportunities for observing tsunami electromagnetic signals. These fluctuating signals (periods ranging from 10-20 min) are generally found to be within ± ˜1 nT and coincide with the arrival of the tsunami waves. Previous studies focused on tsunami electromagnetic characteristics, as well as modeling the signal for individual events. This study instead aims to provide the time-frequency characteristics for a range of tsunami signals and a method to separate the data's noise using additional data from a remote observatory. We focus on four Pacific Ocean events of varying tsunami signal amplitude: (1) the 2011 Tohoku, Japan event (M9.0), (2) the 2010 Chile event (M8.8), (3) the 2009 Samoa event (M8.0) and, (4) the 2007 Kuril Islands event (M8.1). We find possible tsunami signals in high-pass filtered data and successfully isolate the signals from noise using a cross-wavelet analysis. The cross-wavelet analysis reveals that the longer period signals precede the stronger, shorter period signals. Our results are very encouraging for using tsunami magnetic signals in warning systems.

  16. Real-time extreme weather event attribution with forecast seasonal SSTs

    NASA Astrophysics Data System (ADS)

    Haustein, K.; Otto, F. E. L.; Uhe, P.; Schaller, N.; Allen, M. R.; Hermanson, L.; Christidis, N.; McLean, P.; Cullen, H.

    2016-06-01

    Within the last decade, extreme weather event attribution has emerged as a new field of science and garnered increasing attention from the wider scientific community and the public. Numerous methods have been put forward to determine the contribution of anthropogenic climate change to individual extreme weather events. So far nearly all such analyses were done months after an event has happened. Here we present a new method which can assess the fraction of attributable risk of a severe weather event due to an external driver in real-time. The method builds on a large ensemble of atmosphere-only general circulation model simulations forced by seasonal forecast sea surface temperatures (SSTs). Taking the England 2013/14 winter floods as an example, we demonstrate that the change in risk for heavy rainfall during the England floods due to anthropogenic climate change, is of similar magnitude using either observed or seasonal forecast SSTs. Testing the dynamic response of the model to the anomalous ocean state for January 2014, we find that observed SSTs are required to establish a discernible link between a particular SST pattern and an atmospheric response such as a shift in the jetstream in the model. For extreme events occurring under strongly anomalous SST patterns associated with known low-frequency climate modes, however, forecast SSTs can provide sufficient guidance to determine the dynamic contribution to the event.

  17. The effect of time constraints and running phases on combined event pistol shooting performance.

    PubMed

    Dadswell, Clare; Payton, Carl; Holmes, Paul; Burden, Adrian

    2016-01-01

    The combined event is a crucial aspect of the modern pentathlon competition, but little is known about how shooting performance changes through the event. This study aimed to identify (i) how performance-related variables changed within each shooting series and (ii) how performance-related variables changed between each shooting series. Seventeen modern pentathletes completed combined event trials. An optoelectronic shooting system recorded score and pistol movement, and force platforms recorded centre of pressure movement 1 s prior to every shot. Heart rate and blood lactate values were recorded throughout the event. Whilst heart rate and blood lactate significantly increased between series (P < 0.05), there were no accompanying changes in the time period that participants spent aiming at the target, shot score, pistol movement or centre of pressure movement (P > 0.05). Thus, combined event shooting performance following each running phase appears similar to shooting performance following only 20 m of running. This finding has potential implications for the way in which modern pentathletes train for combined event shooting, and highlights the need for modern pentathletes to establish new methods with which to enhance shooting accuracy.

  18. The influence of pubertal timing and stressful life events on depression and delinquency among Chinese adolescents.

    PubMed

    Chen, Jie; Yu, Jing; Wu, Yun; Zhang, Jianxin

    2015-06-01

    This study aimed to investigate the influences of pubertal timing and stressful life events on Chinese adolescents' depression and delinquency. Sex differences in these influences were also examined. A large sample with 4,228 participants aged 12-15 years (53% girls) was recruited in Beijing, China. Participants' pubertal development, stressful life events, depressive symptoms, and delinquency were measured using self-reported questionnaires. Both early maturing girls and boys displayed more delinquency than their same-sex on-time and late maturing peers. Early maturing girls displayed more depressive symptoms than on-time and late maturing girls, but boys in the three maturation groups showed similar levels of depressive symptoms. The interactive effects between early pubertal timing and stressful life events were significant in predicting depression and delinquency, particularly for girls. Early pubertal maturation is an important risk factor for Chinese adolescents' depression and delinquency. Stressful life events intensified the detrimental effects of early pubertal maturation on adolescents' depression and delinquency, particularly for girls.

  19. Intensity/time profiles of solar particle events at one astronomical unit

    NASA Technical Reports Server (NTRS)

    Shea, M. A.

    1988-01-01

    A description of the intensity-time profiles of solar proton events observed at the orbit of the earth is presented. The discussion, which includes descriptive figures, presents a general overview of the subject without the detailed mathematical description of the physical processes which usually accompany most reviews.

  20. Individual Change and the Timing and Onset of Important Life Events: Methods, Models, and Assumptions

    ERIC Educational Resources Information Center

    Grimm, Kevin; Marcoulides, Katerina

    2016-01-01

    Researchers are often interested in studying how the timing of a specific event affects concurrent and future development. When faced with such research questions there are multiple statistical models to consider and those models are the focus of this paper as well as their theoretical underpinnings and assumptions regarding the nature of the…

  1. A joint model for nonparametric functional mapping of longitudinal trajectory and time-to-event

    PubMed Central

    Lin, Min; Wu, Rongling

    2006-01-01

    Background The characterization of the relationship between a longitudinal response process and a time-to-event has been a pressing challenge in biostatistical research. This has emerged as an important issue in genetic studies when one attempts to detect the common genes or quantitative trait loci (QTL) that govern both a longitudinal trajectory and developmental event. Results We present a joint statistical model for functional mapping of dynamic traits in which the event times and longitudinal traits are taken to depend on a common set of genetic mechanisms. By fitting the Legendre polynomial of orthogonal properties for the time-dependent mean vector, our model does not rely on any curve, which is different from earlier parametric models of functional mapping. This newly developed nonparametric model is demonstrated and validated by an example for a forest tree in which stemwood growth and the time to first flower are jointly modelled. Conclusion Our model allows for the detection of specific QTL that govern both longitudinal traits and developmental processes through either pleiotropic effects or close linkage, or both. This model will have great implications for integrating longitudinal and event data to gain better insights into comprehensive biology and biomedicine. PMID:16539724

  2. Modeling Repeatable Events Using Discrete-Time Data: Predicting Marital Dissolution

    ERIC Educational Resources Information Center

    Teachman, Jay

    2011-01-01

    I join two methodologies by illustrating the application of multilevel modeling principles to hazard-rate models with an emphasis on procedures for discrete-time data that contain repeatable events. I demonstrate this application using data taken from the 1995 National Survey of Family Growth (NSFG) to ascertain the relationship between multiple…

  3. Non-parametric estimation and model checking procedures for marginal gap time distributions for recurrent events.

    PubMed

    Kvist, Kajsa; Gerster, Mette; Andersen, Per Kragh; Kessing, Lars Vedel

    2007-12-30

    For recurrent events there is evidence that misspecification of the frailty distribution can cause severe bias in estimated regression coefficients (Am. J. Epidemiol 1998; 149:404-411; Statist. Med. 2006; 25:1672-1684). In this paper we adapt a procedure originally suggested in (Biometrika 1999; 86:381-393) for parallel data for checking the gamma frailty to recurrent events. To apply the model checking procedure, a consistent non-parametric estimator for the marginal gap time distributions is needed. This is in general not possible due to induced dependent censoring in the recurrent events setting, however, in (Biometrika 1999; 86:59-70) a non-parametric estimator for the joint gap time distributions based on the principle of inverse probability of censoring weights is suggested. Here, we attempt to apply this estimator in the model checking procedure and the performance of the method is investigated with simulations and applied to Danish registry data. The method is further investigated using the usual Kaplan-Meier estimator and a marginalized estimator for the marginal gap time distributions. We conclude that the procedure only works when the recurrent event is common and when the intra-individual association between gap times is weak.

  4. Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System.

    PubMed

    Wang, Yu-Long; Shi, Peng; Lim, Cheng-Chew; Liu, Yuan

    2016-12-01

    This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.

  5. Event-Triggered Generalized Dissipativity Filtering for Neural Networks With Time-Varying Delays.

    PubMed

    Wang, Jia; Zhang, Xian-Ming; Han, Qing-Long

    2016-01-01

    This paper is concerned with event-triggered generalized dissipativity filtering for a neural network (NN) with a time-varying delay. The signal transmission from the NN to its filter is completed through a communication channel. It is assumed that the network measurement of the NN is sampled periodically. An event-triggered communication scheme is introduced to design a suitable filter such that precious communication resources can be saved significantly while certain filtering performance can be ensured. On the one hand, the event-triggered communication scheme is devised to select only those sampled signals violating a certain threshold to be transmitted, which directly leads to saving of precious communication resources. On the other hand, the filtering error system is modeled as a time-delay system closely dependent on the parameters of the event-triggered scheme. Based on this model, a suitable filter is designed such that certain filtering performance can be ensured, provided that a set of linear matrix inequalities are satisfied. Furthermore, since a generalized dissipativity performance index is introduced, several kinds of event-triggered filtering issues, such as H∞ filtering, passive filtering, mixed H∞ and passive filtering, (Q,S,R) -dissipative filtering, and L2 - L∞ filtering, are solved in a unified framework. Finally, two examples are given to illustrate the effectiveness of the proposed method.

  6. Time period and lesbian identity events: a comparison of Norwegian lesbians across 1986 and 2005.

    PubMed

    Giertsen, Merethe; Anderssen, Norman

    2007-11-01

    The purpose of the present work was to investigate the assumption that the lives of lesbians are easier today. When exploring the hypothesis that identity events (e.g., coming out to parents) among lesbian women have changed over time and happen earlier in life today, we expected to find several time period effects. Two national samples obtained through mailed questionnaires were compared, 1986 (n = 123) and 2005 (n = 236), age range 20-49. Time period effects were found, including informants reporting identifying as lesbian earlier in life. Time period effects, however, were not found regarding relational identity events such as informing others about one's identity status. The findings did not reveal any conclusive evidence that it is easier to establish a lesbian lifestyle today.

  7. Real-time gait event detection for normal subjects from lower trunk accelerations.

    PubMed

    González, Rafael C; López, Antonio M; Rodriguez-Uría, Javier; Alvarez, Diego; Alvarez, Juan C

    2010-03-01

    In this paper we report on a novel algorithm for the real-time detection and timing of initial (IC) and final contact (FC) gait events. We process the vertical and antero-posterior accelerations registered at the lower trunk (L3 vertebra). The algorithm is based on a set of heuristic rules extracted from a set of 1719 steps. An independent experiment was conducted to compare the results of our algorithms with those obtained from a Digimax force platform. The results show small deviations from times of occurrence of events recorded from the platform (13+/-35 ms for IC and 9+/-54 ms for FC). Results for the FC timing are especially relevant in this field, as no previous work has addressed its temporal location through the processing of lower trunk accelerations. The delay in the real-time detection of the IC is 117+/-39 ms and 34+/-72 ms for the FC, improving previously reported results for real-time detection of events from lower trunk accelerations.

  8. Correlation between night time VLF amplitude fluctuations and seismic events in Indian sub-continent

    NASA Astrophysics Data System (ADS)

    Ray, Suman; Chakrabarti, Sandip Kumar; Sasmal, Sudipta

    We present the results of an analysis of yearlong (2007) monitoring of night time data of the VLF signal amplitude. We use the VLF signals, transmitted from the Indian Navy station VTX (latitude 8.43(°) N, longitude 77.73(°) E) at 18.2 kHz and received at the Indian Centre for Space Physics, Kolkata (latitude 22.5(°) N, 87.5(°) E). We analyzed this data to find out the correlation between night time amplitude fluctuation and seismic events. We found, analyzing individual earthquakes (with magnitudes >5) as well as from statistical analysis (of all the events with effective magnitudes greater than 3.5), that night time fluctuation of the signal amplitude has the highest probability to be beyond the 2σ levels about three days prior to the seismic events. Recently an earthquake of magnitude 7.4 occurred at South-western Pakistan (latitude 28.9(°) N, 64(°) E). We analyze the night time VLF signals for two weeks around this earthquake day to see if there were any precursory effects of this earthquake. We find that the amplitude of the night time VLF signals anomalously fluctuated four days before this earthquake. Thus, the night time fluctuation could be considered as a precursor to enhanced seismic activities.

  9. Systematic investigation of time windows for adverse event data mining for recently approved drugs.

    PubMed

    Hochberg, Alan M; Hauben, Manfred; Pearson, Ronald K; O'Hara, Donald J; Reisinger, Stephanie J

    2009-06-01

    The optimum timing of drug safety data mining for a new drug is uncertain. The objective of this study was to compare cumulative data mining versus mining with sliding time windows. Adverse Event Reporting System data (2001-2005) were studied for 27 drugs. A literature database was used to evaluate signals of disproportionate reporting (SDRs) from an urn model data-mining algorithm. Data mining was applied cumulatively and with sliding time windows from 1 to 4 years in width. Time from SDR generation to the appearance of a publication describing the corresponding adverse event was calculated. Cumulative data mining and 1- to 2-year sliding windows produced the most SDRs for recently approved drugs. In the first postmarketing year, data mining produced SDRs an average of 800 days in advance of publications regarding the corresponding drug-event combination. However, this timing advantage reduced to zero by year 4. The optimum window width for sliding windows should increase with time on the market. Data mining may be most useful for early signal detection during the first 3 years of a drug's postmarketing life. Beyond that, it may be most useful for supporting or weakening hypotheses.

  10. Analysis of inter-event times for avalanches on a conical bead pile with cohesion

    NASA Astrophysics Data System (ADS)

    Lehman, Susan; Johnson, Nathan; Tieman, Catherine; Wainwright, Elliot

    2015-03-01

    We investigate the critical behavior of a 3D conical bead pile built from uniform 3 mm steel spheres. Beads are added to the pile by dropping them onto the apex one at a time; avalanches are measured through changes in pile mass. We investigate the dynamic response of the pile by recording avalanches from the pile over tens of thousands of bead drops. We have previously shown that the avalanche size distribution follows a power law for beads dropped onto the pile apex from a low drop height. We are now tuning the critical behavior of the system by adding cohesion from a uniform magnetic field and find an increase in both size and number for very large avalanches and decreases in the mid-size avalanches. The resulting bump in the avalanche distribution moves to larger avalanche size as the cohesion in the system is increased. We compare the experimental inter-event time distribution to both the Brownian passage-time and Weibull distributions, and observe a shift from the Weibull to Brownian passage-time as we raise the threshold from measuring time between events of all sizes to time between only the largest system-spanning events. These results are both consistent with those from a mean-field model of slip avalanches in a shear system [Dahmen, Nat Phys 7, 554 (2011)].

  11. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

    NASA Astrophysics Data System (ADS)

    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.; Bagby, L.; Baller, B.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; James, C.; de Vries, J. Jan; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van de Water, R. G.; Viren, B.; Weber, M.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-03-01

    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

  12. gPhoton: Time-tagged GALEX photon events analysis tools

    NASA Astrophysics Data System (ADS)

    Million, Chase C.; Fleming, S. W.; Shiao, B.; Loyd, P.; Seibert, M.; Smith, M.

    2016-03-01

    Written in Python, gPhoton calibrates and sky-projects the ~1.1 trillion ultraviolet photon events detected by the microchannel plates on the Galaxy Evolution Explorer Spacecraft (GALEX), archives these events in a publicly accessible database at the Mikulski Archive for Space Telescopes (MAST), and provides tools for working with the database to extract scientific results, particularly over short time domains. The software includes a re-implementation of core functionality of the GALEX mission calibration pipeline to produce photon list files from raw spacecraft data as well as a suite of command line tools to generate calibrated light curves, images, and movies from the MAST database.

  13. Relative Time-scale for Channeling Events Within Chaotic Terrains, Margaritifer Sinus, Mars

    NASA Technical Reports Server (NTRS)

    Janke, D.

    1985-01-01

    A relative time scale for ordering channel and chaos forming events was constructed for areas within the Margaritifer Sinus region of Mars. Transection and superposition relationships of channels, chaotic terrain, and the surfaces surrounding them were used to create the relative time scale; crater density studies were not used. Channels and chaos in contact with one another were treated as systems. These systems were in turn treated both separately (in order to understand internal relationships) and as members of the suite of Martian erosional forms (in order to produce a combined, master time scale). Channeling events associated with chaotic terrain development occurred over an extended geomorphic period. The channels can be divided into three convenient groups: those that pre-date intercrater plains development post-plains, pre-chasma systems; and those associated with the development of the Vallis Marineris chasmata. No correlations with cyclic climatic changes, major geologic events in other regions on Mars, or triggering phenomena (for example, specific impact events) were found.

  14. The Dependence of Characteristic Times of Gradual SEP Events on Their Associated CME Properties

    NASA Astrophysics Data System (ADS)

    Pan, Z. H.; Wang, C. B.; Xue, X. H.; Wang, Y. M.

    It is generally believed that coronal mass ejections CMEs are the drivers of shocks that accelerate gradual solar energetic particles SEPs One might expect that the characteristics of the SEP intensity time profiles observed at 1 AU are determined by properties of the associated CMEs such as the radial speed and the angular width Recently Kahler statistically investigated the characteristic times of gradual SEP events observed from 1998-2002 and their associated coronal mass ejection properties Astrophys J 628 1014--1022 2005 Three characteristic times of gradual SEP events are determined as functions of solar source longitude 1 T 0 the time from associated CME launch to SEP onset at 1 AU 2 T R the rise time from SEP onset to the time when the SEP intensity is a factor of 2 below peak intensity and 3 T D the duration over which the SEP intensity is within a factor of 2 of the peak intensity However in his study the CME speeds and angular widths are directly taken from the LASCO CME catalog In this study we analyze the radial speeds and the angular widths of CMEs by an ice-cream cone model and re-investigate their correlationships with the characteristic times of the corresponding SEP events We find T R and T D are significantly correlated with radial speed for SEP events in the best-connected longitude range and there is no correlation between T 0 and CME radial speed and angular width which is consistent with Kahler s results On the other hand it s found that T R and T D are also have

  15. Dietary patterns associated with overweight and obesity among Brazilian schoolchildren: an approach based on the time-of-day of eating events.

    PubMed

    Kupek, Emil; Lobo, Adriana S; Leal, Danielle B; Bellisle, France; de Assis, Maria Alice A

    2016-12-01

    Several studies reported that the timing of eating events has critical implications in the prevention of obesity, but dietary patterns regarding the time-of-day have not been explored in children. The aim of this study was to derive latent food patterns of daily eating events and to examine their associations with overweight/obesity among schoolchildren. A population-based cross-sectional study was conducted with 7-10-year-old Brazilian schoolchildren (n 1232) who completed the Previous Day Food Questionnaire, illustrated with twenty-one foods/beverages in six daily eating events. Latent class analysis was used to derive dietary patterns whose association with child weight status was evaluated by multivariate multinomial regression. Four mutually exclusive latent classes of dietary patterns were identified and labelled according to the time-of-day of eating events and food intake probability (FIP): (A) higher FIP only at lunch; (B) lower FIP at all eating events; (C) higher FIP at lunch, afternoon and evening snacks; (D) lower FIP at breakfast and at evening snack, higher FIP at other meals/snacks. The percentages of children within these classes were 32·3, 48·6, 15·1 and 4·0 %, respectively. After controlling for potential confounders, the mean probabilities of obesity for these classes were 6 % (95 % CI 3·0, 9·0), 13 % (95 % CI 9·0, 17·0), 12 % (95 % CI 6·0, 19) and 11 % (95 % CI 5·0, 17·0), in the same order. In conclusion, the children eating traditional lunch with rice and beans as the main meal of the day (class A) had the lowest obesity risk, thus reinforcing the importance of both the food type and the time-of-day of its intake for weight status.

  16. Multivariate analysis in thoracic research.

    PubMed

    Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

    2015-03-01

    Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

  17. Multivariate analysis in thoracic research

    PubMed Central

    Mengual-Macenlle, Noemí; Marcos, Pedro J.; Golpe, Rafael

    2015-01-01

    Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use. PMID:25922743

  18. Lessons Learned from Real-Time, Event-Based Internet Science Communications

    NASA Technical Reports Server (NTRS)

    Phillips, T.; Myszka, E.; Gallagher, D. L.; Adams, M. L.; Koczor, R. J.; Whitaker, Ann F. (Technical Monitor)

    2001-01-01

    For the last several years the Science Directorate at Marshall Space Flight Center has carried out a diverse program of Internet-based science communication. The Directorate's Science Roundtable includes active researchers, NASA public relations, educators, and administrators. The Science@NASA award-winning family of Web sites features science, mathematics, and space news. The program includes extended stories about NASA science, a curriculum resource for teachers tied to national education standards, on-line activities for students, and webcasts of real-time events. The focus of sharing science activities in real-time has been to involve and excite students and the public about science. Events have involved meteor showers, solar eclipses, natural very low frequency radio emissions, and amateur balloon flights. In some cases, broadcasts accommodate active feedback and questions from Internet participants. Through these projects a pattern has emerged in the level of interest or popularity with the public. The pattern differentiates projects that include science from those that do not, All real-time, event-based Internet activities have captured public interest at a level not achieved through science stories or educator resource material exclusively. The worst event-based activity attracted more interest than the best written science story. One truly rewarding lesson learned through these projects is that the public recognizes the importance and excitement of being part of scientific discovery. Flying a camera to 100,000 feet altitude isn't as interesting to the public as searching for viable life-forms at these oxygen-poor altitudes. The details of these real-time, event-based projects and lessons learned will be discussed.

  19. Statistical Property and Model for the Inter-Event Time of Terrorism Attacks

    NASA Astrophysics Data System (ADS)

    Zhu, Jun-Fang; Han, Xiao-Pu; Wang, Bing-Hong

    2010-06-01

    The inter-event time of terrorism attack events is investigated by empirical data and model analysis. Empirical evidence shows that it follows a scale-free property. In order to understand the dynamic mechanism of such a statistical feature, an opinion dynamic model with a memory effect is proposed on a two-dimensional lattice network. The model mainly highlights the role of individual social conformity and self-affirmation psychology. An attack event occurs when the order parameter indicating the strength of public opposition opinion is smaller than a critical value. Ultimately, the model can reproduce the same statistical property as the empirical data and gives a good understanding for the possible dynamic mechanism of terrorism attacks.

  20. Time forecast of a break-off event from a hanging glacier

    NASA Astrophysics Data System (ADS)

    Faillettaz, J.; Funk, M.; Vagliasindi, M.

    2015-09-01

    A cold hanging glacier located on the south face of the Grandes Jorasses (Mont Blanc, Italy) broke off on the 23 and 29 September 2014 with a total estimated ice volume of 105 000 m3. Thanks to very accurate surface displacement measurements taken right up to the final break-off, this event could be successfully predicted 10 days in advance, enabling local authorities to take the necessary safety measures. The break-off event also confirmed that surface displacements experience a power law acceleration along with superimposed log-periodic oscillations prior to the final rupture. This paper describes the methods used to achieve a satisfactory time forecast in real time and demonstrates, using a retrospective analysis, their potential for the development of early-warning systems in real time.

  1. Time forecast of a break-off event from a hanging glacier

    NASA Astrophysics Data System (ADS)

    Faillettaz, Jérome; Funk, Martin; Vagliasindi, Marco

    2016-06-01

    A cold hanging glacier located on the south face of the Grandes Jorasses (Mont Blanc, Italy) broke off on the 23 and 29 September 2014 with a total estimated ice volume of 105 000 m3. Thanks to accurate surface displacement measurements taken up to the final break-off, this event was successfully predicted 10 days in advance, enabling local authorities to take the necessary safety measures. The break-off event also confirmed that surface displacements experienced a power law acceleration along with superimposed log-periodic oscillations prior to the final rupture. This paper describes the methods used to achieve a satisfactory time forecast in real time and demonstrates, using a retrospective analysis, their potential for the development of early-warning systems in real time.

  2. Adults’ reports of their earliest memories: Consistency in events, ages, and narrative characteristics over time

    PubMed Central

    Bauer, Patricia J.; Tasdemir-Ozdes, Aylin; Larkina, Marina

    2014-01-01

    Earliest memories have been of interest since the late 1800s, when it was first noted that most adults do not have memories from the first years of life (so-called childhood amnesia). Several characteristics of adults’ earliest memories have been investigated, including emotional content, the perspective from which they are recalled, and vividness. The focus of the present research was a feature of early memories heretofore relatively neglected in the literature, namely, their consistency. Adults reported their earliest memories 2 to 4 times over a 4-year period. Reports of earliest memories were highly consistent in the events identified as the bases for earliest memories, the reported age at the time of the event, and in terms of qualities of the narrative descriptions. These findings imply stability in the boundary that marks the offset of childhood amnesia, as well as in the beginning of a continuous sense of self over time. PMID:24836979

  3. Regression with incomplete covariates and left-truncated time-to-event data.

    PubMed

    Shen, Hua; Cook, Richard J

    2013-03-15

    Studies of chronic diseases routinely sample individuals subject to conditions on an event time of interest. In epidemiology, for example, prevalent cohort studies aiming to evaluate risk factors for survival following onset of dementia require subjects to have survived to the point of screening. In clinical trials designed to assess the effect of experimental cancer treatments on survival, patients are required to survive from the time of cancer diagnosis to recruitment. Such conditions yield samples featuring left-truncated event time distributions. Incomplete covariate data often arise in such settings, but standard methods do not deal with the fact that individuals' covariate distributions are also affected by left truncation. We describe an expectation-maximization algorithm for dealing with incomplete covariate data in such settings, which uses the covariate distribution conditional on the selection criterion. We describe an extension to deal with subgroup analyses in clinical trials for the case in which the stratification variable is incompletely observed.

  4. Music, clicks, and their imaginations favor differently the event-based timing component for rhythmic movements.

    PubMed

    Bravi, Riccardo; Quarta, Eros; Del Tongo, Claudia; Carbonaro, Nicola; Tognetti, Alessandro; Minciacchi, Diego

    2015-06-01

    The involvement or noninvolvement of a clock-like neural process, an effector-independent representation of the time intervals to produce, is described as the essential difference between event-based and emergent timing. In a previous work (Bravi et al. in Exp Brain Res 232:1663-1675, 2014a. doi: 10.1007/s00221-014-3845-9 ), we studied repetitive isochronous wrist's flexion-extensions (IWFEs), performed while minimizing visual and tactile information, to clarify whether non-temporal and temporal characteristics of paced auditory stimuli affect the precision and accuracy of the rhythmic motor performance. Here, with the inclusion of new recordings, we expand the examination of the dataset described in our previous study to investigate whether simple and complex paced auditory stimuli (clicks and music) and their imaginations influence in a different way the timing mechanisms for repetitive IWFEs. Sets of IWFEs were analyzed by the windowed (lag one) autocorrelation-wγ(1), a statistical method recently introduced for the distinction between event-based and emergent timing. Our findings provide evidence that paced auditory information and its imagination favor the engagement of a clock-like neural process, and specifically that music, unlike clicks, lacks the power to elicit event-based timing, not counteracting the natural shift of wγ(1) toward positive values as frequency of movements increase.

  5. A New Characteristic Function for Fast Time-Reverse Seismic Event Location

    NASA Astrophysics Data System (ADS)

    Hendriyana, Andri; Bauer, Klaus; Weber, Michael; Jaya, Makky; Muksin, Muksin

    2015-04-01

    Microseismicity produced by natural activities is usually characterized by low signal-to-noise ratio and huge amount of data as recording is conducted for a long period of time. Locating microseismic events is preferably carried out using migration-based methods such as time-reverse modeling (TRM). The original TRM is based on backpropagating the wavefield from the receiver down to the source location. Alternatively, we are using a characteristic function (CF) derived from the measured wavefield as input for the TRM. The motivation for such a strategy is to avoid undesired contributions from secondary arrivals which may generate artifacts in the final images. In this presentation, we introduce a new CF as input for TRM method. To obtain this CF, initially we apply kurtosis-based automatic onset detection and convolution with a given wavelet. The convolution with low frequency wavelets allows us to conduct time-reverse modeling using coarser sampling hence it will reduce computing time. We apply the method to locate seismic events measured along an active part of the Sumatra Fault around the Tarutung pull-apart basin (North Sumatra, Indonesia). The results show that seismic events are well-determined since they are concentrated along the Sumatran fault. Internal details of the Tarutung basin structure could be derived. Our results are consistent with those obtained from inversion of manually picked travel time data.

  6. APNEA list mode data acquisition and real-time event processing

    SciTech Connect

    Hogle, R.A.; Miller, P.; Bramblett, R.L.

    1997-11-01

    The LMSC Active Passive Neutron Examinations and Assay (APNEA) Data Logger is a VME-based data acquisition system using commercial-off-the-shelf hardware with the application-specific software. It receives TTL inputs from eighty-eight {sup 3}He detector tubes and eight timing signals. Two data sets are generated concurrently for each acquisition session: (1) List Mode recording of all detector and timing signals, timestamped to 3 microsecond resolution; (2) Event Accumulations generated in real-time by counting events into short (tens of microseconds) and long (seconds) time bins following repetitive triggers. List Mode data sets can be post-processed to: (1) determine the optimum time bins for TRU assay of waste drums, (2) analyze a given data set in several ways to match different assay requirements and conditions and (3) confirm assay results by examining details of the raw data. Data Logger events are processed and timestamped by an array of 15 TMS320C40 DSPs and delivered to an embedded controller (PowerPC604) for interim disk storage. Three acquisition modes, corresponding to different trigger sources are provided. A standard network interface to a remote host system (Windows NT or SunOS) provides for system control, status, and transfer of previously acquired data. 6 figs.

  7. Foreshocks and aftershocks of Pisagua 2014 earthquake: time and space evolution of megathrust event.

    NASA Astrophysics Data System (ADS)

    Fuenzalida Velasco, Amaya; Rietbrock, Andreas; Wollam, Jack; Thomas, Reece; de Lima Neto, Oscar; Tavera, Hernando; Garth, Thomas; Ruiz, Sergio

    2016-04-01

    The 2014 Pisagua earthquake of magnitude 8.2 is the first case in Chile where a foreshock sequence was clearly recorded by a local network, as well all the complete sequence including the mainshock and its aftershocks. The seismicity of the last year before the mainshock include numerous clusters close to the epicentral zone (Ruiz et al; 2014) but it was on 16th March that this activity became stronger with the Mw 6.7 precursory event taking place in front of Iquique coast at 12 km depth. The Pisagua earthquake arrived on 1st April 2015 breaking almost 120 km N-S and two days after a 7.6 aftershock occurred in the south of the rupture, enlarging the zone affected by this sequence. In this work, we analyse the foreshocks and aftershock sequence of Pisagua earthquake, from the spatial and time evolution for a total of 15.764 events that were recorded from the 1st March to 31th May 2015. This event catalogue was obtained from the automatic analyse of seismic raw data of more than 50 stations installed in the north of Chile and the south of Peru. We used the STA/LTA algorithm for the detection of P and S arrival times on the vertical components and then a method of back propagation in a 1D velocity model for the event association and preliminary location of its hypocenters following the algorithm outlined by Rietbrock et al. (2012). These results were then improved by locating with NonLinLoc software using a regional velocity model. We selected the larger events to analyse its moment tensor solution by a full waveform inversion using ISOLA software. In order to understand the process of nucleation and propagation of the Pisagua earthquake, we also analysed the evolution in time of the seismicity of the three months of data. The zone where the precursory events took place was strongly activated two weeks before the mainshock and remained very active until the end of the analysed period with an important quantity of the seismicity located in the upper plate and having

  8. Relative timing of last glacial maximum and late-glacial events in the central tropical Andes

    NASA Astrophysics Data System (ADS)

    Bromley, Gordon R. M.; Schaefer, Joerg M.; Winckler, Gisela; Hall, Brenda L.; Todd, Claire E.; Rademaker, Kurt M.

    2009-11-01

    Whether or not tropical climate fluctuated in synchrony with global events during the Late Pleistocene is a key problem in climate research. However, the timing of past climate changes in the tropics remains controversial, with a number of recent studies reporting that tropical ice age climate is out of phase with global events. Here, we present geomorphic evidence and an in-situ cosmogenic 3He surface-exposure chronology from Nevado Coropuna, southern Peru, showing that glaciers underwent at least two significant advances during the Late Pleistocene prior to Holocene warming. Comparison of our glacial-geomorphic map at Nevado Coropuna to mid-latitude reconstructions yields a striking similarity between Last Glacial Maximum (LGM) and Late-Glacial sequences in tropical and temperate regions. Exposure ages constraining the maximum and end of the older advance at Nevado Coropuna range between 24.5 and 25.3 ka, and between 16.7 and 21.1 ka, respectively, depending on the cosmogenic production rate scaling model used. Similarly, the mean age of the younger event ranges from 10 to 13 ka. This implies that (1) the LGM and the onset of deglaciation in southern Peru occurred no earlier than at higher latitudes and (2) that a significant Late-Glacial event occurred, most likely prior to the Holocene, coherent with the glacial record from mid and high latitudes. The time elapsed between the end of the LGM and the Late-Glacial event at Nevado Coropuna is independent of scaling model and matches the period between the LGM termination and Late-Glacial reversal in classic mid-latitude records, suggesting that these events in both tropical and temperate regions were in phase.

  9. Real-time gesture interface based on event-driven processing from stereo silicon retinas.

    PubMed

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael; Park, Paul K J; Shin, Chang-Woo; Ryu, Hyunsurk Eric; Kang, Byung Chang

    2014-12-01

    We propose a real-time hand gesture interface based on combining a stereo pair of biologically inspired event-based dynamic vision sensor (DVS) silicon retinas with neuromorphic event-driven postprocessing. Compared with conventional vision or 3-D sensors, the use of DVSs, which output asynchronous and sparse events in response to motion, eliminates the need to extract movements from sequences of video frames, and allows significantly faster and more energy-efficient processing. In addition, the rate of input events depends on the observed movements, and thus provides an additional cue for solving the gesture spotting problem, i.e., finding the onsets and offsets of gestures. We propose a postprocessing framework based on spiking neural networks that can process the events received from the DVSs in real time, and provides an architecture for future implementation in neuromorphic hardware devices. The motion trajectories of moving hands are detected by spatiotemporally correlating the stereoscopically verged asynchronous events from the DVSs by using leaky integrate-and-fire (LIF) neurons. Adaptive thresholds of the LIF neurons achieve the segmentation of trajectories, which are then translated into discrete and finite feature vectors. The feature vectors are classified with hidden Markov models, using a separate Gaussian mixture model for spotting irrelevant transition gestures. The disparity information from stereovision is used to adapt LIF neuron parameters to achieve recognition invariant of the distance of the user to the sensor, and also helps to filter out movements in the background of the user. Exploiting the high dynamic range of DVSs, furthermore, allows gesture recognition over a 60-dB range of scene illuminance. The system achieves recognition rates well over 90% under a variety of variable conditions with static and dynamic backgrounds with naïve users.

  10. Multitarget real-time PCR-based system: monitoring for unauthorized genetically modified events in India.

    PubMed

    Randhawa, Gurinder Jit; Singh, Monika; Sood, Payal; Bhoge, Rajesh K

    2014-07-23

    A multitarget TaqMan real-time PCR (RTi-PCR) based system was developed to monitor unauthorized genetically modified (GM) events in India. Most of the GM events included in this study are either authorized for commercial cultivation or field trials, which were indigenously developed or imported for research purposes. The developed system consists of a 96-well prespotted plate with lyophilized primers and probes, for simultaneous detection of 47 targets in duplicate, including 21 event-specific sequences, 5 construct regions, 15 for transgenic elements, and 6 taxon-specific targets for cotton, eggplant, maize, potato, rice, and soybean. Limit of detection (LOD) of assays ranged from 0.1 to 0.01% GM content for different targets. Applicability, robustness, and practical utility of the developed system were verified with stacked GM cotton event, powdered samples of proficiency testing and two unknown test samples. This user-friendly multitarget approach can be efficiently utilized for monitoring the unauthorized GM events in an Indian context.

  11. The development and validation of a multivariable model to predict whether patients referred for total knee replacement are suitable surgical candidates at the time of initial consultation

    PubMed Central

    Churchill, Laura; Malian, Samuel J.; Chesworth, Bert M.; Bryant, Dianne; MacDonald, Steven J.; Marsh, Jacquelyn D.; Giffin, J. Robert

    2016-01-01

    Background In previous studies, 50%–70% of patients referred to orthopedic surgeons for total knee replacement (TKR) were not surgical candidates at the time of initial assessment. The purpose of our study was to identify and cross-validate patient self-reported predictors of suitability for TKR and to determine the clinical utility of a predictive model to guide the timing and appropriateness of referral to a surgeon. Methods We assessed pre-consultation patient data as well as the surgeon’s findings and post-consultation recommendations. We used multivariate logistic regression to detect self-reported items that could identify suitable surgical candidates. Results Patients’ willingness to undergo surgery, higher rating of pain, greater physical function, previous intra-articular injections and patient age were the factors predictive of patients being offered and electing to undergo TKR. Conclusion The application of the model developed in our study would effectively reduce the proportion of nonsurgical referrals by 25%, while identifying the vast majority of surgical candidates (> 90%). Using patient-reported information, we can correctly predict the outcome of specialist consultation for TKR in 70% of cases. To reduce long waits for first consultation with a surgeon, it may be possible to use these items to educate and guide referring clinicians and patients to understand when specialist consultation is the next step in managing the patient with severe osteoarthritis of the knee. PMID:28234616

  12. A novel multivariate approach using science-based calibration for direct coating thickness determination in real-time NIR process monitoring.

    PubMed

    Möltgen, C-V; Herdling, T; Reich, G

    2013-11-01

    This study demonstrates an approach, using science-based calibration (SBC), for direct coating thickness determination on heart-shaped tablets in real-time. Near-Infrared (NIR) spectra were collected during four full industrial pan coating operations. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film up to a film thickness of 28 μm. The application of SBC permits the calibration of the NIR spectral data without using costly determined reference values. This is due to the fact that SBC combines classical methods to estimate the coating signal and statistical methods for the noise estimation. The approach enabled the use of NIR for the measurement of the film thickness increase from around 8 to 28 μm of four independent batches in real-time. The developed model provided a spectroscopic limit of detection for the coating thickness of 0.64 ± 0.03 μm root-mean square (RMS). In the commonly used statistical methods for calibration, such as Partial Least Squares (PLS), sufficiently varying reference values are needed for calibration. For thin non-functional coatings this is a challenge because the quality of the model depends on the accuracy of the selected calibration standards. The obvious and simple approach of SBC eliminates many of the problems associated with the conventional statistical methods and offers an alternative for multivariate calibration.

  13. Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data

    PubMed Central

    2014-01-01

    Background Network meta-analysis methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on network meta-analysis mainly focussing on the synthesis of aggregate data, methods have been developed that allow the use of individual patient-level data specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of individual patient-level and summary time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers. Methods This paper introduces a novel network meta-analysis modelling approach that allows individual patient-level (time to event with censoring) and summary-level data (event count for a given follow-up time) to be synthesised jointly by assuming an underlying, common, distribution of time to healing. Alternative model assumptions were tested within the motivating example. Model fit and adequacy measures were used to compare and select models. Results Due to the availability of individual patient-level data in our example we were able to use a Weibull distribution to describe time to healing; otherwise, we would have been limited to specifying a uniparametric distribution. Absolute effectiveness estimates were more sensitive than relative effectiveness estimates to a range of alternative specifications for the model. Conclusions The synthesis of time to event data considering individual patient-level data provides modelling flexibility, and can be particularly important when absolute effectiveness estimates, and not just relative effect estimates, are of interest. PMID:25209121

  14. Implications of small-bowel transit time in the detection rate of capsule endoscopy: A multivariable multicenter study of patients with obscure gastrointestinal bleeding

    PubMed Central

    Girelli, Carlo Maria; Soncini, Marco; Rondonotti, Emanuele

    2017-01-01

    AIM To define the role of small-bowel transit time in the detection rate of significant small-bowel lesions. METHODS Small-bowel capsule endoscopy records, prospectively collected from 30 participating centers in the Lombardy Registry from October 2011 to December 2013, were included in the study if the clinical indication was obscure gastrointestinal bleeding and the capsule reached the cecum. Based on capsule findings, we created two groups: P2 (significant findings) and P0-1 (normal/negligible findings). Groups were compared for age, gender, small-bowel transit time, type of instrument, modality of capsule performance (outpatients vs inpatients), bowel cleanliness, and center volume. RESULTS We retrieved and scrutinized 1,433 out of 2,295 capsule endoscopy records (62.4%) fulfilling the inclusion criteria. Patients were 67 ± 15 years old, and 815 (57%) were males. In comparison with patients in the P0-1 group, those in the P2 group (n = 776, 54%) were older (P < 0.0001), had a longer small-bowel transit time (P = 0.0015), and were more frequently examined in low-volume centers (P < 0.001). Age and small-bowel transit time were correlated (P < 0.001), with age as the sole independent predictor on multivariable analysis. Findings of the P2 group were artero-venous malformations (54.5%), inflammatory (23.6%) and protruding (10.4%) lesions, and luminal blood (11.5%). CONCLUSION In this selected, prospectively collected cohort of small-bowel capsule endoscopy performed for obscure gastrointestinal bleeding, a longer small-bowel transit time was associated with a higher detection rate of significant lesions, along with age and a low center volume, with age serving as an independent predictor. PMID:28216977

  15. Extreme event return times in long-term memory processes near 1/f

    NASA Astrophysics Data System (ADS)

    Blender, R.; Fraedrich, K.; Sienz, F.

    2008-07-01

    The distribution of extreme event return times and their correlations are analyzed in observed and simulated long-term memory (LTM) time series with 1/f power spectra. The analysis is based on tropical temperature and mixing ratio (specific humidity) time series from TOGA COARE with 1 min resolution and an approximate 1/f power spectrum. Extreme events are determined by Peak-Over-Threshold (POT) crossing. The Weibull distribution represents a reasonable fit to the return time distributions while the power-law predicted by the stretched exponential for 1/f deviates considerably. For a comparison and an analysis of the return time predictability, a very long simulated time series with an approximate 1/f spectrum is produced by a fractionally differenced (FD) process. This simulated data confirms the Weibull distribution (a power law can be excluded). The return time sequences show distinctly weaker long-term correlations than the original time series (correlation exponent γ≍0.56).

  16. Sample size and robust marginal methods for cluster-randomized trials with censored event times.

    PubMed

    Zhong, Yujie; Cook, Richard J

    2015-03-15

    In cluster-randomized trials, intervention effects are often formulated by specifying marginal models, fitting them under a working independence assumption, and using robust variance estimates to address the association in the responses within clusters. We develop sample size criteria within this framework, with analyses based on semiparametric Cox regression models fitted with event times subject to right censoring. At the design stage, copula models are specified to enable derivation of the asymptotic variance of estimators from a marginal Cox regression model and to compute the number of clusters necessary to satisfy power requirements. Simulation studies demonstrate the validity of the sample size formula in finite samples for a range of cluster sizes, censoring rates, and degrees of within-cluster association among event times. The power and relative efficiency implications of copula misspecification is studied, as well as the effect of within-cluster dependence in the censoring times. Sample size criteria and other design issues are also addressed for the setting where the event status is only ascertained at periodic assessments and times are interval censored.

  17. Monotonic continuous-time random walks with drift and stochastic reset events

    NASA Astrophysics Data System (ADS)

    Montero, Miquel; Villarroel, Javier

    2013-01-01

    In this paper we consider a stochastic process that may experience random reset events which suddenly bring the system to the starting value and analyze the relevant statistical magnitudes. We focus our attention on monotonic continuous-time random walks with a constant drift: The process increases between the reset events, either by the effect of the random jumps, or by the action of the deterministic drift. As a result of all these combined factors interesting properties emerge, like the existence (for any drift strength) of a stationary transition probability density function, or the faculty of the model to reproduce power-law-like behavior. General formulas for two extreme statistics, the survival probability, and the mean exit time are also derived. To corroborate in an independent way the results of the paper, Monte Carlo methods were used. These numerical estimations are in full agreement with the analytical predictions.

  18. A Bayesian Approach for Instrumental Variable Analysis with Censored Time-to-Event Outcome

    PubMed Central

    Li, Gang; Lu, Xuyang

    2014-01-01

    Instrumental variable (IV) analysis has been widely used in economics, epidemiology, and other fields to estimate the causal effects of covariates on outcomes, in the presence of unobserved confounders and/or measurement errors in covariates. However, IV methods for time-to-event outcome with censored data remain underdeveloped. This paper proposes a Bayesian approach for IV analysis with censored time-to-event outcome by using a two-stage linear model. A Markov Chain Monte Carlo sampling method is developed for parameter estimation for both normal and non-normal linear models with elliptically contoured error distributions. Performance of our method is examined by simulation studies. Our method largely reduces bias and greatly improves coverage probability of the estimated causal effect, compared to the method that ignores the unobserved confounders and measurement errors. We illustrate our method on the Women's Health Initiative Observational Study and the Atherosclerosis Risk in Communities Study. PMID:25393617

  19. Prediction of a time-to-event trait using genome wide SNP data

    PubMed Central

    2013-01-01

    Background A popular objective of many high-throughput genome projects is to discover various genomic markers associated with traits and develop statistical models to predict traits of future patients based on marker values. Results In this paper, we present a prediction method for time-to-event traits using genome-wide single-nucleotide polymorphisms (SNPs). We also propose a MaxTest associating between a time-to-event trait and a SNP accounting for its possible genetic models. The proposed MaxTest can help screen out nonprognostic SNPs and identify genetic models of prognostic SNPs. The performance of the proposed method is evaluated through simulations. Conclusions In conjunction with the MaxTest, the proposed method provides more parsimonious prediction models but includes more prognostic SNPs than some naive prediction methods. The proposed method is demonstrated with real GWAS data. PMID:23418752

  20. Not ready for prime time: transitional events in the extremely preterm infant.

    PubMed

    Armentrout, Debra

    2014-01-01

    Successful transition from intrauterine to extrauterine life involves significant physiologic changes. The majority of these changes occur relatively quickly during those first moments following delivery; however, transition for the extremely preterm infant occurs over a longer period of time. Careful assessment and perceptive interventions on the part of neonatal care providers is essential as the extremely preterm infant adjusts to life outside the womb. This article will focus on respiratory, cardiovascular, gastrointestinal, and neurologic transitional events experienced by the extremely premature infant.

  1. Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality

    PubMed Central

    Hu, Yanzhu; Ai, Xinbo

    2016-01-01

    Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a synthetic method, named small-shuffle partial symbolic transfer entropy spectrum (SSPSTES), for inferring association network from multivariate time series. The method synthesizes surrogate data, partial symbolic transfer entropy (PSTE) and Granger causality. A proper threshold selection is crucial for common correlation identification methods and it is not easy for users. The proposed method can not only identify the strong correlation without selecting a threshold but also has the ability of correlation quantification, direction identification and temporal relation identification. The method can be divided into three layers, i.e. data layer, model layer and network layer. In the model layer, the method identifies all the possible pair-wise correlation. In the network layer, we introduce a filter algorithm to remove the indirect weak correlation and retain strong correlation. Finally, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pair-wise variables, and then get the weighted directed association network. Two numerical simulated data from linear system and nonlinear system are illustrated to show the steps and performance of the proposed approach. The ability of the proposed method is approved by an application finally. PMID:27832153

  2. Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra.

    PubMed

    Chasset, Thibaut; Häbe, Tim T; Ristivojevic, Petar; Morlock, Gertrud E

    2016-09-23

    Quality control of propolis is challenging, as it is a complex natural mixture of compounds, and thus, very difficult to analyze and standardize. Shown on the example of 30 French propolis samples, a strategy for an improved quality control was demonstrated in which high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with selected mass signals obtained by desorption-based scanning mass spectrometry (MS). The French propolis sample extracts were separated by a newly developed reversed phase (RP)-HPTLC method. The fingerprints obtained by two different detection modes, i.e. after (1) derivatization and fluorescence detection (FLD) at UV 366nm and (2) scanning direct analysis in real time (DART)-MS, were analyzed by multivariate data analysis. Thus, RP-HPTLC-FLD and RP-HPTLC-DART-MS fingerprints were explored and the best classification was obtained using both methods in combination with pattern recognition techniques, such as principal component analysis. All investigated French propolis samples were divided in two types and characteristic patterns were observed. Phenolic compounds such as caffeic acid, p-coumaric acid, chrysin, pinobanksin, pinobanksin-3-acetate, galangin, kaempferol, tectochrysin and pinocembrin were identified as characteristic marker compounds of French propolis samples. This study expanded the research on the European poplar type of propolis and confirmed the presence of two botanically different types of propolis, known as the blue and orange types.

  3. Profiling and multivariate statistical analysis of Panax ginseng based on ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry.

    PubMed

    Wu, Wei; Sun, Le; Zhang, Zhe; Guo, Yingying; Liu, Shuying

    2015-03-25

    An ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) method was developed for the detection and structural analysis of ginsenosides in white ginseng and related processed products (red ginseng). Original neutral, malonyl, and chemically transformed ginsenosides were identified in white and red ginseng samples. The aglycone types of ginsenosides were determined by MS/MS as PPD (m/z 459), PPT (m/z 475), C-24, -25 hydrated-PPD or PPT (m/z 477 or m/z 493), and Δ20(21)-or Δ20(22)-dehydrated-PPD or PPT (m/z 441 or m/z 457). Following the structural determination, the UHPLC-Q-TOF-MS-based chemical profiling coupled with multivariate statistical analysis method was applied for global analysis of white and processed ginseng samples. The chemical markers present between the processed products red ginseng and white ginseng could be assigned. Process-mediated chemical changes were recognized as the hydrolysis of ginsenosides with large molecular weight, chemical transformations of ginsenosides, changes in malonyl-ginsenosides, and generation of 20-(R)-ginsenoside enantiomers. The relative contents of compounds classified as PPD, PPT, malonyl, and transformed ginsenosides were calculated based on peak areas in ginseng before and after processing. This study provides possibility to monitor multiple components for the quality control and global evaluation of ginseng products during processing.

  4. The timing of the Black Sea flood event: Insights from modeling of glacial isostatic adjustment

    NASA Astrophysics Data System (ADS)

    Goldberg, Samuel L.; Lau, Harriet C. P.; Mitrovica, Jerry X.; Latychev, Konstantin

    2016-10-01

    We present a suite of gravitationally self-consistent predictions of sea-level change since Last Glacial Maximum (LGM) in the vicinity of the Bosphorus and Dardanelles straits that combine signals associated with glacial isostatic adjustment (GIA) and the flooding of the Black Sea. Our predictions are tuned to fit a relative sea level (RSL) record at the island of Samothrace in the north Aegean Sea and they include realistic 3-D variations in viscoelastic structure, including lateral variations in mantle viscosity and the elastic thickness of the lithosphere, as well as weak plate boundary zones. We demonstrate that 3-D Earth structure and the magnitude of the flood event (which depends on the pre-flood level of the lake) both have significant impact on the predicted RSL change at the location of the Bosphorus sill, and therefore on the inferred timing of the marine incursion. We summarize our results in a plot showing the predicted RSL change at the Bosphorus sill as a function of the timing of the flood event for different flood magnitudes up to 100 m. These results suggest, for example, that a flood event at 9 ka implies that the elevation of the sill was lowered through erosion by ∼14-21 m during, and after, the flood. In contrast, a flood event at 7 ka suggests erosion of ∼24-31 m at the sill since the flood. More generally, our results will be useful for future research aimed at constraining the details of this controversial, and widely debated geological event.

  5. Event-driven time-optimal control for a class of discontinuous bioreactors.

    PubMed

    Moreno, Jaime A; Betancur, Manuel J; Buitrón, Germán; Moreno-Andrade, Iván

    2006-07-05

    Discontinuous bioreactors may be further optimized for processing inhibitory substrates using a convenient fed-batch mode. To do so the filling rate must be controlled in such a way as to push the reaction rate to its maximum value, by increasing the substrate concentration just up to the point where inhibition begins. However, an exact optimal controller requires measuring several variables (e.g., substrate concentrations in the feed and in the tank) and also good model knowledge (e.g., yield and kinetic parameters), requirements rarely satisfied in real applications. An environmentally important case, that exemplifies all these handicaps, is toxicant wastewater treatment. There the lack of online practical pollutant sensors may allow unforeseen high shock loads to be fed to the bioreactor, causing biomass inhibition that slows down the treatment process and, in extreme cases, even renders the biological process useless. In this work an event-driven time-optimal control (ED-TOC) is proposed to circumvent these limitations. We show how to detect a "there is inhibition" event by using some computable function of the available measurements. This event drives the ED-TOC to stop the filling. Later, by detecting the symmetric event, "there is no inhibition," the ED-TOC may restart the filling. A fill-react cycling then maintains the process safely hovering near its maximum reaction rate, allowing a robust and practically time-optimal operation of the bioreactor. An experimental study case of a wastewater treatment process application is presented. There the dissolved oxygen concentration was used to detect the events needed to drive the controller.

  6. Solving chromatographic challenges in comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry using multivariate curve resolution-alternating least squares.

    PubMed

    Parastar, Hadi; Radović, Jagoš R; Bayona, Josep M; Tauler, Roma

    2013-07-01

    Multivariate curve resolution-alternating least squares (MCR-ALS) analysis is proposed to solve chromatographic challenges during two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) analysis of complex samples, such as crude oil extract. In view of the fact that the MCR-ALS method is based on the fulfillment of the bilinear model assumption, three-way and four-way GC × GC-TOFMS data are preferably arranged in a column-wise superaugmented data matrix in which mass-to-charge ratios (m/z) are in its columns and the elution times in the second and first chromatographic columns are in its rows. Since m/z values are common for all measured spectra in all second-column modulations, unavoidable chromatographic challenges such as retention time shifts within and between GC × GC-TOFMS experiments are properly handled. In addition, baseline/background contributions can be modeled by adding extra components to the MCR-ALS model. Another outstanding aspect of MCR-ALS analysis is its extreme flexibility to consider all samples (standards, unknowns, and replicates) in a single superaugmented data matrix, allowing joint analysis. In this way, resolution, identification, and quantification results can be simultaneously obtained in a very fast and reliable way. The potential of MCR-ALS analysis is demonstrated in GC × GC-TOFMS analysis of a North Sea crude oil extract sample with relative errors in estimated concentrations of target compounds below 6.0 % and relative standard deviations lower than 7.0 %. The results obtained, along with reasonable values for the lack of fit of the MCR-ALS model and high values of the reversed match factor in mass spectra similarity searches, confirm the reliability of the proposed strategy for GC × GC-TOFMS data analysis.

  7. Infants’ Looking to Surprising Events: When Eye-Tracking Reveals More than Looking Time

    PubMed Central

    Yeung, H. Henny; Denison, Stephanie; Johnson, Scott P.

    2016-01-01

    Research on infants’ reasoning abilities often rely on looking times, which are longer to surprising and unexpected visual scenes compared to unsurprising and expected ones. Few researchers have examined more precise visual scanning patterns in these scenes, and so, here, we recorded 8- to 11-month-olds’ gaze with an eye tracker as we presented a sampling event whose outcome was either surprising, neutral, or unsurprising: A red (or yellow) ball was drawn from one of three visible containers populated 0%, 50%, or 100% with identically colored balls. When measuring looking time to the whole scene, infants were insensitive to the likelihood of the sampling event, replicating failures in similar paradigms. Nevertheless, a new analysis of visual scanning showed that infants did spend more time fixating specific areas-of-interest as a function of the event likelihood. The drawn ball and its associated container attracted more looking than the other containers in the 0% condition, but this pattern was weaker in the 50% condition, and even less strong in the 100% condition. Results suggest that measuring where infants look may be more sensitive than simply how much looking there is to the whole scene. The advantages of eye tracking measures over traditional looking measures are discussed. PMID:27926920

  8. Infants' Looking to Surprising Events: When Eye-Tracking Reveals More than Looking Time.

    PubMed

    Yeung, H Henny; Denison, Stephanie; Johnson, Scott P

    2016-01-01

    Research on infants' reasoning abilities often rely on looking times, which are longer to surprising and unexpected visual scenes compared to unsurprising and expected ones. Few researchers have examined more precise visual scanning patterns in these scenes, and so, here, we recorded 8- to 11-month-olds' gaze with an eye tracker as we presented a sampling event whose outcome was either surprising, neutral, or unsurprising: A red (or yellow) ball was drawn from one of three visible containers populated 0%, 50%, or 100% with identically colored balls. When measuring looking time to the whole scene, infants were insensitive to the likelihood of the sampling event, replicating failures in similar paradigms. Nevertheless, a new analysis of visual scanning showed that infants did spend more time fixating specific areas-of-interest as a function of the event likelihood. The drawn ball and its associated container attracted more looking than the other containers in the 0% condition, but this pattern was weaker in the 50% condition, and even less strong in the 100% condition. Results suggest that measuring where infants look may be more sensitive than simply how much looking there is to the whole scene. The advantages of eye tracking measures over traditional looking measures are discussed.

  9. Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity.

    PubMed

    Jeni, László A; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F; Kanade, Takeo

    2014-01-01

    In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods.

  10. Meteorological factors and timing of the initiating event of human parturition

    NASA Astrophysics Data System (ADS)

    Hirsch, Emmet; Lim, Courtney; Dobrez, Deborah; Adams, Marci G.; Noble, William

    2011-03-01

    The aim of this study was to determine whether meteorological factors are associated with the timing of either onset of labor with intact membranes or rupture of membranes prior to labor—together referred to as `the initiating event' of parturition. All patients delivering at Evanston Hospital after spontaneous labor or rupture of membranes at ≥20 weeks of gestation over a 6-month period were studied. Logistic regression models of the initiating event of parturition using clinical variables (maternal age, gestational age, parity, multiple gestation and intrauterine infection) with and without the addition of meteorological variables (barometric pressure, temperature and humidity) were compared. A total of 1,088 patients met the inclusion criteria. Gestational age, multiple gestation and chorioamnionitis were associated with timing of initiation of parturition ( P < 0.01). The addition of meteorological to clinical variables generated a statistically significant improvement in prediction of the initiating event; however, the magnitude of this improvement was small (less than 2% difference in receiver-operating characteristic score). These observations held regardless of parity, fetal number and gestational age. Meteorological factors are associated with the timing of parturition, but the magnitude of this association is small.

  11. Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity

    PubMed Central

    Jeni, László A.; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F.; Kanade, Takeo

    2016-01-01

    In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods1. PMID:27830214

  12. Time-frequency analysis of event-related potentials: a brief tutorial.

    PubMed

    Herrmann, Christoph S; Rach, Stefan; Vosskuhl, Johannes; Strüber, Daniel

    2014-07-01

    Event-related potentials (ERPs) reflect cognitive processes and are usually analyzed in the so-called time domain. Additional information on cognitive functions can be assessed when analyzing ERPs in the frequency domain and treating them as event-related oscillations (EROs). This procedure results in frequency spectra but lacks information about the temporal dynamics of EROs. Here, we describe a method-called time-frequency analysis-that allows analyzing both the frequency of an ERO and its evolution over time. In a brief tutorial, the reader will learn how to use wavelet analysis in order to compute time-frequency transforms of ERP data. Basic steps as well as potential artifacts are described. Rather than in terms of formulas, descriptions are in textual form (written text) with numerous figures illustrating the topics. Recommendations on how to present frequency and time-frequency data in journal articles are provided. Finally, we briefly review studies that have applied time-frequency analysis to mismatch negativity paradigms. The deviant stimulus of such a paradigm evokes an ERO in the theta frequency band that is stronger than for the standard stimulus. Conversely, the standard stimulus evokes a stronger gamma-band response than does the deviant. This is interpreted in the context of the so-called match-and-utilization model.

  13. Determination of the event collision time with the ALICE detector at the LHC

    NASA Astrophysics Data System (ADS)

    Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; An, M.; Andrei, C.; Andrews, H. A.; Andronic, A.; Anguelov, V.; Anson, C.; Antičić, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V.; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Boldizsár, L.; Bombara, M.; Bonora, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buitron, S. A. I.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crkovská, J.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Deisting, A.; Deloff, A.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Di Ruzza, B.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Duggal, A. K.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Espagnon, B.; Esumi, S.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Gallio, M.; Galvan, C. D.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Garg, P.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Gay Ducati, M. B.; Germain, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, A. S.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Graham, K. L.; Greiner, L.; Grelli, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grosso, R.; Gruber, L.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Guzman, I. B.; Haake, R.; Hadjidakis, C.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbär, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Herrmann, F.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Hladky, J.; Horak, D.; Hosokawa, R.; Hristov, P.; Hughes, C.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Isakov, V.; Islam, M. S.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacak, B.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Khatun, A.; Khuntia, A.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, J.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kundu, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lapidus, K.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lazaridis, L.; Lea, R.; Leardini, L.; Lee, S.; Lehas, F.; Lehner, S.; Lehrbach, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Llope, W.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lupi, M.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Mao, Y.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzilli, M.; Mazzoni, M. A.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Mhlanga, S.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Mishra, T.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Münning, K.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Myers, C. J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Negrao De Oliveira, R. A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Ohlson, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pacik, V.; Pagano, D.; Pagano, P.; Paić, G.; Pal, S. K.; Palni, P.; Pan, J.; Pandey, A. K.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, J.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Peng, X.; Pereira Da Costa, H.; Peresunko, D.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Poppenborg, H.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Pozdniakov, V.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Rana, D. B.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Ratza, V.; Ravasenga, I.; Read, K. F.; Redlich, K.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rodríguez Cahuantzi, M.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarkar, N.; Sarma, P.; Sas, M. H. P.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schmidt, M.; Schukraft, J.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sett, P.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singhal, V.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spiriti, E.; Sputowska, I.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Sumowidagdo, S.; Suzuki, K.; Swain, S.; Szabo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thakur, D.; Thomas, D.; Tieulent, R.; Tikhonov, A.; Timmins, A. R.; Toia, A.; Tripathy, S.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Umaka, E. N.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vázquez Doce, O.; Vechernin, V.; Veen, A. M.; Velure, A.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Vértesi, R.; Vickovic, L.; Vigolo, S.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Virgili, T.; Vislavicius, V.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Voscek, D.; Vranic, D.; Vrláková, J.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Willems, G. A.; Williams, M. C. S.; Windelband, B.; Winn, M.; Witt, W. E.; Yalcin, S.; Yang, P.; Yano, S.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zmeskal, J.

    2017-02-01

    Particle identification is an important feature of the ALICE detector at the LHC. In particular, for particle identification via the time-of-flight technique, the precise determination of the event collision time represents an important ingredient of the quality of the measurement. In this paper, the different methods used for such a measurement in ALICE by means of the T0 and the TOF detectors are reviewed. Efficiencies, resolution and the improvement of the particle identification separation power of the methods used are presented for the different LHC colliding systems (pp, p-Pb and Pb-Pb) during the first period of data taking of LHC (RUN 1).

  14. Adaptation-Induced Compression of Event Time Occurs Only for Translational Motion.

    PubMed

    Fornaciai, Michele; Arrighi, Roberto; Burr, David C

    2016-03-22

    Adaptation to fast motion reduces the perceived duration of stimuli displayed at the same location as the adapting stimuli. Here we show that the adaptation-induced compression of time is specific for translational motion. Adaptation to complex motion, either circular or radial, did not affect perceived duration of subsequently viewed stimuli. Adaptation with multiple patches of translating motion caused compression of duration only when the motion of all patches was in the same direction. These results show that adaptation-induced compression of event-time occurs only for uni-directional translational motion, ruling out the possibility that the neural mechanisms of the adaptation occur at early levels of visual processing.

  15. Optimal Futility Interim Design: A Predictive Probability of Success Approach with Time-to-Event Endpoint.

    PubMed

    Tang, Zhongwen

    2015-01-01

    An analytical way to compute predictive probability of success (PPOS) together with credible interval at interim analysis (IA) is developed for big clinical trials with time-to-event endpoints. The method takes account of the fixed data up to IA, the amount of uncertainty in future data, and uncertainty about parameters. Predictive power is a special type of PPOS. The result is confirmed by simulation. An optimal design is proposed by finding optimal combination of analysis time and futility cutoff based on some PPOS criteria.

  16. Stochastic univariate and multivariate time series analysis of PM2.5 and PM10 air pollution: A comparative case study for Plovdiv and Asenovgrad, Bulgaria

    NASA Astrophysics Data System (ADS)

    Gocheva-Ilieva, S.; Stoimenova, M.; Ivanov, A.; Voynikova, D.; Iliev, I.

    2016-10-01

    Fine particulate matter PM2.5 and PM10 air pollutants are a serious problem in many urban areas affecting both the health of the population and the environment as a whole. The availability of large data arrays for the levels of these pollutants makes it possible to perform statistical analysis, to obtain relevant information, and to find patterns within the data. Research in this field is particularly topical for a number of Bulgarian cities, European country, where in recent years regulatory air pollution health limits are constantly being exceeded. This paper examines average daily data for air pollution with PM2.5 and PM10, collected by 3 monitoring stations in the cities of Plovdiv and Asenovgrad between 2011 and 2016. The goal is to find and analyze actual relationships in data time series, to build adequate mathematical models, and to develop short-term forecasts. Modeling is carried out by stochastic univariate and multivariate time series analysis, based on Box-Jenkins methodology. The best models are selected following initial transformation of the data and using a set of standard and robust statistical criteria. The Mathematica and SPSS software were used to perform calculations. This examination showed measured concentrations of PM2.5 and PM10 in the region of Plovdiv and Asenovgrad regularly exceed permissible European and national health and safety thresholds. We obtained adequate stochastic models with high statistical fit with the data and good quality forecasting when compared against actual measurements. The mathematical approach applied provides an independent alternative to standard official monitoring and control means for air pollution in urban areas.

  17. MARSIS Data Bad Time Stamp: Analysis and Solution of an Anomaly Event in a Space Mission

    NASA Astrophysics Data System (ADS)

    Giuppi, S.; Cartacci, M.; Cicchetti, A.; Frigeri, A.; Noschese, R.; Orosei, R.

    2012-04-01

    Mars Express is Europe's first spacecraft to the Red Planet. The spacecraft has been orbiting Mars since December 2003, carrying a suite of instruments that are investigating many scientific aspects of this planet in unprecedented detail. The observations are particularly focused on martian atmosphere, surface and subsurface. The most innovative instrument on board of Mars Express is MARSIS, a subsurface radar sounder with a 40-meter antenna. The main objective of MARSIS is to look for water from the martian surface down to about 5 kilometers below the surface. It provides the first opportunity to detect liquid water directly. It is also able to characterize the surface elevation, roughness, and radar reflectivity of the planet and to study the interaction of the atmosphere and solar wind in the red planet's ionosphere. MARSIS Data are stored on the on-board memory and periodically sent to Earth ground stations. Spacecraft Event Time (SCET) is the time an event occurs in relation to a spacecraft as measured by the spacecraft clock. Since it takes time for a radio transmission to reach the spacecraft from the earth, the usual operation of a spacecraft is done via an uploaded commanding script containing SCET markers to ensure a certain timeline of events. Occasionally the generation time (SCET) of the MARSIS science packets recorded during an observation gets corrupted. This means that while some of the data have the correct SCET, some other data have a SCET not compliant with the effective generation time. For this reason with the standard procedure it is possible to retrieve only partial data. In this paper we describe the cause of the anomaly occurrence and the procedures to be applied depending on the circumstances that arise. The application of these procedures is been successful and allowed to circumvent the problem.

  18. Model-based estimation of measures of association for time-to-event outcomes

    PubMed Central

    2014-01-01

    Background Hazard ratios are ubiquitously used in time to event applications to quantify adjusted covariate effects. Although hazard ratios are invaluable for hypothesis testing, other adjusted measures of association, both relative and absolute, should be provided to fully appreciate studies results. The corrected group prognosis method is generally used to estimate the absolute risk reduction and the number needed to be treated for categorical covariates. Methods The goal of this paper is to present transformation models for time-to-event outcomes to obtain, directly from estimated coefficients, the measures of association widely used in biostatistics together with their confidence interval. Pseudo-values are used for a practical estimation of transformation models. Results Using the regression model estimated through pseudo-values with suitable link functions, relative risks, risk differences and the number needed to treat, are obtained together with their confidence intervals. One example based on literature data and one original application to the study of prognostic factors in primary retroperitoneal soft tissue sarcomas are presented. A simulation study is used to show some properties of the different estimation methods. Conclusions Clinically useful measures of treatment or exposure effect are widely available in epidemiology. When time to event outcomes are present, the analysis is performed generally resorting to predicted values from Cox regression model. It is now possible to resort to more general regression models, adopting suitable link functions and pseudo values for estimation, to obtain alternative measures of effect directly from regression coefficients together with their confidence interval. This may be especially useful when, in presence of time dependent covariate effects, it is not straightforward to specify the correct, if any, time dependent functional form. The method can easily be implemented with standard software. PMID:25106903

  19. Multivariate meta-analysis: potential and promise.

    PubMed

    Jackson, Dan; Riley, Richard; White, Ian R

    2011-09-10

    The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice.

  20. Full waveform inversion of repeating seismic events to estimate time-lapse velocity changes

    NASA Astrophysics Data System (ADS)

    Kamei, R.; Lumley, D.

    2017-02-01

    Seismic monitoring provides valuable information regarding the time-varying changes in subsurface physical properties caused by natural or man-made processes. However, the resulting changes in the earth's subsurface properties are often small both in terms of magnitude and spatial extent, leading to minimal time-lapse differences in seismic amplitude or traveltime. In order to better extract information from the time-lapse data, we show that exploiting the full seismic waveform information can be critical. In this study, we develop and test methods of full waveform inversion that estimate an optimal subsurface model of time-varying elastic properties in order to fit the observed time-lapse seismic data with predicted waveforms based on numerical solutions of the wave equation. Time-lapse full waveform inversion is non-linear and non-unique, and depends on the knowledge of the baseline velocity model before a change, and (non-)repeatability of earthquake source and sensor parameters, and of ambient and cultural noise. We propose to use repeating earthquake data sets acquired with permanent arrays of seismic sensors to enhance the repeatability of source and sensor parameters. We further develop and test time-lapse parallel, double-difference and bootstrapping inversion strategies to mitigate the dependence on the baseline velocity model. The parallel approach uses a time-invariant full waveform inversion method to estimate velocity models independently of the different source event times. The double-difference approach directly estimates velocity changes from time-lapse waveform differences, requiring excellent repeatability. The bootstrapping approach inverts for velocity models sequentially in time, implicitly constraining the time-lapse inversions, while relaxing an explicit requirement for high data repeatability. We assume that prior to the time-lapse inversion, we can estimate the true source locations and the origin time of the events, and also we can also

  1. Neutron measurements with Time-Resolved Event-Counting Optical Radiation (TRECOR) detector

    NASA Astrophysics Data System (ADS)

    Brandis, M.; Vartsky, D.; Dangendorf, V.; Bromberger, B.; Bar, D.; Goldberg, M. B.; Tittelmeier, K.; Friedman, E.; Czasch, A.; Mardor, I.; Mor, I.; Weierganz, M.

    2012-04-01

    Results are presented from the latest experiment with a new neutron/gamma detector, a Time-Resolved, Event-Counting Optical Radiation (TRECOR) detector. It is composed of a scintillating fiber-screen converter, bending mirror, lens and Event-Counting Image Intensifier (ECII), capable of specifying the position and time-of-flight of each event. TRECOR is designated for a multipurpose integrated system that will detect Special Nuclear Materials (SNM) and explosives in cargo. Explosives are detected by Fast-Neutron Resonance Radiography, and SNM by Dual Discrete-Energy gamma-Radiography. Neutrons and gamma-rays are both produced in the 11B(d,n+γ)12C reaction. The two detection modes can be implemented simultaneously in TRECOR, using two adjacent radiation converters that share a common optical readout. In the present experiment the neutron detection mode was studied, using a plastic scintillator converter. The measurements were performed at the PTB cyclotron, using the 9Be(d,n) neutron spectrum obtained from a thick Be-target at Ed ~ 13 MeV\\@. The basic characteristics of this detector were investigated, including the Contrast Transfer Function (CTF), Point Spread Function (PSF) and elemental discrimination capability.

  2. Chapter 8: Spatiotemporal dynamics in bacterial cells: real-time studies with single-event resolution.

    PubMed

    Golding, Ido; Cox, Edward C

    2008-01-01

    To produce a quantitative picture of cellular life, one has to study the processes comprising it in individual living cells, quantifying intracellular dynamics with sufficient resolution to describe individual events in space and time. To perform such studies, we have recently developed a novel measurement approach, based on quantitative fluorescence microscopy, and applied it to the study of transcription in Escherichia coli and of the spatiotemporal dynamics of individual mRNA molecules in the cell (Golding and Cox, 2004, 2006a; Golding et al., 2005). The ability to detect individual events in real time depends on the engineering of an endogenous cellular process for amplifying the biological signal, in a way which allows signal detection to be independent of slow and highly stochastic cellular processes (Golding and Cox, 2006a). In this chapter, we describe the ingredients of our system and the way data is acquired and analyzed. We attempt to give general lessons for researchers who wish to implement a similar approach for the study of transcription in other organisms and, more generally, for the study of cellular processes with single-event resolution.

  3. Unchanged Levels of Soluble CD14 and IL-6 Over Time Predict Serious Non-AIDS Events in HIV-1-Infected People.

    PubMed

    Sunil, Meena; Nigalye, Maitreyee; Somasunderam, Anoma; Martinez, Maria Laura; Yu, Xiaoying; Arduino, Roberto C; Utay, Netanya S; Bell, Tanvir K

    2016-12-01

    HIV-1-infected persons have increased risk of serious non-AIDS events (SNAEs) despite suppressive antiretroviral therapy. Increased circulating levels of soluble CD14 (sCD14), soluble CD163 (sCD163), and interleukin-6 (IL-6) at a single time point have been associated with SNAEs. However, whether changes in these biomarker levels predict SNAEs in HIV-1-infected persons is unknown. We hypothesized that greater decreases in inflammatory biomarkers would be associated with fewer SNAEs. We identified 39 patients with SNAEs, including major cardiovascular events, end stage renal disease, decompensated cirrhosis, non-AIDS-defining malignancies, and death of unknown cause, and age- and sex-matched HIV-1-infected controls. sCD14, sCD163, and IL-6 were measured at study enrollment (T1) and proximal to the event (T2) or equivalent duration in matched controls. Over ∼34 months, unchanged rather than decreasing levels of sCD14 and IL-6 predicted SNAEs. Older age and current illicit substance abuse, but not HCV coinfection, were associated with SNAEs. In a multivariate analysis, older age, illicit substance use, and unchanged IL-6 levels remained significantly associated with SNAEs. Thus, the trajectories of sCD14 and IL-6 levels predict SNAEs. Interventions to decrease illicit substance use may decrease the risk of SNAEs in HIV-1-infected persons.

  4. Diagnosis of delay-deadline failures in real time discrete event models.

    PubMed

    Biswas, Santosh; Sarkar, Dipankar; Bhowal, Prodip; Mukhopadhyay, Siddhartha

    2007-10-01

    In this paper a method for fault detection and diagnosis (FDD) of real time systems has been developed. A modeling framework termed as real time discrete event system (RTDES) model is presented and a mechanism for FDD of the same has been developed. The use of RTDES framework for FDD is an extension of the works reported in the discrete event system (DES) literature, which are based on finite state machines (FSM). FDD of RTDES models are suited for real time systems because of their capability of representing timing faults leading to failures in terms of erroneous delays and deadlines, which FSM-based ones cannot address. The concept of measurement restriction of variables is introduced for RTDES and the consequent equivalence of states and indistinguishability of transitions have been characterized. Faults are modeled in terms of an unmeasurable condition variable in the state map. Diagnosability is defined and the procedure of constructing a diagnoser is provided. A checkable property of the diagnoser is shown to be a necessary and sufficient condition for diagnosability. The methodology is illustrated with an example of a hydraulic cylinder.

  5. Towards real-time regional earthquake simulation I: real-time moment tensor monitoring (RMT) for regional events in Taiwan

    NASA Astrophysics Data System (ADS)

    Lee, Shiann-Jong; Liang, Wen-Tzong; Cheng, Hui-Wen; Tu, Feng-Shan; Ma, Kuo-Fong; Tsuruoka, Hiroshi; Kawakatsu, Hitoshi; Huang, Bor-Shouh; Liu, Chun-Chi

    2014-01-01

    We have developed a real-time moment tensor monitoring system (RMT) which takes advantage of a grid-based moment tensor inversion technique and real-time broad-band seismic recordings to automatically monitor earthquake activities in the vicinity of Taiwan. The centroid moment tensor (CMT) inversion technique and a grid search scheme are applied to obtain the information of earthquake source parameters, including the event origin time, hypocentral location, moment magnitude and focal mechanism. All of these source parameters can be determined simultaneously within 117 s after the occurrence of an earthquake. The monitoring area involves the entire Taiwan Island and the offshore region, which covers the area of 119.3°E to 123.0°E and 21.0°N to 26.0°N, with a depth from 6 to 136 km. A 3-D grid system is implemented in the monitoring area with a uniform horizontal interval of 0.1° and a vertical interval of 10 km. The inversion procedure is based on a 1-D Green's function database calculated by the frequency-wavenumber (fk) method. We compare our results with the Central Weather Bureau (CWB) catalogue data for earthquakes occurred between 2010 and 2012. The average differences between event origin time and hypocentral location are less than 2 s and 10 km, respectively. The focal mechanisms determined by RMT are also comparable with the Broadband Array in Taiwan for Seismology (BATS) CMT solutions. These results indicate that the RMT system is realizable and efficient to monitor local seismic activities. In addition, the time needed to obtain all the point source parameters is reduced substantially compared to routine earthquake reports. By connecting RMT with a real-time online earthquake simulation (ROS) system, all the source parameters will be forwarded to the ROS to make the real-time earthquake simulation feasible. The RMT has operated offline (2010-2011) and online (since January 2012 to present) at the Institute of Earth Sciences (IES), Academia Sinica

  6. Validation of Cross-Sectional Time Series and Multivariate Adaptive Regression Splines Models for the Prediction of Energy Expenditure in Children and Adolescents Using Doubly Labeled Water12

    PubMed Central

    Butte, Nancy F.; Wong, William W.; Adolph, Anne L.; Puyau, Maurice R.; Vohra, Firoz A.; Zakeri, Issa F.

    2010-01-01

    Accurate, nonintrusive, and inexpensive techniques are needed to measure energy expenditure (EE) in free-living populations. Our primary aim in this study was to validate cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on observable participant characteristics, heart rate (HR), and accelerometer counts (AC) for prediction of minute-by-minute EE, and hence 24-h total EE (TEE), against a 7-d doubly labeled water (DLW) method in children and adolescents. Our secondary aim was to demonstrate the utility of CSTS and MARS to predict awake EE, sleep EE, and activity EE (AEE) from 7-d HR and AC records, because these shorter periods are not verifiable by DLW, which provides an estimate of the individual's mean TEE over a 7-d interval. CSTS and MARS models were validated in 60 normal-weight and overweight participants (ages 5–18 y). The Actiheart monitor was used to simultaneously measure HR and AC. For prediction of TEE, mean absolute errors were 10.7 ± 307 kcal/d and 18.7 ± 252 kcal/d for CSTS and MARS models, respectively, relative to DLW. Corresponding root mean square error values were 305 and 251 kcal/d for CSTS and MARS models, respectively. Bland-Altman plots indicated that the predicted values were in good agreement with the DLW-derived TEE values. Validation of CSTS and MARS models based on participant characteristics, HR monitoring, and accelerometry for the prediction of minute-by-minute EE, and hence 24-h TEE, against the DLW method indicated no systematic bias and acceptable limits of agreement for pediatric groups and individuals under free-living conditions. PMID:20573939

  7. Using time-of-flight secondary ion mass spectrometry and multivariate statistical analysis to detect and image octabenzyl-polyhedral oligomeric silsesquioxane in polycarbonate

    NASA Astrophysics Data System (ADS)

    Smentkowski, V. S.; Duong, H. M.; Tamaki, R.; Keenan, M. R.; Ohlhausen, J. A. Tony; Kotula, P. G.

    2006-11-01

    Silsesquioxane, with an empirical formula of RSiO 3/2, has the potential to combine the mechanical properties of plastics with the oxidative stability of ceramics in one material [D.W. Scott, J. Am. Chem. Soc. 68 (1946) 356; K.J. Shea, D.A. Loy, Acc. Chem. Res. 34 (2001) 707; K.-M. Kim, D.-K. Keum, Y. Chujo, Macromolecules 36 (2003) 867; M.J. Abad, L. Barral, D.P. Fasce, R.J.J. William, Macromolecules 36 (2003) 3128]. The high sensitivity, surface specificity, and ability to detect and image high mass additives make time-of-flight secondary ion mass spectrometry (ToF-SIMS) a powerful surface analytical instrument for the characterization of polymer composite surfaces in an analytical laboratory [J.C. Vickerman, D. Briggs (Eds.), ToF-SIMS Surface Analysis by Mass Spectrometry, Surface Spectra/IMPublications, UK, 2001; X. Vanden Eynde, P. Bertand, Surf. Interface Anal. 27 (1999) 157; P.M. Thompson, Anal. Chem. 63 (1991) 2447; S.J. Simko, S.R. Bryan, D.P. Griffis, R.W. Murray, R.W. Linton, Anal. Chem. 57 (1985) 1198; S. Affrossman, S.A. O'Neill, M. Stamm, Macromolecules 31 (1998) 6280]. In this paper, we compare ToF-SIMS spectra of control samples with spectra generated from polymer nano-composites based on octabenzyl-polyhedral oligomeric silsesquioxane (BnPOSS) as well as spectra (and images) generated from multivariate statistical analysis (MVSA) of the entire spectral image. We will demonstrate that ToF-SIMS is able to detect and image low concentrations of BnPOSS in polycarbonate. We emphasize the use of MVSA tools for converting the massive amount of data contained in a ToF-SIMS spectral image into a smaller number of useful chemical components (spectra and images) that fully describe the ToF-SIMS measurement.

  8. Time-Frequency Data Reduction for Event Related Potentials: Combining Principal Component Analysis and Matching Pursuit

    NASA Astrophysics Data System (ADS)

    Aviyente, Selin; Bernat, Edward M.; Malone, Stephen M.; Iacono, William G.

    2010-12-01

    Joint time-frequency representations offer a rich representation of event related potentials (ERPs) that cannot be obtained through individual time or frequency domain analysis. This representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to experimentally relevant components are essential. In this paper, we present a method that reduces the large volume of ERP time-frequency data into a few significant time-frequency parameters. The proposed method is based on applying the widely used matching pursuit (MP) approach, with a Gabor dictionary, to principal components extracted from the time-frequency domain. The proposed PCA-Gabor decomposition is compared with other time-frequency data reduction methods such as the time-frequency PCA approach alone and standard matching pursuit methods using a Gabor dictionary for both simulated and biological data. The results show that the proposed PCA-Gabor approach performs better than either the PCA alone or the standard MP data reduction methods, by using the smallest amount of ERP data variance to produce the strongest statistical separation between experimental conditions.

  9. Event-related EEG time-frequency PCA and the orienting reflex to auditory stimuli.

    PubMed

    Barry, Robert J; De Blasio, Frances M; Bernat, Edward M; Steiner, Genevieve Z

    2015-04-01

    We recently reported an auditory habituation series with counterbalanced indifferent and significant (counting) instructions. Time-frequency (t-f) analysis of electrooculogram-corrected EEG was used to explore event-related synchronization (ERS)/desynchronization (ERD) in four EEG bands using arbitrarily selected time epochs and traditional frequency ranges. ERS in delta, theta, and alpha, and subsequent ERD in theta, alpha, and beta, showed substantial decrement over trials, yet effects of stimulus significance (count vs. no-task) were minimal. Here, we used principal components analysis (PCA) of the t-f data to investigate the natural frequency and time combinations involved in such stimulus processing. We identified four ERS and four ERD t-f components: six showed decrement over trials, four showed count > no-task effects, and six showed Significance × Trial interactions. This increased sensitivity argues for the wider use of our data-driven t-f PCA approach.

  10. Real-time gait event detection for lower limb amputees using a single wearable sensor.

    PubMed

    Maqbool, H F; Husman, M A B; Awad, M I; Abouhossein, A; Mehryar, P; Iqbal, N; Dehghani-Sanij, A A

    2016-08-01

    This paper presents a rule-based real-time gait event/phase detection system (R-GEDS) using a shank mounted inertial measurement unit (IMU) for lower limb amputees during the level ground walking. Development of the algorithm is based on the shank angular velocity in the sagittal plane and linear acceleration signal in the shank longitudinal direction. System performance was evaluated with four control subjects (CS) and one transfemoral amputee (TFA) and the results were validated with four FlexiForce footswitches (FSW). The results showed a data latency for initial contact (IC) and toe off (TO) within a range of ± 40 ms for both CS and TFA. A delay of about 3.7 ± 62 ms for a foot-flat start (FFS) and an early detection of -9.4 ± 66 ms for heel-off (HO) was found for CS. Prosthetic side showed an early detection of -105 ± 95 ms for FFS whereas intact side showed a delay of 141 ±73 ms for HO. The difference in the kinematics of the TFA and CS is one of the potential reasons for high variations in the time difference. Overall, detection accuracy was 99.78% for all the events in both groups. Based on the validated results, the proposed system can be used to accurately detect the temporal gait events in real-time that leads to the detection of gait phase system and therefore, can be utilized in gait analysis applications and the control of lower limb prostheses.

  11. Time is of the essence: an application of a relational event model for animal social networks.

    PubMed

    Patison, K P; Quintane, E; Swain, D L; Robins, G; Pattison, P

    Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregated to represent a relationship as part of one (or several) pictures of the network of relations among animals, in a way that parallels human social networks. This transformation entails loss of information about interaction timing and sequence, which are particularly important to understand the formation of relationships or their disruption. Here, we describe a new statistical model, termed the relational event model, that enables the analysis of fine-grained animal association data as a continuous time sequence without requiring aggregation of the data. We apply the model to a unique data set of interaction between familiar and unfamiliar steers during a series of 36 experiments to investigate the process of social disruption and relationship formation. We show how the model provides key insights into animal behaviour in terms of relationship building, the integration process of unfamiliar animals and group building dynamics. The relational event model is well suited to data structures that are common to animal behavioural studies and can therefore be applied to a range of social interaction data to understand animal social dynamics.

  12. Integrated survival analysis using an event-time approach in a Bayesian framework

    USGS Publications Warehouse

    Walsh, Daniel P.; Dreitz, VJ; Heisey, Dennis M.

    2015-01-01

    Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the

  13. Integrated survival analysis using an event-time approach in a Bayesian framework

    PubMed Central

    Walsh, Daniel P; Dreitz, Victoria J; Heisey, Dennis M

    2015-01-01

    Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the

  14. Solar Energetic-Particle Release Times in Historic Ground-Level Events

    NASA Astrophysics Data System (ADS)

    Reames, Donald V.

    2009-11-01

    Ground-level events (GLEs) are large solar energetic-particle events with sufficiently hard spectra for GeV protons to be detected by neutron monitors at ground level. For each of 30 well-observed historic GLEs from four solar cycles, extending back to 1973, I have plotted onset times versus velocity-1 for particles observed on the IMP-7 and 8, ISEE-3, Wind, and GOES spacecraft and by neutron monitors. A linear fit on such a plot for each GLE determines the initial solar particle release (SPR) time, as the intercept, and the magnetic path length traversed, as the slope, of the fitted line. Magnetic path lengths and SPR times are well determined by the fits and cannot be used as adjustable parameters to make particle and photon emission times coincide. SPR times follow the onsets of shock-induced type II radio bursts and the coronal height of the coronal mass ejection (CME)-driven shock at SPR time can be determined for GLEs spanning an interval of solar longitude of ~140 deg. For a given GLE, all particle species and energies diverge from a single SPR point at a given coronal height and footpoint longitude of the field line to the Earth. These heights tend to increase with longitudinal distance away from the source, a pattern expected for shock acceleration. Acceleration for magnetically well-connected large GLEs begins at ~2 solar radii, in contrast to non-GLEs that have been found to be strongly associated with shocks above ~3 solar radii. The higher densities and magnetic field strengths at lower altitudes may be responsible for the acceleration of higher-energy particles in GLEs, while those GLEs that begin above 3R S may compensate by having higher shock speeds. These results support the joint dependence of maximum particle energy on magnetic field strength, injected particle density, and shock speed, all predicted theoretically.

  15. Time-Based and Event-Based Prospective Memory in Autism Spectrum Disorder: The Roles of Executive Function and Theory of Mind, and Time-Estimation

    ERIC Educational Resources Information Center

    Williams, David; Boucher, Jill; Lind, Sophie; Jarrold, Christopher

    2013-01-01

    Prospective memory (remembering to carry out an action in the future) has been studied relatively little in ASD. We explored time-based (carry out an action at a pre-specified time) and event-based (carry out an action upon the occurrence of a pre-specified event) prospective memory, as well as possible cognitive correlates, among 21…

  16. Perceiving Control Over Aversive and Fearful Events Can Alter How We Experience Those Events: An Investigation of Time Perception in Spider-Fearful Individuals

    PubMed Central

    Buetti, Simona; Lleras, Alejandro

    2012-01-01

    We used a time perception task to study the effects of the subjective experience of control on emotion and cognitive processing. This task is uniquely sensitive to the emotionality of the stimuli: high-arousing negative stimuli are perceived as lasting longer than high-arousing positive events, while the opposite pattern is observed for low-arousing stimuli. We evaluated the temporal distortions of emotionally charged events in non-anxious (Experiments 1 and 5) and spider-fearful individuals (Experiments 2–4). Participants were shown images of varying durations between 400 and 1600 ms and were asked to report if the perceived duration of the image seemed closer to a short (400 ms) or to a long (1600 ms) standard duration. Our results replicate previous findings showing that the emotional content of the image modulated the perceived duration of that image. More importantly, we studied whether giving participants the illusion that they have some control over the emotional content of the images could eliminate this temporal distortion. Results confirmed this hypothesis, even though our participant population was composed of highly reactive emotional individuals (spider-fearful) facing fear-related images (spiders). Further, we also showed that under conditions of little-to-no control, spider-fearful individuals perceive temporal distortions in a distinct manner from non-anxious participants: the duration of events was entirely determined by the valence of the events, rather than by the typical valence × arousal interaction. That is, spider-fearful participants perceived negative events as lasting longer than positive events, regardless of their level of arousal. Finally, we also showed that under conditions of cognitive dissonance, control can eliminate temporal distortions of low arousal events, but not of high-arousing events, providing an important boundary condition to the otherwise positive effects of control on time estimation. PMID:23060824

  17. NASA Climate Days: Promoting Climate Literacy One Ambassador and One Event at a Time

    NASA Astrophysics Data System (ADS)

    Weir, H. M.; Lewis, P. M.; Chambers, L. H.; Millham, R. A.; Richardson, A.

    2012-12-01

    presentations from the training, along with downloadable Climate Day Kit materials. Utilizing informal educators from museums, aquariums, libraries and other similar venues allow the hard-to-understand, sometimes-controversial, topic of climate change to be presented to the public in tailored events that suit an individual community's needs. Included in the process of scheduling and executing these climate events, the Ambassadors participate in virtual conferences to discuss progress, to ensure proper evaluation and to allow ample time for questions from the trainers and scientists. This ensures an accurate stream of information from the scientist to the public in a fashion that can be understood and digested by the layperson, helping them to make better-informed decisions about societal issues related to global climate change. Through a series of local Climate Day events, it is hoped that the public will have the opportunity to have first hand experience with the topic of climate change, leaving with a better understanding of its scientific basis. Outcome: This paper will summarize the various methods and strategies used in the Climate Day training events. A discussion of methods that work and those that do not for informal education will help provide a better understanding of the challenges faced in educating the public on such a controversial and hard-to-understand topic.

  18. Boosting joint models for longitudinal and time-to-event data.

    PubMed

    Waldmann, Elisabeth; Taylor-Robinson, David; Klein, Nadja; Kneib, Thomas; Pressler, Tania; Schmid, Matthias; Mayr, Andreas

    2017-03-21

    Joint models for longitudinal and time-to-event data have gained a lot of attention in the last few years as they are a helpful technique clinical studies where longitudinal outcomes are recorded alongside event times. Those two processes are often linked and the two outcomes should thus be modeled jointly in order to prevent the potential bias introduced by independent modeling. Commonly, joint models are estimated in likelihood-based expectation maximization or Bayesian approaches using frameworks where variable selection is problematic and that do not immediately work for high-dimensional data. In this paper, we propose a boosting algorithm tackling these challenges by being able to simultaneously estimate predictors for joint models and automatically select the most influential variables even in high-dimensional data situations. We analyze the performance of the new algorithm in a simulation study and apply it to the Danish cystic fibrosis registry that collects longitudinal lung function data on patients with cystic fibrosis together with data regarding the onset of pulmonary infections. This is the first approach to combine state-of-the art algorithms from the field of machine-learning with the model class of joint models, providing a fully data-driven mechanism to select variables and predictor effects in a unified framework of boosting joint models.

  19. Event-related EEG time-frequency analysis and the Orienting Reflex to auditory stimuli.

    PubMed

    Barry, Robert J; Steiner, Genevieve Z; De Blasio, Frances M

    2012-06-01

    Sokolov's classic works discussed electroencephalogram (EEG) alpha desynchronization as a measure of the Orienting Reflex (OR). Early studies confirmed that this reduced with repeated auditory stimulation, but without reliable stimulus-significance effects. We presented an auditory habituation series with counterbalanced indifferent and significant (counting) instructions. Time-frequency analysis of electrooculogram (EOG)-corrected EEG was used to explore prestimulus levels and the timing and amplitude of event-related increases and decreases in 4 classic EEG bands. Decrement over trials and response recovery were substantial for the transient increase (in delta, theta, and alpha) and subsequent desynchronization (in theta, alpha, and beta). There was little evidence of dishabituation and few effects of counting. Expected effects in stimulus-induced alpha desynchronization were confirmed. Two EEG response patterns over trials and conditions, distinct from the full OR pattern, warrant further research.

  20. Adaptation-Induced Compression of Event Time Occurs Only for Translational Motion

    PubMed Central

    Fornaciai, Michele; Arrighi, Roberto; Burr, David C.

    2016-01-01

    Adaptation to fast motion reduces the perceived duration of stimuli displayed at the same location as the adapting stimuli. Here we show that the adaptation-induced compression of time is specific for translational motion. Adaptation to complex motion, either circular or radial, did not affect perceived duration of subsequently viewed stimuli. Adaptation with multiple patches of translating motion caused compression of duration only when the motion of all patches was in the same direction. These results show that adaptation-induced compression of event-time occurs only for uni-directional translational motion, ruling out the possibility that the neural mechanisms of the adaptation occur at early levels of visual processing. PMID:27003445

  1. DEIMOS Spectroscopy of GALEX Time Domain Survey Tidal Disruption Event Candidates

    NASA Astrophysics Data System (ADS)

    Gezari, Suvi

    2011-08-01

    We propose for Keck II DEIMOS follow-up spectroscopy of extreme UV-flaring galaxies from the GALEX Time Domain Survey that are candidates for flares from the tidal disruption of stars around dormant supermassive black holes. GALEX has conducted an innovative dedicated survey in the time domain in the NUV, over a wide field of view (42 deg^2) with a cadence of 2 days to discover and characterize a wide range of UV variable and transient sources, including variable stars, quasars, active galactic nuclei, and Type II SNe. Here we propose for follow-up low-resolution spectroscopy of galaxies which demonstrated large amplitude UV flares to investigate their nature, and identify candidate tidal disruption events.

  2. Post-event human decision errors: operator action tree/time reliability correlation

    SciTech Connect

    Hall, R E; Fragola, J; Wreathall, J

    1982-11-01

    This report documents an interim framework for the quantification of the probability of errors of decision on the part of nuclear power plant operators after the initiation of an accident. The framework can easily be incorporated into an event tree/fault tree analysis. The method presented consists of a structure called the operator action tree and a time reliability correlation which assumes the time available for making a decision to be the dominating factor in situations requiring cognitive human response. This limited approach decreases the magnitude and complexity of the decision modeling task. Specifically, in the past, some human performance models have attempted prediction by trying to emulate sequences of human actions, or by identifying and modeling the information processing approach applicable to the task. The model developed here is directed at describing the statistical performance of a representative group of hypothetical individuals responding to generalized situations.

  3. Prospective and retrospective semantic processing: prediction, time, and relationship strength in event-related potentials.

    PubMed

    Luka, Barbara J; Van Petten, Cyma

    2014-08-01

    Semantic context effects have variously been attributed to prospective processing - predictions about upcoming words - or to retrospective appreciation of relationships after reading both context and target. In two experiments, we altered the core variable distinguishing prospective from retrospective processing, namely time. Word pairs varying in strength of relationship were presented sequentially, to allow time for anticipation of the second word, or simultaneously. For both sorts of presentation, the amplitude of the N400 component of the event-related potential was graded from Unrelated to Moderate/Weak to Strong associates. Strong associates showed a temporal advantage over weaker associates - an earlier context effect - only during sequential presentation. Spatial distributions of the N400 context effects also differed for simultaneous versus sequential presentation.

  4. Tracking Visual Events in Time in the Absence of Time Perception: Implicit Processing at the ms Level

    PubMed Central

    Poncelet, Patrick Eric; Giersch, Anne

    2015-01-01

    Previous studies have suggested that even if subjects deem two visual stimuli less than 20 ms apart to be simultaneous, implicitly they are nonetheless distinguished in time. It is unclear, however, how information is encoded within this short timescale. We used a priming paradigm to demonstrate how successive visual stimuli are processed over time intervals of less than 20 ms. The primers were two empty square frames displayed either simultaneously or with a 17ms asynchrony. The primers were followed by the target information after a delay of 25 ms to 100 ms. The two square frames were filled in one after another with a delay of 100 ms between them, and subjects had to decide on the location of the first of the frames to be filled in. In a second version of the paradigm, only one square frame was filled in, and subjects had to decide where it was positioned. The influence of the primers is revealed through faster response times depending on the location of the first and second primers. Experiment 1 replicates earlier results, with a bias towards the side of the second primer, but only when there is a delay of 75 to 100 ms between primers and targets. The following experiments suggest this effect to be relatively independent of the task context, except for a slight effect on the time course of the biases. For the temporal order judgment task, identical results were observed when subjects have to answer to the side of the second rather than the first target, showing the effect to be independent of the hand response, and suggesting it might be related to a displacement of attention. All in all the results suggest the flow of events is followed more efficiently than suggested by explicit asynchrony judgment studies. We discuss the possible impact of these results on our understanding of the sense of time continuity. PMID:26030155

  5. The past, present, and future of the U.S. electric power sector: Examining regulatory changes using multivariate time series approaches

    NASA Astrophysics Data System (ADS)

    Binder, Kyle Edwin

    The U.S. energy sector has undergone continuous change in the regulatory, technological, and market environments. These developments show no signs of slowing. Accordingly, it is imperative that energy market regulators and participants develop a strong comprehension of market dynamics and the potential implications of their actions. This dissertation contributes to a better understanding of the past, present, and future of U.S. energy market dynamics and interactions with policy. Advancements in multivariate time series analysis are employed in three related studies of the electric power sector. Overall, results suggest that regulatory changes have had and will continue to have important implications for the electric power sector. The sector, however, has exhibited adaptability to past regulatory changes and is projected to remain resilient in the future. Tests for constancy of the long run parameters in a vector error correction model are applied to determine whether relationships among coal inventories in the electric power sector, input prices, output prices, and opportunity costs have remained constant over the past 38 years. Two periods of instability are found, the first following railroad deregulation in the U.S. and the second corresponding to a number of major regulatory changes in the electric power and natural gas sectors. Relationships among Renewable Energy Credit prices, electricity prices, and natural gas prices are estimated using a vector error correction model. Results suggest that Renewable Energy Credit prices do not completely behave as previously theorized in the literature. Potential reasons for the divergence between theory and empirical evidence are the relative immaturity of current markets and continuous institutional intervention. Potential impacts of future CO2 emissions reductions under the Clean Power Plan on economic and energy sector activity are estimated. Conditional forecasts based on an outlined path for CO2 emissions are

  6. Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events

    PubMed Central

    Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

    2016-01-01

    Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate. PMID:28066225

  7. Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

    PubMed

    Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

    2016-01-01

    Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

  8. Analysis of locality-sensitive hashing for fast critical event prediction on physiological time series.

    PubMed

    Kim, Yongwook Bryce; O'Reilly, Una-May

    2016-08-01

    We apply the sublinear time, scalable locality-sensitive hashing (LSH) and majority discrimination to the problem of predicting critical events based on physiological waveform time series. Compared to using the linear exhaustive k-nearest neighbor search, our proposed method vastly speeds up prediction time up to 25 times while sacrificing only 1% of accuracy when demonstrated on an arterial blood pressure dataset extracted from the MIMIC2 database. We compare two widely used variants of LSH, the bit sampling based (L1LSH) and the random projection based (E2LSH) methods to measure their direct impact on retrieval and prediction accuracy. We experimentally show that the more sophisticated E2LSH performs worse than L1LSH in terms of accuracy, correlation, and the ability to detect false negatives. We attribute this to E2LSH's simultaneous integration of all dimensions when hashing the data, which actually makes it more impotent against common noise sources such as data misalignment. We also demonstrate that the deterioration of accuracy due to approximation at the retrieval step of LSH has a diminishing impact on the prediction accuracy as the speed up gain accelerates.

  9. Estimating time-correlation functions by sampling and unbiasing dynamically activated events.

    PubMed

    Athènes, Manuel; Marinica, Mihai-Cosmin; Jourdan, Thomas

    2012-11-21

    Transition path sampling is a rare-event method that estimates state-to-state time-correlation functions in many-body systems from samples of short trajectories. In this framework, it is proposed to bias the importance function using the lowest Jacobian eigenvalue moduli along the dynamical trajectory. A lowest eigenvalue modulus is related to the lowest eigenvalue of the Hessian matrix and is evaluated here using the Lanczos algorithm as in activation-relaxation techniques. This results in favoring the sampling of activated trajectories and enhancing the occurrence of the rare reactive trajectories of interest, those corresponding to transitions between locally stable states. Estimating the time-correlation functions involves unbiasing the sample of simulated trajectories which is done using the multi-state Bennett acceptance ratio (MBAR) method. To assess the performance of our procedure, we compute the time-correlation function associated with the migration of a vacancy in α-iron. The derivative of the estimated time-correlation function yields a migration rate in agreement with the one given by transition state theory. Besides, we show that the information relative to rejected trajectories can be recycled within MBAR, resulting in a substantial speed-up. Unlike original transition path-sampling, our approach does not require computing the reversible work to confine the trajectory endpoints to a reactive state.

  10. Toward real-time particle tracking using an event-based dynamic vision sensor

    NASA Astrophysics Data System (ADS)

    Drazen, David; Lichtsteiner, Patrick; Häfliger, Philipp; Delbrück, Tobi; Jensen, Atle

    2011-11-01

    Optically based measurements in high Reynolds number fluid flows often require high-speed imaging techniques. These cameras typically record data internally and thus are limited by the amount of onboard memory available. A novel camera technology for use in particle tracking velocimetry is presented in this paper. This technology consists of a dynamic vision sensor in which pixels operate in parallel, transmitting asynchronous events only when relative changes in intensity of approximately 10% are encountered with a temporal resolution of 1 μs. This results in a recording system whose data storage and bandwidth requirements are about 100 times smaller than a typical high-speed image sensor. Post-processing times of data collected from this sensor also increase to about 10 times faster than real time. We present a proof-of-concept study comparing this novel sensor with a high-speed CMOS camera capable of recording up to 2,000 fps at 1,024 × 1,024 pixels. Comparisons are made in the ability of each system to track dense (ρ >1 g/cm3) particles in a solid-liquid two-phase pipe flow. Reynolds numbers based on the bulk velocity and pipe diameter up to 100,000 are investigated.

  11. A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

    PubMed Central

    Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

    2017-01-01

    Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

  12. Three Dimensional Structure and Time Evolution of a Transition Region Explosive Event Observed in He II

    NASA Astrophysics Data System (ADS)

    Fox, J. L.; Kankelborg, C. C.; Thomas, R. J.; Longcope, D.

    2007-12-01

    Transition Region Explosive Events (TREEs) have been observed with slit spectrographs since at least 1975, most commonly in lines of C IV (1548A,1550A) and Si IV (1393A, 1402A). We report what we believe to be the first observation of a TREE in He II 304A. With the MOSES sounding rocket, a novel type of imaging spectrograph, we are able to see the spatial and spectral structure of the event. It consists of a bright core expelling two jets, oppositely directed but not collinear, which curve away from the axis of the core. The jets have both line-of-sight and sky-plane motion. The core is a region of high non-thermal doppler broadening, characteristic of TREEs. It is possible to resolve the core broadening into red and blue line-of-sight components. MOSES captured approximately 150 sec of time evolution before the rocket flight ended. We see the beginning (core activation) and middle (jet ejection), but not the end. It is clear from our data-set that TREEs in He II 304A are much less common than observed in other wavelengths.

  13. Sensitivity Analysis of Per-Protocol Time-to-Event Treatment Efficacy in Randomized Clinical Trials

    PubMed Central

    Gilbert, Peter B.; Shepherd, Bryan E.; Hudgens, Michael G.

    2013-01-01

    Summary Assessing per-protocol treatment effcacy on a time-to-event endpoint is a common objective of randomized clinical trials. The typical analysis uses the same method employed for the intention-to-treat analysis (e.g., standard survival analysis) applied to the subgroup meeting protocol adherence criteria. However, due to potential post-randomization selection bias, this analysis may mislead about treatment efficacy. Moreover, while there is extensive literature on methods for assessing causal treatment effects in compliers, these methods do not apply to a common class of trials where a) the primary objective compares survival curves, b) it is inconceivable to assign participants to be adherent and event-free before adherence is measured, and c) the exclusion restriction assumption fails to hold. HIV vaccine efficacy trials including the recent RV144 trial exemplify this class, because many primary endpoints (e.g., HIV infections) occur before adherence is measured, and nonadherent subjects who receive some of the planned immunizations may be partially protected. Therefore, we develop methods for assessing per-protocol treatment efficacy for this problem class, considering three causal estimands of interest. Because these estimands are not identifiable from the observable data, we develop nonparametric bounds and semiparametric sensitivity analysis methods that yield estimated ignorance and uncertainty intervals. The methods are applied to RV144. PMID:24187408

  14. Area-Specific Information Processing in Prefrontal Cortex during a Probabilistic Inference Task: A Multivariate fMRI BOLD Time Series Analysis

    PubMed Central

    Demanuele, Charmaine; Kirsch, Peter; Esslinger, Christine; Zink, Mathias; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

    2015-01-01

    Introduction Discriminating spatiotemporal stages of information processing involved in complex cognitive processes remains a challenge for neuroscience. This is especially so in prefrontal cortex whose subregions, such as the dorsolateral prefrontal (DLPFC), anterior cingulate (ACC) and orbitofrontal (OFC) cortices are known to have differentiable roles in cognition. Yet it is much less clear how these subregions contribute to different cognitive processes required by a given task. To investigate this, we use functional MRI data recorded from a group of healthy adults during a “Jumping to Conclusions” probabilistic reasoning task. Methods We used a novel approach combining multivariate test statistics with bootstrap-based procedures to discriminate between different task stages reflected in the fMRI blood oxygenation level dependent signal pattern and to unravel differences in task-related information encoded by these regions. Furthermore, we implemented a new feature extraction algorithm that selects voxels from any set of brain regions that are jointly maximally predictive about specific task stages. Results Using both the multivariate statistics approach and the algorithm that searches for maximally informative voxels we show that during the Jumping to Conclusions task, the DLPFC and ACC contribute more to the decision making phase comprising the accumulation of evidence and probabilistic reasoning, while the OFC is more involved in choice evaluation and uncertainty feedback. Moreover, we show that in presumably non-task-related regions (temporal cortices) all information there was about task processing could be extracted from just one voxel (indicating the unspecific nature of that information), while for prefrontal areas a wider multivariate pattern of activity was maximally informative. Conclusions/Significance We present a new approach to reveal the different roles of brain regions during the processing of one task from multivariate activity patterns

  15. Real-time measurements of spontaneous breathers and rogue wave events in optical fibre modulation instability

    PubMed Central

    Närhi, Mikko; Wetzel, Benjamin; Billet, Cyril; Toenger, Shanti; Sylvestre, Thibaut; Merolla, Jean-Marc; Morandotti, Roberto; Dias, Frederic; Genty, Goëry; Dudley, John M.

    2016-01-01

    Modulation instability is a fundamental process of nonlinear science, leading to the unstable breakup of a constant amplitude solution of a physical system. There has been particular interest in studying modulation instability in the cubic nonlinear Schrödinger equation, a generic model for a host of nonlinear systems including superfluids, fibre optics, plasmas and Bose–Einstein condensates. Modulation instability is also a significant area of study in the context of understanding the emergence of high amplitude events that satisfy rogue wave statistical criteria. Here, exploiting advances in ultrafast optical metrology, we perform real-time measurements in an optical fibre system of the unstable breakup of a continuous wave field, simultaneously characterizing emergent modulation instability breather pulses and their associated statistics. Our results allow quantitative comparison between experiment, modelling and theory, and are expected to open new perspectives on studies of instability dynamics in physics. PMID:27991513

  16. Real-time measurements of spontaneous breathers and rogue wave events in optical fibre modulation instability

    NASA Astrophysics Data System (ADS)

    Närhi, Mikko; Wetzel, Benjamin; Billet, Cyril; Toenger, Shanti; Sylvestre, Thibaut; Merolla, Jean-Marc; Morandotti, Roberto; Dias, Frederic; Genty, Goëry; Dudley, John M.

    2016-12-01

    Modulation instability is a fundamental process of nonlinear science, leading to the unstable breakup of a constant amplitude solution of a physical system. There has been particular interest in studying modulation instability in the cubic nonlinear Schrödinger equation, a generic model for a host of nonlinear systems including superfluids, fibre optics, plasmas and Bose-Einstein condensates. Modulation instability is also a significant area of study in the context of understanding the emergence of high amplitude events that satisfy rogue wave statistical criteria. Here, exploiting advances in ultrafast optical metrology, we perform real-time measurements in an optical fibre system of the unstable breakup of a continuous wave field, simultaneously characterizing emergent modulation instability breather pulses and their associated statistics. Our results allow quantitative comparison between experiment, modelling and theory, and are expected to open new perspectives on studies of instability dynamics in physics.

  17. Prediction of solar energetic particle event histories using real-time particle and solar wind measurements

    NASA Technical Reports Server (NTRS)

    Roelof, E. C.; Gold, R. E.

    1978-01-01

    The comparatively well-ordered magnetic structure in the solar corona during the decline of Solar Cycle 20 revealed a characteristic dependence of solar energetic particle injection upon heliographic longitude. When analyzed using solar wind mapping of the large scale interplanetary magnetic field line connection from the corona to the Earth, particle fluxes display an approximately exponential dependence on heliographic longitude. Since variations in the solar wind velocity (and hence the coronal connection longitude) can severely distort the simple coronal injection profile, the use of real-time solar wind velocity measurements can be of great aid in predicting the decay of solar particle events. Although such exponential injection profiles are commonplace during 1973-1975, they have also been identified earlier in Solar Cycle 20, and hence this structure may be present during the rise and maximum of the cycle, but somewhat obscured by greater temporal variations in particle injection.

  18. Timing and chemistry of igneous events associated with the Southern Oklahoma Aulacogen

    NASA Astrophysics Data System (ADS)

    Charles Gilbert, M.

    1983-05-01

    Igneous activity in the Southern Oklahoma Aulacogen of North America was concentrated in the early rifting stages of aulacogen development. The time span over which liquids rose may not have exceeded 50 m.y. and certainly terminated before the Upper Cambrian. Igneous activity began with three basaltic liquids, stratigraphically identifiable but perhaps not all distinct genetically. This was followed by one large rhyolitic-granitic episode of A-type character. One final basaltic event ended the activity. All the basaltic types seem to be tholeiitic showing more kinship with either the older, Proterozoic North American Midcontinental Rift or the northern part of the Cenozoic Rio Grande Rift, than the Cenozoic East African Rift. Two major uplifts occurred: one between the earlier basalts and the rhyolite, and one much later, after all igneous activity was over, in the Pennsylvanian.

  19. Real-time measurements of spontaneous breathers and rogue wave events in optical fibre modulation instability.

    PubMed

    Närhi, Mikko; Wetzel, Benjamin; Billet, Cyril; Toenger, Shanti; Sylvestre, Thibaut; Merolla, Jean-Marc; Morandotti, Roberto; Dias, Frederic; Genty, Goëry; Dudley, John M

    2016-12-19

    Modulation instability is a fundamental process of nonlinear science, leading to the unstable breakup of a constant amplitude solution of a physical system. There has been particular interest in studying modulation instability in the cubic nonlinear Schrödinger equation, a generic model for a host of nonlinear systems including superfluids, fibre optics, plasmas and Bose-Einstein condensates. Modulation instability is also a significant area of study in the context of understanding the emergence of high amplitude events that satisfy rogue wave statistical criteria. Here, exploiting advances in ultrafast optical metrology, we perform real-time measurements in an optical fibre system of the unstable breakup of a continuous wave field, simultaneously characterizing emergent modulation instability breather pulses and their associated statistics. Our results allow quantitative comparison between experiment, modelling and theory, and are expected to open new perspectives on studies of instability dynamics in physics.

  20. Timing of a Substorm Event at ~07:13UT, Jan 29, 2008

    NASA Astrophysics Data System (ADS)

    Liu, J.; Angelopoulos, V.; Frey, H. U.; McFadden, J. P.; Glassmeier, K.; Mende, S. B.; Russell, C. T.

    2009-12-01

    We report a timing analysis on a substorm around ~07:10UT on Jan 29, 2008 captured by the THEMIS spacecraft. The spacecraft (probes) were aligned along the tail between XGSM=-7 RE to -30 RE. During the time of the substorm, the solar wind had a vz component of ~50 km/s corresponding to a 6.5o southward tilt of the magnetotail. Thus we rotate the GSM coordinate system 6.5o anticlockwise around the Y axis to form a more physical coordinate system and investigate the satellite data in this coordinate system. The most distant probe P1 (XGSM=-29.5 RE) detected a bipolar magnetic signature corresponding to a tailward moving structure. P2 (XGSM=-18.5 RE) also saw magnetic signatures indicating tailward moving structure, while P3 (XGSM=-10.8 RE) and P4 (XGSM=-10.6 RE) captured dipolarization fronts and Earthward flows. THEMIS ground stations and all-sky imagers recorded Pi2 pulsations and brightening in a white-light auroral imager. We perform a detailed timing analysis of probe and ground-based data and reconstruct the time sequence of phenomena during this substorm. The earliest event related to the substorm was the Earthward beams on P3 and P4, followed by the aurora intensification at 07:12:22UT. The first magnetic deflection was detected by P2 and then bipolar perturbation in the north-south component of the magnetic field was captured by P1 at 07:12:32UT. Dipolarization fronts as well as convective flows arrived at P3 and P4 later at ~07:13:35UT accompanied by sudden increase of the cumulative magnetic flux transferred Earthward, and ground magnetic pulsations happened about the same time or later. We consider this substorm to be generated by tail reconnection at ~18 RE, different from the interpretation by Lui et al. [2008] on the same event. It is inferred that reconnection in the tail preceded the aurora intensification by ~2 minutes and preceded the ground magnetic perturbation and near-Earth dipolarization by ~3 minutes.

  1. Synthetic-type control charts for time-between-events monitoring.

    PubMed

    Yen, Fang Yen; Chong, Khoo Michael Boon; Ha, Lee Ming

    2013-01-01

    This paper proposes three synthetic-type control charts to monitor the mean time-between-events of a homogenous Poisson process. The first proposed chart combines an Erlang (cumulative time between events, Tr ) chart and a conforming run length (CRL) chart, denoted as Synth-Tr chart. The second proposed chart combines an exponential (or T) chart and a group conforming run length (GCRL) chart, denoted as GR-T chart. The third proposed chart combines an Erlang chart and a GCRL chart, denoted as GR-Tr chart. By using a Markov chain approach, the zero- and steady-state average number of observations to signal (ANOS) of the proposed charts are obtained, in order to evaluate the performance of the three charts. The optimal design of the proposed charts is shown in this paper. The proposed charts are superior to the existing T chart, Tr chart, and Synth-T chart. As compared to the EWMA-T chart, the GR-T chart performs better in detecting large shifts, in terms of the zero- and steady-state performances. The zero-state Synth-T4 and GR-Tr (r = 3 or 4) charts outperform the EWMA-T chart for all shifts, whereas the Synth-Tr (r = 2 or 3) and GR-T 2 charts perform better for moderate to large shifts. For the steady-state process, the Synth-Tr and GR-Tr charts are more efficient than the EWMA-T chart in detecting small to moderate shifts.

  2. On data-based analysis of extreme events in multidimensional non-stationary meteorological systems: Based on advanced time series analysis methods and general extreme value theory

    NASA Astrophysics Data System (ADS)

    Kaiser, O.; Horenko, I.

    2012-04-01

    Given an observed series of extreme events we are interested to capture the significant trend in the underlying dynamics. Since the character of such systems is strongly non-linear and non-stationary, the detection of significant characteristics and their attribution is a complex task. A standard tool in statistics to describe the probability distribution of extreme events is the General Extreme Value Theory (GEV). While the univariate stationary GEV distribution is well studied and results in fitting the data to the model parameters using Likelihood Techniques and Bayesian Methods (Coles,'01; Davison, Rames, '00 ), analysis of non-stationary extremes is based on the a priori assumption about the trend behavior (e.g linear combination of external factors/polynomials (Coles,'01)). Additionally, analysis of multivariate, non-stationary extreme events remains still a strong challenge, since analysis without strong a priori assumptions is limited to low dimensional cases (Nychka, Cooley,'09). We introduce FEM-GEV approach, which is based on GEV and advanced Finite Element time series analysis Methods (FEM) (Horenko,'10-11). The main idea of the FEM framework is to interpolate adaptively the corresponding non-stationary model parameters by a linear convex combination of K local stationary models and a switching process between them. To apply FEM framework to a time series of extremes we extend FEM by defining the model parameters wrt GEV distribution, as external factors we consider global atmospheric patterns. The optimal number of local models K and the best combination of external factors is estimated using Akaike Information Criteria. FEM-GEV approach allows to study the non-stationary dynamics of GEV parameters without a priori assumptions on the trend behavior and also captures the non-linear, non-stationary dependence on external factors. The series of extremes has by definition no connection to real time scale, for this reason the results of FEM-GEV can be only

  3. Time course of spatial contextual interference: event history analyses of simultaneous masking by nonoverlapping patterns.

    PubMed

    Panis, Sven; Hermens, Frouke

    2014-02-01

    Simultaneous masking refers to the impairment of performance on a visual target by simultaneously presented flankers. Whereas the spatial aspects of simultaneous masking have been studied extensively, the time course of these spatial influences is much less well understood. We here measure response latency and accuracy in a simultaneous masking paradigm and apply event history analysis to study the time course of target-flanker interactions. In our experiments, we presented a central target vernier flanked on both sides by 12 aligned distractor verniers that were either shorter, longer, or equal in length (Experiment 1), and that also were congruent or incongruent in their spatial offset with the target (Experiment 2). Response time distributions showed that there were more fast responses when the target was flanked by short flankers. Conditional accuracy functions showed that accuracy of responses dropped when the flankers had the same length as the target, but only for slow responses. These results are at odds with accounts based solely on lateral neural interactions or response competition, and instead suggest that top-down visual object-to-feature interference occurs when the target is not selected fast enough, congruent with object substitution theory.

  4. Specimen Pooling for Efficient Use of Biospecimens in Studies of Time to a Common Event

    PubMed Central

    Saha-Chaudhuri, Paramita; Weinberg, Clarice R.

    2013-01-01

    For case-control studies that rely on expensive assays for biomarkers, specimen pooling offers a cost-effective and efficient way to estimate individual-level odds ratios. Pooling helps to conserve irreplaceable biospecimens for the future, mitigates limit-of-detection problems, and enables inclusion of individuals who have limited available volumes of biospecimen. Pooling can also allow the study of a panel of biomarkers under a fixed assay budget. Here, we extend this method for application to discrete-time survival studies. Assuming a proportional odds logistic model for risk of a common outcome, we propose a design strategy that forms pooling sets within those experiencing the outcome at the same event time. We show that the proposed design enables a cost-effective analysis to assess the association of a biomarker with the outcome. Because the standard likelihood is slightly misspecified for the proposed pooling strategy under a nonnull biomarker effect, the proposed approach produces slightly biased estimates of exposure odds ratios. We explore the extent of this bias via simulations and illustrate the method by revisiting a data set relating polychlorinated biphenyls and 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene to time to pregnancy. PMID:23821316

  5. A Real-Time Web Services Hub to Improve Situation Awareness during Flash Flood Events

    NASA Astrophysics Data System (ADS)

    Salas, F. R.; Liu, F.; Maidment, D. R.; Hodges, B. R.

    2011-12-01

    The central Texas corridor is one of the most flash flood-prone regions in the United States. Over the years, flash floods have resulted in hundreds of flood fatalities and billions of dollars in property damage. In order to mitigate risk to residents and infrastructure during flood events, both citizens and emergency responders need to exhibit proactive behavior instead of reactive. Real-time and forecasted flood information is fairly limited and hard to come by at varying spatial scales. The University of Texas at Austin has collaborated with IBM Research-Austin and ESRI to build a distributed real-time flood information system through a framework that leverages large scale data management and distribution, Open Geospatial Consortium standardized web services, and smart map applications. Within this paradigm, observed precipitation data encoded in WaterML is ingested into HEC-HMS and then delivered to a high performance hydraulic routing software package developed by IBM that utilizes the latest advancements in VLSI design, numerical linear algebra and numerical integration techniques on contemporary multicore architecture to solve fully dynamic Saint Venant equations at both small and large scales. In this paper we present a real-time flood inundation map application that in conjunction with a web services Hub, seamlessly integrates hydrologic information available through both public and private data services, model services and mapping services. As a case study for this project, we demonstrate how this system has been implemented in the City of Austin, Texas.

  6. Framework for modeling urban restoration resilience time in the aftermath of an extreme event

    USGS Publications Warehouse

    Ramachandran, Varun; Long, Suzanna K.; Shoberg, Thomas G.; Corns, Steven; Carlo, Héctor

    2015-01-01

    The impacts of extreme events continue long after the emergency response has terminated. Effective reconstruction of supply-chain strategic infrastructure (SCSI) elements is essential for postevent recovery and the reconnectivity of a region with the outside. This study uses an interdisciplinary approach to develop a comprehensive framework to model resilience time. The framework is tested by comparing resilience time results for a simulated EF-5 tornado with ground truth data from the tornado that devastated Joplin, Missouri, on May 22, 2011. Data for the simulated tornado were derived for Overland Park, Johnson County, Kansas, in the greater Kansas City, Missouri, area. Given the simulated tornado, a combinatorial graph considering the damages in terms of interconnectivity between different SCSI elements is derived. Reconstruction in the aftermath of the simulated tornado is optimized using the proposed framework to promote a rapid recovery of the SCSI. This research shows promising results when compared with the independent quantifiable data obtained from Joplin, Missouri, returning a resilience time of 22 days compared with 25 days reported by city and state officials.

  7. Extreme weather event in spring 2013 delayed breeding time of Great Tit and Blue Tit.

    PubMed

    Glądalski, Michał; Bańbura, Mirosława; Kaliński, Adam; Markowski, Marcin; Skwarska, Joanna; Wawrzyniak, Jarosław; Zieliński, Piotr; Bańbura, Jerzy

    2014-12-01

    The impact of climatic changes on life cycles by re-scheduling the timing of reproduction is an important topic in studies of biodiversity. Global warming causes and will probably cause in the future not only raising temperatures but also an increasing frequency of extreme weather events. In 2013, the winter in central and north Europe ended late, with low temperatures and long-retained snow cover--this extreme weather phenomenon acted in opposition to the increasing temperature trend. In 2013, thermal conditions measured by the warmth sum in the period 15 March–15 April, a critical time for early breeding passerines, went far beyond the range of the warmth sums for at least 40 preceding years. Regardless of what was the reason for the extreme early spring 2013 and assuming that there is a potential for more atypical years because of climate change, we should look closely at every extreme phenomenon and its consequences for the phenology of organisms. In this paper, we report that the prolonged occurrence of winter conditions during the time that is crucial for Blue Tit (Cyanistes caeruleus) and Great Tit (Parus major) reproduction caused a substantial delay in the onset of egg laying in comparison with typical springs.

  8. Probability of occurrence of planetary ionosphere storms associated with the magnetosphere disturbance storm time events

    NASA Astrophysics Data System (ADS)

    Gulyaeva, T. L.; Arikan, F.; Stanislawska, I.

    2014-11-01

    The ionospheric W index allows to distinguish state of the ionosphere and plasmasphere from quiet conditions (W = 0 or ±1) to intense storm (W = ±4) ranging the plasma density enhancements (positive phase) or plasma density depletions (negative phase) regarding the quiet ionosphere. The global W index maps are produced for a period 1999-2014 from Global Ionospheric Maps of Total Electron Content, GIM-TEC, designed by Jet Propulson Laboratory, converted from geographic frame (-87.5:2.5:87.5° in latitude, -180:5:180° in longitude) to geomagnetic frame (-85:5:85° in magnetic latitude, -180:5:180° in magnetic longitude). The probability of occurrence of planetary ionosphere storm during the magnetic disturbance storm time, Dst, event is evaluated with the superposed epoch analysis for 77 intense storms (Dst ≤ -100 nT) and 230 moderate storms (-100 < Dst ≤ -50 nT) with start time, t0, defined at Dst storm main phase onset. It is found that the intensity of negative storm, iW-, exceeds the intensity of positive storm, iW+, by 1.5-2 times. An empirical formula of iW+ and iW- in terms of peak Dst is deduced exhibiting an opposite trends of relation of intensity of ionosphere-plasmasphere storm with regard to intensity of Dst storm.

  9. [Event related potentials and emotional pictures:effect of stimulus presentation time].

    PubMed

    Naumann, E; Becker, G; Maier, S; Diedrich, O; Bartussek, D

    1997-01-01

    The perception of the emotional content of a stimulus is a preattentive automatic process which causes an emotional reaction. As the ongoing stream of behavior might be disturbed by the emotional reaction, a controlled process is initialited at the same time, which normally leads to an inhibition of the emotional response. By means of event related potentials it should be possible to observe these controlled processes. In a first study using photographs from the International Affective Picture System, Diedrich et al. (1997) reported enhanded P300 amplitudes for emotional stimuli, even when the task distracted from the emotional content of the stimuli. This was interpreted as an index of the additional, controlled information processing elicited by the emotional content of the stimuli. Additionally, Diedrich et al. observed a frontel slow positivity, which might indicate the inhibition of the emotional response. However, this frontal slow wave might also be explained by the stimulus presentation time, which lasted 500 ms. This study is a conceptual replication of the experiment of Diedrich et al. Stimulus presentation time of neutral and emotional slides was varied in three steps (250 ms, 500 ms and 2000 ms). Subjects either performed a structural or an emotion-focused task on the stimuli. The results for the P300 component were exactly replicated. However, the variation of slow frontal positivity differed from that in the first study. Differences in the intensity of the emotional stimuli are discussed as a reason für this result.

  10. Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

    NASA Astrophysics Data System (ADS)

    Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

    2016-12-01

    The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

  11. A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance-Structure Models to Block-Toeplitz Matrices Representing Single-Subject Multivariate Time-Series.

    PubMed

    Molenaar, P C; Nesselroade, J R

    1998-07-01

    The study of intraindividual variability pervades empirical inquiry in virtually all subdisciplines of psychology. The statistical analysis of multivariate time-series data - a central product of intraindividual investigations -requires special modeling techniques. The dynamic factor model (DFM), which is a generalization of the traditional common factor model, has been proposed by Molenaar (1985) for systematically extracting information from multivariate time- series via latent variable modeling. Implementation of the DFM model has taken several forms, one of which involves specifying it as a covariance-structure model and estimating its parameters from a block-Toeplitz matrix derived from the multivariate time-ser~es. We compare two methods for estimating DFM parameters within a covariance-structure framework - pseudo-Maximum Likelihood (p-ML) and Asymptotically Distribution Free (ADF) estimation - by means of a Monte Carlo simulation. Both methods appear to give consistent model parameter estimates of comparable precision, but only the ADF method gives standard errors and chi-square statistics that appear to be consistent. The relative ordering of the values of all estimates appears to be very similar across methods. When the manifest time-series is relatively short, the two methods appear to perform about equally well.

  12. wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information

    NASA Astrophysics Data System (ADS)

    Thanos, Konstantinos-Georgios; Thomopoulos, Stelios C. A.

    2016-05-01

    wayGoo is a fully functional application whose main functionalities include content geolocation, event scheduling, and indoor navigation. However, significant information about events do not reach users' attention, either because of the size of this information or because some information comes from real - time data sources. The purpose of this work is to facilitate event management operations by prioritizing the presented events, based on users' interests using both, static and real - time data. Through the wayGoo interface, users select conceptual topics that are interesting for them. These topics constitute a browsing behavior vector which is used for learning users' interests implicitly, without being intrusive. Then, the system estimates user preferences and return an events list sorted from the most preferred one to the least. User preferences are modeled via a Naïve Bayesian Network which consists of: a) the `decision' random variable corresponding to users' decision on attending an event, b) the `distance' random variable, modeled by a linear regression that estimates the probability that the distance between a user and each event destination is not discouraging, ` the seat availability' random variable, modeled by a linear regression, which estimates the probability that the seat availability is encouraging d) and the `relevance' random variable, modeled by a clustering - based collaborative filtering, which determines the relevance of each event users' interests. Finally, experimental results show that the proposed system contribute essentially to assisting users in browsing and selecting events to attend.

  13. Real-time Monitoring Network to Characterize Anthropogenic and Natural Events Affecting the Hudson River, NY

    NASA Astrophysics Data System (ADS)

    Islam, M. S.; Bonner, J. S.; Fuller, C.; Kirkey, W.; Ojo, T.

    2011-12-01

    The Hudson River watershed spans 34,700 km2 predominantly in New York State, including agricultural, wilderness, and urban areas. The Hudson River supports many activities including shipping, supplies water for municipal, commercial, and agricultural uses, and is an important recreational resource. As the population increases within this watershed, so does the anthropogenic impact on this natural system. To address the impacts of anthropogenic and natural activities on this ecosystem, the River and Estuary Observatory Network (REON) is being developed through a joint venture between the Beacon Institute, Clarkson University, General Electric Inc. and IBM Inc. to monitor New York's Hudson and Mohawk Rivers in real-time. REON uses four sensor platform types with multiple nodes within the network to capture environmentally relevant episodic events. Sensor platform types include: 1) fixed robotic vertical profiler (FRVP); 2) mobile robotic undulating platform (MRUP); 3) fixed acoustic Doppler current profiler (FADCP) and 4) Autonomous Underwater Vehicle (AUV). The FRVP periodically generates a vertical profile with respect to water temperature, salinity, dissolved oxygen, particle concentration and size distribution, and fluorescence. The MRUP utilizes an undulating tow-body tethered behind a research vessel to measure the same set of water parameters as the FRVP, but does so 'synchronically' over a highly-resolved spatial regime. The fixed ADCP provides continuous water current profiles. The AUV maps four-dimensional (time, latitude, longitude, depth) variation of water quality, water currents and bathymetry along a pre-determined transect route. REON data can be used to identify episodic events, both anthropogenic and natural, that impact the Hudson River. For example, a strong heat signature associated with cooling water discharge from the Indian Point nuclear power plant was detected with the MRUP. The FRVP monitoring platform at Beacon, NY, located in the

  14. Multivariable Control Systems

    DTIC Science & Technology

    1968-01-01

    one). Examples abound of systems with numerous controlled variables, and the modern tendency is toward ever greater utilization of systems and plants of this kind. We call them multivariable control systems (MCS).

  15. Digitized pressure-time records, selected nuclear events. Technical report, 1 September 1982-1 April 1986

    SciTech Connect

    McMullan, F.W.; Bryant, E.J.

    1986-04-30

    Pressure-time records are presented for selected atmospheric nuclear events. The records were extracted from published test reports, digitized, and given uniform pressure-time scales for a given event and a given range to permit easier comparison. Data include p-t, q-t, p(tot)-t, Mach No-t, and Impulse-t as appropriate. Selected data were scaled to 1 kT.

  16. Emotional modulation of attention affects time perception: evidence from event-related potentials.

    PubMed

    Tamm, Maria; Uusberg, Andero; Allik, Jüri; Kreegipuu, Kairi

    2014-06-01

    Emotional effects on human time perception are generally attributed to arousal speeding up or slowing down the internal clock. The aim of the present study is to investigate the less frequently considered role of attention as an alternative mediator of these effects with the help of event-related potentials (ERPs). Participants produced short intervals (0.9, 1.5, 2.7, and 3.3s) while viewing high arousal images with pleasant and unpleasant contents in comparison to neutral images. Behavioral results revealed that durations were overproduced for the 0.9s interval whereas, for 2.7 and 3.3s intervals, underproduction was observed. The effect of affective valence was present for the shorter durations and decreased as the target intervals became longer. More specifically, the durations for unpleasant images were less overproduced in the 0.9s intervals, and for the 1.5s trials, durations for unpleasant images were slightly underproduced, compared to pleasant images, which were overproduced. The analysis of different ERP components suggests possible attention processes related to the timing of affective images in addition to changes in pacemaker speed. Early Posterior Negativity (EPN) was larger for positive than for negative images, indicating valence-specific differences in activation of early attention mechanisms. Within the early P1 and the Late Positive Potential (LPP) components, both pleasant and unpleasant stimuli exhibited equal affective modulation. Contingent Negative Variation (CNV) remained independent of both timing performance and affective modulation. This pattern suggests that both pleasant and unpleasant stimuli enhanced arousal and captured attention, but the latter effect was more pronounced for pleasant stimuli. The valence-specificity of affective attention revealed by ERPs combined with behavioral timing results suggests that attention processes indeed contribute to emotion-induced temporal distortions, especially for longer target intervals.

  17. Modeling a Typical Winter-time Dust Event over the Arabian Peninsula and the Red Sea

    SciTech Connect

    Kalenderski, S.; Stenchikov, G.; Zhao, Chun

    2013-02-20

    We used WRF-Chem, a regional meteorological model coupled with an aerosol-chemistry component, to simulate various aspects of the dust phenomena over the Arabian Peninsula and Red Sea during a typical winter-time dust event that occurred in January 2009. The model predicted that the total amount of emitted dust was 18.3 Tg for the entire dust outburst period and that the two maximum daily rates were ~2.4 Tg/day and ~1.5 Tg/day, corresponding to two periods with the highest aerosol optical depth that were well captured by ground- and satellite-based observations. The model predicted that the dust plume was thick, extensive, and mixed in a deep boundary layer at an altitude of 3-4 km. Its spatial distribution was modeled to be consistent with typical spatial patterns of dust emissions. We utilized MODIS-Aqua and Solar Village AERONET measurements of the aerosol optical depth (AOD) to evaluate the radiative impact of aerosols. Our results clearly indicated that the presence of dust particles in the atmosphere caused a significant reduction in the amount of solar radiation reaching the surface during the dust event. We also found that dust aerosols have significant impact on the energy and nutrient balances of the Red Sea. Our results showed that the simulated cooling under the dust plume reached 100 W/m2, which could have profound effects on both the sea surface temperature and circulation. Further analysis of dust generation and its spatial and temporal variability is extremely important for future projections and for better understanding of the climate and ecological history of the Red Sea.

  18. Clonal status of actionable driver events and the timing of mutational processes in cancer evolution.

    PubMed

    McGranahan, Nicholas; Favero, Francesco; de Bruin, Elza C; Birkbak, Nicolai Juul; Szallasi, Zoltan; Swanton, Charles

    2015-04-15

    Deciphering whether actionable driver mutations are found in all or a subset of tumor cells will likely be required to improve drug development and precision medicine strategies. We analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions. Although mutations in known driver genes typically occurred early in cancer evolution, we also identified later subclonal "actionable" mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), EGFR (L858R), and KRAS (G12D), which may compromise the efficacy of targeted therapy approaches. More than 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K (phosphatidylinositol 3-kinase)-AKT-mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal. Mutations in the RAS-MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTOR signaling. Analysis of late mutations revealed a link between APOBEC-mediated mutagenesis and the acquisition of subclonal driver mutations and uncovered putative cancer genes involved in subclonal expansions, including CTNNA2 and ATXN1. Our results provide a pan-cancer census of driver events within the context of intratumor heterogeneity and reveal patterns of tumor evolution across cancers. The frequent presence of subclonal driver mutations suggests the need to stratify targeted therapy response according to the proportion of tumor cells in which the driver is identified.

  19. Fractal analysis of GPS time series for early detection of disastrous seismic events

    NASA Astrophysics Data System (ADS)

    Filatov, Denis M.; Lyubushin, Alexey A.

    2017-03-01

    A new method of fractal analysis of time series for estimating the chaoticity of behaviour of open stochastic dynamical systems is developed. The method is a modification of the conventional detrended fluctuation analysis (DFA) technique. We start from analysing both methods from the physical point of view and demonstrate the difference between them which results in a higher accuracy of the new method compared to the conventional DFA. Then, applying the developed method to estimate the measure of chaoticity of a real dynamical system - the Earth's crust, we reveal that the latter exhibits two distinct mechanisms of transition to a critical state: while the first mechanism has already been known due to numerous studies of other dynamical systems, the second one is new and has not previously been described. Using GPS time series, we demonstrate efficiency of the developed method in identification of critical states of the Earth's crust. Finally we employ the method to solve a practically important task: we show how the developed measure of chaoticity can be used for early detection of disastrous seismic events and provide a detailed discussion of the numerical results, which are shown to be consistent with outcomes of other researches on the topic.

  20. Assessment of realistic nowcasting lead-times based on predictability analysis of Mediterranean Heavy Precipitation Events

    NASA Astrophysics Data System (ADS)

    Bech, Joan; Berenguer, Marc

    2014-05-01

    Operational quantitative precipitation forecasts (QPF) are provided routinely by weather services or hydrological authorities, particularly those responsible for densely populated regions of small catchments, such as those typically found in Mediterranean areas prone to flash-floods. Specific rainfall values are used as thresholds for issuing warning levels considering different time frameworks (mid-range, short-range, 24h, 1h, etc.), for example 100 mm in 24h or 60 mm in 1h. There is a clear need to determine how feasible is a specific rainfall value for a given lead-time, in particular for very short range forecasts or nowcasts typically obtained from weather radar observations (Pierce et al 2012). In this study we assess which specific nowcast lead-times can be provided for a number of heavy precipitation events (HPE) that affected Catalonia (NE Spain). The nowcasting system we employed generates QPFs through the extrapolation of rainfall fields observed with weather radar following a Lagrangian approach developed and tested successfully in previous studies (Berenguer et al. 2005, 2011).Then QPFs up to 3h are compared with two quality controlled observational data sets: weather radar quantitative precipitation estimates (QPE) and raingauge data. Several high-impact weather HPE were selected including the 7 September 2005 Llobregat Delta river tornado outbreak (Bech et al. 2007) or the 2 November 2008 supercell tornadic thunderstorms (Bech et al. 2011) both producing, among other effects, local flash floods. In these two events there were torrential rainfall rates (30' amounts exceeding 38.2 and 12.3 mm respectively) and 24h accumulation values above 100 mm. A number of verification scores are used to characterize the evolution of precipitation forecast quality with time, which typically presents a decreasing trend but showing an strong dependence on the selected rainfall threshold and integration period. For example considering correlation factors, 30

  1. Multivariate postprocessing techniques for probabilistic hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

    2016-04-01

    Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power

  2. Time-based and event-based prospective memory in autism spectrum disorder: the roles of executive function and theory of mind, and time-estimation.

    PubMed

    Williams, David; Boucher, Jill; Lind, Sophie; Jarrold, Christopher

    2013-07-01

    Prospective memory (remembering to carry out an action in the future) has been studied relatively little in ASD. We explored time-based (carry out an action at a pre-specified time) and event-based (carry out an action upon the occurrence of a pre-specified event) prospective memory, as well as possible cognitive correlates, among 21 intellectually high-functioning children with ASD, and 21 age- and IQ-matched neurotypical comparison children. We found impaired time-based, but undiminished event-based, prospective memory among children with ASD. In the ASD group, time-based prospective memory performance was associated significantly with diminished theory of mind, but not with diminished cognitive flexibility. There was no evidence that time-estimation ability contributed to time-based prospective memory impairment in ASD.

  3. Characteristic Times of Gradual Solar Energetic Particle Events and Their Dependence on Associated Coronal Mass Ejection Properties

    DTIC Science & Technology

    2005-08-01

    2. REPORT TYPE 3. DATES COVERED (From - To) 01-08-2005 REPRINT 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Characteristic Times of Gradual Solar ...coronagraph on SOHO observed during 1998-2002 to statistically determine three characteristic times of gradual solar energetic particle (SEP) events as...functions of solar source longitude: (1) To, the time from associated CME launch to SEP onset at I AU, (2) TR, the rise time from SEO onset to the time when

  4. A Bayesian Framework for Functional Mapping through Joint Modeling of Longitudinal and Time-to-Event Data

    PubMed Central

    Das, Kiranmoy; Li, Runze; Huang, Zhongwen; Gai, Junyi; Wu, Rongling

    2012-01-01

    The most powerful and comprehensive approach of study in modern biology is to understand the whole process of development and all events of importance to development which occur in the process. As a consequence, joint modeling of developmental processes and events has become one of the most demanding tasks in statistical research. Here, we propose a joint modeling framework for functional mapping of specific quantitative trait loci (QTLs) which controls developmental processes and the timing of development and their causal correlation over time. The joint model contains two submodels, one for a developmental process, known as a longitudinal trait, and the other for a developmental event, known as the time to event, which are connected through a QTL mapping framework. A nonparametric approach is used to model the mean and covariance function of the longitudinal trait while the traditional Cox proportional hazard (PH) model is used to model the event time. The joint model is applied to map QTLs that control whole-plant vegetative biomass growth and time to first flower in soybeans. Results show that this model should be broadly useful for detecting genes controlling physiological and pathological processes and other events of interest in biomedicine. PMID:22685454

  5. Event-specific detection of stacked genetically modified maize Bt11 x GA21 by UP-M-PCR and real-time PCR.

    PubMed

    Xu, Wentao; Yuan, Yanfang; Luo, Yunbo; Bai, Weibin; Zhang, Chunjiao; Huang, Kunlun

    2009-01-28

    More and more stacked GMOs have been developed for more improved functional properties and/or a stronger intended characteristic, such as antipest, improved product efficiency etc. Bt11 x GA21 is a new kind of stacked GM maize developed by Monsanto Company. Since there are no unique flanking sequences in stacked GMOs, up to now, no appropriate method has been reported to accurately detect them. In this passage, a novel universal primer multiplex PCR (UP-M-PCR) was developed and applied as a rapid screening method for the simultaneous detection of five target sequences (NOS, 35S, Bt11 event, GA21 event, and IVR) in maize Bt11 x GA21. This method overcame the disadvantages rooted deeply in conventional multiplex PCR such as complex manipulation, lower sensitivity, self-inhibition and amplification disparity resulting from different primers. What's more, it got a high specificity and had a detection limit of 0.1% (approximates to 38 haploid genome copies). Furthermore, real-time PCR combined with multivariate statistical analysis was used for accurate quantification of stacked GM maize Bt11 x GA21 in 100% GM maize mixture (Bt11 x GA21, Bt11 and GA21). Detection results showed that this method could accurately validate the content of Bt11, GA21 and Bt11 x GA21 in 100% GM mixture with a detection limit of 0.5% (approximates to 200 haploid genome copies) and a low relative standard deviation <5%. All the data proved that this method may be widely applied in event-specific detection of other stacked GMOs in GM-mixture.

  6. The variations of long time period slow slip events along the Ryukyu subduction zone

    NASA Astrophysics Data System (ADS)

    Tu, Y. T.; Heki, K.

    2014-12-01

    Slow slip events (SSEs) are a type of slow earthquakes that can be observed with Global Positioning System (GPS) networks in the world. Those events are detected on intensely coupled plate boundaries such as Cascadia subduction zone (Dragert et al., 2001), western North America, Mexico (Kostoglodov et al., 2003), Alaska (Ohta et al., 2007) and Tokai and Boso areas (Ozawa et al., 2002, 2003), central Japan and are considered to have relations to large subduction thrust earthquakes. However, in southwestern Ryukyu trench where most of researchers believe that it should be a decoupled plate boundary, SSEs recur regularly and are located at a patch that is as deep as 20 to 40 km (Heki and Kataoka, 2008). For comprehending the characteristics and time variations of SSEs in this area, the GEONET GPS data of 16 years are used in this study. During 1997 to 2014, more than thirty SSEs are identified near Hateruma Island, Ryukyu. The average recurrence interval is calculated to be 6.3 months and release seismic moment is Mw 6.6 on average. However, the values of recurrence interval are not invariable. From 1997 to 2002, interval period of SSEs is 7.5 months, but during 2002 to 2008, the interval period decreases suddenly to 5.5 months. After 2008, the value restores to 7.2 months again. Furthermore, the slip amount of SSEs in this area varies with time. From 1997 to 2002, the slip is 9.5 cm/year; and during 2002 to 2008, the value slightly increases to 10.5 cm/year. However, in 2008 to 2013, the slip drops to 6.6 cm/year, but accord to the trend of cumulative slip, the slip value would increase in 2014. Considering these data, we find the slip values increase conspicuously in 2002 and 2013. Coincidentally, one Mw 7.1 thrust earthquake occurred in 2002 and earthquake swarm activity started in the Okinawa trough approximately 50km north of the SSE patch. In 2013, another earthquake swarm activity occurred in nearly the same area as the 2002 activity. This suggests that the

  7. How the timing of weather events influences early development in a large mammal.

    PubMed

    Hendrichsen, D K; Tyler, N J C

    2014-07-01

    Capturing components of the weather that drive environment-animal interactions is a perennial problem in ecology. Identifying biologically significant elements of weather conditions in sensible statistics suitable for analysis of life history variation and population dynamics is central. Meteorological variables such as temperature, precipitation, and wind modulate rates of heat loss in animals, but analysis of their effects on endothermic species is complicated by the fact that their influence on energy balance is not invariably linear, even across the thermoneutral range. Rather, the thermal load imposed by a given set of weather conditions is a function of organisms' metabolic requirement, which, crucially, may vary spontaneously both seasonally and across different life phases. We propose that the endogenous component of variation in metabolic demand introduces a temporal dimension and that, as a consequence, the specific effect of meteorological variables on energy balance and attendant life history parameters is a function of the timing of weather events with respect to the organism's metabolic rhythm(s). To test this, we examined how a spontaneous increase in metabolic demand influenced the effect of weather on early development in a large mammal. Specifically, we examined interaction between the exponential rise in the energy requirements of pregnancy and depth of snow, which restricts dams' access to forage, on the body mass of reindeer calves (Rangifer tarandus) at weaning. As expected, we detected a significant temporal component: the specific negative effect of snow on weaning mass was not constant, but increased across pregnancy. The life history response was therefore better predicted by interaction between the magnitude and the timing of weather events than by their magnitude alone. To our knowledge, this is the first demonstration of the influence of an endogenous metabolic dynamic on the impact of weather on a life history trait in a free

  8. Non-equilibrium effects of core-cooling and time-dependent internal heating on mantle flush events

    NASA Astrophysics Data System (ADS)

    Yuen, D. A.; Balachandar, S.; Steinbach, V. C.; Honda, S.; Reuteler, D. M.; Smedsmo, J. J.; Lauer, G. S.

    We have examined the non-equilibrium effects of core-cooling and time-dependent internal-heating on the thermal evolution of the Earth's mantle and on mantle flush events caused by the two major phase transitions. Both two- and three-dimensional models have been employed. The mantle viscosity responds to the secular cooling through changes in the averaged temperature field. A viscosity which decreases algebraically with the average temperature has been considered. The time-dependent internal-heating is prescribed to decrease exponentially with a single decay time. We have studied the thermal histories with initial Rayleigh numbers between 2 x 107 and 108 . Flush events, driven by the non-equilibrium forcings, are much more dramatic than those produced by the equilibrium boundary conditions and constant internal heating. Multiple flush events are found under non-equilibrium conditions in which there is very little internal heating or very fast decay rates of internal-heating. Otherwise, the flush events take place in a relatively continuous fashion. Prior to massive flush events small-scale percolative structures appear in the 3D temperature fields. Time-dependent signatures, such as the surface heat flux, also exhibits high frequency oscillatory patterns prior to massive flush events. These two observations suggest that the flush event may be a self-organized critical phenomenon. The Nusselt number as a function of the time-varying Ra does not follow the Nusselt vs. Rayleigh number power-law relationship based on equilibrium (constant temperature) boundary conditions. Instead Nu(t) may vary non-monotonically with time because of the mantle flush events. Convective processes in the mantle operate quite differently under non-equilibrium conditions from its behaviour under the usual equilibrium situations.

  9. Real-time detection and classification of anomalous events in streaming data

    DOEpatents

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

    2016-04-19

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

  10. Correlation Analyses Between the Characteristic Times of Gradual Solar Energetic Particle Events and the Properties of Associated Coronal Mass Ejections

    NASA Astrophysics Data System (ADS)

    Pan, Z. H.; Wang, C. B.; Wang, Yuming; Xue, X. H.

    2011-06-01

    It is generally believed that gradual solar energetic particles (SEPs) are accelerated by shocks associated with coronal mass ejections (CMEs). Using an ice-cream cone model, the radial speed and angular width of 95 CMEs associated with SEP events during 1998 - 2002 are calculated from SOHO/LASCO observations. Then, we investigate the relationships between the kinematic properties of these CMEs and the characteristic times of the intensity-time profile of their accompanied SEP events observed at 1 AU. These characteristic times of SEP are i) the onset time from the accompanying CME eruption at the Sun to the SEP arrival at 1 AU, ii) the rise time from the SEP onset to the time when the SEP intensity is one-half of peak intensity, and iii) the duration over which the SEP intensity is within a factor of two of the peak intensity. It is found that the onset time has neither significant correlation with the radial speed nor with the angular width of the accompanying CME. For events that are poorly connected to the Earth, the SEP rise time and duration have no significant correlation with the radial speed and angular width of the associated CMEs. However, for events that are magnetically well connected to the Earth, the SEP rise time and duration have significantly positive correlations with the radial speed and angular width of the associated CMEs. This indicates that a CME event with wider angular width and higher speed may more easily drive a strong and wide shock near to the Earth-connected interplanetary magnetic field lines, may trap and accelerate particles for a longer time, and may lead to longer rise time and duration of the ensuing SEP event.

  11. Estimation of short-time cross-correlation between frequency bands of event related EEG.

    PubMed

    Zygierewicz, J; Mazurkiewicz, J; Durka, P J; Franaszczuk, P J; Crone, N E

    2006-10-30

    Simultaneous variations of the event-related power changes (ERD/ERS) are often observed in a number of frequency bands. ERD/ERS measures are usually based on the relative changes of power in a given single frequency band. Within such an approach one cannot answer questions concerning the mutual relations between the band-power variations observed in different frequency bands. This paper addresses the problem of estimating and assessing the significance of the average cross-correlation between ERD/ERS phenomena occurring in two frequency bands. The cross-correlation function in a natural way also provides estimation of the delay between ERD/ERS in those bands. The proposed method is based on estimating the short-time cross-correlation function between relative changes of power in two selected frequency bands. The cross-correlation function is estimated in each trial separately and then averaged across trials. The significance of those mean cross-correlation functions is evaluated by means of a nonparametric test. The basic properties of the method are presented on simulated signals, and an example application to real EEG and ECoG signals is given.

  12. Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France.

    PubMed

    Abat, Cédric; Chaudet, Hervé; Colson, Philippe; Rolain, Jean-Marc; Raoult, Didier

    2015-08-01

    Infectious diseases are a major threat to humanity, and accurate surveillance is essential. We describe how to implement a laboratory data-based surveillance system in a clinical microbiology laboratory. Two historical Microsoft Excel databases were implemented. The data were then sorted and used to execute the following 2 surveillance systems in Excel: the Bacterial real-time Laboratory-based Surveillance System (BALYSES) for monitoring the number of patients infected with bacterial species isolated at least once in our laboratory during the study periodl and the Marseille Antibiotic Resistance Surveillance System (MARSS), which surveys the primary β-lactam resistance phenotypes for 15 selected bacterial species. The first historical database contained 174,853 identifications of bacteria, and the second contained 12,062 results of antibiotic susceptibility testing. From May 21, 2013, through June 4, 2014, BALYSES and MARSS enabled the detection of 52 abnormal events for 24 bacterial species, leading to 19 official reports. This system is currently being refined and improved.

  13. Flowgraph: The Display of Clinical Data and Events in Time-Oriented Graphic Form

    PubMed Central

    Foy, John L.; Esterhay, Robert J.

    1980-01-01

    Clinicians have often found it useful, in both ongoing patient care and in the preparation of case summaries, to record multiple variables simultaneously on one graph, frequently superimposed on the patient's vital-signs chart. The totally-electronic patient record of the Problem Oriented Medical Information System (PROMIS) makes it possible to generate these graphs automatically, on line, at the user's request. Such a capability has been added to PROMIS during preparations for its installation in this cancer treatment research facility. User-specified data from the patient record is plotted against time on a touch-sensitive CRT. Most items are graphed each on a single line, with a mark indicating that a test was performed, a drug given, an assessment made, or whatever. This form of display presents a pictorial abstract of the patient's record, from which the clinician can often quickly form an impression of events in the patient's recent or remote history. Where details are desired, the user can call on the extensive PROMIS flowsheet facility directly from the graph by touch-selection of the region of interest.

  14. Orbit Determination and Navigation of the Time History of Events and Macroscale Interactions during Substorms (THEMIS)

    NASA Technical Reports Server (NTRS)

    Morinelli, Patrick; Cosgrove, jennifer; Blizzard, Mike; Nicholson, Ann; Robertson, Mika

    2007-01-01

    This paper provides an overview of the launch and early orbit activities performed by the NASA Goddard Space Flight Center's (GSFC) Flight Dynamics Facility (FDF) in support of five probes comprising the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft. The FDF was tasked to support THEMIS in a limited capacity providing backup orbit determination support for validation purposes for all five THEMIS probes during launch plus 30 days in coordination with University of California Berkeley Flight Dynamics Center (UCB/FDC). The FDF's orbit determination responsibilities were originally planned to be as a backup to the UCB/FDC for validation purposes only. However, various challenges early on in the mission and a Spacecraft Emergency declared thirty hours after launch placed the FDF team in the role of providing the orbit solutions that enabled contact with each of the probes and the eventual termination of the Spacecraft Emergency. This paper details the challenges and various techniques used by the GSFC FDF team to successfully perform orbit determination for all five THEMIS probes during the early mission. In addition, actual THEMIS orbit determination results are presented spanning the launch and early orbit mission phase. Lastly, this paper enumerates lessons learned from the THEMIS mission, as well as demonstrates the broad range of resources and capabilities within the FDF for supporting critical launch and early orbit navigation activities, especially challenging for constellation missions.

  15. Orbit Determination and Navigation of the Time History of Events and Macroscale Interactions during Substorms (THEMIS)

    NASA Technical Reports Server (NTRS)

    Morinelli, Patrick; Cosgrove, Jennifer; Blizzard, Mike; Robertson, Mike

    2007-01-01

    This paper provides an overview of the launch and early orbit activities performed by the NASA Goddard Space Flight Center's (GSFC) Flight Dynamics Facility (FDF) in support of five probes comprising the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft. The FDF was tasked to support THEMIS in a limited capacity providing backup orbit determination support for validation purposes for all five THEMIS probes during launch plus 30 days in coordination with University of California Berkeley Flight Dynamics Center (UCB/FDC)2. The FDF's orbit determination responsibilities were originally planned to be as a backup to the UCB/FDC for validation purposes only. However, various challenges early on in the mission and a Spacecraft Emergency declared thirty hours after launch placed the FDF team in the role of providing the orbit solutions that enabled contact with each of the probes and the eventual termination of the Spacecraft Emergency. This paper details the challenges and various techniques used by the GSFC FDF team to successfully perform orbit determination for all five THEMIS probes during the early mission. In addition, actual THEMIS orbit determination results are presented spanning the launch and early orbit mission phase. Lastly, this paper enumerates lessons learned from the THEMIS mission, as well as demonstrates the broad range of resources and capabilities within the FDF for supporting critical launch and early orbit navigation activities, especially challenging for constellation missions.

  16. A Time Scale for Major Events in Early Mars Crustal Evolution

    NASA Technical Reports Server (NTRS)

    Frey, Herbert V.

    2004-01-01

    The population of visible and buried impact basins > 200 km diameter revealed by high resolution gridded MOLA data and the cumulative frequency curves derived for these pvide a basis for a chronology of major events in early martian history. The relative chronology can be given in terms of N(200) crater retention ages; 'absolute ages' can be assigued using the Hartmann-Neukum (H&N) model chronology. In terms of billions of H&N years, the crustal dichotomy formed by large impact basins at 4.12 +/- 0.08 BYA (N(200) = 3.0-3.2) and the global magnetic field died at about or slightly before the same time (4.15 +/- 0.08 BYA (N(200) = 3.5). In this chronology, the buried lowlands are approx. 120 my younger than the buried highlands, approx. 160 my younger than the highlands overall and approx. 340 my younger than the oldest crater retention surface we see, defined by the largest impact basins.

  17. Early events in insulin fibrillization studied by time-lapse atomic force microscopy.

    PubMed

    Podestà, Alessandro; Tiana, Guido; Milani, Paolo; Manno, Mauro

    2006-01-15

    The importance of understanding the mechanism of protein aggregation into insoluble amyloid fibrils lies not only in its medical consequences, but also in its more basic properties of self-organization. The discovery that a large number of uncorrelated proteins can form, under proper conditions, structurally similar fibrils has suggested that the underlying mechanism is a general feature of polypeptide chains. In this work, we address the early events preceding amyloid fibril formation in solutions of zinc-free human insulin incubated at low pH and high temperature. Here, we show by time-lapse atomic force microscopy that a steady-state distribution of protein oligomers with a quasiexponential tail is reached within a few minutes after heating. This metastable phase lasts for a few hours, until fibrillar aggregates are observable. Although for such complex systems different aggregation mechanisms can occur simultaneously, our results indicate that the prefibrillar phase is mainly controlled by a simple coagulation-evaporation kinetic mechanism, in which concentration acts as a critical parameter. These experimental facts, along with the kinetic model used, suggest a critical role for thermal concentration fluctuations in the process of fibril nucleation.

  18. Rainfall time series synthesis from queue scheduling of rain event fractals over radio links

    NASA Astrophysics Data System (ADS)

    Alonge, Akintunde A.; Afullo, Thomas J.

    2015-12-01

    Rainfall attenuation over wireless networks stems from random fluctuations in the natural process of arriving rainfall rates over radio links. This arrival process results in discernible rainfall traffic pattern which manifests as naturally scheduled and queue-generated rain spikes. Hence, the phenomenon of rainfall process can be approached as a semi-Markovian queueing process, with event characteristics dependent on queue parameters. However, a constraint to this approach is the knowledge of the physical characteristics of queue-generated rain spikes. Therefore, this paper explores the probability theory and descriptive mathematics of rain spikes in rainfall processes. This investigation presents the synthesis of rainfall queue with rain spikes at subtropical and equatorial locations of Durban (29°52'S, 30°58'E) and Butare (2°36'S, 29°44'E), respectively. The resulting comparative analysis of rainfall distributions, using error analysis at both locations, reveals that queue-generated rainfall compares well with measured rainfall data set. This suggests that the time-varying process of rainfall, though stochastic, can be synthesized via queue scheduling with the application of relevant queue parameters at any location.

  19. Late-Time Follow-up of ASAS-SN Tidal Disruption Events

    NASA Astrophysics Data System (ADS)

    Warren-Son Holoien, Thomas; ASAS-SN Team

    2017-01-01

    Humanity should have a continuous record of the sky, and for the past 3.5 years, the All-Sky Automated Survey for SuperNovae (ASAS-SN or "Assassin") has been working to provide that record. ASAS-SN is a long-term project to monitor the entire sky with a rapid cadence using a global array of small telescopes in both hemispheres, searching for new bright transients that can be studied in detail by the world's astronomers. By focusing only on the brightest objects, ASAS-SN limits its discoveries to only those that can be studied in the greatest detail, and it is unique among professional surveys in this respect. While the primary goal of ASAS-SN is a complete survey of bright, nearby supernovae, ASAS-SN also finds many other interesting transients. ASAS-SN has discovered 3 of the brightest tidal disruption events (TDEs) ever found at optical wavelengths, and we have performed extensive follow-up studies of these objects since discovery. I will present the results of late-time follow-up studies of the ASAS-SN TDEs and discuss the deeper insight into TDE physics that can be gained from this work.

  20. The time course of psychological stress as revealed by event-related potentials.

    PubMed

    Yang, Juan; Qi, Mingming; Guan, Lili; Hou, Yan; Yang, Yu

    2012-11-14

    Psychological stress is common in everyday life and is believed to affect emotion, cognition and health. Previous brain imaging studies have been able to identify the brain regions involved in the stress response. However, our understanding of the temporal neurological response to psychological stress is limited. The present work aims to investigate the time course of psychological stress induced by a mental arithmetic task, utilizing event-related potentials (ERPs). The elicitation of stress was verified by self-reports of stress and increases in salivary cortisol levels. The subjective and physiological data showed that the stress-elicitation paradigm successfully induced a mild-to-moderate level of psychological stress. The electrophysiological data showed that the amplitude of occipital N1 was more negative in the control task than in the stress task, and the latency of frontal P2 was shorter in the stress task than in the control task. Our results provide electrophysiological evidence that psychological stress occurs primarily at the early stage of cognitive processing.

  1. A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

    PubMed

    Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

    2015-09-20

    Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system.

  2. Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France

    PubMed Central

    Abat, Cédric; Chaudet, Hervé; Colson, Philippe; Rolain, Jean-Marc

    2015-01-01

    Infectious diseases are a major threat to humanity, and accurate surveillance is essential. We describe how to implement a laboratory data–based surveillance system in a clinical microbiology laboratory. Two historical Microsoft Excel databases were implemented. The data were then sorted and used to execute the following 2 surveillance systems in Excel: the Bacterial real-time Laboratory-based Surveillance System (BALYSES) for monitoring the number of patients infected with bacterial species isolated at least once in our laboratory during the study periodl and the Marseille Antibiotic Resistance Surveillance System (MARSS), which surveys the primary β-lactam resistance phenotypes for 15 selected bacterial species. The first historical database contained 174,853 identifications of bacteria, and the second contained 12,062 results of antibiotic susceptibility testing. From May 21, 2013, through June 4, 2014, BALYSES and MARSS enabled the detection of 52 abnormal events for 24 bacterial species, leading to 19 official reports. This system is currently being refined and improved. PMID:26196165

  3. Mother-Child Joint Conversational Exchanges during Events: Linkages to Children's Memory Reports over Time

    ERIC Educational Resources Information Center

    Hedrick, Amy M.; San Souci, Priscilla; Haden, Catherine A.; Ornstein, Peter A.

    2009-01-01

    This longitudinal study explores linkages between patterns of mother-child conversation as events unfold and children's subsequent event memory reports. Eighty-nine mother-child dyads took part in novel "adventures" in their homes when the children were 36 and 42 months old. In contrast to "low joint talk" dyads, the conversations of "high joint…

  4. Observations of Time Variable Magnitude Events of Phoebe, Ariel, and Titania

    NASA Astrophysics Data System (ADS)

    Miller, Charles; Chanover, N. J.; Holtzman, J. A.; Verbiscer, A. J.

    2007-10-01

    Visual observations of Saturn's moon Phoebe and Uranus' moons Ariel and Titania were made from the Apache Point Observatory (APO). Phoebe was observed with the APO 1 meter telescope over a two month period from 06 January to 04 March 2005, bracketing the zero-phase opposition on 13 January 2005. Phoebe was observed at Sun-Phoebe-Earth phase angles as low as 0.05 degrees on consecutive nights immediately before and after opposition in V, B, R, and I filters. Light curves of the opposition surge, the brightness increase that occurs as the phase angle drops below 0.10 degrees, are presented from this data. The data were processed using standard IRAF aperture photometry image processing techniques. The magnitude and duration of the opposition surge provide clues about the grain size of surface particles on Phoebe. Observations were also made of Uranian moons during mutual occultations in August 2007. Mutual satellite occultations are taking place throughout 2007 as Uranus passes through its equinox, which occurs once every 42 years. The timing and flux variation of satellite occultations provide a check on the accuracy of satellite orbital models. Light curves for Ariel and Titania in R and I filters as they are occulted by Umbriel are presented from data acquired with the APO 1 meter and 3.5 meter telescopes. Comparison is made to the predicted total flux reduction and event timing for each occultation as calculated by the Institut de Mecanique Celeste et de Calcul des Ephemerides (IMCCE) and implications of the results on determination of the relative orbital inclinations of Umbriel, Ariel, and Titania are discussed. This work was supported by an NMSU Space and Aerospace Research Cluster Graduate Fellowship .

  5. Multivariate bubbles and antibubbles

    NASA Astrophysics Data System (ADS)

    Fry, John

    2014-08-01

    In this paper we develop models for multivariate financial bubbles and antibubbles based on statistical physics. In particular, we extend a rich set of univariate models to higher dimensions. Changes in market regime can be explicitly shown to represent a phase transition from random to deterministic behaviour in prices. Moreover, our multivariate models are able to capture some of the contagious effects that occur during such episodes. We are able to show that declining lending quality helped fuel a bubble in the US stock market prior to 2008. Further, our approach offers interesting insights into the spatial development of UK house prices.

  6. Multivariate Data EXplorer (MDX)

    SciTech Connect

    Steed, Chad Allen

    2012-08-01

    The MDX toolkit facilitates exploratory data analysis and visualization of multivariate datasets. MDX provides and interactive graphical user interface to load, explore, and modify multivariate datasets stored in tabular forms. MDX uses an extended version of the parallel coordinates plot and scatterplots to represent the data. The user can perform rapid visual queries using mouse gestures in the visualization panels to select rows or columns of interest. The visualization panel provides coordinated multiple views whereby selections made in one plot are propagated to the other plots. Users can also export selected data or reconfigure the visualization panel to explore relationships between columns and rows in the data.

  7. Diagnosing and attributing neuropsychiatric events to systemic lupus erythematosus: time to untie the Gordian knot?

    PubMed

    Tay, Sen Hee; Mak, Anselm

    2016-10-15

    Neurological and psychiatric syndromes, collectively referred to as NPSLE, occur frequently in SLE. The frequency of NPSLE varies from 21 to 95%; however, only 13-38% of neuropsychiatric (NP) events could be attributable to SLE in the NPSLE SLICC inception cohort. This variability in the frequency of NPSLE is attributable to the low specificity of the ACR case definitions for SLE-attributed NP syndromes, inclusion of minor NP events in the ACR nomenclature, difficulty in ascertainment of NP events and diverse experience of rheumatologists in the clinical assessment of NP events. Making the correct and early attribution of NP events to SLE is important to institute appropriate immunosuppressive treatment for favourable outcomes. Various attribution models using composite decision rules have been developed and used to ascribe NP events to SLE. This review will focus on the various clinical presentations, diagnostic work-up and attributions of the common NPSLE syndromes, including other NP events not included in the ACR nomenclature but which have come to attention in recent years.

  8. Time-to-Event Analysis of Individual Variables Associated with Nursing Students' Academic Failure: A Longitudinal Study

    ERIC Educational Resources Information Center

    Dante, Angelo; Fabris, Stefano; Palese, Alvisa

    2013-01-01

    Empirical studies and conceptual frameworks presented in the extant literature offer a static imagining of academic failure. Time-to-event analysis, which captures the dynamism of individual factors, as when they determine the failure to properly tailor timely strategies, impose longitudinal studies which are still lacking within the field. The…

  9. Hierarchy of temporal responses of multivariate self-excited epidemic processes

    NASA Astrophysics Data System (ADS)

    Saichev, Alexander; Maillart, Thomas; Sornette, Didier

    2013-04-01

    Many natural and social systems are characterized by bursty dynamics, for which past events trigger future activity. These systems can be modelled by so-called self-excited Hawkes conditional Poisson processes. It is generally assumed that all events have similar triggering abilities. However, some systems exhibit heterogeneity and clusters with possibly different intra- and inter-triggering, which can be accounted for by generalization into the "multivariate" self-excited Hawkes conditional Poisson processes. We develop the general formalism of the multivariate moment generating function for the cumulative number of first-generation and of all generation events triggered by a given mother event (the "shock") as a function of the current time t. This corresponds to studying the response function of the process. A variety of different systems have been analyzed. In particular, for systems in which triggering between events of different types proceeds through a one-dimension directed or symmetric chain of influence in type space, we report a novel hierarchy of intermediate asymptotic power law decays ˜ 1/ t 1-( m+1) θ of the rate of triggered events as a function of the distance m of the events to the initial shock in the type space, where 0 < θ < 1 for the relevant long-memory processes characterizing many natural and social systems. The richness of the generated time dynamics comes from the cascades of intermediate events of possibly different kinds, unfolding via random changes of types genealogy.

  10. Demanding response time requirements on coherent receivers due to fast polarization rotations caused by lightning events.

    PubMed

    Krummrich, Peter M; Ronnenberg, David; Schairer, Wolfgang; Wienold, Daniel; Jenau, Frank; Herrmann, Maximilian

    2016-05-30

    Lightning events can cause fast polarization rotations and phase changes in optical transmission fibers due to strong electrical currents and magnetic fields. Whereas these are unlikely to affect legacy transmission systems with direct detection, different mechanisms have to be considered in systems with local oscillator based coherent receivers and digital signal processing. A theoretical analysis reveals that lightning events can result in polarization rotations with speeds as fast as a few hundred kRad/s. We discuss possible mechanisms how such lightning events can affect coherent receivers with digital signal processing. In experimental investigations with a high current pulse generator and transponder prototypes, we observed post FEC errors after polarization rotation events which can be expected from lightning strikes.

  11. Timing and order of transmission events is not directly reflected in a pathogen phylogeny.

    PubMed

    Romero-Severson, Ethan; Skar, Helena; Bulla, Ingo; Albert, Jan; Leitner, Thomas

    2014-09-01

    Pathogen phylogenies are often used to infer spread among hosts. There is, however, not an exact match between the pathogen phylogeny and the host transmission history. Here, we examine in detail the limitations of this relationship. First, all splits in a pathogen phylogeny of more than 1 host occur within hosts, not at the moment of transmission, predating the transmission events as described by the pretransmission interval. Second, the order in which nodes in a phylogeny occur may be reflective of the within-host dynamics rather than epidemiologic relationships. To investigate these phenomena, motivated by within-host diversity patterns, we developed a two-phase coalescent model that includes a transmission bottleneck followed by linear outgrowth to a maximum population size followed by either stabilization or decline of the population. The model predicts that the pretransmission interval shrinks compared with predictions based on constant population size or a simple transmission bottleneck. Because lineages coalesce faster in a small population, the probability of a pathogen phylogeny to resemble the transmission history depends on when after infection a donor transmits to a new host. We also show that the probability of inferring the incorrect order of multiple transmissions from the same host is high. Finally, we compare time of HIV-1 infection informed by genetic distances in phylogenies to independent biomarker data, and show that, indeed, the pretransmission interval biases phylogeny-based estimates of when transmissions occurred. We describe situations where caution is needed not to misinterpret which parts of a phylogeny that may indicate outbreaks and tight transmission clusters.

  12. LATE-TIME RADIO EMISSION FROM X-RAY-SELECTED TIDAL DISRUPTION EVENTS

    SciTech Connect

    Bower, Geoffrey C.; Cenko, S. Bradley; Silverman, Jeffrey M.; Bloom, Joshua S.; Metzger, Brian D.

    2013-02-15

    We present new observations with the Karl G. Jansky Very Large Array of seven X-ray-selected tidal disruption events (TDEs). The radio observations were carried out between 9 and 22 years after the initial X-ray discovery, and thus probe the late-time formation of relativistic jets and jet interactions with the interstellar medium in these systems. We detect a compact radio source in the nucleus of the galaxy IC 3599 and a compact radio source that is a possible counterpart to RX J1420.4+5334. We find no radio counterparts for five other sources with flux density upper limits between 51 and 200 {mu}Jy (3{sigma}). If the detections truly represent late radio emission associated with a TDE, then our results suggest that a fraction, {approx}> 10%, of X-ray-detected TDEs are accompanied by relativistic jets. We explore several models for producing late radio emission, including interaction of the jet with gas in the circumnuclear environment (blast wave model), and emission from the core of the jet itself. Upper limits on the radio flux density from archival observations suggest that the jet formation may have been delayed for years after the TDE, possibly triggered by the accretion rate dropping below a critical threshold of {approx}10{sup -2}-10{sup -3} M-dot {sub Edd}. The non-detections are also consistent with this scenario; deeper radio observations can determine whether relativistic jets are present in these systems. The emission from RX J1420.4+5334 is also consistent with the predictions of the blast wave model; however, the radio emission from IC 3599 is substantially underluminous, and its spectral slope is too flat, relative to the blast wave model expectations. Future radio monitoring of IC 3599 and RX J1420.4+5334 will help to better constrain the nature of the jets in these systems.

  13. Time distribution of heavy rainfall events in south west of Iran

    NASA Astrophysics Data System (ADS)

    Ghassabi, Zahra; kamali, G. Ali; Meshkatee, Amir-Hussain; Hajam, Sohrab; Javaheri, Nasrolah

    2016-07-01

    Accurate knowledge of rainfall time distribution is a fundamental issue in many Meteorological-Hydrological studies such as using the information of the surface runoff in the design of the hydraulic structures, flood control and risk management, and river engineering studies. Since the main largest dams of Iran are in the south-west of the country (i.e. South Zagros), this research investigates the temporal rainfall distribution based on an analytical numerical method to increase the accuracy of hydrological studies in Iran. The United States Soil Conservation Service (SCS) estimated the temporal rainfall distribution in various forms. Hydrology studies usually utilize the same distribution functions in other areas of the world including Iran due to the lack of sufficient observation data. However, we first used Weather Research Forecasting (WRF) model to achieve the simulated rainfall results of the selected storms on south west of Iran in this research. Then, a three-parametric Logistic function was fitted to the rainfall data in order to compute the temporal rainfall distribution. The domain of the WRF model is 30.5N-34N and 47.5E-52.5E with a resolution of 0.08 degree in latitude and longitude. We selected 35 heavy storms based on the observed rainfall data set to simulate with the WRF Model. Storm events were scrutinized independently from each other and the best analytical three-parametric logistic function was fitted for each grid point. The results show that the value of the coefficient a of the logistic function, which indicates rainfall intensity, varies from the minimum of 0.14 to the maximum of 0.7. Furthermore, the values of the coefficient B of the logistic function, which indicates rain delay of grid points from start time of rainfall, vary from 1.6 in south-west and east to more than 8 in north and central parts of the studied area. In addition, values of rainfall intensities are lower in south west of IRAN than those of observed or proposed by the

  14. Times to key events in Zika virus infection and implications for blood donation: a systematic review

    PubMed Central

    Ott, Cassandra T; Carcelen, Andrea C; Konikoff, Jacob M; Williamson, Joe; Bi, Qifang; Kucirka, Lauren M; Cummings, Derek AT; Reich, Nicholas G; Chaisson, Lelia H

    2016-01-01

    Abstract Objective To estimate the timing of key events in the natural history of Zika virus infection. Methods In February 2016, we searched PubMed, Scopus and the Web of Science for publications containing the term Zika. By pooling data, we estimated the incubation period, the time to seroconversion and the duration of viral shedding. We estimated the risk of Zika virus contaminated blood donations. Findings We identified 20 articles on 25 patients with Zika virus infection. The median incubation period for the infection was estimated to be 5.9 days (95% credible interval, CrI: 4.4–7.6), with 95% of people who developed symptoms doing so within 11.2 days (95% CrI: 7.6–18.0) after infection. On average, seroconversion occurred 9.1 days (95% CrI: 7.0–11.6) after infection. The virus was detectable in blood for 9.9 days (95% CrI: 6.9–21.4) on average. Without screening, the estimated risk that a blood donation would come from an infected individual increased by approximately 1 in 10 000 for every 1 per 100 000 person–days increase in the incidence of Zika virus infection. Symptom-based screening may reduce this rate by 7% (relative risk, RR: 0.93; 95% CrI: 0.89–0.99) and antibody screening, by 29% (RR: 0.71; 95% CrI: 0.28–0.88). Conclusion Neither symptom- nor antibody-based screening for Zika virus infection substantially reduced the risk that blood donations would be contaminated by the virus. Polymerase chain reaction testing should be considered for identifying blood safe for use in pregnant women in high-incidence areas. PMID:27821887

  15. Scaling Time Warp-based Discrete Event Execution to 104 Processors on Blue Gene Supercomputer

    SciTech Connect

    Perumalla, Kalyan S

    2007-01-01

    Lately, important large-scale simulation applications, such as emergency/event planning and response, are emerging that are based on discrete event models. The applications are characterized by their scale (several millions of simulated entities), their fine-grained nature of computation (microseconds per event), and their highly dynamic inter-entity event interactions. The desired scale and speed together call for highly scalable parallel discrete event simulation (PDES) engines. However, few such parallel engines have been designed or tested on platforms with thousands of processors. Here an overview is given of a unique PDES engine that has been designed to support Time Warp-style optimistic parallel execution as well as a more generalized mixed, optimistic-conservative synchronization. The engine is designed to run on massively parallel architectures with minimal overheads. A performance study of the engine is presented, including the first results to date of PDES benchmarks demonstrating scalability to as many as 16,384 processors, on an IBM Blue Gene supercomputer. The results show, for the first time, the promise of effectively sustaining very large scale discrete event execution on up to 104 processors.

  16. Real time imaging of live cell ATP leaking or release events by chemiluminescence microscopy

    SciTech Connect

    Zhang, Yun

    2008-12-18

    The purpose of this research was to expand the chemiluminescence microscopy applications in live bacterial/mammalian cell imaging and to improve the detection sensitivity for ATP leaking or release events. We first demonstrated that chemiluminescence (CL) imaging can be used to interrogate single bacterial cells. While using a luminometer allows detecting ATP from cell lysate extracted from at least 10 bacterial cells, all previous cell CL detection never reached this sensitivity of single bacteria level. We approached this goal with a different strategy from before: instead of breaking bacterial cell membrane and trying to capture the transiently diluted ATP with the firefly luciferase CL assay, we introduced the firefly luciferase enzyme into bacteria using the modern genetic techniques and placed the CL reaction substrate D-luciferin outside the cells. By damaging the cell membrane with various antibacterial drugs including antibiotics such as Penicillins and bacteriophages, the D-luciferin molecules diffused inside the cell and initiated the reaction that produces CL light. As firefly luciferases are large protein molecules which are retained within the cells before the total rupture and intracellular ATP concentration is high at the millmolar level, the CL reaction of firefly luciferase, ATP and D-luciferin can be kept for a relatively long time within the cells acting as a reaction container to generate enough photons for detection by the extremely sensitive intensified charge coupled device (ICCD) camera. The result was inspiring as various single bacterium lysis and leakage events were monitored with 10-s temporal resolution movies. We also found a new way of enhancing diffusion D-luciferin into cells by dehydrating the bacteria. Then we started with this novel single bacterial CL imaging technique, and applied it for quantifying gene expression levels from individual bacterial cells. Previous published result in single cell gene expression quantification

  17. Illustration of compositional variations over time of Chinese porcelain glazes combining micro-X-ray Fluorescence spectrometry, multivariate data analysis and Seger formulas

    NASA Astrophysics Data System (ADS)

    Van Pevenage, J.; Verhaeven, E.; Vekemans, B.; Lauwers, D.; Herremans, D.; De Clercq, W.; Vincze, L.; Moens, L.; Vandenabeele, P.

    2015-01-01

    In this research, the transparent glaze layers of Chinese porcelain samples were investigated. Depending on the production period, these samples can be divided into two groups: the samples of group A dating from the Kangxi period (1661-1722), and the samples of group B produced under emperor Qianlong (1735-1795). Due to the specific sample preparation method and the small spot size of the X-ray beam, investigation of the transparent glaze layers is enabled. Despite the many existing research papers about glaze investigations of ceramics and/or porcelain ware, this research reveals new insights into the glaze composition and structure of Chinese porcelain samples. In this paper it is demonstrated, using micro-X-ray Fluorescence (μ-XRF) spectrometry, multivariate data analysis and statistical analysis (Hotelling's T-Square test) that the transparent glaze layers of the samples of groups A and B are significantly different (95% confidence level). Calculation of the Seger formulas, enabled classification of the glazes. Combining all the information, the difference in composition of the Chinese porcelain glazes of the Kangxi period and the Qianlong period can be demonstrated.

  18. Finite-Time State Estimation for Recurrent Delayed Neural Networks With Component-Based Event-Triggering Protocol.

    PubMed

    Wang, Licheng; Wang, Zidong; Wei, Guoliang; Alsaadi, Fuad E

    2017-02-06

    This paper deals with the event-based finite-time state estimation problem for a class of discrete-time stochastic neural networks with mixed discrete and distributed time delays. In order to mitigate the burden of data communication, a general component-based event-triggered transmission mechanism is proposed to determine whether the measurement output should be released to the estimator at certain time-point according to a specific triggering condition. A new concept of finite-time boundedness in the mean square is put forward to quantify the estimation performance by introducing a settling-like time function. The objective of the addressed problem is to construct an event-based state estimator to estimate the neuron states such that, in the presence of both mixed time delays and external noise disturbances, the dynamics of the estimation error is finite-time bounded in the mean square with a prescribed error upper bound. Sufficient conditions are established, via stochastic analysis techniques, to guarantee the desired estimation performance. By solving an optimization problem with some inequality constraints, the explicit expression of the estimator gain matrix is characterized to minimize the settling-like time. Finally, a numerical simulation example is exploited to demonstrate the effectiveness of the proposed estimator design scheme.

  19. Time-dependent three-dimensional (latitude, longitude, altitude) response of the ionosphere to the 2009 SSW event

    NASA Astrophysics Data System (ADS)

    Azeem, S. I.; Crowley, G.; Reynolds, A.

    2013-12-01

    Recent studies have shown variations in the low and mid latitude ionosphere that are linked to Sudden Stratospheric Warming events. These studies suggest that during SSW events the equatorial electric fields vary in a quasi-deterministic way, producing vertical plasma drifts that deviate from climatological values more than expected. Although previous studies have provided important information on the ionospheric response to SSW events, they have been fairly localized. Therefore, broader observational capabilities and data are required that can unambiguously reveal the instantaneous global response of the ionosphere to SSW events. In this paper, we present four-dimensional (latitude, longitude, height and time) results of the Ionospheric Data Assimilation Four-Dimensional (IDA4D) algorithm to describe a global view of the ionospheric response to the 2009 SSW event. We use the IDA4D to assimilate ionosondes, ground-based GPS TEC, DORIS, CHAMP and GRACE occultation measurements for several days in January 2009 during the SSW event. IDA4D results show that at the peak of the 2009 SSW event, TEC values in the low latitudes were elevated in the morning hours while they were suppressed in the evening sector. The effects of enhanced dynamo forcing during the January 2009 SSW were also captured by the IDA4D showing an increased separation of the Appleton Anomaly peaks. The IDA4D results will be discussed in the context of horizontal, vertical and temporal evolution of ionospheric disturbances associated with the 2009 SSW event. The evolution of longitudinal, local time, and height (where applicable) variations of various plasma parameters (such as Ne, TEC, NmF2, hmF2, foF2) through the full 2009 SSW cycle (including genesis, onset, and recovery) will be presented.

  20. A time-varying subjective quality model for mobile streaming videos with stalling events

    NASA Astrophysics Data System (ADS)

    Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C.

    2015-09-01

    Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

  1. MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.

    PubMed

    Cockfield, Jeremy; Su, Kyungmin; Robbins, Kay A

    2013-01-01

    Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED

  2. The origins of multifractality in financial time series and the effect of extreme events

    NASA Astrophysics Data System (ADS)

    Green, Elena; Hanan, William; Heffernan, Daniel

    2014-06-01

    This paper presents the results of multifractal testing of two sets of financial data: daily data of the Dow Jones Industrial Average (DJIA) index and minutely data of the Euro Stoxx 50 index. Where multifractal scaling is found, the spectrum of scaling exponents is calculated via Multifractal Detrended Fluctuation Analysis. In both cases, further investigations reveal that the temporal correlations in the data are a more significant source of the multifractal scaling than are the distributions of the returns. It is also shown that the extreme events which make up the heavy tails of the distribution of the Euro Stoxx 50 log returns distort the scaling in the data set. The most extreme events are inimical to the scaling regime. This result is in contrast to previous findings that extreme events contribute to multifractality.

  3. Resiliency Over Time of Elders’ Age Stereotypes After Encountering Stressful Events

    PubMed Central

    Slade, Martin D.; Chung, Pil H.; Gill, Thomas M.

    2015-01-01

    Objective. To examine whether the age stereotypes of older individuals would become more negative or else show resiliency following stressful events and to examine whether age-stereotype negativity would increase the likelihood of experiencing a stressful event (i.e., hospitalization). Method. Age stereotypes of 231 participants, 70 years and older, were assessed across 10 years, before and after the occurrence of hospitalizations and bereavements. Results. Age-stereotype negativity was resilient despite encountering stressful events. In contrast, more negative age stereotypes were associated with a 50% greater likelihood of experiencing a hospitalization. Discussion. The robustness of negative age stereotypes was expressed in their capacity to resist change as well as generate it. PMID:24997287

  4. Modeling the Potential Volume of Gas Hydrates Over Time and During Transient Climate Events

    NASA Astrophysics Data System (ADS)

    Dickens, G. R.; Dickens, G. R.

    2001-12-01

    Gas hydrates in marine sediment probably serve as a large bacterially mediated capacitor in the global carbon cycle, storing and releasing CH4 with changes in external forcing. Although germinal, models of the global carbon cycle that incorporate gas hydrates require characterization of the available pore space -- the potential volume -- over time, especially during transient climate events. Potentially, gas hydrates can occur between the seafloor and a locus of subbottom depths where geothermal gradients intersect gas-gas hydrate-pore water equilibrium curves. Perpendicular to a given continental margin, the lens shaped area between these two bounding surfaces (Asl) varies according to seven basic parameters: gas composition, water activity (aw), bottom water temperature (Tb), geothermal gradient (G), slope depth (zslb), slope gradient (Z) and sea level relative to the shelf break (zo). Assuming pure CH4 gas, ~35 km2 of sediment can host gas hydrate across an average continental margin at a Pleistocene lowstand (aw = 0.981, Tb = 0° C, G = 0.05° C/m; zslb = 4000 m; Z = 0.04; zo = 0). However, this potential area would decrease with smaller aw, higher Tb, greater G, shallower zslb, steeper Z and lower zo, and increase with opposite external conditions. Of the basic parameters, temperature (Tb and G) and bathymetry (zslb and Z) can particularly influence the distribution of gas hydrate on continental slopes. A hydrothermal gradient (i.e., surface temperatures > Tb) will also decrease Asl, although minimally, especially if Tb exceeds 5° . The sum of parallel cross-sectional areas along a margin combined with porosity (φ ) gives the potential volume of gas hydrate (V). Assuming ~200,000 km of continental margin with φ of 0.50, ~3.5 x 106 km3 of pore space can contain gas hydrates at present-day, a volume that compares favorably with previous estimates (1.2 to 6.4 x 106 km3) although underlying approaches differ fundamentally. Since the Triassic, VGlob probably has

  5. Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

    NASA Astrophysics Data System (ADS)

    Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

    2015-04-01

    Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations

  6. Joint modelling of repeated measurements and time-to-event outcomes: flexible model specification and exact likelihood inference.

    PubMed

    Barrett, Jessica; Diggle, Peter; Henderson, Robin; Taylor-Robinson, David

    2015-01-01

    Random effects or shared parameter models are commonly advocated for the analysis of combined repeated measurement and event history data, including dropout from longitudinal trials. Their use in practical applications has generally been limited by computational cost and complexity, meaning that only simple special cases can be fitted by using readily available software. We propose a new approach that exploits recent distributional results for the extended skew normal family to allow exact likelihood inference for a flexible class of random-effects models. The method uses a discretization of the timescale for the time-to-event outcome, which is often unavoidable in any case when events correspond to dropout. We place no restriction on the times at which repeated measurements are made. An analysis of repeated lung function measurements in a cystic fibrosis cohort is used to illustrate the method.

  7. Sample Size Estimation for Negative Binomial Regression Comparing Rates of Recurrent Events with Unequal Follow-Up Time.

    PubMed

    Tang, Yongqiang

    2015-01-01

    A sample size formula is derived for negative binomial regression for the analysis of recurrent events, in which subjects can have unequal follow-up time. We obtain sharp lower and upper bounds on the required size, which is easy to compute. The upper bound is generally only slightly larger than the required size, and hence can be used to approximate the sample size. The lower and upper size bounds can be decomposed into two terms. The first term relies on the mean number of events in each group, and the second term depends on two factors that measure, respectively, the extent of between-subject variability in event rates, and follow-up time. Simulation studies are conducted to assess the performance of the proposed method. An application of our formulae to a multiple sclerosis trial is provided.

  8. Long-term memory: a natural mechanism for the clustering of extreme events and anomalous residual times in climate records.

    PubMed

    Bunde, Armin; Eichner, Jan F; Kantelhardt, Jan W; Havlin, Shlomo

    2005-02-04

    We study the statistics of the return intervals between extreme events above a certain threshold in long-term persistent records. We find that the long-term memory leads (i) to a stretched exponential distribution of the return intervals, (ii) to a pronounced clustering of extreme events, and (iii) to an anomalous behavior of the mean residual time to the next event that depends on the history and increases with the elapsed time in a counterintuitive way. We present an analytical scaling approach and demonstrate that all these features can be seen in long climate records. The phenomena should also occur in heartbeat records, Internet traffic, and stock market volatility and have to be taken into account for an efficient risk evaluation.

  9. Investigating neural primacy in Major Depressive Disorder: multivariate Granger causality analysis of resting-state fMRI time-series data.

    PubMed

    Hamilton, J P; Chen, G; Thomason, M E; Schwartz, M E; Gotlib, I H

    2011-07-01

    Major Depressive Disorder (MDD) has been conceptualized as a neural network-level disease. Few studies of the neural bases of depression, however, have used analytical techniques that are capable of testing network-level hypotheses of neural dysfunction in this disorder. Moreover, of those that have, fewer still have attempted to determine the directionality of influence within functionally abnormal networks of structures. We used multivariate GC analysis, a technique that estimates the extent to which preceding neural activity in one or more seed regions predicts subsequent activity in target brain regions, to analyze blood-oxygen-level-dependent (BOLD) data collected during eyes-closed rest from depressed and never-depressed persons. We found that activation in the hippocampus predicted subsequent increases in ventral anterior cingulate cortex (vACC) activity in depression, and that activity in the medial prefrontal cortex and vACC were mutually reinforcing in MDD. Hippocampal and vACC activation in depressed participants predicted subsequent decreases in dorsal cortical activity. This study shows that, on a moment-by-moment basis, there is increased excitatory activity among limbic and paralimbic structures, as well as increased inhibition in the activity of dorsal cortical structures, by limbic structures in depression; these aberrant patterns of effective connectivity implicate disturbances in the mesostriatal dopamine system in depression. These findings advance the neural theory of depression by detailing specific patterns of limbic excitation in MDD, by making explicit the primary role of limbic inhibition of dorsal cortex in the cortico-limbic relation posited to underlie depression, and by presenting an integrated neurofunctional account of altered dopamine function in this disorder.

  10. Time scales of biogeochemical and organismal responses to individual precipitation events

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In temperate grasslands, spatial and intra-annual variability in the activity of plants and microbes are structured by patterns in the precipitation regime. While the effects of total annual precipitation have been well-explored, the ecological dynamics associated with individual precipitation event...

  11. Constraining timing and origin of extreme wave events, Shirazuka Lowlands, Japan

    NASA Astrophysics Data System (ADS)

    Riedesel, Svenja; Brill, Dominik; Brückner, Helmut; De Batist, Marc; Fujiwara, Osamu; Garrett, Ed; Heyvaert, Vanessa M. A.; Miyairi, Yosuke; Opitz, Stephan; Seeliger, Martin; Shishikura, Masanubu; Yokoyama, Yusuke; Zander, Anja

    2016-04-01

    Tsunami and storm surges are major threats on coastal settlements. The Pacific Coast of southwest Japan is impacted by typhoons and tsunamis caused by earthquakes along the Nankai trough. This part of the Philippine Sea to Eurasia Plate subduction zone is expected to cause another earthquake and tsunami in near future. To improve the predictability of potential events, it is important to establish chronologies of former tsunamis as a basis for long-term recurrence intervals. Characterization of potential event deposits following a multi-proxy approach provides information about sediment source, transport dynamics and depositional processes. Sandwiched between a mid-Pleistocene terrace and a beach ridge, the coastal lowlands at Shirasuka, are ideally situated to record evidence of typhoons and tsunamis. Sediment cores from the lowlands include seven potential extreme wave event deposits. Their age, roughly constrained from a radiocarbon chronology, is historical. However, since the radiocarbon plateau deteriorates the precision of radiocarbon dating, optically stimulated luminescence dating was tested at this site. Quartz, as the favoured mineral for dating young and potentially poorly bleached sediments failed due to low signal intensity, absence of a fast component, and sensitivity to IR stimulation. Instead, feldspar dating is applied, using a standard IR50 and the post-IR-IR130 protocol to account for both signal stability (anomalous fading) and bleachability of the relatively young age of the sediments (<1000 years). The promising feldspar luminescence properties revealed by both protocols may offer the potential to establish robust OSL ages for all seven recorded event deposits that, in the end, may help to refine the existing radiocarbon chronology. Beside the establishment of a high-resolution OSL chronology, sedimentological, geochemical and microfaunal analyses allow a more detailed characterization of the event deposits. By applying the end

  12. Transient multivariable sensor evaluation

    DOEpatents

    Vilim, Richard B.; Heifetz, Alexander

    2017-02-21

    A method and system for performing transient multivariable sensor evaluation. The method and system includes a computer system for identifying a model form, providing training measurement data, generating a basis vector, monitoring system data from sensor, loading the system data in a non-transient memory, performing an estimation to provide desired data and comparing the system data to the desired data and outputting an alarm for a defective sensor.

  13. Multivariate Quantitative Chemical Analysis

    NASA Technical Reports Server (NTRS)

    Kinchen, David G.; Capezza, Mary

    1995-01-01

    Technique of multivariate quantitative chemical analysis devised for use in determining relative proportions of two components mixed and sprayed together onto object to form thermally insulating foam. Potentially adaptable to other materials, especially in process-monitoring applications in which necessary to know and control critical properties of products via quantitative chemical analyses of products. In addition to chemical composition, also used to determine such physical properties as densities and strengths.

  14. A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits.

    PubMed

    Gouwanda, Darwin; Gopalai, Alpha Agape

    2015-02-01

    Gait events detection allows clinicians and biomechanics researchers to determine timing of gait events, to estimate duration of stance phase and swing phase and to segment gait data. It also aids biomedical engineers to improve the design of orthoses and FES (functional electrical stimulation) systems. In recent years, researchers have resorted to using gyroscopes to determine heel-strike (HS) and toe-off (TO) events in gait cycles. However, these methods are subjected to significant delays when implemented in real-time gait monitoring devices, orthoses, and FES systems. Therefore, the work presented in this paper proposes a method that addresses these delays, to ensure real-time gait event detection. The proposed algorithm combines the use of heuristics and zero-crossing method to identify HS and TO. Experiments involving: (1) normal walking; (2) walking with knee brace; and (3) walking with ankle brace for overground walking and treadmill walking were designed to verify and validate the identified HS and TO. The performance of the proposed method was compared against the established gait detection algorithms. It was observed that the proposed method produced detection rate that was comparable to earlier reported methods and recorded reduced time delays, at an average of 100 ms.

  15. Hemispheric Differences in the Time-Course of Semantic Priming Processes: Evidence from Event-Related Potentials (ERPs)

    ERIC Educational Resources Information Center

    Bouaffre, Sarah; Faita-Ainseba, Frederique

    2007-01-01

    To investigate hemispheric differences in the timing of word priming, the modulation of event-related potentials by semantic word relationships was examined in each cerebral hemisphere. Primes and targets, either categorically (silk-wool) or associatively (needle-sewing) related, were presented to the left or right visual field in a go/no-go…

  16. DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

    PubMed Central

    Lawhern, Vernon; Hairston, W. David; Robbins, Kay

    2013-01-01

    Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration. PMID:23638169

  17. Tracking the Time Course of Word-Frequency Effects in Auditory Word Recognition with Event-Related Potentials

    ERIC Educational Resources Information Center

    Dufour, Sophie; Brunelliere, Angele; Frauenfelder, Ulrich H.

    2013-01-01

    Although the word-frequency effect is one of the most established findings in spoken-word recognition, the precise processing locus of this effect is still a topic of debate. In this study, we used event-related potentials (ERPs) to track the time course of the word-frequency effect. In addition, the neighborhood density effect, which is known to…

  18. Distinct and shared cognitive functions mediate event- and time-based prospective memory impairment in normal ageing

    PubMed Central

    Gonneaud, Julie; Kalpouzos, Grégoria; Bon, Laetitia; Viader, Fausto; Eustache, Francis; Desgranges, Béatrice

    2011-01-01

    Prospective memory (PM) is the ability to remember to perform an action at a specific point in the future. Regarded as multidimensional, PM involves several cognitive functions that are known to be impaired in normal aging. In the present study, we set out to investigate the cognitive correlates of PM impairment in normal aging. Manipulating cognitive load, we assessed event- and time-based PM, as well as several cognitive functions, including executive functions, working memory and retrospective episodic memory, in healthy subjects covering the entire adulthood. We found that normal aging was characterized by PM decline in all conditions and that event-based PM was more sensitive to the effects of aging than time-based PM. Whatever the conditions, PM was linked to inhibition and processing speed. However, while event-based PM was mainly mediated by binding and retrospective memory processes, time-based PM was mainly related to inhibition. The only distinction between high- and low-load PM cognitive correlates lays in an additional, but marginal, correlation between updating and the high-load PM condition. The association of distinct cognitive functions, as well as shared mechanisms with event- and time-based PM confirms that each type of PM relies on a different set of processes. PMID:21678154

  19. Language Context Effects on Interlingual Homograph Recognition: Evidence from Event-Related Potentials and Response Times in Semantic Priming.

    ERIC Educational Resources Information Center

    de Bruijn, Ellen R. A.; Dijkstra, Ton; Chwilla, Dorothee J.; Schriefers, Herbert J.

    2001-01-01

    Dutch-English bilinguals performed a generalized lexical decision task on triplets of items, responding with "yes" if all items wee correct Dutch and/or English words, and with "no" if one or ore of the items was not a word in wither language. Semantic priming effects were found in on-line response times. Event-related…

  20. Genomic Variation by Whole-Genome SNP Mapping Arrays Predicts Time-to-Event Outcome in Patients with Chronic Lymphocytic Leukemia

    PubMed Central

    Schweighofer, Carmen D.; Coombes, Kevin R.; Majewski, Tadeusz; Barron, Lynn L.; Lerner, Susan; Sargent, Rachel L.; O'Brien, Susan; Ferrajoli, Alessandra; Wierda, William G.; Czerniak, Bogdan A.; Medeiros, L. Jeffrey; Keating, Michael J.; Abruzzo, Lynne V.

    2013-01-01

    Genomic abnormalities, such as deletions in 11q22 or 17p13, are associated with poorer prognosis in patients with chronic lymphocytic leukemia (CLL). We hypothesized that unknown regions of copy number variation (CNV) affect clinical outcome and can be detected by array-based single-nucleotide polymorphism (SNP) genotyping. We compared SNP genotypes from 168 untreated patients with CLL with genotypes from 73 white HapMap controls. We identified 322 regions of recurrent CNV, 82 of which occurred significantly more often in CLL than in HapMap (CLL-specific CNV), including regions typically aberrant in CLL: deletions in 6q21, 11q22, 13q14, and 17p13 and trisomy 12. In univariate analyses, 35 of total and 11 of CLL-specific CNVs were associated with unfavorable time-to-event outcomes, including gains or losses in chromosomes 2p, 4p, 4q, 6p, 6q, 7q, 11p, 11q, and 17p. In multivariate analyses, six CNVs (ie, CLL-specific variations in 11p15.1-15.4 or 6q27) predicted time-to-treatment or overall survival independently of established markers of prognosis. Moreover, genotypic complexity (ie, the number of independent CNVs per patient) significantly predicted prognosis, with a median time-to-treatment of 64 months versus 23 months in patients with zero to one versus two or more CNVs, respectively (P = 3.3 × 10−8). In summary, a comparison of SNP genotypes from patients with CLL with HapMap controls allowed us to identify known and unknown recurrent CNVs and to determine regions and rates of CNV that predict poorer prognosis in patients with CLL. PMID:23273604

  1. Automated SVD filtering of time-frequency distribution for enhancing the SNR of microseismic/microquake events

    NASA Astrophysics Data System (ADS)

    Iqbal, Naveed; Zerguine, Azzedine; Kaka, SanLinn; Al-Shuhail, Abdullatif

    2016-12-01

    Recently, there has been a growing interest in continuous passive recording of passive microseismic experiments during reservoir fluid-injection monitoring, hydraulic-fracture monitoring and fault-movement monitoring, to name a few. The ability to accurately detect and analyze microseismic events generated by these activities is valuable in monitoring them. However, microseismic events usually have very low signal-to-noise ratio (SNR), especially when monitoring sensors (receivers) are located at the surface where coherent and non-coherent noise sources are overwhelming. Therefore, enhancing the SNR of the microseismic event will improve the localization process over the reservoir. In this study, a new method of enhancing the microseismic event is presented which relies on one trace per receiver record unlike other methods. The proposed method relies on a time-frequency representation and noise eliminating process which uses the singular-value decomposition (SVD) technique. Furthermore, the SVD is applied on the matrix representing the time-frequency decomposition of a trace. More importantly, an automated SVD filtering is proposed, so the SVD filtering becomes observation-driven instead of user-defined. Finally, it is shown that the proposed technique gives promising results with very low SNR, making it suitable to locate passive microseismic events even if the sensors are located on the surface.

  2. Timing and duration of climate variability during the 8.2 ka event reconstructed from four speleothems from Germany

    NASA Astrophysics Data System (ADS)

    Wenz, Sarah; Scholz, Denis; Spötl, Christoph; Plessen, Birgit; Mischel, Simon; Breitenbach, Sebastian F. M.; Jochum, Klaus Peter; Fohlmeister, Jens

    2016-04-01

    The most prominent climate anomaly of the Holocene is the 8.2 ka event, which reflects the impact of a dramatic freshwater influx into the North Atlantic during an interglacial climate state. Thus, it can be considered as a possible analogue for future climate change. Due to the short-lived nature of the event (160.5 ± 5.5 years; Thomas et al., 2007), a detailed investigation requires archives of both high temporal resolution and accurate chronology. We present high-resolution stable oxygen and carbon isotope (ca. 3-4 years) as well as sub-annually resolved trace element records of the 8.2 ka event from stalagmites (BB-3, Bu4, HLK2 and TV1) from three cave systems in Germany (Blessberg Cave, Bunker Cave and Herbstlabyrinth). The location of these caves in central European is well suited in order to detect changes in temperature and precipitation in relation to changes in the North Atlantic region (Fohlmeister et al., 2012). The 8.2 ka event is clearly recorded as a pronounced negative excursion in the δ18O values of all four speleothems. While stalagmites BB-3 from Blessberg Cave and Bu4 from Bunker Cave also show a negative excursion in the δ13C values during the event, the two speleothems from Herbstlabyrinth show no distinctive features in their δ13C values. The timing, duration and structure of the event differ between the individual records. In BB-3, the event occurs earlier (ca. 8.4 ka) and has a relatively short duration of ca. 90 years. In Bu4, the event occurs later (ca. 8.1 ka) and shows a relatively long duration of more than 200 years. In the two speleothems from the Herbstlabyrinth, the event is replicated and has a timing between 8.3 and 8.1 ka and a duration of ca. 150 years. These differences may at least in part be related to the dating uncertainties of 100-200 years (95 % confidence limits). References: Fohlmeister, J., Schroder-Ritzrau, A., Scholz, D., Spötl, C., Riechelmann, D.F.C., Mudelsee, M., Wackerbarth, A., Gerdes, A., Riechelmann, S

  3. Influence of lag time on event-based rainfall-runoff modeling using the data driven approach

    NASA Astrophysics Data System (ADS)

    Talei, Amin; Chua, Lloyd H. C.

    2012-05-01

    SummaryThis study investigated the effect of lag time on the performance of data-driven models, specifically the adaptive network-based fuzzy inference system (ANFIS), in event-based rainfall-runoff modeling. Rainfall and runoff data for a catchment in Singapore were chosen for this study. For the purpose of this study, lag time was determined from cross-correlation analysis of the rainfall and runoff time series. Rainfall antecedents were the only inputs of the models and direct runoff was the desired output. An ANFIS model with three sub-models defined based on three different ranges of lag times was developed. The performance of the sub-models was compared with previously developed ANFIS models and the physically-based Storm Water Management Model (SWMM). The ANFIS sub-models gave significantly superior results in terms of the RMSE, r2, CE and the prediction of the peak discharge, compared to other ANFIS models where the lag time was not considered. In addition, the ANFIS sub-models provided results that were comparable with results from SWMM. It is thus concluded that the lag time plays an important role in the selection of events for training and testing of data-driven models in event-based rainfall-runoff modeling.

  4. Palynological constraints on timing and duration of Siberian Traps volcanic events

    NASA Astrophysics Data System (ADS)

    Visscher, Henk; Svensen, Henrik; Looy, Cindy; Fristad, Kirsten; Polozov, Alexander; Planke, Sverre

    2010-05-01

    Lacustrine sediments intercalated locally in the voluminous flood basalts and pyroclastic rocks of the Siberian Traps igneous province are characterized by the presence of surprisingly diverse assemblages of macroscopic and microscopic plant fossils. In addition, these intertrappean sediments contain a wide variety of faunal remains, such as conchostracans, ostracodes, gastropods and insects. Outside the area of presently exposed flood basalt, plant fossils may also occur abundantly in the sedimentary infill of crater lakes above vent structures in the southern part of the Tunguska Basin on the Siberian Platform. Because of a possible cause-effect relationship between Siberian Traps magmatism and end-Permian mass-extinctions, vegetation that must have grown in the immediate vicinity of the eruptive centres is one of the most obvious biota to be investigated for evidence of terrestrial biosphere crisis. On the basis of literature information and new palynological data from cored crater-lake sediments, in this presentation we briefly address the basic question to what extent the Siberian plant fossil record confirms age-equivalence between biotic and volcanic events. At present, most published biostratigraphic interpretations of the floral and faunal records refute any correspondence of end-Permian biotic turnover with the Siberian Traps. In effect, the records are long since being used to advocate an exclusively Triassic age for the Siberian volcanism, the main phase of flood basalt eruption taking place during late Early Triassic (Olenekian) and early Middle Triassic (Anisian) times. However, re-evaluation of the chronostratigraphic significance of plant megafossils and faunal remains has resulted in alternative views, which suggest a Late Permian age for part or the whole of the volcanic sequence exposed on the Siberian Platform. Compositional characters of palynomorph assemblages indicate age-equivalence of the flood basalts in the northern part of the Tunguska

  5. Life in the Times of Whypox: A Virtual Epidemic as a Community Event

    NASA Astrophysics Data System (ADS)

    Kafai, Yasmin B.; Feldon, David; Fields, Deborah; Giang, Michael; Quintero, Maria

    In the past ten years, multiplayer games have increased in popularity with now millions of players spending dozens of hours or more online each week. Researchers have documented many aspects of the activities and motivations of players highlighting how players in these communities are defined by a common set of endeavors and social practices. (2003) called game communities for this reason ‘affinity' groups. Often particular practices such as avatar selling and adena farming or events such as warrior revolts and virtual elections are used to illustrate issues with community norms (Steinkuehler, 2006), ownership and freedom of expression (Taylor, 2002; 2005) in virtual worlds. With few exceptions (Cassell, Huffaker, Tversky, & Ferriman, 2006), most of these practices and events have been emergent phenomena.

  6. Beyond Visibility: the "Crucifixion Eclipse" in the Context of Some Other Astronomical Events of the Times

    NASA Astrophysics Data System (ADS)

    Gaskell, C. M.

    1993-12-01

    A variety of astronomical, biblical and other historical evidence favors Friday April 3, AD 33 as the date of the crucifixion of Jesus Christ (see Hoehner 1977, "Chronological Aspects of the Life of Christ"). There was also a partial lunar eclipse on that day. Schaefer (1990, QJRAS, 31, 53) has shown convincingly that, while technically the eclipse did occur while the moon was above the horizon in Jerusalem, this eclipse could not have been seen from Jerusalem. However there is good evidence that predictable celestial events were regarded as significant even if they were not visible because of daylight or clouds. Some specific examples will be given of celestial events which would not have been visible from the region, but which were none the less regarded as highly significant during this period. It will be argued that the significance of the lunar eclipse on the day of the crucifixion would be independent of its visibility.

  7. Late Time Monitoring of the Exceptional Tidal Disruption Event Swift J1644+57

    NASA Astrophysics Data System (ADS)

    Levan, Andrew

    2013-09-01

    The discovery of a population of relativistic tidal disruption events has opened a new window; viewing accretion around massive black holes from start to finish on short timescales, and offering a new route to probing the ubiquity of black holes in galaxies. Here we propose continued follow-up of the first, and by far best studied of the events - Swift J1644+57. Observing after the rapid switch off of the jet we will understand if the ongoing X-ray emission is due to the tidal flare itself, or if there is a faint underlying AGN. In turn, we will study the nature of the accretion and gain insights into what may have made Swift J1644+57 produce a jet. In concert with approved observations with HST and Spitzer this will create a dataset with legacy value on this rosetta stone object.

  8. Near Real-Time Event Detection & Prediction Using Intelligent Software Agents

    DTIC Science & Technology

    2006-03-01

    recognition. While domain-specific methodologies have garnered varying success levels, a general approach for this complex task has yet to be found...robust event pattern recognition. While domain-specific methodologies have garnered varying success levels, a general approach for this complex...task has yet to be found and therefore motivates this research effort. The overall research goal is to develop, test, and validate a robust generic

  9. Time Series Modeling of Army Mission Command Communication Networks: An Event-Driven Analysis

    DTIC Science & Technology

    2013-06-01

    critical events. In a detailed analysis of the email corpus of the Enron Corporation, Diesner and Carley (2005; see also Murshed et al. 2007) found that...established contacts and formal roles. The Enron crisis is instructive as a network with a critical period of failure. Other researchers have also found...Diesner, J., Frantz, T. L., & Carley, K. M. (2005). Communication networks from the Enron email corpus “It’s always about the people. Enron is no

  10. It’s always snack time: An investigation of event scripts in young children

    PubMed Central

    Musher-Eizenman, Dara R.; Marx, Jenna M.; Taylor, Maija B.

    2015-01-01

    This study examined whether young children include eating in their cognitive scripts for various events, and whether food-related scripts are associated with body mass index (BMI) percentile. Data were collected in a structured interview format. Participants, recruited from area preschools and day cares, provided a four-activity sequence for each of three events, and responses were recorded verbatim. Forty-four children (45% female) participated, with an average BMI percentile of 73.3% (SD = 25.9). Data were binarily coded to indicate whether each response was food-related. Frequencies were obtained, and responses were correlated with BMI percentile. Over 22% of the activities in the children’s scripts involved food. The number of food-related activities reported was positively correlated with children’s BMI percentile (r = 0.53, p = 0.03). Results provide preliminary evidence that food features prominently in young children’s event scripts and that children with higher BMI percentiles may possess scripts that feature more food-related themes. Future researchers should investigate the causal nature of this relationship. PMID:25447019

  11. Topics in Multivariate Approximation Theory.

    DTIC Science & Technology

    1982-05-01

    include tensor products, multivariate polynomial interpolation , esp. Kergin Interpolation , and the recent developments of multivariate B-splines. t1...AMS (MOS) Subject Classifications: 41-02, 41A05, 41A10, 41A15, 41A63, 41A65 Key Words: multivariate, B-splines, Kergin interpolation , linear projectors...splines and in multivariate polynomial interpolation . These developments may well provide the theoretical foundation for efficient methods of

  12. Event-based state estimation for a class of complex networks with time-varying delays: A comparison principle approach

    NASA Astrophysics Data System (ADS)

    Zhang, Wenbing; Wang, Zidong; Liu, Yurong; Ding, Derui; Alsaadi, Fuad E.

    2017-01-01

    The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator.

  13. Survival Outcomes and Effect of Early vs. Deferred cART Among HIV-Infected Patients Diagnosed at the Time of an AIDS-Defining Event: A Cohort Analysis

    PubMed Central

    Mussini, Cristina; Johnson, Margaret; d'Arminio Monforte, Antonella; Antinori, Andrea; Gill, M. John; Sighinolfi, Laura; Uberti-Foppa, Caterina; Borghi, Vanni; Sabin, Caroline

    2011-01-01

    Objectives We analyzed clinical progression among persons diagnosed with HIV at the time of an AIDS-defining event, and assessed the impact on outcome of timing of combined antiretroviral treatment (cART). Methods Retrospective, European and Canadian multicohort study.. Patients were diagnosed with HIV from 1997–2004 and had clinical AIDS from 30 days before to 14 days after diagnosis. Clinical progression (new AIDS event, death) was described using Kaplan-Meier analysis stratifying by type of AIDS event. Factors associated with progression were identified with multivariable Cox regression. Progression rates were compared between those starting early (<30 days after AIDS event) or deferred (30–270 days after AIDS event) cART. Results The median (interquartile range) CD4 count and viral load (VL) at diagnosis of the 584 patients were 42 (16, 119) cells/µL and 5.2 (4.5, 5.7) log10 copies/mL. Clinical progression was observed in 165 (28.3%) patients. Older age, a higher VL at diagnosis, and a diagnosis of non-Hodgkin lymphoma (NHL) (vs. other AIDS events) were independently associated with disease progression. Of 366 patients with an opportunistic infection, 178 (48.6%) received early cART. There was no significant difference in clinical progression between those initiating cART early and those deferring treatment (adjusted hazard ratio 1.32 [95% confidence interval 0.87, 2.00], p = 0.20). Conclusions Older patients and patients with high VL or NHL at diagnosis had a worse outcome. Our data suggest that earlier initiation of cART may be beneficial among HIV-infected patients diagnosed with clinical AIDS in our setting. PMID:22043301

  14. Introduction to multivariate discrimination

    NASA Astrophysics Data System (ADS)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  15. Multivariate volume rendering

    SciTech Connect

    Crawfis, R.A.

    1996-03-01

    This paper presents a new technique for representing multivalued data sets defined on an integer lattice. It extends the state-of-the-art in volume rendering to include nonhomogeneous volume representations. That is, volume rendering of materials with very fine detail (e.g. translucent granite) within a voxel. Multivariate volume rendering is achieved by introducing controlled amounts of noise within the volume representation. Varying the local amount of noise within the volume is used to represent a separate scalar variable. The technique can also be used in image synthesis to create more realistic clouds and fog.

  16. Are Jewish deathdates affected by the timing of important religious events?

    PubMed

    Lee, P; Smith, G

    2000-01-01

    Earlier studies reported a decline in September mortality in New York City and Budapest during years when Yom Kippur was in the interval September 28 through October 3, and fewer deaths among Californians with Jewish surnames during the week preceding Passover than during the week after Passover. These studies suggest that some Jews are able to postpone their deaths until after the celebration of an important religious event. We reexamine these findings using new data and find no statistically persuasive evidence that Jewish deaths decline before religious holidays. We do find an increase in deaths in the weeks shortly before and after birthdays.

  17. Expressive timing facilitates the neural processing of phrase boundaries in music: evidence from event-related potentials.

    PubMed

    Istók, Eva; Friberg, Anders; Huotilainen, Minna; Tervaniemi, Mari

    2013-01-01

    The organization of sound into meaningful units is fundamental to the processing of auditory information such as speech and music. In expressive music performance, structural units or phrases may become particularly distinguishable through subtle timing variations highlighting musical phrase boundaries. As such, expressive timing may support the successful parsing of otherwise continuous musical material. By means of the event-related potential technique (ERP), we investigated whether expressive timing modulates the neural processing of musical phrases. Musicians and laymen listened to short atonal scale-like melodies that were presented either isochronously (deadpan) or with expressive timing cues emphasizing the melodies' two-phrase structure. Melodies were presented in an active and a passive condition. Expressive timing facilitated the processing of phrase boundaries as indicated by decreased N2b amplitude and enhanced P3a amplitude for target phrase boundaries and larger P2 amplitude for non-target boundaries. When timing cues were lacking, task demands increased especially for laymen as reflected by reduced P3a amplitude. In line, the N2b occurred earlier for musicians in both conditions indicating general faster target detection compared to laymen. Importantly, the elicitation of a P3a-like response to phrase boundaries marked by a pitch leap during passive exposure suggests that expressive timing information is automatically encoded and may lead to an involuntary allocation of attention towards significant events within a melody. We conclude that subtle timing variations in music performance prepare the listener for musical key events by directing and guiding attention towards their occurrences. That is, expressive timing facilitates the structuring and parsing of continuous musical material even when the auditory input is unattended.

  18. Expressive Timing Facilitates the Neural Processing of Phrase Boundaries in Music: Evidence from Event-Related Potentials

    PubMed Central

    Istók, Eva; Friberg, Anders; Huotilainen, Minna; Tervaniemi, Mari

    2013-01-01

    The organization of sound into meaningful units is fundamental to the processing of auditory information such as speech and music. In expressive music performance, structural units or phrases may become particularly distinguishable through subtle timing variations highlighting musical phrase boundaries. As such, expressive timing may support the successful parsing of otherwise continuous musical material. By means of the event-related potential technique (ERP), we investigated whether expressive timing modulates the neural processing of musical phrases. Musicians and laymen listened to short atonal scale-like melodies that were presented either isochronously (deadpan) or with expressive timing cues emphasizing the melodies’ two-phrase structure. Melodies were presented in an active and a passive condition. Expressive timing facilitated the processing of phrase boundaries as indicated by decreased N2b amplitude and enhanced P3a amplitude for target phrase boundaries and larger P2 amplitude for non-target boundaries. When timing cues were lacking, task demands increased especially for laymen as reflected by reduced P3a amplitude. In line, the N2b occurred earlier for musicians in both conditions indicating general faster target detection compared to laymen. Importantly, the elicitation of a P3a-like response to phrase boundaries marked by a pitch leap during passive exposure suggests that expressive timing information is automatically encoded and may lead to an involuntary allocation of attention towards significant events within a melody. We conclude that subtle timing variations in music performance prepare the listener for musical key events by directing and guiding attention towards their occurrences. That is, expressive timing facilitates the structuring and parsing of continuous musical material even when the auditory input is unattended. PMID:23383088

  19. Decaplex and real-time PCR based detection of MON531 and MON15985 Bt cotton events.

    PubMed

    Randhawa, Gurinder Jit; Chhabra, Rashmi; Singh, Monika

    2010-09-22

    The genetically modified (GM) Bt crops expressing delta-endotoxins from Bacillus thuringiensis provide protection against a wide range of lepidopteron insect pests throughout the growing season of the plant. Bt cotton is the only commercialized crop in India that is planted on an area of 7.6 million hectares. With the increase in development and commercialization of transgenic crops, it is necessary to develop appropriate qualitative and quantitative methods for detection of different transgenic events. The present study reports on the development of a decaplex polymerase chain reaction (PCR) assay for simultaneous detection of transgene sequences, specific transgene constructs, and endogenous stearoyl acyl desaturase (Sad1) gene in two events of Bt cotton, i.e., MON531 and MON15985. The decaplex PCR assay is an efficient tool to identify and discriminate the two major commercialized events of Bt cotton, i.e., MON531 and MON15985, in India. Real-time PCR assays were also developed for quantification of cry1Ac and cry2Ab genes being employed in these two events. The quantitative method was developed using seven serial dilutions containing different levels of Bt cotton DNA mixed with a non-Bt counterpart ranging from 0.01 to 100%. The results revealed that the biases from the true value and the relative standard deviations were all within the range of ±20%. The limit of quantification (LOQ) of the developed real-time PCR method has also been established up to 0.01%.

  20. Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

    NASA Technical Reports Server (NTRS)

    Martin, Rodney Alexander; Das, Santanu

    2010-01-01

    The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

  1. Storm-Time Substorms and Sawtooth Events: Test for Substorm Models

    NASA Astrophysics Data System (ADS)

    Pulkkinen, T. I.; Tanskanen, E. I.; Reeves, G. D.; Donovan, E.; Singer, H. J.; Slavin, J. A.

    2005-12-01

    A substorm search engine is used to identify substorm onsets that occur during magnetic storms in the period 2001-2004. Each substorm is analyzed in detail using several parameters to classify the events. Peak amplitude of the substorm is defined from the AL-index. Existence and type of energetic particle injections are determined from the LANL energetic ion and electron data. Tail magnetic field measurements (GOES, Cluster, Geotail) are used to infer whether a thin current sheet was formed prior to the substorm onset. Latitudinal magnetometer chains (CANOPUS, IMAGE) are used to determine whether the main expansion direction was poleward or equatorward. Possible triggers for the onset and intensity of the driving electric field are identified from the solar wind and interplanetary magnetic field measurements (ACE, WIND). The goal of the study is to statistically examine to what extent the stormtime substorms show signatures typically associated classical non-storm substorms and to what extent the activity is characteristic only of storm periods. Furthermore, the goal is to identify the "sawtooth events" from the data set, and examine whether the activation characteristics differ from the other stormtime activations.

  2. Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.

    PubMed

    Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R

    2017-01-01

    Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

  3. Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

    PubMed Central

    Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

    2017-01-01

    Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

  4. The 2009-2010 Guerrero Slow Slip Event Monitored by InSAR, Using Time Series Approach

    NASA Astrophysics Data System (ADS)

    Bacques, G.; Pathier, E.; Lasserre, C.; Cotton, F.; Radiguet, M.; Cycle Sismique et Déformations Transitoires

    2011-12-01

    Time Series approach. Time Series approach is useful for monitoring ground deformation evolution during the slow slip events and makes the slip propagation mapping upon the subduction plane a promising goal. Here we present our first results concerning the 2009-2010 slow slip events, particularly the distribution of the cumulative surface displacement in LOS (satellite Line Of Sight), the slip distribution associated on the fault plane and the ground deformation evolution obtained. Finally, we open the discussion with a first comparison between the 2009-2010 and the 2006 events that reveal some differences concerning the amplitude and the distribution of the ground deformation.

  5. Time-varying autoregressive model for spectral analysis of microseismic experiments and long-period volcanic events

    NASA Astrophysics Data System (ADS)

    Tary, J. B.; Herrera, R. H.; van der Baan, M.

    2014-01-01

    Recent studies show that the frequency content of continuous passive recordings contains useful information for the study of hydraulic fracturing experiments as well as longstanding applications in volcano and global seismology. The short-time Fourier transform (STFT) is usually used to obtain the time-frequency representation of a seismic trace. Yet, this transform has two main disadvantages, namely its fixed time-frequency resolution and spectral leakage. Here, we describe two methods based on autoregressive (AR) models: the short-time autoregressive method (ST-AR) and the Kalman smoother (KS). These two methods allow for the AR coefficients to vary over time in order to follow time-varying frequency contents. The outcome of AR methods depends mainly on the number of AR coefficients. We use a robust approach to estimate the optimum order of the AR methods that best matches the spectral comparison between Fourier and AR spectra. Comparing the outcomes of the three methods on a synthetic signal, a long-period volcanic event, and microseismic data, we show that the STFT and both AR methods are able to track fast changes in frequency content. The STFT provides reasonable results even for noisy data using a simple and effective algorithm. The coefficients of the AR filter are defined at all time in the case of the KS. However, its better time resolution is slightly offset by a lower frequency resolution and its computational complexity. The ST-AR has a high spectral resolution and the lowest sensitivity to background noises, facilitating the identification of the various frequency components. The estimated AR coefficients can also be used to extract parts of the signal. The study of long-term phenomena, such as resonance frequencies, or transient events, such as long-period events, could help to gain further insight on reservoir deformation during hydraulic fracturing experiments as well as global or volcano seismological signals.

  6. Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data.

    PubMed

    Yuen, Hok Pan; Mackinnon, Andrew

    2016-01-01

    Joint modelling has emerged to be a potential tool to analyse data with a time-to-event outcome and longitudinal measurements collected over a series of time points. Joint modelling involves the simultaneous modelling of the two components, namely the time-to-event component and the longitudinal component. The main challenges of joint modelling are the mathematical and computational complexity. Recent advances in joint modelling have seen the emergence of several software packages which have implemented some of the computational requirements to run joint models. These packages have opened the door for more routine use of joint modelling. Through simulations and real data based on transition to psychosis research, we compared joint model analysis of time-to-event outcome with the conventional Cox regression analysis. We also compared a number of packages for fitting joint models. Our results suggest that joint modelling do have advantages over conventional analysis despite its potential complexity. Our results also suggest that the results of analyses may depend on how the methodology is implemented.

  7. Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data

    PubMed Central

    2016-01-01

    Joint modelling has emerged to be a potential tool to analyse data with a time-to-event outcome and longitudinal measurements collected over a series of time points. Joint modelling involves the simultaneous modelling of the two components, namely the time-to-event component and the longitudinal component. The main challenges of joint modelling are the mathematical and computational complexity. Recent advances in joint modelling have seen the emergence of several software packages which have implemented some of the computational requirements to run joint models. These packages have opened the door for more routine use of joint modelling. Through simulations and real data based on transition to psychosis research, we compared joint model analysis of time-to-event outcome with the conventional Cox regression analysis. We also compared a number of packages for fitting joint models. Our results suggest that joint modelling do have advantages over conventional analysis despite its potential complexity. Our results also suggest that the results of analyses may depend on how the methodology is implemented. PMID:27781169

  8. A model-based fault-detection and prediction scheme for nonlinear multivariable discrete-time systems with asymptotic stability guarantees.

    PubMed

    Thumati, Balaje T; Jagannathan, S

    2010-03-01

    In this paper, a novel, unified model-based fault-detection and prediction (FDP) scheme is developed for nonlinear multiple-input-multiple-output (MIMO) discrete-time systems. The proposed scheme addresses both state and output faults by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output signals of the system. The fault-detection (FD) scheme comprises online approximator in discrete time (OLAD) with a robust adaptive term. An output residual is generated by comparing the FD estimator output with that of the measured system output. A fault is detected when this output residual exceeds a predefined threshold. Upon detecting the fault, the robust adaptive terms and the OLADs are initiated wherein the OLAD approximates the unknown fault dynamics online while the robust adaptive terms help in ensuring asymptotic stability of the FD design. Using the OLAD outputs, a fault diagnosis scheme is introduced. A stable parameter update law is developed not only to tune the OLAD parameters but also to estimate the time to failure (TTF), which is considered as a first step for prognostics. The asymptotic stability of the FDP scheme enhances the detection and TTF accuracy. The effectiveness of the proposed approach is demonstrated using a fourth-order MIMO satellite system.

  9. Importance of long-time simulations for rare event sampling in zinc finger proteins.

    PubMed

    Godwin, Ryan; Gmeiner, William; Salsbury, Freddie R

    2016-01-01

    Molecular dynamics (MD) simulation methods have seen significant improvement since their inception in the late 1950s. Constraints of simulation size and duration that once impeded the field have lessened with the advent of better algorithms, faster processors, and parallel computing. With newer techniques and hardware available, MD simulations of more biologically relevant timescales can now sample a broader range of conformational and dynamical changes including rare events. One concern in the literature has been under which circumstances it is sufficient to perform many shorter timescale simulations and under which circumstances fewer longer simulations are necessary. Herein, our simulations of the zinc finger NEMO (2JVX) using multiple simulations of length 15, 30, 1000, and 3000 ns are analyzed to provide clarity on this point.