DEFF Research Database (Denmark)
Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae
We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on re...
Liu, Minling; Li, Lixian; Yu, Wei; Chen, Jie; Xiong, Weibin; Chen, Shuang; Yu, Li
2017-03-21
It has been well recognized that the effects of many prognostic factors could change during long-term follow-up. Although marriage has been proven to be a significant prognostic factor for the survival of colon cancer, whether the effect of marriage is constant with time remain unknown. This study analyzed the impact of marital status on the mortality of colon cancer patients with an extended Cox model that allowed for time-varying effects. We identified 71,955 patients who underwent colectomy between 2004 and 2009 to treat colon adenocarcinoma from the Surveilance, Epidemiology and End Results Database. The multivariate extended Cox model was used to evaluate the effect of marital status on all-cause mortality, while the Fine-Gray competing risks model was used for colon cancer-specific mortality, with death from other causes as the competing risk. The unmarried patients carried a 1.37-fold increased risk of all-cause mortality compared with the married patients (95%CI: 1.33-1.40; pMarriage is a dependent prognosis factor for survival of surgically treated colon adenocarcinoma patients. Psychological interventions are suggested to improve receipt of treatment among unmarried patients, as their poor survival may be due to the inefficient treatment.
Testing for time-varying loadings in dynamic factor models
DEFF Research Database (Denmark)
Mikkelsen, Jakob Guldbæk
Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....
Time-varying risk aversion. An application to energy hedging
Energy Technology Data Exchange (ETDEWEB)
Cotter, John [Centre for Financial Markets, School of Business, University College Dublin, Blackrock, Co. Dublin (Ireland); Hanly, Jim [School of Accounting and Finance, Dublin Institute of Technology, Dublin 2 (Ireland)
2010-03-15
Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)
Time-varying risk aversion. An application to energy hedging
International Nuclear Information System (INIS)
Cotter, John; Hanly, Jim
2010-01-01
Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)
Endogenous time-varying risk aversion and asset returns.
Berardi, Michele
2016-01-01
Stylized facts about statistical properties for short horizon returns in financial markets have been identified in the literature, but a satisfactory understanding for their manifestation is yet to be achieved. In this work, we show that a simple asset pricing model with representative agent is able to generate time series of returns that replicate such stylized facts if the risk aversion coefficient is allowed to change endogenously over time in response to unexpected excess returns under evolutionary forces. The same model, under constant risk aversion, would instead generate returns that are essentially Gaussian. We conclude that an endogenous time-varying risk aversion represents a very parsimonious way to make the model match real data on key statistical properties, and therefore deserves careful consideration from economists and practitioners alike.
On the Anonymity Risk of Time-Varying User Profiles
Directory of Open Access Journals (Sweden)
Silvia Puglisi
2017-04-01
Full Text Available Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some online resource, new information is added to the user profile. Exposing private data does not only reveal information about single users’ preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident in social networks where users receive suggestions based on their friends’ activities. We propose an information-theoretic approach to measure the differential update of the anonymity risk of time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third-party services get to know about the users when a new activity is shared. We use actual Facebook data to show how our model can be applied to a real-world scenario.
Optimal International Asset Allocation with Time-varying Risk
Flavin, Thomas; Wickens, M.R.
2006-01-01
This paper examines the optimal allocation each period of an internationally diversified portfolio from the different points of view of a UK and a US investor. We find that investor location affects optimal asset allocation. The presence of exchange rate risk causes the markets to appear not fully integrated and creates a preference for home assets. Domestic equity is the dominant asset in the optimal portfolio for both investors, but the US investor bears less risk than the UK...
The estimation of time-varying risks in asset pricing modelling using B-Spline method
Nurjannah; Solimun; Rinaldo, Adji
2017-12-01
Asset pricing modelling has been extensively studied in the past few decades to explore the risk-return relationship. The asset pricing literature typically assumed a static risk-return relationship. However, several studies found few anomalies in the asset pricing modelling which captured the presence of the risk instability. The dynamic model is proposed to offer a better model. The main problem highlighted in the dynamic model literature is that the set of conditioning information is unobservable and therefore some assumptions have to be made. Hence, the estimation requires additional assumptions about the dynamics of risk. To overcome this problem, the nonparametric estimators can also be used as an alternative for estimating risk. The flexibility of the nonparametric setting avoids the problem of misspecification derived from selecting a functional form. This paper investigates the estimation of time-varying asset pricing model using B-Spline, as one of nonparametric approach. The advantages of spline method is its computational speed and simplicity, as well as the clarity of controlling curvature directly. The three popular asset pricing models will be investigated namely CAPM (Capital Asset Pricing Model), Fama-French 3-factors model and Carhart 4-factors model. The results suggest that the estimated risks are time-varying and not stable overtime which confirms the risk instability anomaly. The results is more pronounced in Carhart’s 4-factors model.
Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California
Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.
2016-12-01
Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.
A New Time-varying Concept of Risk in a Changing Climate.
Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P
2016-10-20
In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.
A New Time-varying Concept of Risk in a Changing Climate
Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P.
2016-10-01
In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.
Unbiasedness and time varying risk premia in the crude oil futures market
International Nuclear Information System (INIS)
Moosa, I.A.; Al-Loughani, N.E.
1994-01-01
This paper presents some empirical evidence on market efficiency and unbiasedness in the crude oil futures market and some related issues. On the basis of monthly observations on spot and futures prices of the West Texas Intermediate (WTI) crude oil, several tests are carried out on the relevant hypotheses. The evidence suggests that futures prices are neither unbiased nor efficient forecasters of spot prices. Furthermore, a GARCH-M(1,1) model reveals the existence of a time varying risk premium. (author)
Projective synchronization of time-varying delayed neural network with adaptive scaling factors
International Nuclear Information System (INIS)
Ghosh, Dibakar; Banerjee, Santo
2013-01-01
Highlights: • Projective synchronization in coupled delayed neural chaotic systems with modulated delay time is introduced. • An adaptive rule for the scaling factors is introduced. • This scheme is highly applicable in secure communication. -- Abstract: In this work, the projective synchronization between two continuous time delayed neural systems with time varying delay is investigated. A sufficient condition for synchronization for the coupled systems with modulated delay is presented analytically with the help of the Krasovskii–Lyapunov approach. The effect of adaptive scaling factors on synchronization are also studied in details. Numerical simulations verify the effectiveness of the analytic results
Control of the tokamak safety factor profile with time-varying constraints using MPC
International Nuclear Information System (INIS)
Maljaars, E.; Felici, F.; De Baar, M.R.; Geelen, P.J.M.; Steinbuch, M.; Van Dongen, J.; Hogeweij, G.M.D.
2015-01-01
A controller is designed for the tokamak safety factor profile that takes real-time-varying operational and physics limits into account. This so-called model predictive controller (MPC) employs a prediction model in order to compute optimal control inputs that satisfy the given limits. The use of linearized models around a reference trajectory results in a quadratic programming problem that can easily be solved online. The performance of the controller is analysed in a set of ITER L-mode scenarios simulated with the non-linear plasma transport code RAPTOR. It is shown that the controller can reduce the tracking error due to an overestimation or underestimation of the modelled transport, while making a trade-off between residual error and amount of controller action. It is also shown that the controller can account for a sudden decrease in the available actuator power, while providing warnings ahead of time about expected violations of operational and physics limits. This controller can be extended and implemented in existing tokamaks in the near future. (paper)
Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.
Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod
2017-07-15
There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal
Directory of Open Access Journals (Sweden)
Lingyun Li
2013-01-01
Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.
Optimal Consumption and Investment under Time-Varying Relative Risk Aversion
DEFF Research Database (Denmark)
Steffensen, Mogens
2011-01-01
We consider the continuous time consumption-investment problem originally formalized and solved by Merton in case of constant relative risk aversion. We present a complete solution for the case where relative risk aversion with respect to consumption varies with time, having in mind an investor...... with age-dependent risk aversion. This provides a new motivation for life-cycle investment rules. We study the optimal consumption and investment rules, in particular in the case where the relative risk aversion with respect to consumption is increasing with age....
Time-varying betas and Cross-Sectional Return-Risk Relation: Evidence from the UK
Fraser, P; MacGregor, B.; Hoesli, M.; Hamelink, F.
2004-01-01
The seminal study by Fama and MacBeth in 1973 initiated a stream of papers testing for the cross-sectional relation between return and risk. The debate as to whether beta is a valid measure of risk was reanimated by Fama and French and subsequent studies. Rather than focusing on exogenous variables
Time-varying disaster risk models: An empirical assessment of the Rietz-Barro hypothesis
DEFF Research Database (Denmark)
Irarrazabal, Alfonso; Parra-Alvarez, Juan Carlos
This paper revisits the fit of disaster risk models where a representative agent has recursive preferences and the probability of a macroeconomic disaster changes over time. We calibrate the model as in Wachter (2013) and perform two sets of tests to assess the empirical performance of the model ...... and hence to reduce the Sharpe Ratio, a lower elasticity of substitution generates a more reasonable level for the equity risk premium and for the volatility of the government bond returns without compromising the ability of the price-dividend ratio to predict excess returns....
Time-varying individual risk attitudes over the Great Recession: A comparison of Germany and Ukraine
Dohmen, T.J.; Lehmann, H.; Pignatti, N.
We use the panel data of the German Socio-Economic Panel (SOEP) and of the Ukrainian Longitudinal Monitoring Survey (ULMS) to investigate whether risk attitudes have primary (exogenous) determinants that are valid in different stages of economic development and in a different structural context,
Shi, Wei; Xia, Jun
2017-02-01
Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.
Andrew Worthington; Helen Higgs
2005-01-01
This paper examines market risk in four demutualised and self-listed stock exchanges: the Australian Stock Exchange, the Deutsche Börse, the London Stock Exchange and the Singapore Stock Exchange. Daily company and MSCI index returns provide the respective asset and market portfolio data. A bivariate MA-GARCH model is used to estimate time-varying betas for each exchange from listing until 7 June 2005. While the results indicate significant beta volatility, unit root tests show the betas to b...
Terry-McElrath, Yvonne M; O'Malley, Patrick M; Patrick, Megan E; Miech, Richard A
2017-11-01
Perceived risk of harm has long been a key preventive factor for adolescent marijuana use. However, in recent years, perceived risk has decreased markedly and marijuana use has increased only slightly, leading to new questions about their association. This study investigates the magnitude and stability of the US adolescent marijuana risk/use association from 1991 to 2016, overall and by gender and race/ethnicity. Self-reported data on past 12-month marijuana use, perceived risk of regular marijuana use, gender, and race/ethnicity were obtained from 275,768 US 12th grade students participating in the nationally representative Monitoring the Future study. Time-varying effect modeling (TVEM) was used to examine the marijuana risk/use association over time. Both before and after controlling for gender and race/ethnicity, perceived risk was a strong protective factor against adolescent marijuana use. The magnitude of the great risk/use association strengthened for Hispanic students; remained generally stable over time for 12th graders overall, males, females, and White students; and weakened for Black students. The magnitude of the moderate risk/use association strengthened for 12th graders overall, males, females, White and Hispanic students, but did not continue to strengthen for Black students from 2005 onwards. In general, marijuana use prevalence decreased over time within all levels of perceived risk. Perceived risk remains a strong protective factor for adolescent marijuana use, and the protective association for moderate risk (vs. no/slight risk) is actually increasing over time. Results suggest that accurate and credible information on the risks associated with marijuana use should remain a key component of prevention efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.
Time-varying causal network of the Korean financial system based on firm-specific risk premiums
Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin
2016-09-01
The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.
The Volatility of Long-term Bond Returns: Persistent Interest Shocks and Time-varying Risk Premiums
DEFF Research Database (Denmark)
Osterrieder, Daniela; Schotman, Peter C.
We develop a model that can match two stylized facts of the term-structure. The first stylized fact is the predictability of excess returns on long-term bonds. Modeling this requires sufficient volatility and persistence in the price of risk. The second stylized fact is that long-term yields...... are dominated by a level factor, which requires persistence in the spot interest rate. We find that a fractionally integrated process for the short rate plus a fractionally integrated specification for the price of risk leads to an analytically tractable almost affine term structure model that can explain...... the stylized facts. In a decomposition of long-term bond returns we find that the expectations component from the level factor is more volatile than the returns themselves. It therefore takes a volatile risk premium that is negatively correlated with innovations in the level factor to explain the volatility...
de Jong, Roy G; Burden, Andrea M; de Kort, Sander; van Herk-Sukel, Myrthe P; Vissers, Pauline A; Janssen, Paddy K; Haak, Harm R; Masclee, Ad A; de Vries, Frank; Janssen-Heijnen, Maryska L
2017-01-01
Previous studies on metformin use and gastrointestinal (GI) cancer risk have yielded inconclusive results on metformin's chemoprotective effects. We aimed to evaluate GI cancer risk in users of metformin in The Netherlands using a time-varying approach in a large population-based database. A cohort
Sun, Bo; Sunkavalli, Kalyan; Ramamoorthi, Ravi; Belhumeur, Peter N; Nayar, Shree K
2007-01-01
The properties of virtually all real-world materials change with time, causing their bidirectional reflectance distribution functions (BRDFs) to be time varying. However, none of the existing BRDF models and databases take time variation into consideration; they represent the appearance of a material at a single time instance. In this paper, we address the acquisition, analysis, modeling, and rendering of a wide range of time-varying BRDFs (TVBRDFs). We have developed an acquisition system that is capable of sampling a material's BRDF at multiple time instances, with each time sample acquired within 36 sec. We have used this acquisition system to measure the BRDFs of a wide range of time-varying phenomena, which include the drying of various types of paints (watercolor, spray, and oil), the drying of wet rough surfaces (cement, plaster, and fabrics), the accumulation of dusts (household and joint compound) on surfaces, and the melting of materials (chocolate). Analytic BRDF functions are fit to these measurements and the model parameters' variations with time are analyzed. Each category exhibits interesting and sometimes nonintuitive parameter trends. These parameter trends are then used to develop analytic TVBRDF models. The analytic TVBRDF models enable us to apply effects such as paint drying and dust accumulation to arbitrary surfaces and novel materials.
Wang, Molin; Liao, Xiaomei; Laden, Francine; Spiegelman, Donna
2016-06-15
Identification of the latency period and age-related susceptibility, if any, is an important aspect of assessing risks of environmental, nutritional, and occupational exposures. We consider estimation and inference for latency and age-related susceptibility in relative risk and excess risk models. We focus on likelihood-based methods for point and interval estimation of the latency period and age-related windows of susceptibility coupled with several commonly considered exposure metrics. The method is illustrated in a study of the timing of the effects of constituents of air pollution on mortality in the Nurses' Health Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Wang, Molin; Liao, Xiaomei; Laden, Francine; Spiegelman, Donna
2016-01-01
Identification of the latency period and age-related susceptibility, if any, is an important aspect of assessing risks of environmental, nutritional and occupational exposures. We consider estimation and inference for latency and age-related susceptibility in relative risk and excess risk models. We focus on likelihood-based methods for point and interval estimation of the latency period and age-related windows of susceptibility coupled with several commonly considered exposure metrics. The method is illustrated in a study of the timing of the effects of constituents of air pollution on mortality in the Nurses’ Health Study. PMID:26750582
Directory of Open Access Journals (Sweden)
Simoens Frederik
2006-01-01
Full Text Available This paper concerns channel tracking in a multiantenna context for correlated flat-fading channels obeying a Gauss-Markov model. It is known that data-aided tracking of fast-fading channels requires a lot of pilot symbols in order to achieve sufficient accuracy, and hence decreases the spectral efficiency. To overcome this problem, we design a code-aided estimation scheme which exploits information from both the pilot symbols and the unknown coded data symbols. The algorithm is derived based on a factor graph representation of the system and application of the sum-product algorithm. The sum-product algorithm reveals how soft information from the decoder should be exploited for the purpose of estimation and how the information bits can be detected. Simulation results illustrate the effectiveness of our approach.
Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H
2016-03-01
Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and the risk of hip fracture. A cohort of patients with a first prescription for antidepressants (SSRI or tricyclic antidepressants) was extracted from the Dutch Mondriaan and Spanish Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP) general practice databases for the period 2001-2009. The net (total) effect of SSRI versus no SSRI on the risk of hip fracture was estimated using time-varying Cox regression, stratification and covariate adjustment using the PS, and MSM. In MSM, censoring was accounted for by inverse probability of censoring weights. The crude hazard ratio (HR) of SSRI use versus no SSRI use on hip fracture was 1.75 (95%CI: 1.12, 2.72) in Mondriaan and 2.09 (1.89, 2.32) in BIFAP. After confounding adjustment using time-varying Cox regression, stratification, and covariate adjustment using the PS, HRs increased in Mondriaan [2.59 (1.63, 4.12), 2.64 (1.63, 4.25), and 2.82 (1.63, 4.25), respectively] and decreased in BIFAP [1.56 (1.40, 1.73), 1.54 (1.39, 1.71), and 1.61 (1.45, 1.78), respectively]. MSMs with stabilized weights yielded HR 2.15 (1.30, 3.55) in Mondriaan and 1.63 (1.28, 2.07) in BIFAP when accounting for censoring and 2.13 (1.32, 3.45) in Mondriaan and 1.66 (1.30, 2.12) in BIFAP without accounting for censoring. In this empirical study, differences between the different methods to control for time-dependent confounding were small. The observed differences in treatment effect estimates between the databases are likely attributable to different confounding information in the datasets, illustrating that adequate information on (time-varying) confounding is crucial to prevent bias. Copyright © 2016 John Wiley & Sons, Ltd.
Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H
2016-01-01
BACKGROUND: Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and
Time varying determinants of bond flows to emerging markets
Directory of Open Access Journals (Sweden)
Yasemin Erduman
2016-06-01
Full Text Available This paper investigates the time varying nature of the determinants of bond flows with a focus on the global financial crisis period. We estimate a time varying regression model using Bayesian estimation methods, where the posterior distribution is approximated by Gibbs sampling algorithm. Our findings suggest that the interest rate differential is the most significant pull factor of portfolio bond flows, along with the inflation rate, while the growth rate does not play a significant role. Among the push factors, global liquidity is the most important driver of bond flows. It matters the most, when unconventional monetary easing policies were first announced; and its importance as a determinant of portfolio bond flows decreases over time, starting with the Eurozone crisis, and diminishes with the tapering talk. Global risk appetite and the risk perception towards the emerging countries also have relatively small and stable significant effects on bond flows.
... cells do not invade nearby tissues or spread. Risk Factors Key Points Factors That are Known to ... chemicals . Factors That are Known to Increase the Risk of Cancer Cigarette Smoking and Tobacco Use Tobacco ...
Multivariate time-varying volatility modeling using probabilistic fuzzy systems
Basturk, N.; Almeida, R.J.; Golan, R.; Kaymak, U.
2016-01-01
Methods to accurately analyze financial risk have drawn considerable attention in financial institutions. One difficulty in financial risk analysis is the fact that banks and other financial institutions invest in several assets which show time-varying volatilities and hence time-varying financial
International Nuclear Information System (INIS)
Dennery, M.; Dupont, M.A.
2007-01-01
This article deals with the development of risk management in the gas sector business: why a risk factor legal mention must precede any published financial information? Do gas companies have to face new risks? Is there specific risks bound to gas activities? Why companies want to master their risks? Is it mandatory or just a new habit? Do they expect a real benefit in return? These are the risk management questions that are analyzed in this article which is based on the public communication of 15 gas companies randomly selected over the world. The information comes from their annual reports or from documents available on their web sites. The intention of this document is not to be exhaustive or to make statistics but only to shade light on the risk factors of the gas sector. (J.S.)
Pemodelan Markov Switching Dengan Time-varying Transition Probability
Savitri, Anggita Puri; Warsito, Budi; Rahmawati, Rita
2016-01-01
Exchange rate or currency is an economic variable which reflects country's state of economy. It fluctuates over time because of its ability to switch the condition or regime caused by economic and political factors. The changes in the exchange rate are depreciation and appreciation. Therefore, it could be modeled using Markov Switching with Time-Varying Transition Probability which observe the conditional changes and use information variable. From this model, time-varying transition probabili...
Time Varying Market Integration and Expected Rteurns in Emerging Markets
de Jong, F.C.J.M.; de Roon, F.A.
2001-01-01
We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value
A time-varying magnetic flux concentrator
International Nuclear Information System (INIS)
Kibret, B; Premaratne, M; Lewis, P M; Thomson, R; Fitzgerald, P B
2016-01-01
It is known that diverse technological applications require the use of focused magnetic fields. This has driven the quest for controlling the magnetic field. Recently, the principles in transformation optics and metamaterials have allowed the realization of practical static magnetic flux concentrators. Extending such progress, here, we propose a time-varying magnetic flux concentrator cylindrical shell that uses electric conductors and ferromagnetic materials to guide magnetic flux to its center. Its performance is discussed based on finite-element simulation results. Our proposed design has potential applications in magnetic sensors, medical devices, wireless power transfer, and near-field wireless communications. (paper)
Heart disease - prevention; CVD - risk factors; Cardiovascular disease - risk factors; Coronary artery disease - risk factors; CAD - risk ... a certain health condition. Some risk factors for heart disease you cannot change, but some you can. ...
Time-Varying Periodicity in Intraday Volatility
DEFF Research Database (Denmark)
Andersen, Torben Gustav; Thyrsgaard, Martin; Todorov, Viktor
We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined...... with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across...... with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility...
Flexible time-varying filter banks
Tuncer, Temel E.; Nguyen, Truong Q.
1993-09-01
Linear phase maximally flat FIR Butterworth filter approximations are discussed and a new filter design method is introduced. This variable cutoff filter design method uses the cosine modulated versions of a prototype filter. The design procedure is simple and different variants of this procedure can be used to obtain close to optimum linear phase filters. Using this method, flexible time-varying filter banks with good reconstruction error are introduced. These types of oversampled filter banks have small magnitude error which can be easily controlled by the appropriate choice of modulation frequency. This error can be further decreased by magnitude equalization without increasing the computational complexity considerably. Two dimensional design examples are also given.
Time varying, multivariate volume data reduction
Energy Technology Data Exchange (ETDEWEB)
Ahrens, James P [Los Alamos National Laboratory; Fout, Nathaniel [UC DAVIS; Ma, Kwan - Liu [UC DAVIS
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
Robbins, Catherine J; Connors, K C; Sheehan, Timothy J; Vaughan, James S
2005-06-01
Minimize surprises on your financial statement by adopting a model for integrated risk management that: Examines interrelationships among operations, investments, and financing. Incorporates concepts of the capital asset pricing model to manage unexpected volatility
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
TIME-VARYING DYNAMICAL STAR FORMATION RATE
Energy Technology Data Exchange (ETDEWEB)
Lee, Eve J.; Chang, Philip; Murray, Norman, E-mail: evelee@berkeley.edu [Canadian Institute for Theoretical Astrophysics, 60 St. George Street, University of Toronto, Toronto, ON M5S 3H8 (Canada)
2015-02-10
We present numerical evidence of dynamic star formation in which the accreted stellar mass grows superlinearly with time, roughly as t {sup 2}. We perform simulations of star formation in self-gravitating hydrodynamic and magnetohydrodynamic turbulence that is continuously driven. By turning the self-gravity of the gas in the simulations on or off, we demonstrate that self-gravity is the dominant physical effect setting the mass accretion rate at early times before feedback effects take over, contrary to theories of turbulence-regulated star formation. We find that gravitational collapse steepens the density profile around stars, generating the power-law tail on what is otherwise a lognormal density probability distribution function. Furthermore, we find turbulent velocity profiles to flatten inside collapsing regions, altering the size-line width relation. This local flattening reflects enhancements of turbulent velocity on small scales, as verified by changes to the velocity power spectra. Our results indicate that gas self-gravity dynamically alters both density and velocity structures in clouds, giving rise to a time-varying star formation rate. We find that a substantial fraction of the gas that forms stars arrives via low-density flows, as opposed to accreting through high-density filaments.
Tracking time-varying coefficient-functions
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Joensen, Alfred K.
2000-01-01
is a combination of recursive least squares with exponential forgetting and local polynomial regression. It is argued, that it is appropriate to let the forgetting factor vary with the value of the external signal which is the argument of the coefficient functions. Some of the key properties of the modified method...... are studied by simulation...
... You are here: Home For Patients Risk Factors Risk Factors for Scleroderma The cause of scleroderma is ... what biological factors contribute to scleroderma pathogenesis. Genetic Risk Scleroderma does not tend to run in families ...
... Resources Risk Factors & Prevention Back to Patient Resources Risk Factors & Prevention Even people who look healthy and ... Blood Pressure , high cholesterol, diabetes, and thyroid disease. Risk Factors For Arrhythmias and Heart Disease The following ...
Time Varying Market Integration and Expected Rteurns in Emerging Markets
Jong, F.C.J.M. de; Roon, F.A. de
2001-01-01
We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value of the assets that can be held by domestic investors only versus the market value of the assets that can be traded freely.Our empirical analysis for 30 emerging markets shows that there are strong...
One-dimensional radionuclide transport under time-varying conditions
International Nuclear Information System (INIS)
Gelbard, F.; Olague, N.E.; Longsine, D.E.
1990-01-01
This paper discusses new analytical and numerical solutions presented for one-dimensional radionuclide transport under time-varying fluid-flow conditions including radioactive decay. The analytical solution assumes that all radionuclides have identical retardation factors, and is limited to instantaneous releases. The numerical solution does not have these limitations, but is tested against the limiting case given for the analytical solution. Reasonable agreement between the two solutions was found. Examples are given for the transport of a three-member radionuclide chain transported over distances and flow rates comparable to those reported for Yucca Mountain, the proposed disposal site for high-level nuclear waste
Multivariate Option Pricing with Time Varying Volatility and Correlations
DEFF Research Database (Denmark)
Rombouts, Jeroen V.K.; Stentoft, Lars Peter
In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk...... neutral dynamics for a general class of multivariate heteroskedastic models, and we provide a feasible way to price options in this framework. Our framework can be used irrespective of the assumed underlying distribution and dynamics, and it nests several important special cases. We provide an application...... to options on the minimum of two indices. Our results show that not only is correlation important for these options but so is allowing this correlation to be dynamic. Moreover, we show that for the general model exposure to correlation risk carries an important premium, and when this is neglected option...
Time-varying value of electric energy efficiency
Energy Technology Data Exchange (ETDEWEB)
Mims, Natalie A.; Eckman, Tom; Goldman, Charles
2017-06-30
Electric energy efficiency resources save energy and may reduce peak demand. Historically, quantification of energy efficiency benefits has largely focused on the economic value of energy savings during the first year and lifetime of the installed measures. Due in part to the lack of publicly available research on end-use load shapes (i.e., the hourly or seasonal timing of electricity savings) and energy savings shapes, consideration of the impact of energy efficiency on peak demand reduction (i.e., capacity savings) has been more limited. End-use load research and the hourly valuation of efficiency savings are used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity and demand response planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service. This study reviews existing literature on the time-varying value of energy efficiency savings, provides examples in four geographically diverse locations of how consideration of the time-varying value of efficiency savings impacts the calculation of power system benefits, and identifies future research needs to enhance the consideration of the time-varying value of energy efficiency in cost-effectiveness screening analysis. Findings from this study include: -The time-varying value of individual energy efficiency measures varies across the locations studied because of the physical and operational characteristics of the individual utility system (e.g., summer or winter peaking, load factor, reserve margin) as well as the time periods during which savings from measures occur. -Across the four locations studied, some of the largest capacity benefits from energy efficiency are derived from the deferral of transmission and distribution system infrastructure upgrades. However, the deferred cost of such upgrades also exhibited the greatest range
Decker, A. J.
1982-01-01
The use of a Nd:YAG laser to record holographic motion pictures of time-varying reflecting objects and time-varying phase objects is discussed. Sample frames from both types of holographic motion pictures are presented. The holographic system discussed is intended for three-dimensional flow visualization of the time-varying flows that occur in jet-engine components.
Flexible Demand Management under Time-Varying Prices
Liang, Yong
optimization problem when the objective is to minimize the expected total cost and discomfort, then since the decision maker is likely to be risk-averse, and she wants to protect herself from price spikes, we study the robust optimization problem to address the risk-aversion of the decision maker. We conduct numerical studies to evaluate the price of robustness. Next, we present a detailed model that manages multiple types of flexible demand in the absence of knowledge regarding the distributions of related stochastic processes. Specifically, we consider the case in which time-varying prices with general structures are offered to users, and an energy management system for each household makes optimal energy usage, storage, and trading decisions according to the preferences of users. Because of the uncertainties associated with electricity prices, local generation, and the arrival processes of demand, we formulate a stochastic dynamic programming model, and outline a novel and tractable ADP approach to overcome the curses of dimensionality. Then, we perform numerical studies, whose results demonstrate the effectiveness of the ADP approach. At last, we propose another approximation approach based on Q-learning. In addition, we also develop another decentralization-based heuristic. Both the Q-learning approach and the heuristic make necessary assumptions on the knowledge of information, and each of them has unique advantages. We conduct numerical studies on a testing problem. The simulation results show that both the Q-learning and the decentralization based heuristic approaches work well. Lastly, we conclude the paper with some discussions on future extension directions.
... oxygen. Brain cells can die, causing lasting damage. Risk factors are things that increase your chance of ... a disease or condition. This article discusses the risk factors for stroke and things you can do ...
Analysis of time-varying psoriasis lesion image patterns
DEFF Research Database (Denmark)
Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg
2004-01-01
The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed.......The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed....
Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks
Zaal, Peter M. T.; Sweet, Barbara T.
2012-01-01
Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.
Time varying voltage combustion control and diagnostics sensor
Chorpening, Benjamin T [Morgantown, WV; Thornton, Jimmy D [Morgantown, WV; Huckaby, E David [Morgantown, WV; Fincham, William [Fairmont, WV
2011-04-19
A time-varying voltage is applied to an electrode, or a pair of electrodes, of a sensor installed in a fuel nozzle disposed adjacent the combustion zone of a continuous combustion system, such as of the gas turbine engine type. The time-varying voltage induces a time-varying current in the flame which is measured and used to determine flame capacitance using AC electrical circuit analysis. Flame capacitance is used to accurately determine the position of the flame from the sensor and the fuel/air ratio. The fuel and/or air flow rate (s) is/are then adjusted to provide reduced flame instability problems such as flashback, combustion dynamics and lean blowout, as well as reduced emissions. The time-varying voltage may be an alternating voltage and the time-varying current may be an alternating current.
Time-varying mixed logit model for vehicle merging behavior in work zone merging areas.
Weng, Jinxian; Du, Gang; Li, Dan; Yu, Yao
2018-08-01
This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. Copyright © 2018 Elsevier Ltd. All rights reserved.
Design of 2D Time-Varying Vector Fields
Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D.; Zhang, Eugene
2012-01-01
Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.
Design of 2D time-varying vector fields.
Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D; Zhang, Eugene
2012-10-01
Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects.
Design of 2D Time-Varying Vector Fields
Chen, Guoning
2012-10-01
Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.
Do Time-Varying Covariances, Volatility Comovement and Spillover Matter?
Lakshmi Balasubramanyan
2005-01-01
Financial markets and their respective assets are so intertwined; analyzing any single market in isolation ignores important information. We investigate whether time varying volatility comovement and spillover impact the true variance-covariance matrix under a time-varying correlation set up. Statistically significant volatility spillover and comovement between US, UK and Japan is found. To demonstrate the importance of modelling volatility comovement and spillover, we look at a simple portfo...
Soil erosion under multiple time-varying rainfall events
Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.
2010-05-01
Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.
[Risk factors of schizophrenia].
Suvisaari, Jaana
2010-01-01
Schizophrenia is a multifactorial, neurodevelopmental disorder caused by a combination of genetic and environmental risk factors. Disturbances of brain development begin prenatally, while different environmental insults further affect postnatal brain maturation during childhood and adolescence. Genome-wide association studies (GWAS) have succeeded in identifying hundreds of new risk variants for common, multifactorial diseases. In schizophrenia research, GWAS have found several rare copy number variants that considerably increase the risk of schizophrenia, and have shown an association between schizophrenia and the major histocompatibility complex. Research on environmental risk factors in recent years has provided new information particularly on risk factors related to pregnancy and childhood rearing environment. Gene-environment interactions have become a central research topic. There is evidence that genetically susceptible children are more vulnerable to the effects of unstable childhood rearing environment and other environmental risk factors.
International Nuclear Information System (INIS)
Brachner, A.; Grosche, B.
1991-06-01
A broad survey is given of risk factors for neoplasms. The main carcinogenic substances (including also ionizing radiation and air pollution) are listed, and are correlated with the risk factors for various cancers most frequently explained and discussed in the literature. The study is intended to serve as a basis for a general assessment of the incidence of neoplasms in children, and of cancer mortality in the entire population of Bavaria in the years 1983-1989, or 1979-1988, respectively, with the principal idea of drawing up an environment-related health survey. The study therefore takes into account not only ionizing radiation as a main risk factor, but also other risk factors detectable within the ecologic context, as e.g. industrial installations and their effects, refuse incineration plants or waste dumps, or the social status. (orig./MG) [de
Overcoming Spurious Regression Using time-Varying Fourier ...
African Journals Online (AJOL)
Non-stationary time series data have been traditionally analyzed in the frequency domain by assuming constant amplitudes regardless of the timelag. A new approach called time-varying amplitude method (TVAM) is presented here. Oscillations are analyzed for changes in the magnitude of Fourier Coefficients which are ...
Electromagnetic radiation in a time-varying background medium
Budko, N.V.
2009-01-01
Analytical solutions are presented for the electromagnetic radiation by an arbitrary pulsed source into a homogeneous time-varying background medium. In the constant-impedance case an explicit radiation formula is obtained for the synchronous permittivity and permeability described by any positive
Mediation analysis with time varying exposures and mediators.
VanderWeele, Tyler J; Tchetgen Tchetgen, Eric J
2017-06-01
In this paper we consider causal mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are time-varying confounders affected by prior exposure and mediator, natural direct and indirect effects are not identified. However, we define a randomized interventional analogue of natural direct and indirect effects that are identified in this setting. The formula that identifies these effects we refer to as the "mediational g-formula." When there is no mediation, the mediational g-formula reduces to Robins' regular g-formula for longitudinal data. When there are no time-varying confounders affected by prior exposure and mediator values, then the mediational g-formula reduces to a longitudinal version of Pearl's mediation formula. However, the mediational g-formula itself can accommodate both mediation and time-varying confounders and constitutes a general approach to mediation analysis with time-varying exposures and mediators.
Scattering of a TEM wave from a time varying surface
Elcrat, Alan R.; Harder, T. Mark; Stonebraker, John T.
1990-03-01
A solution is given for reflection of a plane wave with TEM polarization from a planar surface with time varying properties. These properties are given in terms of the currents on the surface. The solution is obtained by numerically solving a system of differential-delay equations in the time domain.
Time-varying correlation and common structures in volatility
Liu, Yang
2016-01-01
This thesis studies time series properties of the covariance structure of multivariate asset returns. First, the time-varying feature of correlation is investigated at the intraday level with a new correlation model incorporating the intraday correlation dynamics. Second, the thesis develops a
Contact Dynamics of EHL Contacts under Time Varying Conditions
Venner, Cornelis H.; Popovici, G.; Wijnant, Ysbrand H.; Dalmaz, G.; Lubrecht, A.A.; Priest, M
2004-01-01
By means of numerical simulations of two situations with time varying operating conditions it is shown that the dynamic behaviour of Elasto-Hydrodynamically Lubricated contacts in terms of vibrations can be characterized as: Changes in the mutual approach lead to film thickness changes in the inlet
Electricity Futures Prices : Time Varying Sensitivity to Fundamentals
S-E. Fleten (Stein-Erik); R. Huisman (Ronald); M. Kilic (Mehtap); H.P.G. Pennings (Enrico); S. Westgaard (Sjur)
2014-01-01
textabstractThis paper provides insight in the time-varying relation between electricity futures prices and fundamentals in the form of prices of contracts for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the
Visualizing time-varying harmonics using filter banks
Duque, C.A.; Da Silveira, P.M.; Ribeiro, P.F.
2011-01-01
Although it is well known that Fourier analysis is in reality only accurately applicable to steady state waveforms, it is a widely used tool to study and monitor time-varying signals, such as are commonplace in electrical power systems. The disadvantages of Fourier analysis, such as frequency
Time-Varying Value of Energy Efficiency in Michigan
Energy Technology Data Exchange (ETDEWEB)
Mims, Natalie; Eckman, Tom; Schwartz, Lisa C.
2018-04-02
Quantifying the time-varying value of energy efficiency is necessary to properly account for all of its benefits and costs and to identify and implement efficiency resources that contribute to a low-cost, reliable electric system. Historically, most quantification of the benefits of efficiency has focused largely on the economic value of annual energy reduction. Due to the lack of statistically representative metered end-use load shape data in Michigan (i.e., the hourly or seasonal timing of electricity savings), the ability to confidently characterize the time-varying value of energy efficiency savings in the state, especially for weather-sensitive measures such as central air conditioning, is limited. Still, electric utilities in Michigan can take advantage of opportunities to incorporate the time-varying value of efficiency into their planning. For example, end-use load research and hourly valuation of efficiency savings can be used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service (KEMA 2012). In addition, accurately calculating the time-varying value of efficiency may help energy efficiency program administrators prioritize existing offerings, set incentive or rebate levels that reflect the full value of efficiency, and design new programs.
Optimal routing of hazardous substances in time-varying, stochastic transportation networks
International Nuclear Information System (INIS)
Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.
1998-07-01
This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Several specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions
Vesicle biomechanics in a time-varying magnetic field.
Ye, Hui; Curcuru, Austen
2015-01-01
Cells exhibit distortion when exposed to a strong electric field, suggesting that the field imposes control over cellular biomechanics. Closed pure lipid bilayer membranes (vesicles) have been widely used for the experimental and theoretical studies of cellular biomechanics under this electrodeformation. An alternative method used to generate an electric field is by electromagnetic induction with a time-varying magnetic field. References reporting the magnetic control of cellular mechanics have recently emerged. However, theoretical analysis of the cellular mechanics under a time-varying magnetic field is inadequate. We developed an analytical theory to investigate the biomechanics of a modeled vesicle under a time-varying magnetic field. Following previous publications and to simplify the calculation, this model treated the inner and suspending media as lossy dielectrics, the membrane thickness set at zero, and the electric resistance of the membrane assumed to be negligible. This work provided the first analytical solutions for the surface charges, electric field, radial pressure, overall translational forces, and rotational torques introduced on a vesicle by the time-varying magnetic field. Frequency responses of these measures were analyzed, particularly the frequency used clinically by transcranial magnetic stimulation (TMS). The induced surface charges interacted with the electric field to produce a biomechanical impact upon the vesicle. The distribution of the induced surface charges depended on the orientation of the coil and field frequency. The densities of these charges were trivial at low frequency ranges, but significant at high frequency ranges. The direction of the radial force on the vesicle was dependent on the conductivity ratio between the vesicle and the medium. At relatively low frequencies (biomechanics under a time-varying magnetic field. Biological effects of clinical TMS are not likely to occur via alteration of the biomechanics of brain
Time-varying properties of renal autoregulatory mechanisms
DEFF Research Database (Denmark)
Zou, Rui; Cupples, Will A; Yip, K P
2002-01-01
In order to assess the possible time-varying properties of renal autoregulation, time-frequency and time-scaling methods were applied to renal blood flow under broad-band forced arterial blood pressure fluctuations and single-nephron renal blood flow with spontaneous oscillations obtained from...... normotensive (Sprague-Dawley, Wistar, and Long-Evans) rats, and spontaneously hypertensive rats. Time-frequency analyses of normotensive and hypertensive blood flow data obtained from either the whole kidney or the single-nephron show that indeed both the myogenic and tubuloglomerular feedback (TGF) mechanisms...... have time-varying characteristics. Furthermore, we utilized the Renyi entropy to measure the complexity of blood-flow dynamics in the time-frequency plane in an effort to discern differences between normotensive and hypertensive recordings. We found a clear difference in Renyi entropy between...
Electron dynamics in solid state via time varying wavevectors
Khaneja, Navin
2018-06-01
In this paper, we study electron wavepacket dynamics in electric and magnetic fields. We rigorously derive the semiclassical equations of electron dynamics in electric and magnetic fields. We do it both for free electron and electron in a periodic potential. We do this by introducing time varying wavevectors k(t). In the presence of magnetic field, our wavepacket reproduces the classical cyclotron orbits once the origin of the Schröedinger equation is correctly chosen to be center of cyclotron orbit. In the presence of both electric and magnetic fields, our equations for wavepacket dynamics differ from classical Lorentz force equations. We show that in a periodic potential, on application of electric field, the electron wave function adiabatically follows the wavefunction of a time varying Bloch wavevector k(t), with its energies suitably shifted with time. We derive the effective mass equation and discuss conduction in conductors and insulators.
Modelling Time-Varying Volatility in Financial Returns
DEFF Research Database (Denmark)
Amado, Cristina; Laakkonen, Helinä
2014-01-01
The “unusually uncertain” phase in the global financial markets has inspired many researchers to study the effects of ambiguity (or “Knightian uncertainty”) on the decisions made by investors and their implications for the capital markets. We contribute to this literature by using a modified...... version of the time-varying GARCH model of Amado and Teräsvirta (2013) to analyze whether the increasing uncertainty has caused excess volatility in the US and European government bond markets. In our model, volatility is multiplicatively decomposed into two time-varying conditional components: the first...... being captured by a stable GARCH(1,1) process and the second driven by the level of uncertainty in the financial market....
Scaling properties in time-varying networks with memory
Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong
2015-12-01
The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.
Housing Cycles in Switzerland - A Time-Varying Approach
Drechsel, Dirk
2015-01-01
In light of the strong increase of house prices in Switzerland, we analyze the effects of mortgage rate shocks, changes in the interplay between housing demand and supply and GDP growth on house prices for the time period 1981- 2014. We employ Bayesian time-varying coefficients vector autoregressions to allow different monetary and immigration regimes over time. A number of structural changes, such as regulatory changes in the aftermath of the 1990s real estate crisis, the introduction of fre...
Modeling information diffusion in time-varying community networks
Cui, Xuelian; Zhao, Narisa
2017-12-01
Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.
Time-varying linear control for tiltrotor aircraft
Directory of Open Access Journals (Sweden)
Jing ZHANG
2018-04-01
Full Text Available Tiltrotor aircraft have three flight modes: helicopter mode, airplane mode, and transition mode. A tiltrotor has characteristics of highly nonlinear, time-varying flight dynamics and inertial/control couplings in its transition mode. It can transit from the helicopter mode to the airplane mode by tilting its nacelles, and an effective controller is crucial to accomplish tilting transition missions. Longitudinal dynamic characteristics of the tiltrotor are described by a nonlinear Lagrange-form model, which takes into account inertial/control couplings and aerodynamic interferences. Reference commands for airspeed velocity and attitude in the transition mode are calculated dynamically by visiting a command library which is founded in advance by analyzing the flight envelope of the tiltrotor. A Time-Varying Linear (TVL model is obtained using a Taylor-expansion based online linearization technique from the nonlinear model. Subsequently, based on an optimal control concept, an online optimization based control method with input constraints considered is proposed. To validate the proposed control method, three typical tilting transition missions are simulated using the nonlinear model of XV-15 tiltrotor aircraft. Simulation results show that the controller can be used to control the tiltrotor throughout its operating envelop which includes a transition flight, and can also deal with vertical gust disturbances. Keywords: Constrained optimal control, Inertia/control couplings, Tiltrotor aircraft, Time-varying control, Transition mode
Vector-field statistics for the analysis of time varying clinical gait data.
Donnelly, C J; Alexander, C; Pataky, T C; Stannage, K; Reid, S; Robinson, M A
2017-01-01
In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses
Time-varying long term memory in the European Union stock markets
Sensoy, Ahmet; Tabak, Benjamin M.
2015-10-01
This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.
Directory of Open Access Journals (Sweden)
M. de la Sen
2010-01-01
Full Text Available This paper investigates the stability properties of a class of dynamic linear systems possessing several linear time-invariant parameterizations (or configurations which conform a linear time-varying polytopic dynamic system with a finite number of time-varying time-differentiable point delays. The parameterizations may be timevarying and with bounded discontinuities and they can be subject to mixed regular plus impulsive controls within a sequence of time instants of zero measure. The polytopic parameterization for the dynamics associated with each delay is specific, so that (q+1 polytopic parameterizations are considered for a system with q delays being also subject to delay-free dynamics. The considered general dynamic system includes, as particular cases, a wide class of switched linear systems whose individual parameterizations are timeinvariant which are governed by a switching rule. However, the dynamic system under consideration is viewed as much more general since it is time-varying with timevarying delays and the bounded discontinuous changes of active parameterizations are generated by impulsive controls in the dynamics and, at the same time, there is not a prescribed set of candidate potential parameterizations.
Entropy Rate of Time-Varying Wireless Networks
DEFF Research Database (Denmark)
Cika, Arta; Badiu, Mihai Alin; Coon, Justin P.
2018-01-01
In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy rate. We consider a propagation channel varying over time with random node positions in a closed space and Rayleigh...... fading affecting the connections between nodes. The existence of an edge between two nodes at given locations is modeled by a Markov chain, enabling memory effects in network dynamics. We then derive a lower and an upper bound on the entropy rate of the spatiotemporal network. The entropy rate measures...
Timed arrays wideband and time varying antenna arrays
Haupt, Randy L
2015-01-01
Introduces timed arrays and design approaches to meet the new high performance standards The author concentrates on any aspect of an antenna array that must be viewed from a time perspective. The first chapters briefly introduce antenna arrays and explain the difference between phased and timed arrays. Since timed arrays are designed for realistic time-varying signals and scenarios, the book also reviews wideband signals, baseband and passband RF signals, polarization and signal bandwidth. Other topics covered include time domain, mutual coupling, wideband elements, and dispersion. The auth
Investigating Time-Varying Drivers of Grid Project Emissions Impacts
Energy Technology Data Exchange (ETDEWEB)
Barrett, Emily L.; Thayer, Brandon L.; Pal, Seemita; Studarus, Karen E.
2017-11-15
The emissions consequences of smart grid technologies depend heavily on their context and vary not only by geographical location, but by time of year. The same technology operated to meet the same objective may increase the emissions associated with energy generation for part of the year and decrease emissions during other times. The Grid Project Impact Quantification (GridPIQ) tool provides the ability to estimate these seasonal variations and garner insight into the time-varying drivers of grid project emissions impacts. This work leverages GridPIQ to examine the emissions implications across years and seasons of adding energy storage technology to reduce daily peak demand in California and New York.
Epidemic spreading in time-varying community networks.
Ren, Guangming; Wang, Xingyuan
2014-06-01
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold qc. The epidemic will survive when q > qc and die when q epidemic spreading in complex networks with community structure.
[Pathological gambling: risk factors].
Bouju, G; Grall-Bronnec, M; Landreat-Guillou, M; Venisse, J-L
2011-09-01
In France, consumption of gambling games increased by 148% between 1960 and 2005. In 2004, gamblers lost approximately 0.9% of household income, compared to 0.4% in 1960. This represents approximately 134 Euros per year and per head. In spite of this important increase, the level remains lower than the European average (1%). However, gambling practices may continue to escalate in France in the next few years, particularly with the recent announce of the legalisation of online games and sports betting. With the spread of legalised gambling, pathological gambling rates may increase in France in the next years, in response to more widely available and more attractive gambling opportunities. In this context, there is a need for better understanding of the risk factors that are implicated in the development and maintenance of pathological gambling. This paper briefly describes the major risk factors for pathological gambling by examining the recent published literature available during the first quarter of 2008. This documentary basis was collected by Inserm for the collective expert report procedure on Gambling (contexts and addictions). Seventy-two articles focusing on risk factors for pathological gambling were considered in this review. Only 47 of them were taken into account for analysis. The selection of these 47 publications was based on the guide on literature analysis established by the French National Agency for Accreditation and Assessment in Health (ANAES, 2000). Some publications from more recent literature have also been added, mostly about Internet gambling. We identify three major types of risk factors implicated in gambling problems: some of them are related to the subject (individual factors), others are related to the object of the addiction, here the gambling activity by itself (structural factors), and the last are related to environment (contextual or situational factors). Thus, the development and maintenance of pathological gambling seems to be
Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay
International Nuclear Information System (INIS)
Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia
2009-01-01
This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.
Stochastic analysis of epidemics on adaptive time varying networks
Kotnis, Bhushan; Kuri, Joy
2013-06-01
Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.
Overlapping quadratic optimal control of linear time-varying commutative systems
Czech Academy of Sciences Publication Activity Database
Bakule, Lubomír; Rodellar, J.; Rossell, J. M.
2002-01-01
Roč. 40, č. 5 (2002), s. 1611-1627 ISSN 0363-0129 R&D Projects: GA AV ČR IAA2075802 Institutional research plan: CEZ:AV0Z1075907 Keywords : overlapping * optimal control * linear time-varying systems Subject RIV: BC - Control Systems Theory Impact factor: 1.441, year: 2002
Time-varying Capital Requirements and Disclosure Rules
DEFF Research Database (Denmark)
Kragh, Jonas; Rangvid, Jesper
, implying that resilience in the banking system is also increased. The increase in capital ratios is partly due to a modest reduction in lending. Using a policy changes, we show that banks react stronger to changes in capital requirements when these are public. Our results further suggest that the impact......Unique and confidential Danish data allow us to identify how changes in disclosure requirements and bank-specific time-varying capital requirements affect banks' lending and capital accumu-lation decisions. We find that banks increase their capital ratios after capital requirements are increased...... of capital requirements differ for small and large banks. Large banks raise their capital ratios more, reduce lending less, and accumulate more new capital compared to small banks....
Epidemic spreading in time-varying community networks
Energy Technology Data Exchange (ETDEWEB)
Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou 510665 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)
2014-06-15
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.
Network Coded Cooperation Over Time-Varying Channels
DEFF Research Database (Denmark)
Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Barros, João
2014-01-01
transmissions, e.g., in terms of the rate of packet transmission or the energy consumption. A comprehensive analysis of the MDP solution is carried out under different network conditions to extract optimal rules of packet transmission. Inspired by the extracted rules, we propose two near-optimal heuristics......In this paper, we investigate the optimal design of cooperative network-coded strategies for a three-node wireless network with time-varying, half-duplex erasure channels. To this end, we formulate the problem of minimizing the total cost of transmitting M packets from source to two receivers...... as a Markov Decision Process (MDP). The actions of the MDP model include the source and the type of transmission to be used in a given time slot given perfect knowledge of the system state. The cost of packet transmission is defined such that it can incorporate the difference between broadcast and unicast...
Newtonian cosmology with a time-varying constant of gravitation
International Nuclear Information System (INIS)
McVittie, G.C.
1978-01-01
Newtonian cosmology is based on the Eulerian equations of fluid mechanics combined with Poisson's equation modified by the introduction of a time-varying G. Spherically symmetric model universes are worked out with instantaneously uniform densities. They are indeterminate unless instantaneous uniformity of the pressure is imposed. When G varies as an inverse power of the time, the models can in some cases be shown to depend on the solution of a second-order differential equation which also occurs in the Friedmann models of general relativity. In Section 3, a method for 'passing through' a singularity of this equation is proposed which entails making four arbitrary mathematical assumptions. When G varies as (time) -1 , models with initially cycloidal motion are possible, each cycle becoming longer as time progresses. Finally, gravitation becomes so weak that the model expands to infinity. Kinetic and potential energies for the whole model are derived from the basic equations; their sum is not constant. (author)
Conditional CAPM: Time-varying Betas in the Brazilian Market
Directory of Open Access Journals (Sweden)
Frances Fischberg Blank
2014-10-01
Full Text Available The conditional CAPM is characterized by time-varying market beta. Based on state-space models approach, beta behavior can be modeled as a stochastic process dependent on conditioning variables related to business cycle and estimated using Kalman filter. This paper studies alternative models for portfolios sorted by size and book-to-market ratio in the Brazilian stock market and compares their adjustment to data. Asset pricing tests based on time-series and cross-sectional approaches are also implemented. A random walk process combined with conditioning variables is the preferred model, reducing pricing errors compared to unconditional CAPM, but the errors are still significant. Cross-sectional test show that book-to-market ratio becomes less relevant, but past returns still capture cross-section variation
Renormalization group theory for percolation in time-varying networks.
Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M
2018-05-22
Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.
Inferring time-varying network topologies from gene expression data.
Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas
2007-01-01
Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.
Time-varying vector fields and their flows
Jafarpour, Saber
2014-01-01
This short book provides a comprehensive and unified treatment of time-varying vector fields under a variety of regularity hypotheses, namely finitely differentiable, Lipschitz, smooth, holomorphic, and real analytic. The presentation of this material in the real analytic setting is new, as is the manner in which the various hypotheses are unified using functional analysis. Indeed, a major contribution of the book is the coherent development of locally convex topologies for the space of real analytic sections of a vector bundle, and the development of this in a manner that relates easily to classically known topologies in, for example, the finitely differentiable and smooth cases. The tools used in this development will be of use to researchers in the area of geometric functional analysis.
Parametric estimation of time varying baselines in airborne interferometric SAR
DEFF Research Database (Denmark)
Mohr, Johan Jacob; Madsen, Søren Nørvang
1996-01-01
A method for estimation of time varying spatial baselines in airborne interferometric synthetic aperture radar (SAR) is described. The range and azimuth distortions between two images acquired with a non-linear baseline are derived. A parametric model of the baseline is then, in a least square...... sense, estimated from image shifts obtained by cross correlation of numerous small patches throughout the image. The method has been applied to airborne EMISAR imagery from the 1995 campaign over the Storstrommen Glacier in North East Greenland conducted by the Danish Center for Remote Sensing. This has...... reduced the baseline uncertainties from several meters to the centimeter level in a 36 km scene. Though developed for airborne SAR the method can easily be adopted to satellite data...
Epidemic spreading in time-varying community networks
International Nuclear Information System (INIS)
Ren, Guangming; Wang, Xingyuan
2014-01-01
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q c . The epidemic will survive when q > q c and die when q c . These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure
Directory of Open Access Journals (Sweden)
Beatriz Vaz de Melo Mendes
2005-12-01
Full Text Available It is now widespread the use of Value-at-Risk (VaR as a canonical measure at risk. Most accurate VaR measures make use of some volatility model such as GARCH-type models. However, the pattern of volatility dynamic of a portfolio follows from the (univariate behavior of the risk assets, as well as from the type and strength of the associations among them. Moreover, the dependence structure among the components may change conditionally t past observations. Some papers have attempted to model this characteristic by assuming a multivariate GARCH model, or by considering the conditional correlation coefficient, or by incorporating some possibility for switches in regimes. In this paper we address this problem using time-varying copulas. Our modeling strategy allows for the margins to follow some FIGARCH type model while the copula dependence structure changes over time.
A Novel Time-Varying Friction Compensation Method for Servomechanism
Directory of Open Access Journals (Sweden)
Bin Feng
2015-01-01
Full Text Available Friction is an inevitable nonlinear phenomenon existing in servomechanisms. Friction errors often affect their motion and contour accuracies during the reverse motion. To reduce friction errors, a novel time-varying friction compensation method is proposed to solve the problem that the traditional friction compensation methods hardly deal with. This problem leads to an unsatisfactory friction compensation performance and the motion and contour accuracies cannot be maintained effectively. In this method, a trapezoidal compensation pulse is adopted to compensate for the friction errors. A generalized regression neural network algorithm is used to generate the optimal pulse amplitude function. The optimal pulse duration function and the pulse amplitude function can be established by the pulse characteristic parameter learning and then the optimal friction compensation pulse can be generated. The feasibility of friction compensation method was verified on a high-precision X-Y worktable. The experimental results indicated that the motion and contour accuracies were improved greatly with reduction of the friction errors, in different working conditions. Moreover, the overall friction compensation performance indicators were decreased by more than 54% and this friction compensation method can be implemented easily on most of servomechanisms in industry.
Study of selected phenotype switching strategies in time varying environment
Energy Technology Data Exchange (ETDEWEB)
Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)
2016-03-22
Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.
Innovation diffusion on time-varying activity driven networks
Rizzo, Alessandro; Porfiri, Maurizio
2016-01-01
Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.
Study of selected phenotype switching strategies in time varying environment
International Nuclear Information System (INIS)
Horvath, Denis; Brutovsky, Branislav
2016-01-01
Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.
Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control
Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo
2017-02-01
The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.
Monopoly models with time-varying demand function
Cavalli, Fausto; Naimzada, Ahmad
2018-05-01
We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.
Time-varying multiplex network: Intralayer and interlayer synchronization
Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar
2017-12-01
A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.
Delay-Dependent Guaranteed Cost Control of an Interval System with Interval Time-Varying Delay
Directory of Open Access Journals (Sweden)
Xiao Min
2009-01-01
Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.
International Nuclear Information System (INIS)
Lyman, G.H.
1992-01-01
It is no longer reasonable to divide cancers into those that are genetic in origin and those that are environmental in origin. With rare exception, carcinogenesis involves environmental factors that directly or indirectly exert a change in the cell's genome. Virtually all causes of cancer are multifactorial, sometimes involving an inherited predisposition to the carcinogenic effects of environmental factors, which include chemicals, ionizing radiation, and oncogenic virus. Carcinogenesis is a multistep process including induction, promotion, and progression. Initiation requires an irreversible change in the cellular genome, whereas promotion is commonly associated with prolonged and reversible exposure. Tumor progression results in genotypic and phenotypic changes associated with tumor growth, invasion, and metastasis. Most information on human cancer risk is based on epidemiologic studies involving both exposed and unexposed individuals. The quality of such studies depends on their ability to assess the strength of any association of exposure and disease and careful attention to any potential bias. Few cancers are inherited in a Mendelian fashion. Several preneoplastic conditions, however, are clearly inherited and several malignancies demonstrate weak familial patterns. Environmental factors may exert their effect on DNA in a random fashion, but certain consistent changes, including specific translocations of genetic information, are often found. Currently, there is great interest in the close proximity of certain oncogenes governing growth control to the consistent chromosomal changes observed. Such changes may represent a final common pathway of action for environmental carcinogens. Sufficient laboratory and epidemiologic evidence exists to establish a causal association of several chemical agents with cancer
Effect of a time varying power level in EBR-II on mixed-oxide fuel burnup
International Nuclear Information System (INIS)
Stone, I.Z.; Jost, J.W.; Baker, R.B.
1979-01-01
A refined prediction of burnup of mixed-oxide fuel in EBR-2 is compared with measured data. The calculation utilizes a time-varying power factor and results in a general improvement to previous calculations
Risk Factor Assessment Branch (RFAB)
The Risk Factor Assessment Branch (RFAB) focuses on the development, evaluation, and dissemination of high-quality risk factor metrics, methods, tools, technologies, and resources for use across the cancer research continuum, and the assessment of cancer-related risk factors in the population.
Directory of Open Access Journals (Sweden)
Gülşen Tükenmez Demirc
2011-09-01
Full Text Available Background and Design: There have been reports suggesting the involvement of environmental factors in the disease process of pemphigus. In this study, we aimed to find out the risk factors which could play role in the etiopathogenesis in our pemphigus patients.Material and method: A total of 42 patients (15 male and 27 female who were diagnosed as pemphigus with histopathological and direct immunoflurosence examinations in our clinic between the years 1998-2004, were interviewed for assessment of regarding with the subjects of the demographic properties, occupational groups, educational level, the number of pregnancies, stressfull life events, diet habits, smoking and alcohol consumption before the onset of the disease and the results were compared to 42 age and gender-matched controls with similar socioeconomic circumstances. Results: Working in agriculture and livestock, multi-parity, absence of smoking and stressfull life events were found to be statistically significant in pemphigus patients than in controls. Conclusion: Working in agriculture and livestock, multi-parity, absence of smoking and stressfull life events were assumed to play role in the etiopathogenesis and course of pemphigus.
Perinatal risk factors for strabismus
DEFF Research Database (Denmark)
Torp-Pedersen, Tobias; Boyd, Heather A; Poulsen, Gry
2010-01-01
Little is known about the aetiological factors underlying strabismus. We undertook a large cohort study to investigate perinatal risk factors for strabismus, overall and by subtype.......Little is known about the aetiological factors underlying strabismus. We undertook a large cohort study to investigate perinatal risk factors for strabismus, overall and by subtype....
Applications, dosimetry and biological interactions of static and time-varying magnetic fields
International Nuclear Information System (INIS)
Tenforde, T.S.
1988-08-01
The primary topics of this presentation include: (1) the applications of magnetic fields in research, industry, and medical technologies; (2) mechanisms of interaction of static and time-varying magnetic fields with living systems; (3) human health effects of exposure to static and time-varying magnetic fields in occupational, medical, and residential settings; and (4) recent advances in the dosimetry of extremely-low-frequency electromagnetic fields. The discussion of these topics is centered about two issues of considerable contemporary interest: (1) potential health effects of the fields used in magnetic resonance imaging and in vivo spectroscopy, and (2) the controversial issue of whether exposure to extremely-low-frequency (ELF) electromagnetic fields in the home and workplace leads to an elevated risk of cancer. 11 refs
Population models for time-varying pesticide exposure
Jager T; Jong FMW de; Traas TP; LER; SEC
2007-01-01
A model has recently been developed at RIVM to predict the effects of variable exposure to pesticides of plant and animal populations in surface water. Before a pesticide is placed on the market, the environmental risk of the substance has to be assessed. This risk is estimated by comparing
Risk factors in school shootings.
Verlinden, S; Hersen, M; Thomas, J
2000-01-01
Nine incidents of multiple-victim homicide in American secondary schools are examined and common risk factors are identified. The literature dealing with individual, family, social, societal, and situational risk factors for youth violence and aggression is reviewed along with existing risk assessment methods. Checklists of risk factors for serious youth violence and school violence are used in reviewing each school shooting case. Commonalties among the cases and implications for psychologists practicing in clinical and school settings are discussed.
Stagewise pseudo-value regression for time-varying effects on the cumulative incidence
DEFF Research Database (Denmark)
Zöller, Daniela; Schmidtmann, Irene; Weinmann, Arndt
2016-01-01
In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association...... for time-varying effects. This is implemented by coupling variable selection between the grid times, but determining estimates separately. The effect estimates are regularized to also allow for model fitting with a low to moderate number of observations. This technique is illustrated in an application...
Risks factoring business: accounting measurement
Directory of Open Access Journals (Sweden)
Z.V. Gutsaylyuk
2015-06-01
Full Text Available The paper carried out the identification of risk factors for the development of possible accounting software management. Studied theoretical and methodological aspects of the risk classification of factoring operations in the part of the risk assessment factors. It is proposed to consider the risks factors as the risk that is acceptable controlled by accounting instruments and the risks that can not be taken into account in the accounting records. To minimize the risk factor, accounting-driven tools, a method of self-insurance, which is a factor in the creation of provision for factoring transactions designed to cover unexpected expenses and losses. Provision for factoring factor will establish more stable conditions of financial activity and avoid the fluctuations of profit factor in relation to the writing off of losses on factoring operatsіyam.Developed proposals allow for further research to improve the organizational and methodological basis of accounting and analysis of information as a basis for providing risk management factor, particularly in terms of improving the evaluation questions such risks and their qualitative and quantitative analysis.
Stroke Risk Factors and Symptoms
... Â» [ pdf, 433 kb ] Order Materials Â» Stroke Risk Factors and Symptoms Risk Factors for a Stroke Stroke prevention is still ... it. Treatment can delay complications that increase the risk of stroke. Transient ischemic attacks (TIAs). Seek help. ...
A behavioral asset pricing model with a time-varying second moment
International Nuclear Information System (INIS)
Chiarella, Carl; He Xuezhong; Wang, Duo
2006-01-01
We develop a simple behavioral asset pricing model with fundamentalists and chartists in order to study price behavior in financial markets when chartists estimate both conditional mean and variance by using a weighted averaging process. Through a stability, bifurcation, and normal form analysis, the market impact of the weighting process and time-varying second moment are examined. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced). When the fundamental price becomes unstable, the weighting process leads to different price dynamics, depending on whether the chartists act as either trend followers or contrarians. It is also found that a time-varying second moment of the chartists does not change the stability of the fundamental price, but it does influence the stability of the bifurcations. The bifurcation becomes stable (unstable) when the chartists are more (less) concerned about the market risk characterized by the time-varying second moment. Different routes to complicated price dynamics are also observed. The analysis provides an analytical foundation for the statistical analysis of the corresponding stochastic version of this type of behavioral model
Fracture Risk and Risk Factors for Osteoporosis.
Schürer, Christian; Wallaschofski, Henri; Nauck, Matthias; Völzke, Henry; Schober, Hans-Christof; Hannemann, Anke
2015-05-25
As the population ages, diseases of the elderly are becoming more common, including osteoporosis. Ways to assess the risk of fracture and the distribution and effects of known risk factors for osteoporosis will be important in planning for future healthcare needs, as well as in the development of preventive strategies. The study population included 6029 men and women aged 20-90 who underwent examination in the second follow-up wave of the Study of Health in Pomerania (SHIP-2) or in the basal SHIP-Trend Study. The risk of fracture was estimated on the basis of quantitative ultrasonography of the calcaneus. Prior fractures and risk factors for osteoporosis were ascertained in standardized interviews. 4.6% of the male subjects and 10.6% of the female subjects were judged to have an elevated risk of fracture. The corresponding percentages among subjects over age 65 were 8.8% for men and 28.2% for women. Even among subjects under age 55, risk factors for osteoporosis were associated with lower bone stiffness: the mean stiffness index was 103/98 (men/women) without risk factors, 99/96 with one risk factor, and 93/95 with more than one risk factor. Logistic regression analysis yielded an odds ratio of 1.89 (95% confidence interval: 1.44-2.50; p<0.01) for prevalent fractures among subjects aged 75 and older compared to subjects under age 55. The data indicate a high prevalence of osteoporosis from age 65 onward. These findings are consistent with those of other studies from Germany and across Europe. Younger men and women should already begin taking steps to counteract modifiable risk factors.
Time-Varying Capital Requirements and Disclosure Rules
DEFF Research Database (Denmark)
Imbierowicz, Björn; Kragh, Jonas; Rangvid, Jesper
2018-01-01
We investigate how banks' capital and lending decisions respond to changes in bank-specific capital and disclosure requirements. We find that an increase in the bank-specific regulatory capital requirement results in a higher bank capital ratio, brought about via less asset risk. A decrease...
Time-varying effects in the analysis of customer loyalty
DEFF Research Database (Denmark)
Guillen, Montserrat; Perch Nielsen, Jens; Scheike, Thomas
2011-01-01
Insurance customers usually hold more than one contract with the same insurer. A generalization of classical survival analysis methods is used to examine the risk of losing a customer once an initial insurance policy cancellation has occurred. This method does not assume that the model parameters...
Directory of Open Access Journals (Sweden)
Kai Chang
2013-01-01
Full Text Available Under departures from the cost-of-carry theory, traded spot prices and conditional volatility disturbed from futures market have significant impacts on futures price of emissions allowances, and then we propose time-varying hedge ratios and hedging effectiveness estimation using ECM-GARCH model. Our empirical results show that conditional variance, conditional covariance, and their correlation between between spot and futures prices exhibit time-varying trends. Conditional volatility of spot prices, conditional volatility disturbed from futures market, and conditional correlation of market noises implied from spot and futures markets have significant effects on time-varying hedge ratios and hedging effectiveness. In the immature emissions allowances market, market participants optimize portfolio sizes between spot and futures assets using historical market information and then achieve higher risk reduction of assets portfolio revenues; accordingly, we can obtain better hedging effectiveness through time-varying hedge ratios with departures from the cost-of-carry theory.
Yoon, Heonjun; Kim, Miso; Park, Choon-Su; Youn, Byeng D.
2018-01-01
Piezoelectric vibration energy harvesting (PVEH) has received much attention as a potential solution that could ultimately realize self-powered wireless sensor networks. Since most ambient vibrations in nature are inherently random and nonstationary, the output performances of PVEH devices also randomly change with time. However, little attention has been paid to investigating the randomly time-varying electroelastic behaviors of PVEH systems both analytically and experimentally. The objective of this study is thus to make a step forward towards a deep understanding of the time-varying performances of PVEH devices under nonstationary random vibrations. Two typical cases of nonstationary random vibration signals are considered: (1) randomly-varying amplitude (amplitude modulation; AM) and (2) randomly-varying amplitude with randomly-varying instantaneous frequency (amplitude and frequency modulation; AM-FM). In both cases, this study pursues well-balanced correlations of analytical predictions and experimental observations to deduce the relationships between the time-varying output performances of the PVEH device and two primary input parameters, such as a central frequency and an external electrical resistance. We introduce three correlation metrics to quantitatively compare analytical prediction and experimental observation, including the normalized root mean square error, the correlation coefficient, and the weighted integrated factor. Analytical predictions are in an excellent agreement with experimental observations both mechanically and electrically. This study provides insightful guidelines for designing PVEH devices to reliably generate electric power under nonstationary random vibrations.
Time-varying parameter models for catchments with land use change: the importance of model structure
Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid
2018-05-01
Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
Time-varying parameter models for catchments with land use change: the importance of model structure
Directory of Open Access Journals (Sweden)
S. Pathiraja
2018-05-01
Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
Time-varying synchronization of European stock markets
Czech Academy of Sciences Publication Activity Database
Égert, B.; Kočenda, Evžen
2011-01-01
Roč. 40, č. 2 (2011), s. 394-407 ISSN 0377-7332 R&D Projects: GA ČR(CZ) GA402/08/1376; GA MŠk LC542 Institutional research plan: CEZ:MSM0021620846 Keywords : stock markets * intraday data * comovements Subject RIV: AH - Economics Impact factor: 0.597, year: 2011
Risk factors for stress fractures.
Bennell, K; Matheson, G; Meeuwisse, W; Brukner, P
1999-08-01
Preventing stress fractures requires knowledge of the risk factors that predispose to this injury. The aetiology of stress fractures is multifactorial, but methodological limitations and expediency often lead to research study designs that evaluate individual risk factors. Intrinsic risk factors include mechanical factors such as bone density, skeletal alignment and body size and composition, physiological factors such as bone turnover rate, flexibility, and muscular strength and endurance, as well as hormonal and nutritional factors. Extrinsic risk factors include mechanical factors such as surface, footwear and external loading as well as physical training parameters. Psychological traits may also play a role in increasing stress fracture risk. Equally important to these types of analyses of individual risk factors is the integration of information to produce a composite picture of risk. The purpose of this paper is to critically appraise the existing literature by evaluating study design and quality, in order to provide a current synopsis of the known scientific information related to stress fracture risk factors. The literature is not fully complete with well conducted studies on this topic, but a great deal of information has accumulated over the past 20 years. Although stress fractures result from repeated loading, the exact contribution of training factors (volume, intensity, surface) has not been clearly established. From what we do know, menstrual disturbances, caloric restriction, lower bone density, muscle weakness and leg length differences are risk factors for stress fracture. Other time-honoured risk factors such as lower extremity alignment have not been shown to be causative even though anecdotal evidence indicates they are likely to play an important role in stress fracture pathogenesis.
Managing Multiple Risk Factors
National Research Council Canada - National Science Library
Lollis, Charlie
1998-01-01
...) contribute to the racial differences in cardiovascular risk and events among women. High levels of socioeconomic stress, higher dietary fat intake and sedentary lifestyle are more prevalent among black than white women...
Tracking time-varying parameters with local regression
DEFF Research Database (Denmark)
Joensen, Alfred Karsten; Nielsen, Henrik Aalborg; Nielsen, Torben Skov
2000-01-01
This paper shows that the recursive least-squares (RLS) algorithm with forgetting factor is a special case of a varying-coe\\$cient model, and a model which can easily be estimated via simple local regression. This observation allows us to formulate a new method which retains the RLS algorithm, bu......, but extends the algorithm by including polynomial approximations. Simulation results are provided, which indicates that this new method is superior to the classical RLS method, if the parameter variations are smooth....
Time-Varying Market Integration and Expected Returns in Emerging Markets
de Jong, Frank; de Roon, Frans
2001-01-01
We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market. The level of integration is a time-varying variable that depends on the market value of the assets that can be held by domestic investors only versus the market value of the assets that can be traded freely. Our empirical analysis for 30 emerging markets shows that there are stro...
End-of-the-year economic growth and time-varying expected returns
DEFF Research Database (Denmark)
Møller, Stig V.; Rangvid, Jesper
2015-01-01
We show that macroeconomic growth at the end of the year (fourth quarter or December) strongly influences expected returns on risky financial assets, whereas economic growth during the rest of the year does not. We find this pattern for many different asset classes, across different time periods......, and for US and international data. We also show that movements in the surplus consumption ratio of Campbell and Cochrane (1999) , a theoretically well-founded measure of time-varying risk aversion linked to macroeconomic growth, influence expected returns stronger during the fourth quarter than the other...
... A.S.T. Quiz Hidden Stroke Risk Factors for Women Updated:Nov 22,2016 Excerpted from "What Women Need To Know About The Hidden Risk Factors ... 2012) This year, more than 100,000 U.S. women under 65 will have a stroke. Stroke is ...
Tolerable Time-Varying Overflow on Grass-Covered Slopes
Directory of Open Access Journals (Sweden)
Steven A. Hughes
2015-03-01
Full Text Available Engineers require estimates of tolerable overtopping limits for grass-covered levees, dikes, and embankments that might experience steady overflow. Realistic tolerance estimates can be used for both resilient design and risk assessment. A simple framework is developed for estimating tolerable overtopping on grass-covered slopes caused by slowly-varying (in time overtopping discharge (e.g., events like storm surges or river flood waves. The framework adapts the well-known Hewlett curves of tolerable limiting velocity as a function of overflow duration. It has been hypothesized that the form of the Hewlett curves suggests that the grass erosion process is governed by the flow work on the slope above a critical threshold velocity (referred to as excess work, and the tolerable erosional limit is reached when the cumulative excess work exceeds a given value determined from the time-dependent Hewlett curves. The cumulative excess work is expressed in terms of overflow discharge above a critical discharge that slowly varies in time, similar to a discharge hydrograph. The methodology is easily applied using forecast storm surge hydrographs at specific locations where wave action is minimal. For preliminary planning purposes, when storm surge hydrographs are unavailable, hypothetical equations for the water level and overflow discharge hydrographs are proposed in terms of the values at maximum overflow and the total duration of overflow. An example application is given to illustrate use of the methodology.
Environmental risk factors and pressures
International Nuclear Information System (INIS)
Klinda, J.; Lieskovska, Z.
1998-01-01
In this chapter the physical risk factors (as radiation [air contamination, contamination of the environment components and food contamination], radon and its radioactive decay products, radioactive wastes, noise), chemical risk factors [chemical substances, xenobiotics in the food chain the ozone depletion], wastes (waste generation, waste management, municipal waste management, import, export and transit of waste) and natural an technological hazards (water quality deterioration as a result of various accidents and fire risk) in the Slovak Republic in 1997 are reviewed
Spherical collapse model in time varying vacuum cosmologies
International Nuclear Information System (INIS)
Basilakos, Spyros; Plionis, Manolis; Sola, Joan
2010-01-01
We investigate the virialization of cosmic structures in the framework of flat Friedmann-Lemaitre-Robertson-Walker cosmological models, in which the vacuum energy density evolves with time. In particular, our analysis focuses on the study of spherical matter perturbations, as they decouple from the background expansion, 'turn around', and finally collapse. We generalize the spherical collapse model in the case when the vacuum energy is a running function of the Hubble rate, Λ=Λ(H). A particularly well-motivated model of this type is the so-called quantum field vacuum, in which Λ(H) is a quadratic function, Λ(H)=n 0 +n 2 H 2 , with n 0 ≠0. This model was previously studied by our team using the latest high quality cosmological data to constrain its free parameters, as well as the predicted cluster formation rate. It turns out that the corresponding Hubble expansion history resembles that of the traditional ΛCDM cosmology. We use this Λ(t)CDM framework to illustrate the fact that the properties of the spherical collapse model (virial density, collapse factor, etc.) depend on the choice of the considered vacuum energy (homogeneous or clustered). In particular, if the distribution of the vacuum energy is clustered, then, under specific conditions, we can produce more concentrated structures with respect to the homogeneous vacuum energy case.
International Nuclear Information System (INIS)
Zhang Yunong; Li Zhan
2009-01-01
In this Letter, by following Zhang et al.'s method, a recurrent neural network (termed as Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying convex quadratic-programming problem subject to time-varying linear-equality constraints. Different from conventional gradient-based neural networks (GNN), such a ZNN model makes full use of the time-derivative information of time-varying coefficient. The resultant ZNN model is theoretically proved to have global exponential convergence to the time-varying theoretical optimal solution of the investigated time-varying convex quadratic program. Computer-simulation results further substantiate the effectiveness, efficiency and novelty of such ZNN model and method.
Cardiovascular risk factors and dementia.
Fillit, Howard; Nash, David T; Rundek, Tatjana; Zuckerman, Andrea
2008-06-01
Dementias, such as Alzheimer's disease (AD) and vascular dementia, are disorders of aging populations and represent a significant economic burden. Evidence is accumulating to suggest that cardiovascular disease (CVD) risk factors may be instrumental in the development of dementia. The goal of this review was to discuss the relationship between specific CVD risk factors and dementia and how current treatment strategies for dementia should focus on reducing CVD risks. We conducted a review of the literature for the simultaneous presence of 2 major topics, cardiovascular risk factors and dementia (eg, AD). Special emphasis was placed on clinical outcome studies examining the effects of treatments of pharmacologically modifiable CVD risk factors on dementia and cognitive impairment. Lifestyle risk factors for CVD, such as obesity, lack of exercise, smoking, and certain psychosocial factors, have been associated with an increased risk of cognitive decline and dementia. Some evidence suggests that effectively managing these factors may prevent cognitive decline/dementia. Randomized, placebo-controlled trials of antihypertensive medications have found that such therapy may reduce the risk of cognitive decline, and limited data suggest a benefit for patients with AD. Some small open-label and randomized clinical trials of statins have observed positive effects on cognitive function; larger studies of statins in patients with AD are ongoing. Although more research is needed, current evidence indicates an association between CVD risk factors--such as hypertension, dyslipidemia, and diabetes mellitus--and cognitive decline/dementia. From a clinical perspective, these data further support the rationale for physicians to provide effective management of CVD risk factors and for patients to be compliant with such recommendations to possibly prevent cognitive decline/dementia.
Taft, Casey T.; O'Farrell, Timothy J.; Doron-Lamarca, Susan; Panuzio, Jillian; Suvak, Michael K.; Gagnon, David R.; Murphy, Christopher M.
2010-01-01
Objective: This study examined static and time-varying risk factors for perpetration of intimate partner violence (IPV) among men in treatment for alcohol use disorders. Method: Participants were 178 men diagnosed with alcohol abuse or dependence and their partners. Most (85%) of the men were European American; their average age was 41.0 years.…
Cardiovascular risk factors in men
DEFF Research Database (Denmark)
Gyllenborg, J; Rasmussen, S L; Borch-Johnsen, Knut
2001-01-01
Males have higher risk of cardiovascular disease (CVD) than premenopausal females. Gonadal steroids are probably involved in the gender difference in CVD, but previous results have been conflicting. We investigated the associations between CVD risk factors and sex hormones in a cross-sectional de......Males have higher risk of cardiovascular disease (CVD) than premenopausal females. Gonadal steroids are probably involved in the gender difference in CVD, but previous results have been conflicting. We investigated the associations between CVD risk factors and sex hormones in a cross...
PCA-based detection of damage in time-varying systems
Bellino, A.; Fasana, A.; Garibaldi, L.; Marchesiello, S.
2010-10-01
When performing Structural Health Monitoring, it is well known that the natural frequencies do not depend only on the damage but also on environmental conditions, such as temperature and humidity. The Principal Component Analysis is used to take this problem into account, because it allows eliminating the effect of external factors. The purpose of the present work is to show that this technique can be successfully used not only for time-invariant systems, but also for time-varying ones. Referring to the latter, one of the most studied systems which shows these characteristics is the bridge with crossing loads, such as the case of the railway bridge studied in present paper; in this case, the mass and the velocity of the train can be considered as "environmental" factors.This paper, after a brief description of the PCA method and one example of its application on time-invariant systems, presents the great potentialities of the methodology when applied to time-varying systems. The results show that this method is able to better detect the presence of damage and also to properly distinguish among different levels of crack depths.
Keogh, Ruth H; Mangtani, Punam; Rodrigues, Laura; Nguipdop Djomo, Patrick
2016-01-05
Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.
Directory of Open Access Journals (Sweden)
Ruth H. Keogh
2016-01-01
Full Text Available Abstract Background Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Methods Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. Results The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Conclusions Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.
A simple analytical model for dynamics of time-varying target leverage ratios
Lo, C. F.; Hui, C. H.
2012-03-01
In this paper we have formulated a simple theoretical model for the dynamics of the time-varying target leverage ratio of a firm under some assumptions based upon empirical observations. In our theoretical model the time evolution of the target leverage ratio of a firm can be derived self-consistently from a set of coupled Ito's stochastic differential equations governing the leverage ratios of an ensemble of firms by the nonlinear Fokker-Planck equation approach. The theoretically derived time paths of the target leverage ratio bear great resemblance to those used in the time-dependent stationary-leverage (TDSL) model [Hui et al., Int. Rev. Financ. Analy. 15, 220 (2006)]. Thus, our simple model is able to provide a theoretical foundation for the selected time paths of the target leverage ratio in the TDSL model. We also examine how the pace of the adjustment of a firm's target ratio, the volatility of the leverage ratio and the current leverage ratio affect the dynamics of the time-varying target leverage ratio. Hence, with the proposed dynamics of the time-dependent target leverage ratio, the TDSL model can be readily applied to generate the default probabilities of individual firms and to assess the default risk of the firms.
African Journals Online (AJOL)
2010-02-02
Feb 2, 2010 ... Several factors have been suggested as independent risk factors for their development. Identification of these ... with age, gender or haematological test. ... A meta-analysis of prospective studies on ..... The marked difference may be because monthly .... and dyslipidemia among patients taking first-line,.
A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks
Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim
2018-01-01
In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.
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.
A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks
Rached, Nadhir B.
2018-01-11
In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.
[Risk factors of necrotizing enterocolitis].
Tapia-Rombo, C A; Velasco-Lavín, M R; Nieto-Caldelas, A
1993-09-01
The purpose of the present study is to compare risk factors of necrotizing enterocolitis (NEC) between two group: group A, newborns with the disease and group B, newborns with other diseases different from NEC, in order to know if these risk factors are more frequent or not in the first group. We assessed the clinical records of all the patients hospitalized in the Neonatal Intensive Care Unit and Neonatology Service of the La Raza General Hospital between 1987 and 1991 with the diagnosis of NEC. They were compared with 65 clinical records chosen at random of patients hospitalized in the same Unit with other diagnosis at the same time, and who were discharged by improvement or deceased. In all of them were look for known risk factors for NEC generally accepted such as: prematurity, neonatal asphyxia, poliglobulia, cyanotic congenital heart disease, patent ductus arteriosus, respiratory distress syndrome, catheterization of umbilical vessels, early feeding of elevated formula increases, exchange exchange transfusion, hypoxic ischemic encephalopathy, infection, etc. Just 25 records of the possible 50 with the diagnosis of NEC full filled inclusion criteria. There were no statistically significant difference in weight, sex, mortality and known risk factors of NEC between both groups. Were concluded that NEC is a disease of unknown etiology that should be studied more thoroughly. The known risk factors must be avoided because the patient susceptibility probably play an important role.
Czech Academy of Sciences Publication Activity Database
Baxa, Jaromír; Horváth, R.; Vašíček, B.
2013-01-01
Roč. 9, č. 1 (2013), s. 117-138 ISSN 1572-3089 Institutional support: RVO:67985556 Keywords : Financial stress * Time-varying parameter model * Endogenous regressors Subject RIV: AH - Economics Impact factor: 2.932, year: 2013 http://library.utia.cas.cz/separaty/2013/E/baxa-0395375.pdf
Koopman, S.J.; Mallee, M.I.P.; van der Wel, M.
2010-01-01
In this article we introduce time-varying parameters in the dynamic Nelson-Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson-Siegel model has been recently reformulated as a dynamic factor model with vector autoregressive
Risk factor for febrile seizures
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Odalović Dragica
2014-01-01
Full Text Available Febrile seizures are the most frequent neurological disorder in the childhood. According to American Academy of Pediatrics (AAP, they have been defined as seizures provoked by high temperature in children aged between 6 months and 5 years, without previous history of afebrile seizures, intracranial infections and other possible causes of seizures. Seizures can be typical and atypical, according to the characteristics. Pathogenesis of this disorder has not been clarified yet, and it is believed to be a combination of genetic factors, high body temperature and brain maturation. The risk factors for recurrence of febrile seizures are: age in which seizures appeared for the first time, epilepsy in the first degree relative, febrile seizures in the first degree relative, frequent diseases with fever and low body temperature on the beginning of seizures. The frequency of recurrent seizures The risk for occurrence of epilepsy in children with simple seizures is about 1-1.5%, which is slightly higher compared to general population, while it increases to 4-15% in patients with complex seizures. However, there is no evidence that therapy prevents occurrence of epilepsy. When the prevention of recurrent seizures is considered, it is necessary to separate simple from complex seizures. The aim of this paper was to analyze the most important risk factors for febrile seizures, and to evaluate their impact on occurrence of recurrent seizures. Our study included 125 children with febrile seizures, aged from 6 months to 5 years. The presence of febrile seizures and epilepsy in the first degree relative has been noted in 22% of children. Typical febrile seizures were observed in 76% of cases, and atypical in 24%. Most patients had only one seizure (73.6%. Children, who had seizure earlier in life, had more frequent recurrences. Both risk factors were present in 25% of patients, while 68% of patients had only one risk factor. For the children with febrile disease
International Nuclear Information System (INIS)
Kusama, Tomoko
1979-01-01
For the purposes of radiation protection, the noteworthy risk of thyroid is carcinogenesis. The risk factor which ICRP presented in the publication-26 is 5 x 10 - 6 rem - 1 . This numerical value is based upon the estimated likelihood of inducing fatal thyroid cancer. On the other hand, the risk factor presented by the BEIR report is 4 x 10 - 6 yr - 1 . This value was decided after consideration of the risks of both fatal and non-fatal cancer of thyroid. The following features distinguished thyroid cancer from malignancy of other tissue from medical point of view. 1) A large difference between incidence and mortality in case of thyroid cancer is recognized, because the thyroid cancer could be successfully treated by surgical or radiological treatment. 2) The high prevalence of clinically silent tumor in thyroid gland has been reported. The incidence of thyroid cancer, therefore, is very dependent on methods of medical inspection. The prevalence of radiation induced thyroid cancer is modified by various factors such as age, sex, latency, dose and dose rate. The latent period is very important factors such as ave, sex, latency, dose and dose rate. The latent period is a very important factor in the estimation of accumulated total risk of thyroid malignancy. What is included in the risk caused by thyroid irradiation must be investigated. The risk of non-fatal cancer should be considered in the same way as that of fatal cancer. The dose-equivalent limit of thyroid in non-uniform irradiation caused by radioactive iodine is decided by the limit for non-stochastic effects. Therefore the further consideration of non-stochastic effects of thyroid is necessary. (author)
Shakiba, Maryam; Mansournia, Mohammad Ali; Salari, Arsalan; Soori, Hamid; Mansournia, Nasrin; Kaufman, Jay S
2018-06-01
In longitudinal studies, standard analysis may yield biased estimates of exposure effect in the presence of time-varying confounders that are also intermediate variables. We aimed to quantify the relationship between obesity and coronary heart disease (CHD) by appropriately adjusting for time-varying confounders. This study was performed in a subset of participants from the Atherosclerosis Risk in Communities (ARIC) Study (1987-2010), a US study designed to investigate risk factors for atherosclerosis. General obesity was defined as body mass index (weight (kg)/height (m)2) ≥30, and abdominal obesity (AOB) was defined according to either waist circumference (≥102 cm in men and ≥88 cm in women) or waist:hip ratio (≥0.9 in men and ≥0.85 in women). The association of obesity with CHD was estimated by G-estimation and compared with results from accelerated failure-time models using 3 specifications. The first model, which adjusted for baseline covariates, excluding metabolic mediators of obesity, showed increased risk of CHD for all obesity measures. Further adjustment for metabolic mediators in the second model and time-varying variables in the third model produced negligible changes in the hazard ratios. The hazard ratios estimated by G-estimation were 1.15 (95% confidence interval (CI): 0.83, 1.47) for general obesity, 1.65 (95% CI: 1.35, 1.92) for AOB based on waist circumference, and 1.38 (95% CI: 1.13, 1.99) for AOB based on waist:hip ratio, suggesting that AOB increased the risk of CHD. The G-estimated hazard ratios for both measures were further from the null than those derived from standard models.
Human Leptospirosis and risk factors.
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Yanelis Emilia Tabío Henry
2010-09-01
Full Text Available The human leptospirosis is a zoonosis of world distribution, were risk factors exist that have favored the wild and domestic animal propagation and so man. A descpitive investigation was made with the objective of determining the behavior of risk factors in outpatients by human leptospirosis in “Camilo Cienfuegos“ University General Hospital from Sncti Spíritus In the comprised time period betwen december 1 st and 3 st , 2008.The sample of this study was conformed by 54 risk persons that keep inclusion criteria. Some variables were used:age, sex, risk factors and number of ill persons, according to the month. Some patients of masculine sex prevailed (61,9%, group of ages between 15-29 and 45-59 years (27,7%, patients treated since october to december (53,7%, the direct and indirect contact with animals (46,2 %. The risk factors cassually associated to human leptospirosis turned to be: the masculine sex, the contac with animals, the occupational exposition and the inmersion on sources of sweet water.
Cao, Ying; Rajan, Suja S; Wei, Peng
2016-12-01
A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.
Invariant operator theory for the single-photon energy in time-varying media
International Nuclear Information System (INIS)
Jeong-Ryeol, Choi
2010-01-01
After the birth of quantum mechanics, the notion in physics that the frequency of light is the only factor that determines the energy of a single photon has played a fundamental role. However, under the assumption that the theory of Lewis–Riesenfeld invariants is applicable in quantum optics, it is shown in the present work that this widely accepted notion is valid only for light described by a time-independent Hamiltonian, i.e., for light in media satisfying the conditions, ε(i) = ε(0), μ(t) = μ(0), and σ(t) = 0 simultaneously. The use of the Lewis–Riesenfeld invariant operator method in quantum optics leads to a marvelous result: the energy of a single photon propagating through time-varying linear media exhibits nontrivial time dependence without a change of frequency. (general)
The time-varying role of the family in student time use and achievement
Directory of Open Access Journals (Sweden)
Marie C. Hull
2017-10-01
Full Text Available Abstract In this paper, I use a unique dataset linking administrative school data with birth records to quantify the importance of time-varying family factors for child achievement and time use. Specifically, I take a model of academic achievement commonly used in the test score literature, and I augment it to include a family-year effect. Identification comes from the large number of sibling pairs observed in the same year. While prior literature has focused on specific shocks, such as job loss, I capture the full set of innovations that are shared across siblings in a given year. The distributions of fixed effects reveal that annual family innovations, relative to what was expected based on the previous year, are more important than teacher assignment for student achievement and also play a substantial role in the time students spend on homework, free reading, and television. JEL Classification I21, J13, J24
Sexual harassment: identifying risk factors.
O'Hare, E A; O'Donohue, W
1998-12-01
A new model of the etiology of sexual harassment, the four-factor model, is presented and compared with several models of sexual harassment including the biological model, the organizational model, the sociocultural model, and the sex role spillover model. A number of risk factors associated with sexually harassing behavior are examined within the framework of the four-factor model of sexual harassment. These include characteristics of the work environment (e.g., sexist attitudes among co-workers, unprofessional work environment, skewed sex ratios in the workplace, knowledge of grievance procedures for sexual harassment incidents) as well as personal characteristics of the subject (e.g., physical attractiveness, job status, sex-role). Subjects were 266 university female faculty, staff, and students who completed the Sexual Experience Questionnaire to assess the experience of sexual harassment and a questionnaire designed to assess the risk factors stated above. Results indicated that the four-factor model is a better predictor of sexual harassment than the alternative models. The risk factors most strongly associated with sexual harassment were an unprofessional environment in the workplace, sexist atmosphere, and lack of knowledge about the organization's formal grievance procedures.
Risk factors for undescended testis.
Brouwers, M.M.; Bruijne, L.M. de; Gier, R.P.E. de; Zielhuis, G.A.; Feitz, W.F.J.; Roeleveld, N.
2012-01-01
OBJECTIVE: To contribute to the understanding of the etiology of undescended testis (UDT), by exploring a wide range of potential risk factors in a case-referent study. PATIENTS AND METHODS: Cases and referents were recruited at five hospitals and included 200 boys with surgically corrected UDT and
Seasonality of cardiovascular risk factors
DEFF Research Database (Denmark)
Marti-Soler, Helena; Gubelmann, Cédric; Aeschbacher, Stefanie
2014-01-01
OBJECTIVE: To assess the seasonality of cardiovascular risk factors (CVRF) in a large set of population-based studies. METHODS: Cross-sectional data from 24 population-based studies from 15 countries, with a total sample size of 237 979 subjects. CVRFs included Body Mass Index (BMI) and waist...
Cook, Robert L; Kelso, Natalie E; Brumback, Babette A; Chen, Xinguang
2016-01-01
As persons with HIV are living longer, there is a growing need to investigate factors associated with chronic disease, rate of disease progression and survivorship. Many risk factors for this high-risk population change over time, such as participation in treatment, alcohol consumption and drug abuse. Longitudinal datasets are increasingly available, particularly clinical data that contain multiple observations of health exposures and outcomes over time. Several analytic options are available for assessment of longitudinal data; however, it can be challenging to choose the appropriate analytic method for specific combinations of research questions and types of data. The purpose of this review is to help researchers choose the appropriate methods to analyze longitudinal data, using alcohol consumption as an example of a time-varying exposure variable. When selecting the optimal analytic method, one must consider aspects of exposure (e.g. timing, pattern, and amount) and outcome (fixed or time-varying), while also addressing minimizing bias. In this article, we will describe several analytic approaches for longitudinal data, including developmental trajectory analysis, generalized estimating equations, and mixed effect models. For each analytic strategy, we describe appropriate situations to use the method and provide an example that demonstrates the use of the method. Clinical data related to alcohol consumption and HIV are used to illustrate these methods.
Stabilization of the Wave Equation with Boundary Time-Varying Delay
Directory of Open Access Journals (Sweden)
Hao Li
2014-01-01
Full Text Available We study the stabilization of the wave equation with variable coefficients in a bounded domain and a time-varying delay term in the time-varying, weakly nonlinear boundary feedbacks. By the Riemannian geometry methods and a suitable assumption of nonlinearity, we obtain the uniform decay of the energy of the closed loop system.
Risk factors for congenital hydrocephalus
DEFF Research Database (Denmark)
Munch, Tina Noergaard; Rasmussen, Marie-Louise Hee; Wohlfahrt, Jan
2014-01-01
. Furthermore, to identify the risk factors unique for isolated CHC as compared to syndromic CHC. METHODS: We established a cohort of all children born in Denmark between 1978 and 2008. Information on CHC and maternal medical diseases were obtained from the National Patient Discharge Register, maternal intake...... increased risk of isolated CHC compared to unexposed children (RR 2.52, 95% CI 1.47 to 4.29) (1.5/1000 born children). Risk factors also found for syndromic CHC were: Male gender, multiples and maternal diabetes. CONCLUSIONS: The higher risk for isolated CHC in first-born children as well as behavioural......-born children, we observed 1193 cases of isolated CHC (0.062/1000) born children. First-borns had an increased risk of isolated CHC compared to later-borns (1.32 95% CI 1.17 to 1.49) (0.72/1000 born children). First trimester exposure to maternal use of antidepressants was associated with a significantly...
Experimental evidence for amplitude death induced by a time-varying interaction
Energy Technology Data Exchange (ETDEWEB)
Suresh, K. [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India); Shrimali, M.D. [Department of Physics, Central University of Rajasthan, NH-8, Bandar Sindri, Ajmer 305 801 (India); Prasad, Awadhesh [Department of Physics and Astrophysics, University of Delhi, Delhi 110 007 (India); Thamilmaran, K., E-mail: maran.cnld@gmail.com [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India)
2014-08-01
In this paper, we study the time-varying interaction in coupled oscillatory systems. For this purpose, we have designed a novel time-varying resistive network using an analog switch and inverter circuits. We have applied this time-varying resistive network to mutually coupled identical Chua's oscillators. When the resistances are varied in time, we find that amplitude death arises in coupled identical oscillators. This has been observed numerically as well as verified through hardware experiments. - Highlights: • We have implemented the time-varying interaction in coupled oscillatory systems. • We have designed a novel time-varying resistive network using an analog switch and inverter circuits. • When the resistances are varied in time, we find that amplitude death arises in coupled identical oscillators.
[Risk factors associated to preclampsia].
López-Carbajal, Mario Joaquín; Manríquez-Moreno, María Esther; Gálvez-Camargo, Daniela; Ramírez-Jiménez, Evelia
2012-01-01
preeclampsia constitutes one of the main causes of maternal and perinatal morbidity and mortality. The aim was to identify the risk factors associated to the developmental of preeclampsia mild-moderate and severe, as well as the force of association of these factors in a hospital of second-level medical care. study of cases and controls, a relation 1:1, in women withdrawn of the Service of Gynecology and Obstetrics during 2004 to 2007. Pregnant women with more than 20 weeks gestation were included. In the cases group we included patients with diagnosis of preeclampsia mild-moderate or severe (corroborated clinical and laboratory). In the controls group that had a normal childbirth without pathology during the pregnancy. 42 cases and 42 controls. The average age was of 27 years. The associated risk factors were overweight, obesity, irregular prenatal control, short or long intergenesic period, history of caesarean or preeclampsia in previous pregnancies. the knowledge of the risk factors will allow the accomplishment of preventive measures and decrease the fetal and maternal morbidity and mortality due to preeclampsia.
Do Tick Attachment Times Vary between Different Tick-Pathogen Systems?
Directory of Open Access Journals (Sweden)
Stephanie L. Richards
2017-05-01
Full Text Available Improvements to risk assessments are needed to enhance our understanding of tick-borne disease epidemiology. We review tick vectors and duration of tick attachment required for pathogen transmission for the following pathogens/toxins and diseases: (1 Anaplasma phagocytophilum (anaplasmosis; (2 Babesia microti (babesiosis; (3 Borrelia burgdorferi (Lyme disease; (4 Southern tick-associated rash illness; (5 Borrelia hermsii (tick-borne relapsing fever; (6 Borrelia parkeri (tick-borne relapsing fever; (7 Borrelia turicatae (tick-borne relapsing fever; (8 Borrelia mayonii; (9 Borrelia miyamotoi; (10 Coxiella burnetii (Query fever; (11 Ehrlichia chaffeensis (ehrlichiosis; (12 Ehrlichia ewingii (ehrlichiosis; (13 Ehrlichia muris; (14 Francisella tularensis (tularemia; (15 Rickettsia 364D; (16 Rickettsia montanensis; (17 Rickettsia parkeri (American boutonneuse fever, American tick bite fever; (18 Rickettsia ricketsii (Rocky Mountain spotted fever; (19 Colorado tick fever virus (Colorado tick fever; (20 Heartland virus; (21 Powassan virus (Powassan disease; (22 tick paralysis neurotoxin; and (23 Galactose-α-1,3-galactose (Mammalian Meat Allergy-alpha-gal syndrome. Published studies for 12 of the 23 pathogens/diseases showed tick attachment times. Reported tick attachment times varied (<1 h to seven days between pathogen/toxin type and tick vector. Not all studies were designed to detect the duration of attachment required for transmission. Knowledge of this important aspect of vector competence is lacking and impairs risk assessment for some tick-borne pathogens.
DEFF Research Database (Denmark)
Bøttcher, Louise; Dammeyer, Jesper
2013-01-01
Empirical research has established that children with disabilities are more likely to develop psychopathology than children without disabilities. But too little is known about the association between disability and psychopathology. The aim of this article is to discuss developmental...... psychopathological models that conceptualize the connection between childhood disability and psychopathology. Empirical studies of psychopathology among children with a congenital hearing impairment and children with cerebral palsy will be reviewed, representing in-depth examples of association between disability...... and psychopathology. Both a congenital hearing impairment and cerebral palsy were found to be dominating risk factors for all types of psychopathology, but no relationship was identified between degree of disability and risk of psychopathology. The higher risk cannot be explained by biological impairments alone...
Neurodevelopmental risk factors in schizophrenia
Directory of Open Access Journals (Sweden)
Lobato M.I.
2001-01-01
Full Text Available The authors review environmental and neurodevelopmental risk factors for schizophrenic disorders, with emphasis on minor physical anomalies, particularly craniofacial anomalies and dermatoglyphic variations. The high prevalence of these anomalies among schizophrenic subjects supports the neurodevelopmental theory of the etiology of schizophrenia, since they suggest either genetically or epigenetically controlled faulty embryonic development of structures of ectodermal origin like brain and skin. This may disturb neurodevelopment that in turn may cause these subjects to be at increased risk for the development of schizophrenia and related disorders. The precise confirmation of this theory, at least in some cases, will provide further understanding of these illnesses, allowing easy and inexpensive identification of subjects at risk and providing guidelines for the development of new pharmacological interventions for early treatment and even for primary prevention of the illness.
Delay-Dependent Guaranteed Cost H∞ Control of an Interval System with Interval Time-Varying Delay
Directory of Open Access Journals (Sweden)
Zhongke Shi
2009-01-01
Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost H∞ control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.
Shi, Lei; Yao, Bo; Zhao, Lei; Liu, Xiaotong; Yang, Min; Liu, Yanming
2018-01-01
The plasma sheath-surrounded hypersonic vehicle is a dynamic and time-varying medium and it is almost impossible to calculate time-varying physical parameters directly. The in-fight detection of the time-varying degree is important to understand the dynamic nature of the physical parameters and their effect on re-entry communication. In this paper, a constant envelope zero autocorrelation (CAZAC) sequence based on time-varying frequency detection and channel sounding method is proposed to detect the plasma sheath electronic density time-varying property and wireless channel characteristic. The proposed method utilizes the CAZAC sequence, which has excellent autocorrelation and spread gain characteristics, to realize dynamic time-varying detection/channel sounding under low signal-to-noise ratio in the plasma sheath environment. Theoretical simulation under a typical time-varying radio channel shows that the proposed method is capable of detecting time-variation frequency up to 200 kHz and can trace the channel amplitude and phase in the time domain well under -10 dB. Experimental results conducted in the RF modulation discharge plasma device verified the time variation detection ability in practical dynamic plasma sheath. Meanwhile, nonlinear phenomenon of dynamic plasma sheath on communication signal is observed thorough channel sounding result.
Perinatal risk factors including malformation
International Nuclear Information System (INIS)
Brachner, A.; Grosche, B.
1991-10-01
The study gives a survey of the factors most frequently mentioned in the literature as factors likely to adversely affect a pregnancy. One essential aspect is the discussion of those factors that can be counted among the causes of malformations, as among others, prenatal radiation exposure. The study prepared within the framework of the research project 'Radiobiological environmental monitoring in Bavaria' is intended to serve as a basis for a retrospective and prospective evaluation of infant mortality, perinatal conditions and occurrence of malformations in Bavaria, with the principal idea of drawing up an environment - related health survey. The study therefore, in addition to ionizing radiation also takes into account other detectable risks within the ecologic context, as e.g. industrial installations, refuse incineration plants or waste dumps, or urbanity. (orig./MG) [de
Synchronization of uncertain time-varying network based on sliding mode control technique
Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe
2017-09-01
We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.
Directory of Open Access Journals (Sweden)
Mingzhu Song
2016-01-01
Full Text Available We address the problem of globally asymptotic stability for a class of stochastic nonlinear systems with time-varying delays. By the backstepping method and Lyapunov theory, we design a linear output feedback controller recursively based on the observable linearization for a class of stochastic nonlinear systems with time-varying delays to guarantee that the closed-loop system is globally asymptotically stable in probability. In particular, we extend the deterministic nonlinear system to stochastic nonlinear systems with time-varying delays. Finally, an example and its simulations are given to illustrate the theoretical results.
Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays
Directory of Open Access Journals (Sweden)
Chunmei Wu
2015-01-01
Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.
On the synchronization of neural networks containing time-varying delays and sector nonlinearity
International Nuclear Information System (INIS)
Yan, J.-J.; Lin, J.-S.; Hung, M.-L.; Liao, T.-L.
2007-01-01
We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme
Risk factors for tornado injuries.
Eidson, M; Lybarger, J A; Parsons, J E; MacCormack, J N; Freeman, J I
1990-12-01
Tornadoes in North and South Carolina on 28 March 1984 caused 252 people to be injured seriously enough to require hospitalization and 59 to be killed. To evaluate risk factors, we gathered information on 238 (94%) of those hospitalized and 46 (78%) of those killed. Those hospitalized or deceased had statistically significantly more deep cuts, concussions, unconsciousness and broken bones than those with them at the time of the tornado who were not hospitalized or killed. People living in mobile homes were more likely to be hospitalized or die than people occupying conventional houses. Other risk factors for hospitalization or death included advanced age (60+ years), no physical protection (not having been covered with a blanket or other object), having been struck by broken window glass or other falling objects, home lifted off its foundation, collapsed ceiling or floor, or walls blown away. More awareness of the tornado risk before it strikes and better adherence to tornado protection guidelines could reduce injuries and deaths in the future.
2017-12-08
STATISTICAL LINEAR TIME-VARYING SYSTEM MODEL OF HIGH GRAZING ANGLE SEA CLUTTER FOR COMPUTING INTERFERENCE POWER 1. INTRODUCTION Statistical linear time...beam. We can approximate one of the sinc factors using the Dirichlet kernel to facilitate computation of the integral in (6) as follows: ∣∣∣∣sinc(WB...plotted in Figure 4. The resultant autocorrelation can then be found by substituting (18) into (28). The Python code used to generate Figures 1-4 is found
Positive Almost Periodic Solutions for a Time-Varying Fishing Model with Delay
Directory of Open Access Journals (Sweden)
Xia Li
2011-01-01
Full Text Available This paper is concerned with a time-varying fishing model with delay. By means of the continuation theorem of coincidence degree theory, we prove that it has at least one positive almost periodic solution.
Long memory of financial time series and hidden Markov models with time-varying parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
Hidden Markov models are often used to capture stylized facts of daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior for the ability to reproduce the stylized...... facts have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time-varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared...... daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step predictions....
Identification of time-varying nonlinear systems using differential evolution algorithm
DEFF Research Database (Denmark)
Perisic, Nevena; Green, Peter L; Worden, Keith
2013-01-01
(DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...
Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights
L.F. Hoogerheide (Lennart); R.H. Kleijn (Richard); H.K. van Dijk (Herman); M.J.C.M. Verbeek (Marno)
2009-01-01
textabstractSeveral Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time
An Explicit MOT-TD-VIE Solver for Time Varying Media
Sayed, Sadeed Bin; Ulku, Huseyin Arda; Bagci, Hakan
2016-01-01
An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i
Wavelet ridge diagnosis of time-varying elliptical signals with application to an oceanic eddy
Lilly , J. M.; Gascard , Jean-Claude
2006-01-01
International audience; A method for diagnosing the physical properties of a time-varying ellipse is presented. This essentially involves extending the notion of instantaneous frequency to the bivariate case. New complications, and possibilities, arise from the fact that there are several meaningful forms in which a time-varying ellipse may be represented. A perturbation analysis valid for the near-circular case clarifies these issues. Diagnosis of the ellipse properties may then be performed...
Global stabilization of linear continuous time-varying systems with bounded controls
International Nuclear Information System (INIS)
Phat, V.N.
2004-08-01
This paper deals with the problem of global stabilization of a class of linear continuous time-varying systems with bounded controls. Based on the controllability of the nominal system, a sufficient condition for the global stabilizability is proposed without solving any Riccati differential equation. Moreover, we give sufficient conditions for the robust stabilizability of perturbation/uncertain linear time-varying systems with bounded controls. (author)
Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays
International Nuclear Information System (INIS)
Syed Ali, M.; Balasubramaniam, P.
2009-01-01
In this paper, the Takagi-Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Bidirectional Associative Memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by LMI optimization algorithms to guarantee the exponential stability of uncertain BAM neural networks with time-varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.
Risk factor management: antiatherogenic therapies.
Gielen, Stephan; Sandri, Marcus; Schuler, Gerhard; Teupser, Daniel
2009-08-01
Despite the advances in interventional techniques, the management of stable atherosclerosis remains the domain of optimal guideline-oriented therapy. Recent studies on the effects of aggressive lipid lowering on atheroma volume changes using intravascular ultrasound indicate that it is possible to achieve atherosclerosis regression by reaching low-density lipoprotein (LDL) levels less than 75 mg/dl. The pleiotropic anti-inflammatory effects of statins contribute to the reduction of cardiovascular (CV) event observed with aggressive lipid lowering. As a second important strategy to prevent disease progression, lifestyle changes with regular physical exercise are capable of halting the atherosclerotic process and reducing angina symptoms and CV events. Optimal medical therapy, a healthy lifestyle with regular physical exercise, and coronary interventions are not mutually exclusive treatment strategies. Over the last few decades, both have proved to be effective in significantly reducing the CV mortality in the Western world. However, risk factor modification contributed to at least half the effect in the reduction of CV mortality. This figure provides an estimate of what could be achieved if we were to take risk factor modification more seriously - especially in the acute care setting. The knowledge is there: today we have a better understanding on how to stop progression and even induce regression of atherosclerosis. Much research still needs to be done and will be done. In the meantime, however, our primary focus should lie in implementing what is already known. In addition, it is essential not just to treat CV risk factors, but also to treat them to achieve the target values as set by the guidelines of European Society of Cardiology.
Risk factors of teenage pregnancy
Maria Siettou; Maria Saridi
2011-01-01
Teenage pregnancy is a worldwide medical and social issue, associated with many physical, psychological and social consequences and can result in birth, miscarriage or abortion. Aim: The aim of the present study is to find those risk factors that contribute to teenage pregnancy. Results: In U.S.A., according to data from Unicef, the birth rate among teenagers touches the 52.1% and it is four times higher, than the corresponding rate recorded in the countries of Western Europe. The United King...
Directory of Open Access Journals (Sweden)
Shu-Min Lu
2017-01-01
Full Text Available An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network (RBFNN is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.
On the link between oil price and exchange rate: A time-varying VAR parameter approach
International Nuclear Information System (INIS)
Bremond, Vincent; Razafindrabe, Tovonony; Hache, Emmanuel
2015-07-01
The aim of this paper is to study the relationship between the effective exchange rate of the dollar and the oil price dynamics from 1976 to 2013. In this context, we propose to explore the economic literature dedicated to financial channels factors (exchange rate, monetary policy, and international liquidity) that could affect the oil price dynamics. In addition to oil prices and the effective exchange rate of the dollar, we use the dry cargo index as a proxy for the real economic activity and prices for precious and industrial raw materials. Using a Bayesian time-varying parameter vector auto-regressive estimation, our main results show that the US Dollar effective exchange rate elasticity of the crude oil prices is not constant across the time and remains negative from 1989. It then highlights that a depreciation of the effective exchange rate of the dollar leads to an increase of the crude oil prices. Our paper also demonstrates the growing influence of financial and commodities markets development upon the global economy. (authors)
Risk Factors in Derivatives Markets
Directory of Open Access Journals (Sweden)
Raimonda Martinkutė-Kaulienė
2015-02-01
Full Text Available The objective of the article is to analyse and present the classification of risks actual to derivative securities. The analysis is based on classical and modern literature findings and analysis of newest statistical data. The analysis led to the conclusion, that the main risks typical for derivatives contracts and their traders are market risk, liquidity risk, credit and counterparty risk, legal risk and transactions risk. Pricing risk and systemic risk is also quite important. The analysis showed that market risk is the most important kind of risk that in many situations influences the level of remaining risks.
New risk factors for atherosclerosis and patient risk assessment
Fruchart, Jean-Charles; Nierman, Melchior C.; Stroes, Erik S. G.; Kastelein, John J. P.; Duriez, Patrick
2004-01-01
Advances in our understanding of the ways in which the traditional cardiovascular risk factors, including standard lipid (eg, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol) and nonlipid (eg, hypertension) risk factors, interact to initiate
Skin Cancer: Biology, Risk Factors & Treatment
... turn Javascript on. Feature: Skin Cancer Skin Cancer: Biology, Risk Factors & Treatment Past Issues / Summer 2013 Table ... Articles Skin Cancer Can Strike Anyone / Skin Cancer: Biology, Risk Factors & Treatment / Timely Healthcare Checkup Catches Melanoma ...
459 Preventing Cardiovascular Disease Risk Factors through ...
African Journals Online (AJOL)
FIRST LADY
2011-01-18
Jan 18, 2011 ... injury. Risk factors may be considered as characteristic indicators ... by examining the cardiovascular risk factors that are related to various forms .... Cross country race, Handball, Jogging, Rope jumping, Running Soccer,.
Risk factors identified for certain lymphoma subtypes
In a large international collaborative analysis of risk factors for non-Hodgkin lymphoma (NHL), scientists were able to quantify risk associated with medical history, lifestyle factors, family history of blood or lymph-borne cancers, and occupation for 11
Women's Heart Disease: Heart Disease Risk Factors
... this page please turn JavaScript on. Feature: Women's Heart Disease Heart Disease Risk Factors Past Issues / Winter 2014 Table ... or habits may raise your risk for coronary heart disease (CHD). These conditions are known as risk ...
Risk factors for venous thromboembolism during pregnancy
DEFF Research Database (Denmark)
Jensen, Thomas Bo; Gerds, Thomas Alexander; Grøn, Randi
2013-01-01
Pregnant women are at an increased risk of venous thromboembolism (VTE). Risk factors for VTE among pregnant women are not sufficiently investigated.......Pregnant women are at an increased risk of venous thromboembolism (VTE). Risk factors for VTE among pregnant women are not sufficiently investigated....
Molecular Risk Factors for Schizophrenia.
Modai, Shira; Shomron, Noam
2016-03-01
Schizophrenia (SZ) is a complex and strongly heritable mental disorder, which is also associated with developmental-environmental triggers. As opposed to most diagnosable diseases (yet similar to other mental disorders), SZ diagnosis is commonly based on psychiatric evaluations. Recently, large-scale genetic and epigenetic approaches have been applied to SZ research with the goal of potentially improving diagnosis. Increased computational analyses and applied statistical algorithms may shed some light on the complex genetic and epigenetic pathways contributing to SZ pathogenesis. This review discusses the latest advances in molecular risk factors and diagnostics for SZ. Approaches such as these may lead to a more accurate definition of SZ and assist in creating extended and reliable clinical diagnoses with the potential for personalized treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.
The time-varying association between perceived stress and hunger within and between days.
Huh, Jimi; Shiyko, Mariya; Keller, Stefan; Dunton, Genevieve; Schembre, Susan M
2015-06-01
Examine the association between perceived stress and hunger continuously over a week in free-living individuals. Forty five young adults (70% women, 30% overweight/obese) ages 18 to 24 years (Mean = 20.7, SD = 1.5), with BMI between 17.4 and 36.3 kg/m(2) (Mean = 23.6, SD = 4.0) provided between 513 and 577 concurrent ratings of perceived stress and hunger for 7 days via hourly, text messaging assessments and real-time eating records. Time-varying effect modeling was used to explore whether the within-day fluctuations in stress are related to perceived hunger assessed on a momentary basis. A generally positive stress-hunger relationship was confirmed, but we found that the strength of the relationship was not linear. Rather, the magnitude of the association between perceived stress and hunger changed throughout the day such that only during specific time intervals were stress and hunger significantly related. Specifically, the strength of the positive association peaked during late afternoon hours on weekdays (β = 0.31, p hunger associations that peak in the afternoon or evening hours. While we are unable to infer causality from these analyses, our findings provide empirical evidence for a potentially high-risk time of day for stress-induced eating. Replication of these findings in larger, more diverse samples will aid with the design and implementation of real-time intervention studies aimed at reducing stress-eating. Copyright © 2015 Elsevier Ltd. All rights reserved.
Cole, David A; Martin, Joan M; Jacquez, Farrah M; Tram, Jane M; Zelkowitz, Rachel; Nick, Elizabeth A; Rights, Jason D
2017-07-01
The longitudinal structure of depression in children and adolescents was examined by applying a Trait-State-Occasion structural equation model to 4 waves of self, teacher, peer, and parent reports in 2 age groups (9 to 13 and 13 to 16 years old). Analyses revealed that the depression latent variable consisted of 2 longitudinal factors: a time-invariant dimension that was completely stable over time and a time-varying dimension that was not perfectly stable over time. Different sources of information were differentially sensitive to these 2 dimensions. Among adolescents, self- and parent reports better reflected the time-invariant aspects. For children and adolescents, peer and teacher reports better reflected the time-varying aspects. Relatively high cross-informant agreement emerged for the time-invariant dimension in both children and adolescents. Cross-informant agreement for the time-varying dimension was high for adolescents but very low for children. Implications emerge for theoretical models of depression and for its measurement, especially when attempting to predict changes in depression in the context of longitudinal studies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Robustness analysis of the Zhang neural network for online time-varying quadratic optimization
International Nuclear Information System (INIS)
Zhang Yunong; Ruan Gongqin; Li Kene; Yang Yiwen
2010-01-01
A general type of recurrent neural network (termed as Zhang neural network, ZNN) has recently been proposed by Zhang et al for the online solution of time-varying quadratic-minimization (QM) and quadratic-programming (QP) problems. Global exponential convergence of the ZNN could be achieved theoretically in an ideal error-free situation. In this paper, with the normal differentiation and dynamics-implementation errors considered, the robustness properties of the ZNN model are investigated for solving these time-varying problems. In addition, linear activation functions and power-sigmoid activation functions could be applied to such a perturbed ZNN model. Both theoretical-analysis and computer-simulation results demonstrate the good ZNN robustness and superior performance for online time-varying QM and QP problem solving, especially when using power-sigmoid activation functions.
Jia, Xingyu; Liu, Zhigang; Tao, Long; Deng, Zhongwen
2017-10-16
Frequency scanning interferometry (FSI) with a single external cavity diode laser (ECDL) and time-invariant Kalman filtering is an effective technique for measuring the distance of a dynamic target. However, due to the hysteresis of the piezoelectric ceramic transducer (PZT) actuator in the ECDL, the optical frequency sweeps of the ECDL exhibit different behaviors, depending on whether the frequency is increasing or decreasing. Consequently, the model parameters of Kalman filter appear time varying in each iteration, which produces state estimation errors with time-invariant filtering. To address this, in this paper, a time-varying Kalman filter is proposed to model the instantaneous movement of a target relative to the different optical frequency tuning durations of the ECDL. The combination of the FSI method with the time-varying Kalman filter was theoretically analyzed, and the simulation and experimental results show the proposed method greatly improves the performance of dynamic FSI measurements.
Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach
Directory of Open Access Journals (Sweden)
Jeyhun I. Mikayilov
2017-11-01
Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.
Finite-time stability of neutral-type neural networks with random time-varying delays
Ali, M. Syed; Saravanan, S.; Zhu, Quanxin
2017-11-01
This paper is devoted to the finite-time stability analysis of neutral-type neural networks with random time-varying delays. The randomly time-varying delays are characterised by Bernoulli stochastic variable. This result can be extended to analysis and design for neutral-type neural networks with random time-varying delays. On the basis of this paper, we constructed suitable Lyapunov-Krasovskii functional together and established a set of sufficient linear matrix inequalities approach to guarantee the finite-time stability of the system concerned. By employing the Jensen's inequality, free-weighting matrix method and Wirtinger's double integral inequality, the proposed conditions are derived and two numerical examples are addressed for the effectiveness of the developed techniques.
Some properties of zero power neutron noise in a time-varying medium with delayed neutrons
International Nuclear Information System (INIS)
Kitamura, Y.; Pal, L.; Pazsit, I.; Yamamoto, A.; Yamane, Y.
2008-01-01
The temporal evolution of the distribution of the number of neutrons in a time-varying multiplying system, producing only prompt neutrons, was treated recently with the master equation technique by some of the present authors. Such a treatment gives account of both the so-called zero power reactor noise and the power reactor noise simultaneously. In particular, the first two moments of the neutron number, as well as the concept of criticality for time-varying systems, were investigated and discussed. The present paper extends these investigations to the case when delayed neutrons are also taken into account. Due to the complexity of the description, only the expectation of the neutron number is calculated. The concept of criticality of a time-varying system is also generalized to systems with delayed neutrons. The temporal behaviour of the expectation of the number of neutrons and its asymptotic properties are displayed and discussed
New results on global exponential stability of recurrent neural networks with time-varying delays
International Nuclear Information System (INIS)
Xu Shengyuan; Chu Yuming; Lu Junwei
2006-01-01
This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples
H ∞ synchronization of the coronary artery system with input time-varying delay
International Nuclear Information System (INIS)
Li Xiao-Meng; Zhao Zhan-Shan; Sun Lian-Kun; Zhang Jing
2016-01-01
This paper investigates the H ∞ synchronization of the coronary artery system with input delay and disturbance. We focus on reducing the conservatism of existing synchronization strategies. Base on the triple integral forms of the Lyapunov–Krasovskii functional (LKF), we utilize single and double integral forms of Wirtinger-based inequality to guarantee that the synchronization feedback controller has good performance against time-varying delay and external disturbance. The effectiveness of our strategy can be exhibited by simulations under the different time-varying delays and different disturbances. (paper)
Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay
International Nuclear Information System (INIS)
Mei, Sun; Chang-Yan, Zeng; Li-Xin, Tian
2009-01-01
Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand–supply of energy resource in some regions of China
Exponential stability of fuzzy cellular neural networks with constant and time-varying delays
International Nuclear Information System (INIS)
Liu Yanqing; Tang Wansheng
2004-01-01
In this Letter, the global stability of delayed fuzzy cellular neural networks (FCNN) with either constant delays or time varying delays is proposed. Firstly, we give the existence and uniqueness of the equilibrium point by using the theory of topological degree and the properties of nonsingular M-matrix and the sufficient conditions for ascertaining the global exponential stability by constructing a suitable Lyapunov functional. Secondly, the criteria for guaranteeing the global exponential stability of FCNN with time varying delays are given and the estimation of exponential convergence rate with regard to speed of vary of delays is presented by constructing a suitable Lyapunov functional
International Nuclear Information System (INIS)
Zhang Qun-Jiao; Zhao Jun-Chan
2012-01-01
This paper mainly investigates the exponential synchronization of an inner time-varying complex network with coupling delay. Firstly, the synchronization of complex networks is decoupled into the stability of the corresponding dynamical systems. Based on the Lyapunov function theory, some sufficient conditions to guarantee its stability with any given convergence rate are derived, thus the synchronization of the networks is achieved. Finally, the results are illustrated by a simple time-varying network model with a coupling delay. All involved numerical simulations verify the correctness of the theoretical analysis. (general)
New results on global exponential stability of recurrent neural networks with time-varying delays
Energy Technology Data Exchange (ETDEWEB)
Xu Shengyuan [Department of Automation, Nanjing University of Science and Technology, Nanjing 210094 (China)]. E-mail: syxu02@yahoo.com.cn; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou, Zhejiang 313000 (China); Lu Junwei [School of Electrical and Automation Engineering, Nanjing Normal University, 78 Bancang Street, Nanjing, 210042 (China)
2006-04-03
This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples.
Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay
Sun, Mei; Zeng, Chang-Yan; Tian, Li-Xin
2009-01-01
Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.
Modal Vibration Control in Periodic Time-Varying Structures with Focus on Rotor Blade Systems
DEFF Research Database (Denmark)
Christensen, Rene Hardam; Santos, Ilmar
2004-01-01
of active modal controllers. The main aim is to reduce vibrations in periodic time-varying structures. Special emphasis is given to vibration control of coupled bladed rotor systems. A state feedback modal control law is developed based on modal analysis in periodic time-varying structures. The first step...... in the procedure is a transformation of the model into a time-invariant modal form by applying the modal matrices, which are also periodic time-variant. Due to coupled rotor and blade motions complex vibration modes occur in the modal transformed state space model. This implies that the modal transformed model...
Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2016-01-01
Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....
A Method of Time-Varying Rayleigh Channel Tracking in MIMO Radio System
Institute of Scientific and Technical Information of China (English)
GONG Yan-fei; HE Zi-shu; HAN Chun-lin
2005-01-01
A method of MIMO channel tracking based on Kalman filter and MMSE-DFE is proposed. The Kalman filter tracks the time-varying channel by using the MMSE-DFE decision and the MMSE-DFE conducts the next decision by using the channel estimates produced by the Kalman filter. Polynomial fitting is used to bridge the gap between the channel estimates produced by the Kalman filter and those needed for the DFE decision. Computer simulation demonstrates that this method can track the MIMO time-varying channel effectively.
Modeling polar cap F-region patches using time varying convection
International Nuclear Information System (INIS)
Sojka, J.J.; Bowline, M.D.; Schunk, R.W.; Decker, D.T.; Valladares, C.E.; Sheehan, R.; Anderson, D.N.; Heelis, R.A.
1993-01-01
Here the authors present the results of computerized simulations of the polar cap regions which were able to model the formation of polar cap patches. They used the Utah State University Time-Dependent Ionospheric Model (TDIM) and the Phillips Laboratory (PL) F-region models in this work. By allowing a time varying magnetospheric electric field in the models, they were able to generate the patches. This time varying field generates a convection in the ionosphere. This convection is similar to convective changes observed in the ionosphere at times of southward pointing interplanetary magnetic field, due to changes in the B y component of the IMF
Mean Square Exponential Stability of Stochastic Switched System with Interval Time-Varying Delays
Directory of Open Access Journals (Sweden)
Manlika Rajchakit
2012-01-01
Full Text Available This paper is concerned with mean square exponential stability of switched stochastic system with interval time-varying delays. The time delay is any continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the mean square exponential stability of switched stochastic system with interval time-varying delays and new delay-dependent sufficient conditions for the mean square exponential stability of the switched stochastic system are first established in terms of LMIs. Numerical example is given to show the effectiveness of the obtained result.
Time-Varying Biased Proportional Guidance with Seeker’s Field-of-View Limit
Yang, Zhe; Wang, Hui; Lin, Defu
2016-01-01
Traditional guidance laws with range-to-go information or time-to-go estimation may not be implemented in passive homing missiles since passive seekers cannot measure relative range directly. A time-varying biased proportional guidance law, which only uses line-of-sight (LOS) rate and look angle information, is proposed to satisfy both impact angle constraint and seeker’s field-of-view (FOV) limit. In the proposed guidance law, two time-varying bias terms are applied to divide the trajectory ...
Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
Syed Ali, M.; Balasubramaniam, P.
2008-07-01
In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB.
Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
International Nuclear Information System (INIS)
Syed Ali, M.; Balasubramaniam, P.
2008-01-01
In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB
Optimal critic learning for robot control in time-varying environments.
Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng
2015-10-01
In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.
Systematic Risk Changes, Negative Realized Excess Returns and Time-Varying CAPM Beta
Jiri Novak
2015-01-01
We make two methodological modifications to the method of testing CAPM beta and we show that these significantly affect inferences about the association between CAPM beta and stock returns. While the conventional beta proxy is indeed largely unrelated to realized stock returns (in fact the relationship is slightly negative), using forward-looking beta and eliminating unrealistic assumptions about expected market returns makes it (highly) significant. In addition, we show that complementary em...
The Time-Varying Risk and Return Trade Off in Indian Stock Markets
Mohanty, Roshni; P, Srinivasan
2014-01-01
This paper investigates the relationship between stock market returns and volatility in the Indian stock markets using AR(1)-EGARCH(p, q)-in-Mean model. The study considers daily closing prices of two major indexes of Indian stock exchanges, viz., S&P CNX NIFTY and the BSE-SENSEX of National Stock Exchange (NSE) and Bombay Stock Exchange (BSE), respectively for the period from July 1, 1997 to December 31, 2013. The empirical results show positive but insignificant relationship between stock r...
Survey of risk factors urinary tract infection
A Dehghani; M zahedi; M moezzi; M dafei; H Falahzadeh
2016-01-01
Introduction: Women are very susceptible to urinary tract infections and pregnancy raises the risk of urinary tract infection. In general, little information on the risk factors of urinary tract infection in pregnancy is underway. Urinary tract infection in pregnancy is an important risk factor for pregnancy dire consequences. The purpose of this study is to find risk factors associated with urinary tract infection in pregnant women. Methods: The study was observational and retrospective ...
Do the wealthy have a health advantage? Cardiovascular disease risk factors and wealth.
Hajat, A; Kaufman, J S; Rose, K M; Siddiqi, A; Thomas, J C
2010-12-01
The use of wealth as a measure of socioeconomic status (SES) remains uncommon in epidemiological studies. When used, wealth is often measured crudely and at a single point in time. Our study explores the relationship between wealth and three cardiovascular disease (CVD) risk factors (smoking, obesity and hypertension) in a US population. We improve upon existing literature by using a detailed and validated measure of wealth in a longitudinal setting. We used four waves of data from the Panel Study of Income Dynamics (PSID) collected between 1999 and 2005. Inverse probability weights were employed to control for time-varying confounding and to estimate both relative (risk ratio) and absolute (risk difference) measures of effect. Wealth was defined as inflation-adjusted net worth and specified as a six category variable: one category for those with less than or equal to zero wealth and quintiles of positive wealth. After adjusting for income and other time-varying confounders, as well as baseline covariates, the risk of becoming obese was inversely related to wealth. There was a 40%-89% higher risk of becoming obese among the less wealthy relative to the wealthiest quintile and 11 to 25 excess cases (per 1000 persons) among the less wealthy groups over six years of follow up. Smoking initiation had similar but more moderate effects; risk ratios and differences both revealed a smaller magnitude of effect compared to obesity. Of the three CVD risk factors examined here, hypertension incidence had the weakest association with wealth, showing a smaller increased risk and fewer excess cases among the less wealthy groups. In conclusion, this study found a strong inverse association between wealth and obesity incidence, a moderate inverse association between wealth and smoking initiation and a weak inverse association between wealth and hypertension incidence after controlling for income and other time-varying confounders. Copyright © 2010 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Liu Bingwen
2008-01-01
In this Letter, we consider a class of delayed cellular neural networks with time-varying coefficients. By applying Lyapunov functional method and differential inequality techniques, we establish new results to ensure that all solutions of the networks converge exponentially to zero point
Frequency variations of gravity waves interacting with a time-varying tide
Energy Technology Data Exchange (ETDEWEB)
Huang, C.M.; Zhang, S.D.; Yi, F.; Huang, K.M.; Gan, Q.; Gong, Y. [Wuhan Univ., Hubei (China). School of Electronic Information; Ministry of Education, Wuhan, Hubei (China). Key Lab. of Geospace Environment and Geodesy; State Observatory for Atmospheric Remote Sensing, Wuhan, Hubei (China); Zhang, Y.H. [Nanjing Univ. of Information Science and Technology (China). College of Hydrometeorolgy
2013-11-01
Using a nonlinear, 2-D time-dependent numerical model, we simulate the propagation of gravity waves (GWs) in a time-varying tide. Our simulations show that when aGW packet propagates in a time-varying tidal-wind environment, not only its intrinsic frequency but also its ground-based frequency would change significantly. The tidal horizontal-wind acceleration dominates the GW frequency variation. Positive (negative) accelerations induce frequency increases (decreases) with time. More interestingly, tidal-wind acceleration near the critical layers always causes the GW frequency to increase, which may partially explain the observations that high-frequency GW components are more dominant in the middle and upper atmosphere than in the lower atmosphere. The combination of the increased ground-based frequency of propagating GWs in a time-varying tidal-wind field and the transient nature of the critical layer induced by a time-varying tidal zonal wind creates favorable conditions for GWs to penetrate their originally expected critical layers. Consequently, GWs have an impact on the background atmosphere at much higher altitudes than expected, which indicates that the dynamical effects of tidal-GW interactions are more complicated than usually taken into account by GW parameterizations in global models.
A comparison of time-varying covariates in two smoking cessation interventions for cardiac patients
Prenger, Hendrikje Cornelia; Pieterse, Marcel E.; Braakman-Jansen, Louise Marie Antoinette; Bolman, Catherine; Ruitenbeek-Wiggers, L.; de Vries, H.
2013-01-01
The aim of the study was to explore the time-varying contribution of social cognitive determinants of smoking cessation following an intervention on cessation. Secondary analyses were performed on data from two comparable randomized controlled trials on brief smoking cessation interventions for
International Nuclear Information System (INIS)
Chen, S.-F.
2009-01-01
The asymptotic stability problem for discrete-time systems with time-varying delay subject to saturation nonlinearities is addressed in this paper. In terms of linear matrix inequalities (LMIs), a delay-dependent sufficient condition is derived to ensure the asymptotic stability. A numerical example is given to demonstrate the theoretical results.
Time-varying coefficient estimation in SURE models. Application to portfolio management
DEFF Research Database (Denmark)
Casas, Isabel; Ferreira, Eva; Orbe, Susan
This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases...
Time-varying market integration and expected returns in emerging mrkets
de Jong, F.C.J.M.; de Roon, F.
2001-01-01
We use a simple model in which the expected returns in emerging markets depend on their systematicrisk as measured by their beta relative to the world portfolio as well as on the level ofintegration in that market. The level of integration is a time-varying variable that depends on themarket value
Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.
Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng
2017-01-01
The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.
Bank loan components and the time-varying effects of monetary policy shocks
den Haan, W.J.; Sumner, S.W.; Yamashiro, G.M.
2011-01-01
The impulse response function (IRF) of an aggregate variable is time-varying if the IRFs of its components are different from each other and the relative magnitudes of the components are not constant—two conditions likely to be true in practice. We model the behaviour of loan components and document
Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity
2010-12-10
Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02420 DDRE, 1777...delay U U U U SAR 11 Zach Sweet 781-981-5997 1 Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity Brooke Shrader, Armen
Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior
Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.
2017-01-01
A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.
Delay-dependent exponential stability of cellular neural networks with time-varying delays
International Nuclear Information System (INIS)
Zhang Qiang; Wei Xiaopeng; Xu Jin
2005-01-01
The global exponential stability of cellular neural networks (CNNs) with time-varying delays is analyzed. Two new sufficient conditions ensuring global exponential stability for delayed CNNs are obtained. The conditions presented here are related to the size of delay. The stability results improve the earlier publications. Two examples are given to demonstrate the effectiveness of the obtained results
Exponential stability of switched linear systems with time-varying delay
Directory of Open Access Journals (Sweden)
Satiracoo Pairote
2007-11-01
Full Text Available We use a Lyapunov-Krasovskii functional approach to establish the exponential stability of linear systems with time-varying delay. Our delay-dependent condition allows to compute simultaneously the two bounds that characterize the exponential stability rate of the solution. A simple procedure for constructing switching rule is also presented.
The time-varying shortest path problem with fuzzy transit costs and speedup
Directory of Open Access Journals (Sweden)
Rezapour Hassan
2016-08-01
Full Text Available In this paper, we focus on the time-varying shortest path problem, where the transit costs are fuzzy numbers. Moreover, we consider this problem in which the transit time can be shortened at a fuzzy speedup cost. Speedup may also be a better decision to find the shortest path from a source vertex to a specified vertex.
DEFF Research Database (Denmark)
Andersen, P.; Skjærbæk, P. S.; Kirkegaard, Poul Henning
with the smoothed quanties which have been obtained from SARCOF. The results show the usefulness of the technique for identification of a time varying civil engineering structure. It is found that all the techniques give reliable estiates of the frequencies of the two lowest modes and the first mode shape. Only...
Lyapunov Functions to Caputo Fractional Neural Networks with Time-Varying Delays
Directory of Open Access Journals (Sweden)
Ravi Agarwal
2018-05-01
Full Text Available One of the main properties of solutions of nonlinear Caputo fractional neural networks is stability and often the direct Lyapunov method is used to study stability properties (usually these Lyapunov functions do not depend on the time variable. In connection with the Lyapunov fractional method we present a brief overview of the most popular fractional order derivatives of Lyapunov functions among Caputo fractional delay differential equations. These derivatives are applied to various types of neural networks with variable coefficients and time-varying delays. We show that quadratic Lyapunov functions and their Caputo fractional derivatives are not applicable in some cases when one studies stability properties. Some sufficient conditions for stability of equilibrium of nonlinear Caputo fractional neural networks with time dependent transmission delays, time varying self-regulating parameters of all units and time varying functions of the connection between two neurons in the network are obtained. The cases of time varying Lipschitz coefficients as well as nonLipschitz activation functions are studied. We illustrate our theory on particular nonlinear Caputo fractional neural networks.
DEFF Research Database (Denmark)
Callot, Laurent; Kristensen, Johannes Tang
the monetary policy response to inflation and business cycle fluctuations in the US by estimating a parsimoniously time varying parameter Taylor rule.We document substantial changes in the policy response of the Fed in the 1970s and 1980s, and since 2007, but also document the stability of this response...
The necessity for a time local dimension in systems with time-varying attractors
DEFF Research Database (Denmark)
Særmark, Knud H; Ashkenazy, Y; Levitan, J
1997-01-01
We show that a simple non-linear system for ordinary differential equations may possess a time-varying attractor dimension. This indicates that it is infeasible to characterize EEG and MEG time series with a single time global dimension. We suggest another measure for the description of non...
Analysis of nonlinear systems with time varying inputs and its application to gain scheduling
Directory of Open Access Journals (Sweden)
J.-T. Lim
1996-01-01
Full Text Available An analytical framework for analysis of a class of nonlinear systems with time varying inputs is presented. It is shown that the trajectories of the transformed nonlinear systems are uniformly bounded with an ultimate bound under certain conditions shown in this paper. The result obtained is useful for applications, in particular, analysis and design of gain scheduling.
DEFF Research Database (Denmark)
Pittalà, Fabio; Msallem, Majdi; Hauske, Fabian N.
2012-01-01
We propose a non-weighted feed-forward equalization method with filter update by averaging channel estimations based on short CAZAC sequences. Three averaging methods are presented and tested by simulations in a time-varying 2×2 MIMO optical system....
Global exponential stability of BAM neural networks with time-varying delays and diffusion terms
International Nuclear Information System (INIS)
Wan Li; Zhou Qinghua
2007-01-01
The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established
Global exponential stability of BAM neural networks with time-varying delays and diffusion terms
Wan, Li; Zhou, Qinghua
2007-11-01
The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.
Etienne, Xiaoli L.; Trujillo-Barrera, Andrés; Hoffman, Linwood A.
2017-01-01
We find distiller's dried grains with solubles (DDGS) prices to be positively correlated with both corn and soybean meal prices in the long run. However, neither corn nor soybean meal prices respond to deviations from this long-run relationship. We also identify strong time-varying dynamic
Scalable Video Streaming Adaptive to Time-Varying IEEE 802.11 MAC Parameters
Lee, Kyung-Jun; Suh, Doug-Young; Park, Gwang-Hoon; Huh, Jae-Doo
This letter proposes a QoS control method for video streaming service over wireless networks. Based on statistical analysis, the time-varying MAC parameters highly related to channel condition are selected to predict available bitrate. Adaptive bitrate control of scalably-encoded video guarantees continuity in streaming service even if the channel condition changes abruptly.
A new time-varying harmonic decomposition structure based on recursive hanning window
Martins, C.H.; Silva, L.R.M.; Duque, C.A.; Cerqueira, A.S.; Teixeira, E.C.; Ribeiro, P.F.
2012-01-01
Analysis of power quality phenomena under time-varying conditions has become an important subject as the complexity of the grid increases. As a consequence, several methods have been developed/applied also to study power quality parameters during transient conditions such as time-frequency methods.
Perfect fluid Bianchi Type-I cosmological models with time varying G ...
Indian Academy of Sciences (India)
Abstract. Bianchi Type-I cosmological models containing perfect fluid with time vary- ing G and Λ have been presented. The solutions obtained represent an expansion scalar θ bearing a constant ratio to the anisotropy in the direction of space-like unit vector λi. Of the two models obtained, one has negative vacuum energy ...
Prevalence, risk factors and risk perception of tuberculosis infection ...
African Journals Online (AJOL)
Prevalence, risk factors and risk perception of tuberculosis infection among medical students and healthcare workers in Johannesburg, South Africa. A van Rie, K McCarthy, L Scott, A Dow, WDF Venter, WS Stevens ...
Synthesizing Risk from Summary Evidence Across Multiple Risk Factors.
Shrier, Ian; Colditz, Graham A; Steele, Russell J
2018-07-01
Although meta-analyses provide summary effect estimates that help advise patient care, patients often want to compare their overall health to the general population. The Harvard Cancer Risk Index was published in 2004 and uses risk ratio estimates and prevalence estimates from original studies across many risk factors to provide an answer to this question. However, the published version of the formula only uses dichotomous risk factors and its derivation was not provided. The objective of this brief report was to provide the derivation of a more general form of the equation that allows the incorporation of risk factors with three or more levels.
Cardiovascular risk factors in children.
Fraporti, Marisete Inês; Scherer Adami, Fernanda; Dutra Rosolen, Michele
2017-10-01
Systemic hypertension is one of the main risk factors for cardiovascular disease (CVD). Early diagnosis and treatment of hypertension in childhood can potentially have a significant impact on future adverse outcomes. To investigate the relationship of diastolic (DBP) and systolic blood pressure (SBP) with anthropometric data and area of residence of children in municipalities of Rio Grande do Sul state, Brazil. This is a cross-sectional study of 709 children between six and nine years of age. Blood pressure, weight, height and waist circumference (WC) were measured. Statistical tests had a maximum significance level of 5% (p≤0.05) and the software used was SPSS version 13.0. Obesity was significantly associated with pre-hypertension, and stage 1 and 2 hypertension as assessed by DBP and SBP (≤0.05); high WC was significantly associated with a classification of pre-hypertension and stage 1 hypertension based on DBP and a classification of stage 1 and 2 hypertension based on SBP (≤0.01). Children living in urban areas had significantly higher mean SBP than those living in rural areas. Those with high WC presented higher SBP and DBP compared to children with normal WC. Obese children showed higher mean SBP and DBP compared to those who were overweight or normal weight and mean SBP and DBP also increased with older age and higher mean body mass index and WC. Copyright © 2017 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.
CDC Behavioral Risk Factor Surveillance System (BRFSS)
U.S. Department of Health & Human Services — The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based system of health surveys that collects information on health risk behaviors, preventive...
Krishnan, M.; Bhowmik, B.; Hazra, B.; Pakrashi, V.
2018-02-01
In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Principal Component Analysis (RPCA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/non-linear-states that indicate damage. Most of the works available in the literature deal with algorithms that require windowing of the gathered data owing to their data-driven nature which renders them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, which motivates the development of the present framework that is amenable for online implementation which could be utilized along with suite experimental and numerical investigations. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. TVAR modeling on the principal component explaining maximum variance is utilized and the damage is identified by tracking the TVAR coefficients. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data without requiring any baseline data. Numerical simulations performed on a 5-dof nonlinear system under white noise excitation and El Centro (also known as 1940 Imperial Valley earthquake) excitation, for different damage scenarios, demonstrate the robustness of the proposed algorithm. The method is further validated on results obtained from case studies involving
An estimation of U.S. gasoline demand. A smooth time-varying cointegration approach
International Nuclear Information System (INIS)
Park, Sung Y.; Zhao, Guochang
2010-01-01
In this paper the U.S. gasoline demand from 1976 to 2008 is estimated using a time-varying cointegrating regression. We find that price elasticity increased rapidly during the late 1970s and then decreased until 1987. After a relatively small-scaled 'increase-decrease' cycle from 1987 to 2000, the price elasticity rose again after 2000. The time-varying change of the elasticities may be explained by the proportion of gasoline consumption to income and fluctuation of the degree of necessity. The result of the error correction model shows that a deviation from a long-run equilibrium is corrected quickly, and the welfare analysis illustrates there may be a gain by shifting the tax scheme from income tax to gasoline tax. (author)
H∞ Control for a Networked Control Model of Systems with Two Additive Time-Varying Delays
Directory of Open Access Journals (Sweden)
Hanyong Shao
2014-01-01
Full Text Available This paper is concerned with H∞ control for a networked control model of systems with two additive time-varying delays. A new Lyapunov functional is constructed to make full use of the information of the delays, and for the derivative of the Lyapunov functional a novel technique is employed to compute a tighter upper bound, which is dependent on the two time-varying delays instead of the upper bounds of them. Then the convex polyhedron method is proposed to check the upper bound of the derivative of the Lyapunov functional. The resulting stability criteria have fewer matrix variables but less conservatism than some existing ones. The stability criteria are applied to designing a state feedback controller, which guarantees that the closed-loop system is asymptotically stable with a prescribed H∞ disturbance attenuation level. Finally examples are given to show the advantages of the stability criteria and the effectiveness of the proposed control method.
Robust stabilisation of time-varying delay systems with probabilistic uncertainties
Jiang, Ning; Xiong, Junlin; Lam, James
2016-09-01
For robust stabilisation of time-varying delay systems, only sufficient conditions are available to date. A natural question is as follows: if the existing sufficient conditions are not satisfied, and hence no controllers can be found, what can one do to improve the stability performance of time-varying delay systems? This question is addressed in this paper when there is a probabilistic structure on the parameter uncertainty set. A randomised algorithm is proposed to design a state-feedback controller, which stabilises the system over the uncertainty domain in a probabilistic sense. The capability of the designed controller is quantified by the probability of stability of the resulting closed-loop system. The accuracy of the solution obtained from the randomised algorithm is also analysed. Finally, numerical examples are used to illustrate the effectiveness and advantages of the developed controller design approach.
Achieving Synchronization in Arrays of Coupled Differential Systems with Time-Varying Couplings
Directory of Open Access Journals (Sweden)
Xinlei Yi
2013-01-01
Full Text Available We study complete synchronization of the complex dynamical networks described by linearly coupled ordinary differential equation systems (LCODEs. Here, the coupling is timevarying in both network structure and reaction dynamics. Inspired by our previous paper (Lu et al. (2007-2008, the extended Hajnal diameter is introduced and used to measure the synchronization in a general differential system. Then we find that the Hajnal diameter of the linear system induced by the time-varying coupling matrix and the largest Lyapunov exponent of the synchronized system play the key roles in synchronization analysis of LCODEs with identity inner coupling matrix. As an application, we obtain a general sufficient condition guaranteeing directed time-varying graph to reach consensus. Example with numerical simulation is provided to show the effectiveness of the theoretical results.
Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure
DEFF Research Database (Denmark)
Amado, Christina; Teräsvirta, Timo
multiplier type misspecification tests. Finite-sample properties of these procedures and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice......In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either ad- ditive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change...... in the conditional and unconditional variances where the transition between regimes over time is smooth. A modelling strategy for these new time-varying parameter GARCH models is developed. It relies on a sequence of Lagrange multiplier tests, and the adequacy of the estimated models is investigated by Lagrange...
Estimation of time-varying reactivity by the H∞ optimal linear filter
International Nuclear Information System (INIS)
Suzuki, Katsuo; Shimazaki, Junya; Watanabe, Koiti
1995-01-01
The problem of estimating the time-varying net reactivity from flux measurements is solved for a point reactor kinetics model using a linear filtering technique in an H ∞ settings. In order to sue this technique, an appropriate dynamical model of the reactivity is constructed that can be embedded into the reactor model as one of its variables. A filter, which minimizes the H ∞ norm of the estimation error power spectrum, operates on neutron density measurements corrupted by noise and provides an estimate of the dynamic net reactivity. Computer simulations are performed to reveal the basic characteristics of the H ∞ optimal filter. The results of the simulation indicate that the filter can be used to determine the time-varying reactivity from neutron density measurements that have been corrupted by noise
Directory of Open Access Journals (Sweden)
Da Sun
2016-01-01
Full Text Available A novel control algorithm based on the modified wave-variable controllers is proposed to achieve accurate position synchronization and reasonable force tracking of the nonlinear single-master-multiple-slave teleoperation system and simultaneously guarantee overall system’s stability in the presence of large time-varying delays. The system stability in different scenarios of human and environment situations has been analyzed. The proposed method is validated through experimental work based on the 3-DOF trilateral teleoperation system consisting of three different manipulators. The experimental results clearly demonstrate the feasibility of the proposed algorithm to achieve high transparency and robust stability in nonlinear single-master-multiple-slave teleoperation system in the presence of time-varying delays.
Structural nested mean models for assessing time-varying effect moderation.
Almirall, Daniel; Ten Have, Thomas; Murphy, Susan A
2010-03-01
This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect. Intermediate causal effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study.
Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System
Directory of Open Access Journals (Sweden)
Ruihong Xie
2017-05-01
Full Text Available This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square error is 1.253 mrad when tracking 10° 0.2 Hz signal.
International Nuclear Information System (INIS)
Yang Dong-Sheng; Liu Zhen-Wei; Liu Zhao-Bing; Zhao Yan
2012-01-01
The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time-varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method. (general)
Directory of Open Access Journals (Sweden)
Cheng Liu
2010-01-01
Full Text Available Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.
An estimation of U.S. gasoline demand. A smooth time-varying cointegration approach
Energy Technology Data Exchange (ETDEWEB)
Park, Sung Y. [Department of Economics, University of Illinois, Urbana, IL 61801 (United States); The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005 (China); Zhao, Guochang [Research School of Economics, College of Business and Economics, The Australian National University, Canberra, ACT 2601 (Australia)
2010-01-15
In this paper the U.S. gasoline demand from 1976 to 2008 is estimated using a time-varying cointegrating regression. We find that price elasticity increased rapidly during the late 1970s and then decreased until 1987. After a relatively small-scaled 'increase-decrease' cycle from 1987 to 2000, the price elasticity rose again after 2000. The time-varying change of the elasticities may be explained by the proportion of gasoline consumption to income and fluctuation of the degree of necessity. The result of the error correction model shows that a deviation from a long-run equilibrium is corrected quickly, and the welfare analysis illustrates there may be a gain by shifting the tax scheme from income tax to gasoline tax. (author)
Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.
2013-09-01
This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.
Cao, Jinde; Song, Qiankun
2006-07-01
In this paper, the exponential stability problem is investigated for a class of Cohen-Grossberg-type bidirectional associative memory neural networks with time-varying delays. By using the analysis method, inequality technique and the properties of an M-matrix, several novel sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. Moreover, the exponential convergence rate is estimated. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions and differentiability of the time-varying delays are removed. Two examples with their simulations are given to show the effectiveness of the obtained results.
International Nuclear Information System (INIS)
Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A
2013-01-01
This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)
Estimation and Properties of a Time-Varying GQARCH(1,1-M Model
Directory of Open Access Journals (Sweden)
Sofia Anyfantaki
2011-01-01
analysis of these models computationally infeasible. This paper outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only ( computational operations, where is the sample size. Furthermore, the theoretical dynamic properties of a time-varying GQARCH(1,1-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.
Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling
International Nuclear Information System (INIS)
Jian-Rui, Chen; Li-Cheng, Jiao; Jian-She, Wu; Xiao-Hua, Wang
2009-01-01
A new general network model for two complex networks with time-varying delay coupling is presented. Then we investigate its synchronization phenomena. The two complex networks of the model differ in dynamic nodes, the number of nodes and the coupling connections. By using adaptive controllers, a synchronization criterion is derived. Numerical examples are given to demonstrate the effectiveness of the obtained synchronization criterion. This study may widen the application range of synchronization, such as in chaotic secure communication. (general)
Testing for Change in Mean of Independent Multivariate Observations with Time Varying Covariance
Directory of Open Access Journals (Sweden)
Mohamed Boutahar
2012-01-01
Full Text Available We consider a nonparametric CUSUM test for change in the mean of multivariate time series with time varying covariance. We prove that under the null, the test statistic has a Kolmogorov limiting distribution. The asymptotic consistency of the test against a large class of alternatives which contains abrupt, smooth and continuous changes is established. We also perform a simulation study to analyze the size distortion and the power of the proposed test.
Robust convergence of Cohen-Grossberg neural networks with time-varying delays
International Nuclear Information System (INIS)
Xiong Wenjun; Ma Deyi; Liang Jinling
2009-01-01
In this paper, robust convergence is studied for the Cohen-Grossberg neural networks (CGNNs) with time-varying delays. By applying the differential inequality and the Lyapunov method, some delay-independent conditions are derived ensuring the robust CGNNs to converge, globally, uniformly and exponentially, to a ball in the state space with a pre-specified convergence rate. Finally, the effectiveness of our results are verified by an illustrative example.
International Nuclear Information System (INIS)
Tu Fenghua; Liao Xiaofeng
2005-01-01
We study the problem of estimating the exponential convergence rate and exponential stability for neural networks with time-varying delay. Some criteria for exponential stability are derived by using the linear matrix inequality (LMI) approach. They are less conservative than the existing ones. Some analytical methods are employed to investigate the bounds on the interconnection matrix and activation functions so that the systems are exponentially stable
Improving Delay-Range-Dependent Stability Condition for Systems with Interval Time-Varying Delay
Directory of Open Access Journals (Sweden)
Wei Qian
2013-01-01
Full Text Available This paper discusses the delay-range-dependent stability for systems with interval time-varying delay. Through defining the new Lyapunov-Krasovskii functional and estimating the derivative of the LKF by introducing new vectors, using free matrices and reciprocally convex approach, the new delay-range-dependent stability conditions are obtained. Two well-known examples are given to illustrate the less conservatism of the proposed theoretical results.
Delay-Dependent Asymptotic Stability of Cohen-Grossberg Models with Multiple Time-Varying Delays
Directory of Open Access Journals (Sweden)
Xiaofeng Liao
2007-01-01
Full Text Available Dynamical behavior of a class of Cohen-Grossberg models with multiple time-varying delays is studied in detail. Sufficient delay-dependent criteria to ensure local and global asymptotic stabilities of the equilibrium of this network are derived by constructing suitable Lyapunov functionals. The obtained conditions are shown to be less conservative and restrictive than those reported in the known literature. Some numerical examples are included to demonstrate our results.
On global exponential stability of high-order neural networks with time-varying delays
International Nuclear Information System (INIS)
Zhang Baoyong; Xu Shengyuan; Li Yongmin; Chu Yuming
2007-01-01
This Letter investigates the problem of stability analysis for a class of high-order neural networks with time-varying delays. The delays are bounded but not necessarily differentiable. Based on the Lyapunov stability theory together with the linear matrix inequality (LMI) approach and the use of Halanay inequality, sufficient conditions guaranteeing the global exponential stability of the equilibrium point of the considered neural networks are presented. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria
On global exponential stability of high-order neural networks with time-varying delays
Energy Technology Data Exchange (ETDEWEB)
Zhang Baoyong [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China)]. E-mail: baoyongzhang@yahoo.com.cn; Xu Shengyuan [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China)]. E-mail: syxu02@yahoo.com.cn; Li Yongmin [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China) and Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)]. E-mail: ymlwww@163.com; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)
2007-06-18
This Letter investigates the problem of stability analysis for a class of high-order neural networks with time-varying delays. The delays are bounded but not necessarily differentiable. Based on the Lyapunov stability theory together with the linear matrix inequality (LMI) approach and the use of Halanay inequality, sufficient conditions guaranteeing the global exponential stability of the equilibrium point of the considered neural networks are presented. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria.
Magnetohydrodynamic flow of a rarefied gas near a time-varying accelerated plate
International Nuclear Information System (INIS)
Mishra, S.P.; Mohapatra, Priti
1975-01-01
The flow of an electrically conducting rarefied gas due to the time-varying motion of an infinite flat plate has been studied in the presence of a uniform magnetic field. The magnetic lines of force are taken to be fixed relative to the fluid. General expressions of the velocity and the skin friction have been compared by means of some qraphs and tables. (author)
A note on "Multicriteria adaptive paths in stochastic, time-varying networks"
DEFF Research Database (Denmark)
Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan
In a recent paper, Opasanon and Miller-Hooks study multicriteria adaptive paths in stochastic time-varying networks. They propose a label correcting algorithm for finding the full set of efficient strategies. In this note we show that their algorithm is not correct, since it is based on a property...... that does not hold in general. Opasanon and Miller-Hooks also propose an algorithm for solving a parametric problem. We give a simplified algorithm which is linear in the input size....
International Nuclear Information System (INIS)
Liang Jinling; Cao Jinde
2003-01-01
Employing general Halanay inequality, we analyze the global exponential stability of a class of reaction-diffusion recurrent neural networks with time-varying delays. Several new sufficient conditions are obtained to ensure existence, uniqueness and global exponential stability of the equilibrium point of delayed reaction-diffusion recurrent neural networks. The results extend and improve the earlier publications. In addition, an example is given to show the effectiveness of the obtained result
Uwate, Y; Nishio, Y; Stoop, R
2009-01-01
We explore the synchronization and switching behavior of a system of two identical van der Pol oscillators coupled by a stochastically timevarying resistor. Triggered by the time-varying resistor, the system of oscillators switches between synchronized and anti-synchronized behavior. We find that the preference of the synchronized/antisynchronized state is determined by the ratio of the probabilities of the two resistor states. The length of the phases of maintained resistor states, however, ...
Reliable Memory Feedback Design for a Class of Nonlinear Fuzzy Systems with Time-varying Delay
Institute of Scientific and Technical Information of China (English)
You-Qing Wang; Dong-Hua Zhou; Li-Heng Liu
2007-01-01
This paper is concerned with the robust reliable memory controller design for a class of fuzzy uncertain systems with time-varying delay. The system under consideration is more general than those in other existent works. The controller, which is dependent on the magnitudes and derivative of the delay, is proposed in terms of linear matrix inequality (LMI). The closed-loop system is asymptotically stable for all admissible uncertainties as well as actuator faults. A numerical example is presented for illustration.
International Nuclear Information System (INIS)
Park, Ju H.; Lee, S.M.; Kwon, O.M.
2009-01-01
For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.
Global exponential stability of fuzzy BAM neural networks with time-varying delays
International Nuclear Information System (INIS)
Zhang Qianhong; Luo Wei
2009-01-01
In this paper, a class of fuzzy bidirectional associated memory (BAM) neural networks with time-varying delays are studied. Employing fixed point theorem, matrix theory and inequality analysis, some sufficient conditions are established for the existence, uniqueness and global exponential stability of equilibrium point. The sufficient conditions are easy to verify at pattern recognition and automatic control. Finally, an example is given to show feasibility and effectiveness of our results.
Passivity of memristive BAM neural networks with leakage and additive time-varying delays
Wang, Weiping; Wang, Meiqi; Luo, Xiong; Li, Lixiang; Zhao, Wenbing; Liu, Linlin; Ping, Yuan
2018-02-01
This paper investigates the passivity of memristive bidirectional associate memory neural networks (MBAMNNs) with leakage and additive time-varying delays. Based on some useful inequalities and appropriate Lyapunov-Krasovskii functionals (LKFs), several delay-dependent conditions for passivity performance are obtained in linear matrix inequalities (LMIs). Moreover, the leakage delays as well as additive delays are considered separately. Finally, numerical simulations are provided to demonstrate the feasibility of the theoretical results.
Time-Varying Dynamic Properties of Offshore Wind Turbines Evaluated by Modal Testing
DEFF Research Database (Denmark)
Damgaard, Mads; Andersen, J. K. F.; Ibsen, Lars Bo
2014-01-01
resonance of the wind turbine structure. In this paper, free vibration tests and a numerical Winkler type approach are used to evaluate the dynamic properties of a total of 30 offshore wind turbines located in the North Sea. Analyses indicate time-varying eigenfrequencies and damping ratios of the lowest...... structural eigenmode. Isolating the oscillation oil damper performance, moveable seabed conditions may lead to the observed time dependency....
International Nuclear Information System (INIS)
Lou, X.; Cui, B.
2008-01-01
In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)
Specification and testing of Multiplicative Time-Varying GARCH models with applications
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
2017-01-01
In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smooth...... is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns....
Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.
2014-01-01
This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437
Time-varying economic dominance in financial markets: A bistable dynamics approach
He, Xue-Zhong; Li, Kai; Wang, Chuncheng
2018-05-01
By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.
Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains
Zaal, P. M. T; Pool, D. M.
2014-01-01
In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.
State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.
Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J
2016-01-15
Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.
A Tentative Application Of Morphological Filters To Time-Varying Images
Billard, D.; Poquillon, B.
1989-03-01
In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.
International Nuclear Information System (INIS)
Lin, Chang Sheng; Tseng, Tse Chuan
2014-01-01
Modal Identification from response data only is studied for structural systems under nonstationary ambient vibration. The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm with time-varying threshold level. In the conventional random decrement algorithm, the threshold level for evaluating random dec signatures is defined as the standard deviation value of response data of the reference channel. The distortion of random dec signatures may be, however, induced by the error involved in noise from the original response data in practice. To improve the accuracy of identification, a modification of the sampling procedure in random decrement algorithm is proposed for modal-parameter identification from the nonstationary ambient response data. The time-varying threshold level is presented for the acquisition of available sample time history to perform averaging analysis, and defined as the temporal root-mean-square function of structural response, which can appropriately describe a wide variety of nonstationary behaviors in reality, such as the time-varying amplitude (variance) of a nonstationary process in a seismic record. Numerical simulations confirm the validity and robustness of the proposed modal-identification method from nonstationary ambient response data under noisy conditions.
Tracking control of time-varying knee exoskeleton disturbed by interaction torque.
Li, Zhan; Ma, Wenhao; Yin, Ziguang; Guo, Hongliang
2017-11-01
Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Two-dimensional phononic crystals with time-varying properties: a multiple scattering analysis
International Nuclear Information System (INIS)
Wright, D W; Cobbold, R S C
2010-01-01
Multiple scattering theory is a versatile two- and three-dimensional method for characterizing the acoustic wave transmission through many scatterers. It provides analytical solutions to wave propagation in scattering structures, and its computational complexity grows logarithmically with the number of scatterers. In this paper we show how the 2D method can be adapted to include the effects of time-varying material parameters. Specifically, a new T-matrix is defined to include the effects of frequency modulation that occurs in time-varying phononic crystals. Solutions were verified against finite difference time domain (FDTD) simulations and showed excellent agreement. This new method enables fast characterization of time-varying phononic crystals without the need to resort to lengthy FDTD simulations. Also, the method of combining T-matrices to form the T-supermatrix remains unchanged provided that the new matrix definitions are used. The method is quite compatible with existing implementations of multiple scattering theory and could be readily extended to three-dimensional multiple scattering theory
The Scalp Time-Varying Networks of N170: Reference, Latency, and Information Flow
Directory of Open Access Journals (Sweden)
Yin Tian
2018-04-01
Full Text Available Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG references, namely, AR (average of all recording channels and reference electrode standardization technique (REST, were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.
Hu, Yong; Kwok, Jerry Weilun; Tse, Jessica Yuk-Hang; Luk, Keith Dip-Kei
2014-06-01
Nonsurgical rehabilitation therapy is a commonly used strategy to treat chronic low back pain (LBP). The selection of the most appropriate therapeutic options is still a big challenge in clinical practices. Surface electromyography (sEMG) topography has been proposed to be an objective assessment of LBP rehabilitation. The quantitative analysis of dynamic sEMG would provide an objective tool of prognosis for LBP rehabilitation. To evaluate the prognostic value of quantitative sEMG topographic analysis and to verify the accuracy of the performance of proposed time-varying topographic parameters for identifying the patients who have better response toward the rehabilitation program. A retrospective study of consecutive patients. Thirty-eight patients with chronic nonspecific LBP and 43 healthy subjects. The accuracy of the time-varying quantitative sEMG topographic analysis for monitoring LBP rehabilitation progress was determined by calculating the corresponding receiver-operating characteristic (ROC) curves. Physiologic measure was the sEMG during lumbar flexion and extension. Patients who suffered from chronic nonspecific LBP without the history of back surgery and any medical conditions causing acute exacerbation of LBP during the clinical test were enlisted to perform the clinical test during the 12-week physiotherapy (PT) treatment. Low back pain patients were classified into two groups: "responding" and "nonresponding" based on the clinical assessment. The responding group referred to the LBP patients who began to recover after the PT treatment, whereas the nonresponding group referred to some LBP patients who did not recover or got worse after the treatment. The results of the time-varying analysis in the responding group were compared with those in the nonresponding group. In addition, the accuracy of the analysis was analyzed through ROC curves. The time-varying analysis showed discrepancies in the root-mean-square difference (RMSD) parameters between the
Risk Factors for Depression : Differential Across Age?
Schaakxs, Roxanne; Comijs, Hannie C; van der Mast, Roos C; Schoevers, Robert A; Beekman, Aartjan T F; Penninx, Brenda W J H
INTRODUCTION: The occurrence of well-established risk factors for depression differs across the lifespan. Risk factors may be more strongly associated with depression at ages when occurrence, and therefore expectance, is relatively low ("on-time off-time" hypothesis). This large-scale study examined
Physical risk factors for neck pain
Ariëns, Geertje A M; Van Mechelen, Willem; Bongers, Paulien M.; Bouter, Lex M.; Van Der Wal, Gerrit
2000-01-01
To identify physical risk factors for neck pain, a systematic review of the literature was carried out. Based on methodological quality and study design, 4 levels of evidence were defined to establish the strength of evidence for the relationship between risk factors and neck pain. Altogether, 22
Data collection on risk factors in pregnancy
Zetstra-van der Woude, Alethea Priscilla
2016-01-01
This thesis aims to investigate the different methods of data collection of risk factors in pregnancy. Several observational epidemiologic study designs were used to assess associations between risk factors and negative birth outcomes. We especially looked at the use of folic acid around pregnancy
Transient risk factors of acute occupational injuries
DEFF Research Database (Denmark)
Østerlund, Anna H; Lander, Flemming; Nielsen, Kent
2017-01-01
Objectives The objectives of this study were to (i) identify transient risk factors of occupational injuries and (ii) determine if the risk varies with age, injury severity, job task, and industry risk level. Method A case-crossover design was used to examine the effect of seven specific transient...... risk factors (time pressure, disagreement with someone, feeling sick, being distracted by someone, non-routine task, altered surroundings, and broken machinery and materials) for occupational injuries. In the study, 1693 patients with occupational injuries were recruited from a total of 4002...... in relation to sex, age, job task, industry risk level, or injury severity. Conclusion Use of a case-crossover design identified several worker-related transient risk factors (time pressure, feeling sick, being distracted by someone) that led to significantly increased risks for occupational injuries...
Risk factors of recurrent anal sphincter ruptures
DEFF Research Database (Denmark)
Jangö, Hanna; Langhoff-Roos, J; Rosthøj, Steen
2012-01-01
Please cite this paper as: Jangö H, Langhoff-Roos J, Rosthøj S, Sakse A. Risk factors of recurrent anal sphincter ruptures: a population-based cohort study. BJOG 2012;00:000-000 DOI: 10.1111/j.1471-0528.2012.03486.x. Objective To determine the incidence and risk factors of recurrent anal sphincter...... were used to determine risk factors of recurrent ASR. Main outcome measures The incidence of recurrent ASR and odds ratios for possible risk factors of recurrent ASR: age, body mass index, grade of ASR, birthweight, head circumference, gestational age, presentation, induction of labour, oxytocin...... augmentation, epidural, episiotomy, vacuum extraction, forceps, shoulder dystocia, delivery interval and year of second delivery. Results Out of 159 446 women, 7336 (4.6%) experienced an ASR at first delivery, and 521 (7.1%) had a recurrent ASR (OR 5.91). The risk factors of recurrent ASR in the multivariate...
Contextual factors in liquidity risk
Bonner, C.; van Lelyveld, I.P.P.; Zymek, R.
2015-01-01
We assess the determinants of banks’ liquidity holdings using data for nearly 7000 banks from 25 OECD countries. We highlight the role of several bank-specific, institutional and policy variables in shaping banks’ liquidity risk management. Our main question is whether liquidity regulation
Intrinsic Risk Factors of Falls in Elderly
Directory of Open Access Journals (Sweden)
Yasmin Amatullah
2016-09-01
Full Text Available Background: Falls are common geriatric problems. The risk factors of falls are the intrinsic and extrinsic risk factors. Studies on falls are scarcely conducted in Indonesia, especially in Bandung. Therefore, this study was conducted to identify the intrinsic risk factors of falls among elderly. Methods: A descriptive study was carried out from August to October 2013 at the Geriatric Clinic of Dr. Hasan Sadikin General Hospital Bandung. Fifty three participants were selected according to the inclusion and exclusion criteria using consecutive sampling. The determined variables in this study were classification of the risk of falls, demographic profile, history of falls, disease, and medications. After the selection, the participants were tested by Timed up-and-go test (TUGT. Moreover, an interview and analysis of medical records were carried out to discover the risk factors of falls. The collected data were analyzed and presented in the form of percentages shown in tables. Results: From 53 patients, women (35.66% were considered to have higher risk of fall than men (18.34%. The majority of patients (66% with the risk of fall were from the age group 60–74 years. The major diseases suffered by patients were hypertension, osteoarthritis and diabetes mellitus. Drugs that were widely used were antihypertensive drugs; analgesic and antipyretic drugs and antidiabetic drugs. Conclusions: There are various intrinsic risk factors of falls in elderly and each of the elderly has more than one intrinsic risk factor of falls.
Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.
Li, Shuai; Li, Yangming
2013-10-28
The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.
Chung, Tammy; Maisto, Stephen A
2016-06-01
An important goal of addictions treatment is to develop a positive association between high levels of confidence and motivation to abstain from substance use. This study modeled the time-varying association between confidence and motivation to abstain from marijuana use among youth in treatment, and the time-varying effect of pre-treatment covariates (marijuana abstinence goal and perceived peer marijuana use) on motivation to abstain. 150 adolescents (75% male, 83% White) in community-based intensive outpatient treatment in Pennsylvania completed a pre-treatment assessment of abstinence goal, perceived peer marijuana use, and motivation and confidence to abstain from marijuana. Ratings of motivation and confidence to abstain also were collected after each session. A time-varying effect model (TVEM) was used to characterize changes in the association between confidence and motivation to abstain (lagged), and included covariates representing pre-treatment abstinence goal and perceived peer marijuana use. Confidence and motivation to abstain from marijuana generally increased during treatment. The association between confidence and motivation strengthened across sessions 1-4, and was maintained through later sessions. Pre-treatment abstinence goal had an early time-limited effect (through session 6) on motivation to abstain. Pre-treatment perception of peer marijuana use had a significant effect on motivation to abstain only at session 2. Early treatment sessions represent a critical period during which the association between confidence and motivation to abstain generally increased. The time-limited effects of pre-treatment characteristics suggest the importance of early sessions in addressing abstinence goal and peer substance use that may impact motivation to abstain from marijuana. Copyright © 2016 Elsevier Ltd. All rights reserved.
Emergence of synchronization and regularity in firing patterns in time-varying neural hypernetworks
Rakshit, Sarbendu; Bera, Bidesh K.; Ghosh, Dibakar; Sinha, Sudeshna
2018-05-01
We study synchronization of dynamical systems coupled in time-varying network architectures, composed of two or more network topologies, corresponding to different interaction schemes. As a representative example of this class of time-varying hypernetworks, we consider coupled Hindmarsh-Rose neurons, involving two distinct types of networks, mimicking interactions that occur through the electrical gap junctions and the chemical synapses. Specifically, we consider the connections corresponding to the electrical gap junctions to form a small-world network, while the chemical synaptic interactions form a unidirectional random network. Further, all the connections in the hypernetwork are allowed to change in time, modeling a more realistic neurobiological scenario. We model this time variation by rewiring the links stochastically with a characteristic rewiring frequency f . We find that the coupling strength necessary to achieve complete neuronal synchrony is lower when the links are switched rapidly. Further, the average time required to reach the synchronized state decreases as synaptic coupling strength and/or rewiring frequency increases. To quantify the local stability of complete synchronous state we use the Master Stability Function approach, and for global stability we employ the concept of basin stability. The analytically derived necessary condition for synchrony is in excellent agreement with numerical results. Further we investigate the resilience of the synchronous states with respect to increasing network size, and we find that synchrony can be maintained up to larger network sizes by increasing either synaptic strength or rewiring frequency. Last, we find that time-varying links not only promote complete synchronization, but also have the capacity to change the local dynamics of each single neuron. Specifically, in a window of rewiring frequency and synaptic coupling strength, we observe that the spiking behavior becomes more regular.
Tracking time-varying cerebral autoregulation in response to changes in respiratory PaCO2
International Nuclear Information System (INIS)
Liu, Jia; Simpson, M David; Allen, Robert; Yan, Jingyu
2010-01-01
Cerebral autoregulation has been studied by linear filter systems, with arterial blood pressure (ABP) as the input and cerebral blood flow velocity (CBFV—from transcranial Doppler Ultrasound) as the output. The current work extends this by using adaptive filters to investigate the dynamics of time-varying cerebral autoregulation during step-wise changes in arterial PaCO 2 . Cerebral autoregulation was transiently impaired in 11 normal adult volunteers, by switching inspiratory air to a CO 2 /air mixture (5% CO 2 , 30% O 2 and 65% N 2 ) for approximately 2 min and then back to the ambient air, causing step-wise changes in end-tidal CO 2 (EtCO 2 ). Simultaneously, ABP and CBFV were recorded continuously. Simulated data corresponding to the same protocol were also generated using an established physiological model, in order to refine the signal analysis methods. Autoregulation was quantified by the time-varying phase lead, estimated from the adaptive filter model. The adaptive filter was able to follow rapid changes in autoregulation, as was confirmed in the simulated data. In the recorded signals, there was a slow decrease in autoregulatory function following the step-wise increase in PaCO 2 (but this did not reach a steady state within approximately 2 min of recording), with a more rapid change in autoregulation on return to normocapnia. Adaptive filter modelling was thus able to demonstrate time-varying autoregulation. It was further noted that impairment and recovery of autoregulation during transient increases in EtCO 2 occur in an asymmetric manner, which should be taken into account when designing experimental protocols for the study of autoregulation
A Kalman-filter based approach to identification of time-varying gene regulatory networks.
Directory of Open Access Journals (Sweden)
Jie Xiong
Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.
The relationship between global oil price shocks and China's output: A time-varying analysis
International Nuclear Information System (INIS)
Cross, Jamie; Nguyen, Bao H.
2017-01-01
We employ a class of time-varying Bayesian vector autoregressive (VAR) models on new standard dataset of China's GDP constructed by to examine the relationship between China's economic growth and global oil market fluctuations between 1992Q1 and 2015Q3. We find that: (1) the time varying parameter VAR with stochastic volatility provides a better fit as compared to it's constant counterparts; (2) the impacts of intertemporal global oil price shocks on China's output are often small and temporary in nature; (3) oil supply and specific oil demand shocks generally produce negative movements in China's GDP growth whilst oil demand shocks tend to have positive effects; (4) domestic output shocks have no significant impact on price or quantity movements within the global oil market. The results are generally robust to three commonly employed indicators of global economic activity: Kilian's global real economic activity index, the metal price index and the global industrial production index, and two alternative oil price metrics: the US refiners' acquisition cost for imported crude oil and the West Texas Intermediate price of crude oil. - Highlights: • A class of time-varying BVARs is used to examine the relationship between China's economic growth and global oil market fluctuations. • The impacts of intertemporal global oil price shocks on China's output are often small and temporary in nature. • Oil supply and specific oil demand shocks generally produce negative movements in China's GDP growth while oil demand shocks tend to have positive effects. • Domestic output shocks have no significant impact on price or quantity movements within the global oil market.
Handling Interfaces and Time-varying Properties in Radionuclide Transport Models
Energy Technology Data Exchange (ETDEWEB)
Robinson, Peter; Watson, Claire (Quintessa Ltd., Henley-on-Thames (United Kingdom))
2010-12-15
This report documents studies undertaken by Quintessa during 2010 in preparation for the SR-Site review that will be initiated by SSM in 2011. The studies relate to consequence analysis calculations, that is to the calculation of radionuclide release and transport if a canister is breached. A sister report documents modelling work undertaken to investigate the coupled processes relevant to copper corrosion and buffer erosion. The Q{sub eq} concept is an important part of SKB's current methodology for radionuclide transport using one-dimensional transport modelling; it is used in particular to model transport at the buffer/fracture interface. Quintessa's QPAC code has been used to investigate the Q{sub eq} approach and to explore the importance of heterogeneity in the fracture and spalling on the deposition hole surface. The key conclusions are that: - The basic approach to calculating Q{sub eq} values is sound and can be reproduced in QPAC. - The fracture resistance dominates over the diffusive resistance in the buffer except for the highest velocity cases. - Heterogeneity in the fracture, in terms of uncorrelated random variations in the fracture aperture, tends to reduce releases, so the use of a constant average aperture approach is conservative. - Narrow channels could lead to the same release as larger fractures with the same pore velocity, so a channel enhancement factor of sq root10 should be considered. - A spalling zone that increases the area of contact between flowing water and the buffer has the potential to increase the release significantly and changes the functional dependence of Q{sub eq}frac on the flowing velocity. Quintessa's AMBER software has previously been used to reproduce SKB's one-dimensional transport calculations and AMBER allows the use of time varying properties. This capability has been used to investigate the effects of glacial episodes on radionuclide transport. The main parameters that could be affected are
Handling Interfaces and Time-varying Properties in Radionuclide Transport Models
International Nuclear Information System (INIS)
Robinson, Peter; Watson, Claire
2010-12-01
This report documents studies undertaken by Quintessa during 2010 in preparation for the SR-Site review that will be initiated by SSM in 2011. The studies relate to consequence analysis calculations, that is to the calculation of radionuclide release and transport if a canister is breached. A sister report documents modelling work undertaken to investigate the coupled processes relevant to copper corrosion and buffer erosion. The Q eq concept is an important part of SKB's current methodology for radionuclide transport using one-dimensional transport modelling; it is used in particular to model transport at the buffer/fracture interface. Quintessa's QPAC code has been used to investigate the Q eq approach and to explore the importance of heterogeneity in the fracture and spalling on the deposition hole surface. The key conclusions are that: - The basic approach to calculating Q eq values is sound and can be reproduced in QPAC. - The fracture resistance dominates over the diffusive resistance in the buffer except for the highest velocity cases. - Heterogeneity in the fracture, in terms of uncorrelated random variations in the fracture aperture, tends to reduce releases, so the use of a constant average aperture approach is conservative. - Narrow channels could lead to the same release as larger fractures with the same pore velocity, so a channel enhancement factor of √10 should be considered. - A spalling zone that increases the area of contact between flowing water and the buffer has the potential to increase the release significantly and changes the functional dependence of Q eq frac on the flowing velocity. Quintessa's AMBER software has previously been used to reproduce SKB's one-dimensional transport calculations and AMBER allows the use of time varying properties. This capability has been used to investigate the effects of glacial episodes on radionuclide transport. The main parameters that could be affected are sorption coefficients and flow rates. For both
H∞ Consensus for Multiagent Systems with Heterogeneous Time-Varying Delays
Directory of Open Access Journals (Sweden)
Beibei Wang
2013-01-01
Full Text Available We apply the linear matrix inequality method to consensus and H∞ consensus problems of the single integrator multiagent system with heterogeneous delays in directed networks. To overcome the difficulty caused by heterogeneous time-varying delays, we rewrite the multiagent system into a partially reduced-order system and an integral system. As a result, a particular Lyapunov function is constructed to derive sufficient conditions for consensus of multiagent systems with fixed (switched topologies. We also apply this method to the H∞ consensus of multiagent systems with disturbances and heterogeneous delays. Numerical examples are given to illustrate the theoretical results.
Robust Stabilization of Discrete-Time Systems with Time-Varying Delay: An LMI Approach
Directory of Open Access Journals (Sweden)
Valter J. S. Leite
2008-01-01
Full Text Available Sufficient linear matrix inequality (LMI conditions to verify the robust stability and to design robust state feedback gains for the class of linear discrete-time systems with time-varying delay and polytopic uncertainties are presented. The conditions are obtained through parameter-dependent Lyapunov-Krasovskii functionals and use some extra variables, which yield less conservative LMI conditions. Both problems, robust stability analysis and robust synthesis, are formulated as convex problems where all system matrices can be affected by uncertainty. Some numerical examples are presented to illustrate the advantages of the proposed LMI conditions.
Ponderomotive force of a uniform electromagnetic wave in a time varying dielectric medium
International Nuclear Information System (INIS)
Mori, W.B.; Katsouleas, T.
1992-01-01
A ponderomotive force associated with a uniform electromagnetic wave propagating in a medium with time varying dielectric properties [e.g., ε=ε(x-v 0 t)] is identified. In particular, when a laser ionizes a gas through which it propagates, a force is exerted on the medium at the ionization front that is proportional to (∇ε)E 2 rather than the usual (ε-1)∇E 2 . This force excites a wake in the plasma medium behind the ionization front. The ponderomotive force and wake amplitude are derived and tested with 1D particle-in-cell simulations
Directory of Open Access Journals (Sweden)
Lun Zhai
2014-01-01
Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.
Gold as an Infl ation Hedge in a Time-Varying Coefficient Framework
Beckmann, Joscha; Czudaj, Robert
2012-01-01
This study analyzes the question whether gold provides the ability of hedging against inflation from a new perspective. Using data for four major economies, namely the USA, the UK, the Euro Area, and Japan, we allow for nonlinearity and discriminate between long-run and time-varying short-run dynamics. Thus, we conduct a Markov-switching vector error correction model (MS-VECM) approach for a sample period ranging from January 1970 to December 2011. Our main findings are threefold: First, we s...
Gold as an Infl ation Hedge in a Time-Varying Coeffi cient Framework
Joscha Beckmann; Robert Czudaj
2012-01-01
This study analyzes the question whether gold provides the ability of hedging against inflation from a new perspective. Using data for four major economies, namely the USA, the UK, the Euro Area, and Japan, we allow for nonlinearity and discriminate between long-run and time-varying short-run dynamics. Thus, we conduct a Markov-switching vector error correction model (MS-VECM) approach for a sample period ranging from January 1970 to December 2011. Our main findings are threefold: First, we s...
Distributed Event-Triggered Control of Multiagent Systems with Time-Varying Topology
Directory of Open Access Journals (Sweden)
Jingwei Ma
2014-01-01
Full Text Available This paper studies the consensus of first-order discrete-time multiagent systems, where the interaction topology is time-varying. The event-triggered control is used to update the control input of each agent, and the event-triggering condition is designed based on the combination of the relative states of each agent to its neighbors. By applying the common Lyapunov function method, a sufficient condition for consensus, which is expressed as a group of linear matrix inequalities, is obtained and the feasibility of these linear matrix inequalities is further analyzed. Simulation examples are provided to explain the effectiveness of the theoretical results.
Combined time-varying forecast based on the proper scoring approach for wind power generation
DEFF Research Database (Denmark)
Chen, Xingying; Jiang, Yu; Yu, Kun
2017-01-01
Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error...... distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results...... demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction....
Time-varying exchange rate pass-through: experiences of some industrial countries
Toshitaka Sekine
2006-01-01
This paper estimates exchange rate pass-through of six major industrial countries using a time-varying parameter with stochastic volatility model. Exchange rate pass-through is divided into impacts of exchange rate fluctuations to import prices (first-stage pass-through) and those of import price movements to consumer prices (second-stage pass-through). The paper finds that both stages of pass-through have declined over time for all the sample countries. The decline in second-stage pass-throu...
Scalar Aharonov–Bohm Phase in Ramsey Atom Interferometry under Time-Varying Potential
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Atsuo Morinaga
2016-08-01
Full Text Available In a Ramsey atom interferometer excited by two electromagnetic fields, if atoms are under a time-varying scalar potential during the interrogation time, the phase of the Ramsey fringes shifts owing to the scalar Aharonov–Bohm effect. The phase shift was precisely examined using a Ramsey atom interferometer with a two-photon Raman transition under the second-order Zeeman potential, and a formula for the phase shift was derived. Using the derived formula, the frequency shift due to the scalar Aharonov–Bohm effect in the frequency standards utilizing the Ramsey atom interferometer was discussed.
Multi-disciplinary techniques for understanding time-varying space-based imagery
Casasent, D.; Sanderson, A.; Kanade, T.
1984-06-01
A multidisciplinary program for space-based image processing is reported. This project combines optical and digital processing techniques and pattern recognition, image understanding and artificial intelligence methodologies. Time change image processing was recognized as the key issue to be addressed. Three time change scenarios were defined based on the frame rate of the data change. This report details the recent research on: various statistical and deterministic image features, recognition of sub-pixel targets in time varying imagery, and 3-D object modeling and recognition.
Estimating time-varying RSA to examine psychophysiological linkage of marital dyads.
Gates, Kathleen M; Gatzke-Kopp, Lisa M; Sandsten, Maria; Blandon, Alysia Y
2015-08-01
One of the primary tenets of polyvagal theory dictates that parasympathetic influence on heart rate, often estimated by respiratory sinus arrhythmia (RSA), shifts rapidly in response to changing environmental demands. The current standard analytic approach of aggregating RSA estimates across time to arrive at one value fails to capture this dynamic property within individuals. By utilizing recent methodological developments that enable precise RSA estimates at smaller time intervals, we demonstrate the utility of computing time-varying RSA for assessing psychophysiological linkage (or synchrony) in husband-wife dyads using time-locked data collected in a naturalistic setting. © 2015 Society for Psychophysiological Research.
Analysis on Passivity for Uncertain Neural Networks with Time-Varying Delays
Directory of Open Access Journals (Sweden)
O. M. Kwon
2014-01-01
Full Text Available The problem of passivity analysis for neural networks with time-varying delays and parameter uncertainties is considered. By the consideration of newly constructed Lyapunov-Krasovskii functionals, improved sufficient conditions to guarantee the passivity of the concerned networks are proposed with the framework of linear matrix inequalities (LMIs, which can be solved easily by various efficient convex optimization algorithms. The enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum allowable delay bounds.
International Nuclear Information System (INIS)
Liang Jinling; Cao Jinde
2003-01-01
In this Letter, the problems of boundedness and stability for a general class of non-autonomous recurrent neural networks with variable coefficients and time-varying delays are analyzed via employing Young inequality technique and Lyapunov method. Some simple sufficient conditions are given for boundedness and stability of the solutions for the recurrent neural networks. These results generalize and improve the previous works, and they are easy to check and apply in practice. Two illustrative examples and their numerical simulations are also given to demonstrate the effectiveness of the proposed results
International Nuclear Information System (INIS)
Zhu Xunlin; Wang Youyi
2009-01-01
This Letter studies the exponential stability for a class of neural networks (NNs) with both discrete and distributed time-varying delays. Under weaker assumptions on the activation functions, by defining a more general type of Lyapunov functionals and developing a new convex combination technique, new less conservative and less complex stability criteria are established to guarantee the global exponential stability of the discussed NNs. The obtained conditions are dependent on both discrete and distributed delays, are expressed in terms of linear matrix inequalities (LMIs), and contain fewer decision variables. Numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed conditions.
Gong, Shuqing; Yang, Shaofu; Guo, Zhenyuan; Huang, Tingwen
2018-06-01
The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equations can be transformed into first-order differential equations. Then, a novel controller with a linear diffusive term and discontinuous sign term is designed. By using the controller, the sufficient conditions for assuring the global exponential synchronization of the derive and response neural networks are derived based on Lyapunov stability theory and some inequality techniques. Finally, several numerical simulations are provided to substantiate the effectiveness of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.
Computing and visualizing time-varying merge trees for high-dimensional data
Energy Technology Data Exchange (ETDEWEB)
Oesterling, Patrick [Univ. of Leipzig (Germany); Heine, Christian [Univ. of Kaiserslautern (Germany); Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitry [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Scheuermann, Gerik [Univ. of Leipzig (Germany)
2017-06-03
We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.
Directory of Open Access Journals (Sweden)
Yueyang Li
2014-01-01
Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.
Adaptive control of chaotic systems with stochastic time varying unknown parameters
Energy Technology Data Exchange (ETDEWEB)
Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu
2008-10-15
In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.
Online Estimation of Time-Varying Volatility Using a Continuous-Discrete LMS Algorithm
Directory of Open Access Journals (Sweden)
Jacques Oksman
2008-09-01
Full Text Available The following paper addresses a problem of inference in financial engineering, namely, online time-varying volatility estimation. The proposed method is based on an adaptive predictor for the stock price, built from an implicit integration formula. An estimate for the current volatility value which minimizes the mean square prediction error is calculated recursively using an LMS algorithm. The method is then validated on several synthetic examples as well as on real data. Throughout the illustration, the proposed method is compared with both UKF and offline volatility estimation.
Finite-Time H∞ Filtering for Linear Continuous Time-Varying Systems with Uncertain Observations
Directory of Open Access Journals (Sweden)
Huihong Zhao
2012-01-01
Full Text Available This paper is concerned with the finite-time H∞ filtering problem for linear continuous time-varying systems with uncertain observations and ℒ2-norm bounded noise. The design of finite-time H∞ filter is equivalent to the problem that a certain indefinite quadratic form has a minimum and the filter is such that the minimum is positive. The quadratic form is related to a Krein state-space model according to the Krein space linear estimation theory. By using the projection theory in Krein space, the finite-time H∞ filtering problem is solved. A numerical example is given to illustrate the performance of the H∞ filter.
H∞ state estimation of generalised neural networks with interval time-varying delays
Saravanakumar, R.; Syed Ali, M.; Cao, Jinde; Huang, He
2016-12-01
This paper focuses on studying the H∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov-Krasovskii functional are handled by the Jensen's inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples.
Observation of time-varying photoconductivity and persistent photoconductivity in porous silicon
DEFF Research Database (Denmark)
Frello, T.; Veje, E.; Leistiko, Otto
1996-01-01
We have observed time-varying photoconductivity and persistent photoconductivity in porous silicon, both with time-evolution scales of the order of several minutes or hours. The time evolutions depend on the wavelength and the intensity of the illuminating light. The data indicate the presence...... of at least two competing mechanisms, one is tentatively related to photoinduced creation of charge carriers in the silicon substrate followed by diffusion into the porous silicon layer, and the other is tentatively related to desorption of hydrogen from the porous silicon. ©1996 American Institute of Physics....
Globally exponential stability condition of a class of neural networks with time-varying delays
International Nuclear Information System (INIS)
Liao, T.-L.; Yan, J.-J.; Cheng, C.-J.; Hwang, C.-C.
2005-01-01
In this Letter, the globally exponential stability for a class of neural networks including Hopfield neural networks and cellular neural networks with time-varying delays is investigated. Based on the Lyapunov stability method, a novel and less conservative exponential stability condition is derived. The condition is delay-dependent and easily applied only by checking the Hamiltonian matrix with no eigenvalues on the imaginary axis instead of directly solving an algebraic Riccati equation. Furthermore, the exponential stability degree is more easily assigned than those reported in the literature. Some examples are given to demonstrate validity and excellence of the presented stability condition herein
Resonant e+e- production by time-varying electromagnetic field
International Nuclear Information System (INIS)
Farakos, K.; Koutsoumbas, G.; Tiktopoulos, G.
1990-01-01
As pointed out by Cornwall and Tiktopoulos (CT) strong, time-varying electric fields may produce e + e - pairs in a resonant fashion. This effect could be related to the sharp peaks in the e + e - spectrum observed in the GSI heavy-ion collision experiments. We attempt to go beyond the case of spatially uniform fields discussed by CT. We find that resonant e + e - production indeed takes place for electric fields derived from four-potentials of the form A 1 =A 2 =A 0 =0, A 3 =δ(t)b(x 3 ) provided by b(x) has discontinuities with a jump at least equal to π. (orig.)
Smoldering multiple myeloma risk factors for progression
DEFF Research Database (Denmark)
Sørrig, Rasmus; Klausen, Tobias W; Salomo, Morten
2016-01-01
Several risk scores for disease progression in Smoldering Multiple Myeloma (SMM) patients have been proposed, however, all have been developed using single center registries. To examine risk factors for time to progression (TTP) to Multiple Myeloma (MM) for SMM we analyzed a nationwide population......-based cohort of 321 newly diagnosed SMM patients registered within the Danish Multiple Myeloma Registry between 2005 and 2014. Significant univariable risk factors for TTP were selected for multivariable Cox regression analyses. We found that both an M-protein ≥ 30g/l and immunoparesis significantly influenced......-high risk of transformation to MM. Using only immunoparesis and M-protein ≥ 30g/l, we created a scoring system to identify low, intermediate and high risk SMM. This first population-based study of SMM patients confirms that an M-protein ≥ 30g/l and immunoparesis remain important risk factors for progression...
Musculoskeletal Risk Factors in the Young Athlete.
Moskwa, C A; Nicholas, J A; Goldberg, B
1989-11-01
In brief: Many children and adolescents participate in sports that put them at risk for musculoskeletal injuries. Underlying physical conditions, or risk factors, may predispose them to particular types of sports injuries. Research shows that these risk factors fall into five categories: body type, flexibility, muscle strength, inadequate rehabilitation of a previous injury, and skeletal malalignment and anomalies. Some findings show, for example, that youthful football players who are also heavy have an increased rate of injury, sprains and strains are less common in flexible athletes, and patellar pain or subluxation may be related to a variety of malalignment factors. The authors recommend using a systematic, integrated approach to risk assessment of the athlete, both for detecting risk factors and determining their potential for con tribu ting to a sports injury.
HUMAN PROSTATE CANCER RISK FACTORS
Prostate cancer has the highest prevalence of any non-skin cancer in the human body, with similar likelihood of neoplastic foci found within the prostates of men around the world regardless of diet, occupation, lifestyle, or other factors. Essentially all men with circulating an...
Psychological Risk Factors in Headache
Nicholson, Robert A.; Houle, Timothy T.; Rhudy, Jamie L.; Norton, Peter J.
2008-01-01
Headache is a chronic disease that occurs with varying frequency and results in varying levels of disability. To date, the majority of research and clinical focus has been on the role of biological factors in headache and headache-related disability. However, reliance on a purely biomedical model of headache does not account for all aspects of headache and associated disability. Using a biopsychosocial framework, the current manuscript expands the view of what factors influence headache by considering the role psychological (i.e., cognitive and affective) factors have in the development, course, and consequences of headache. The manuscript initially reviews evidence showing that neural circuits responsible for cognitive–affective phenomena are highly interconnected with the circuitry responsible for headache pain. The manuscript then reviews the influence cognitions (locus of control and self-efficacy) and negative affect (depression, anxiety, and anger) have on the development of headache attacks, perception of headache pain, adherence to prescribed treatment, headache treatment outcome, and headache-related disability. The manuscript concludes with a discussion of the clinical implications of considering psychological factors when treating headache. PMID:17371358
Seismic Risk Perception compared with seismic Risk Factors
Crescimbene, Massimo; La Longa, Federica; Pessina, Vera; Pino, Nicola Alessandro; Peruzza, Laura
2016-04-01
The communication of natural hazards and their consequences is one of the more relevant ethical issues faced by scientists. In the last years, social studies have provided evidence that risk communication is strongly influenced by the risk perception of people. In order to develop effective information and risk communication strategies, the perception of risks and the influencing factors should be known. A theory that offers an integrative approach to understanding and explaining risk perception is still missing. To explain risk perception, it is necessary to consider several perspectives: social, psychological and cultural perspectives and their interactions. This paper presents the results of the CATI survey on seismic risk perception in Italy, conducted by INGV researchers on funding by the DPC. We built a questionnaire to assess seismic risk perception, with a particular attention to compare hazard, vulnerability and exposure perception with the real data of the same factors. The Seismic Risk Perception Questionnaire (SRP-Q) is designed by semantic differential method, using opposite terms on a Likert scale to seven points. The questionnaire allows to obtain the scores of five risk indicators: Hazard, Exposure, Vulnerability, People and Community, Earthquake Phenomenon. The questionnaire was administered by telephone interview (C.A.T.I.) on a statistical sample at national level of over 4,000 people, in the period January -February 2015. Results show that risk perception seems be underestimated for all indicators considered. In particular scores of seismic Vulnerability factor are extremely low compared with house information data of the respondents. Other data collected by the questionnaire regard Earthquake information level, Sources of information, Earthquake occurrence with respect to other natural hazards, participation at risk reduction activities and level of involvement. Research on risk perception aims to aid risk analysis and policy-making by
Risk factors of coercion among psychiatric inpatients
DEFF Research Database (Denmark)
Thomsen, Christoffer; Starkopf, Liis; Hastrup, Lene Halling
2017-01-01
PURPOSE: Reducing the use of coercion among patients with mental disorders has long been a political priority. However, risk factors for coercive measures have primarily been investigated in smaller studies. To reduce the use of coercion, it is crucial to identify people at risk which we aim to do...... and having children, reduced the risk of being subjected to coercive measure (all p risk factors associated with coercive measures. Our findings can assist researchers in identifying patients at risk of coercion and thereby help...... measure (21.9%). Clinical characteristics were the foremost predictors of coercion and patients with organic mental disorder had the highest increased risk of being subjected to a coercive measure (OR = 5.56; 95% CI = 5.04, 6.14). The risk of coercion was the highest in the first admission and decreased...
Zhang, Shangbin; Lu, Siliang; He, Qingbo; Kong, Fanrang
2016-09-01
For rotating machines, the defective faults of bearings generally are represented as periodic transient impulses in acquired signals. The extraction of transient features from signals has been a key issue for fault diagnosis. However, the background noise reduces identification performance of periodic faults in practice. This paper proposes a time-varying singular value decomposition (TSVD) method to enhance the identification of periodic faults. The proposed method is inspired by the sliding window method. By applying singular value decomposition (SVD) to the signal under a sliding window, we can obtain a time-varying singular value matrix (TSVM). Each column in the TSVM is occupied by the singular values of the corresponding sliding window, and each row represents the intrinsic structure of the raw signal, namely time-singular-value-sequence (TSVS). Theoretical and experimental analyses show that the frequency of TSVS is exactly twice that of the corresponding intrinsic structure. Moreover, the signal-to-noise ratio (SNR) of TSVS is improved significantly in comparison with the raw signal. The proposed method takes advantages of the TSVS in noise suppression and feature extraction to enhance fault frequency for diagnosis. The effectiveness of the TSVD is verified by means of simulation studies and applications to diagnosis of bearing faults. Results indicate that the proposed method is superior to traditional methods for bearing fault diagnosis.
Nonlinear systems time-varying parameter estimation: Application to induction motors
Energy Technology Data Exchange (ETDEWEB)
Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)
2008-11-15
In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)
Dynamic IQC-Based Control of Uncertain LFT Systems With Time-Varying State Delay.
Yuan, Chengzhi; Wu, Fen
2016-12-01
This paper presents a new exact-memory delay control scheme for a class of uncertain systems with time-varying state delay under the integral quadratic constraint (IQC) framework. The uncertain system is described as a linear fractional transformation model including a state-delayed linear time-invariant (LTI) system and time-varying structured uncertainties. The proposed exact-memory delay controller consists of a linear state-feedback control law and an additional term that captures the delay behavior of the plant. We first explore the delay stability and the L 2 -gain performance using dynamic IQCs incorporated with quadratic Lyapunov functions. Then, the design of exact-memory controllers that guarantee desired L 2 -gain performance is examined. The resulting delay control synthesis conditions are formulated in terms of linear matrix inequalities, which are convex on all design variables including the scaling matrices associated with the IQC multipliers. The IQC-based exact-memory control scheme provides a novel approach for delay control designs via convex optimization, and advances existing control methods in two important ways: 1) better controlled performance and 2) simplified design procedure with less computational cost. The effectiveness and advantages of the proposed approach have been demonstrated through numerical studies.
Joint optimization of green vehicle scheduling and routing problem with time-varying speeds
Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo
2018-01-01
Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370
Bit-level plane image encryption based on coupled map lattice with time-varying delay
Lv, Xiupin; Liao, Xiaofeng; Yang, Bo
2018-04-01
Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.
Relay selection in cooperative communication systems over continuous time-varying fading channel
Directory of Open Access Journals (Sweden)
Ke Geng
2017-02-01
Full Text Available In this paper, we study relay selection under outdated channel state information (CSI in a decode-and-forward (DF cooperative system. Unlike previous researches on cooperative communication under outdated CSI, we consider that the channel varies continuously over time, i.e., the channel not only changes between relay selection and data transmission but also changes during data transmission. Thus the level of accuracy of the CSI used in relay selection degrades with data transmission. We first evaluate the packet error rate (PER of the cooperative system under continuous time-varying fading channel, and find that the PER performance deteriorates more seriously under continuous time-varying fading channel than when the channel is assumed to be constant during data transmission. Then, we propose a repeated relay selection (RRS strategy to improve the PER performance, in which the forwarded data is divided into multiple segments and relay is reselected before the transmission of each segment based on the updated CSI. Finally, we propose a combined relay selection (CRS strategy which takes advantage of three different relay selection strategies to further mitigate the impact of outdated CSI.
Testing and estimating time-varying elasticities of Swiss gasoline demand
International Nuclear Information System (INIS)
Neto, David
2012-01-01
This paper is intended to test and estimate time-varying elasticities for gasoline demand in Switzerland. For this purpose, a smooth time-varying cointegrating parameters model is investigated in order to describe smooth mutations of the Swiss gasoline demand. The methodology, based on Chebyshev polynomials, is rigorously outlined. Our empirical finding states that the time-invariance assumption does not hold for long-run price and income elasticities. Furthermore they highlight that gasoline demand passed through some periods of sensitivity and non sensitivity with respect to the price. Our empirical statements are of great importance to assess the performance of a gasoline tax as an instrument for CO 2 reduction policy. Indeed, such an instrument can contribute to reduce emissions of greenhouse gases only if the demand is not fully inelastic with respect to the price. Our results suggest that such a carbon-tax would not be always suitable since the price elasticity is found not stable over time and not always significant.
Identification of time-varying structural dynamic systems - An artificial intelligence approach
Glass, B. J.; Hanagud, S.
1992-01-01
An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.
Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings
Chen, Po-Chang; Huang, An-Chyau
2005-04-01
An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.
Uniform stability for time-varying infinite-dimensional discrete linear systems
International Nuclear Information System (INIS)
Kubrusly, C.S.
1988-09-01
Stability for time-varying discrete linear systems in a Banach space is investigated. On the one hand, it established a fairly complete collection of necessary and sufficient conditions for uniform asymptotic equistability for input-free systems. This includes uniform and strong power equistability, and uniform and strong l p -equistability, among other technical conditions which also play essential role in stability theory. On other hand, it is shown that uniform asymptotic equistability for input-free systems is equivalent to each of the following concepts of uniform stability for forced systems: l p -input l p -state, c o -input c o -state, bounded-input bounded-state, l p>1 -input bounded-state, c sub (o)-input bounded-state, and convergent-input bounded-state; which are also equivalent to their nonuniform counterparts. For time-varying convergent systems, the above is also equivalent to convergent-input convergent-state stability. The proofs presented here are all ''elementary'' in the sense that they are based essentially only on the Banach-Steinhaus theorem. (autor) [pt
Quantum theory for magnons and phonons interactions under time-varying magnetic fields
International Nuclear Information System (INIS)
Guerreiro, S.C.
1971-01-01
The magnon-fonon interaction in a ferromagnetic material submited to a time-varying magnetic field is studied by quantum methods. This problem has already been solved by semi-classical methods, and one of its results is that under certain conditions a state of lattice vibrations may be completely converted into spin oscillations. The main proporties of magnetoelastic waves in static magnetic fields and extend the quantum treatment for the time varying magnetic field case is revised. Field operators whose equations of motion are analogous to the classical ones are introduced. Their equations, which appear as a linear system of first order coupled equations, are converted into equations for complex functions by an expansion of the field operators in a time t as linear combinations of the same operators in a time t 0 prior to the variation of the magnetic field. The quantity g vector obtained from the classical solution is quantized and shown to be the linear momentum density of the magnetoelastic system, the quantum field spin density operator is deduced for the two interacting fields, and finally the results are used to study the magnetization and lattice displacement vector fields in the case of a system described by a coherent state of one of its normal modes
Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.
Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C
2014-05-01
Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.
Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns
Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro
2017-05-01
The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.
Finite-Time Reentry Attitude Control Using Time-Varying Sliding Mode and Disturbance Observer
Directory of Open Access Journals (Sweden)
Xuzhong Wu
2015-01-01
Full Text Available This paper presents the finite-time attitude control problem for reentry vehicle with redundant actuators in consideration of planet uncertainties and external disturbances. Firstly, feedback linearization technique is used to cancel the nonlinearities of equations of motion to construct a basic mode for attitude controller. Secondly, two kinds of time-varying sliding mode control methods with disturbance observer are integrated with the basic mode in order to enhance the control performance and system robustness. One method is designed based on boundary layer technique and the other is a novel second-order sliding model control method. The finite-time stability analyses of both resultant closed-loop systems are carried out. Furthermore, after attitude controller produces the torque commands, an optimization control allocation approach is introduced to allocate them into aerodynamic surface deflections and on-off reaction control system thrusts. Finally, the numerical simulation results demonstrate that both of the time-varying sliding mode control methods are robust to uncertainties and disturbances without chattering phenomenon. Moreover, the proposed second-order sliding mode control method possesses better control accuracy.
Study on the Variation of Groundwater Level under Time-varying Recharge
Wu, Ming-Chang; Hsieh, Ping-Cheng
2017-04-01
The slopes of the suburbs come to important areas by focusing on the work of soil and water conservation in recent years. The water table inside the aquifer is affected by rainfall, geology and topography, which will result in the change of groundwater discharge and water level. Currently, the way to obtain water table information is to set up the observation wells; however, owing to that the cost of equipment and the wells excavated is too expensive, we develop a mathematical model instead, which might help us to simulate the groundwater level variation. In this study, we will discuss the groundwater level change in a sloping unconfined aquifer with impermeable bottom under time-varying rainfall events. Referring to Child (1971), we employ the Boussinesq equation as the governing equation, and apply the General Integral Transforms Method (GITM) to analyzing the groundwater level after linearizing the Boussinesq equation. After comparing the solution with Verhoest & Troch (2000) and Bansal & Das (2010), we get satisfactory results. To sum up, we have presented an alternative approach to solve the linearized Boussinesq equation for the response of groundwater level in a sloping unconfined aquifer. The present analytical results combine the effect of bottom slope and the time-varying recharge pattern on the water table fluctuations. Owing to the limitation and difficulty of measuring the groundwater level directly, we develop such a mathematical model that we can predict or simulate the variation of groundwater level affected by any rainfall events in advance.
Time-varying metamaterials based on graphene-wrapped microwires: Modeling and potential applications
Salary, Mohammad Mahdi; Jafar-Zanjani, Samad; Mosallaei, Hossein
2018-03-01
The successful realization of metamaterials and metasurfaces requires the judicious choice of constituent elements. In this paper, we demonstrate the implementation of time-varying metamaterials in the terahertz frequency regime by utilizing graphene-wrapped microwires as building blocks and modulation of graphene conductivity through exterior electrical gating. These elements enable enhancement of light-graphene interaction by utilizing optical resonances associated with Mie scattering, yielding a large tunability and modulation depth. We develop a semianalytical framework based on transition-matrix formulation for modeling and analysis of periodic and aperiodic arrays of such time-varying building blocks. The proposed method is validated against full-wave numerical results obtained using the finite-difference time-domain method. It provides an ideal tool for mathematical synthesis and analysis of space-time gradient metamaterials, eliminating the need for computationally expensive numerical models. Moreover, it allows for a wider exploration of exotic space-time scattering phenomena in time-modulated metamaterials. We apply the method to explore the role of modulation parameters in the generation of frequency harmonics and their emerging wavefronts. Several potential applications of such platforms are demonstrated, including frequency conversion, holographic generation of frequency harmonics, and spatiotemporal manipulation of light. The presented results provide key physical insights to design time-modulated functional metadevices using various building blocks and open up new directions in the emerging paradigm of time-modulated metamaterials.
Epidemiology and risk factors of schizophrenia.
Janoutová, Jana; Janácková, Petra; Serý, Omar; Zeman, Tomás; Ambroz, Petr; Kovalová, Martina; Varechová, Katerina; Hosák, Ladislav; Jirík, Vitezslav; Janout, Vladimír
2016-01-01
Schizophrenia is a severe mental disorder that affects approximately one percent of the general population. The pathogenesis of schizophrenia is influenced by many risk factors, both environmental and genetic. The environmental factors include the date of birth, place of birth and seasonal effects, infectious diseases, complications during pregnancy and delivery, substance abuse and stress. At the present time, in addition to environmental factors, genetic factors are assumed to play a role in the development of the schizophrenia. The heritability of schizo- phrenia is up to 80%. If one parent suffers from the condition, the probability that it will be passed down to the offspring is 13%. If it is present in both parents, the risk is more than 20%. The opinions are varied as to the risk factors affecting the development of schizophrenia. Knowing these factors may greatly contribute to prevention of the condition.
Diabetic ketoacidosis: risk factors, mechanisms and management ...
African Journals Online (AJOL)
Diabetic ketoacidosis: risk factors, mechanisms and management strategies in sub-Saharan Africa: a review. ... ketoacidosis is the most common hyperglycaemic emergency in patients with diabetes mellitus, especially type 1 diabetes.
risk factors for abnormal tubal hysterosalpingographic findings
African Journals Online (AJOL)
Administrator
So many presumed risk factors for female tubal infertility are seen among. Nigerian women. ... strategies such as health awareness campaigns against unwanted pregnancy, promotion of responsible ..... of CT findings in acute pyogenic pelvic.
Shoulder Dystocia: Incidence and Risk Factors.
Ouzounian, Joseph G
2016-12-01
Shoulder dystocia complicates ∼1% of vaginal births. Although fetal macrosomia and maternal diabetes are risk factors for shoulder dystocia, for the most part its occurrence remains largely unpredictable and unpreventable.
Risk Factors for Developing Atopic Dermatitis
DEFF Research Database (Denmark)
G. Carson, Charlotte
2013-01-01
The aim of this thesis was to investigate possible risk factors affecting the development of AD. AD is a frequent disease among children and has a substantial impact on the lives of both the child and its family. A better understanding of the disease would enable better treatment, prevention...... and information to the families involved. Previous risk factor studies have been hampered by an unsuitable study design and/or difficulties in standardization when diagnosing AD, which limit their conclusions. In paper I, we conducted a traditional cross-sectional analysis testing 40 possible risk factors...... exposure to dog was the only environmental exposure that significantly reduced the disease manifestation, suggesting other, yet unknown environmental factors affecting the increasing prevalence of AD in children. Length at birth was shown to be inversely associated with the risk of later developing AD...
Awareness of risk factors for cancer
DEFF Research Database (Denmark)
Lagerlund, Magdalena; Hvidberg, Line; Hajdarevic, Senada
2015-01-01
Background: Sweden and Denmark are neighbouring countries with similarities in culture, healthcare, and economics, yet notable differences in cancer statistics. A crucial component of primary prevention is high awareness of risk factors in the general public. We aimed to determine and compare...... awareness of risk factors for cancer between a Danish and a Swedish population sample, and to examine whether there are differences in awareness across age groups. Methods: Data derive from Module 2 of the International Cancer Benchmarking Partnership. Telephone interviews were conducted with 3000 adults...... in Denmark and 3070 in Sweden using the Awareness and Beliefs about Cancer measure. Data reported here relate to awareness of 13 prompted risk factors for cancer. Prevalence ratios with 95 % confidence intervals were calculated to examine associations between country, age, and awareness of risk factors...
THE RISK FACTORS FOR INITIAL REPRODUCTIVE LOSS
Directory of Open Access Journals (Sweden)
Екатерина Игоревна Лебедева
2017-09-01
Conclusion. Mixed somatic and gynecological pathology, abnormalities in hemostasis, combination of inherited and acquired thrombogenic risk factors dominates in women with initial reproductive loss, though only 37,3 % such pregnancies have favorable outcome.
Preventing Cardiovascular Disease Risk Factors through Aerobic ...
African Journals Online (AJOL)
This paper focused on the reduction of cardiovascular disease risk factors, through aerobic exercises. The central argument here is that through exercise there is the tendency for increased strength of the heart muscles. When this is the case, what follows is a reduction in body weight and ultimately less risk on the ...
Risk factors in prevention of drug dependences
Orosova, Ol'ga; Gajdosova, Beata; Madarasova-Geckova, Andrea; Van Dijk, Jitse P.
2007-01-01
The study presents the state-of-art of knowledge of risk factors of drug use as a form of risk behaviour in adolescents in individual, interpersonal, and environmental domain (family, school, society). The attention is paid to general deviation syndrome and to the construct of general tendency to
Risk factors for QTc interval prolongation
Heemskerk, Charlotte P.M.; Pereboom, Marieke; van Stralen, Karlijn; Berger, Florine A.; van den Bemt, Patricia M.L.A.; Kuijper, Aaf F.M.; van der Hoeven, Ruud T M; Mantel-Teeuwisse, Aukje K.; Becker, Matthijs L
2018-01-01
Purpose: Prolongation of the QTc interval may result in Torsade de Pointes, a ventricular arrhythmia. Numerous risk factors for QTc interval prolongation have been described, including the use of certain drugs. In clinical practice, there is much debate about the management of the risks involved. In
Osteoporosis Risk Factors in Eighth Grade Students.
Lysen, Victoria C.; Walker, Robert
1997-01-01
Presents findings from food frequency questionnaires and surveys of 138 Midwestern eighth-grade student-parent pairs. The study examined the incidence of modifiable and nonmodifiable osteoporosis risk factors and compared gender differences. Data analysis indicated that many adolescents possessed several modifiable and nonmodifiable risk factors…
Risk Factors for Homelessness Among US Veterans
Tsai, Jack; Rosenheck, Robert A.
2015-01-01
Homelessness among US veterans has been a focus of research for over 3 decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this is the first systematic review to summarize research on risk factors for homelessness among US veterans and to evaluate the evidence for these risk factors. Thirty-one studies published from 1987 to 2014 were divided into 3 categories: more rigorous studies, less rigorous studies, and studies comparing homeless veterans with homeless nonveterans. The strongest and most consistent risk factors were substance use disorders and mental illness, followed by low income and other income-related factors. There was some evidence that social isolation, adverse childhood experiences, and past incarceration were also important risk factors. Veterans, especially those who served since the advent of the all-volunteer force, were at greater risk for homelessness than other adults. Homeless veterans were generally older, better educated, and more likely to be male, married/have been married, and to have health insurance coverage than other homeless adults. More studies simultaneously addressing premilitary, military, and postmilitary risk factors for veteran homelessness are needed. This review identifies substance use disorders, mental illness, and low income as targets for policies and programs in efforts to end homelessness among veterans. PMID:25595171
Risk factors predisposing to congenital heart defects
International Nuclear Information System (INIS)
Ul Haq, Faheem; Jalil, Fatima; Hashmi, Saman; Jumani, Maliha Iqbal; Imdad, Aamer; Jabeen, Mehnaz; Hashmi, Javad Tauseef; Irfan, Furqan Bin; Imran, Muhammad; Atiq, Mehnaz
2011-01-01
Congenital heart disease (CHD) is associated with multiple risk factors, consanguinity may be one such significant factor. The role of consanguinity in the etiology of CHD is supported by inbreeding studies, which demonstrate an autosomal recessive pattern of inheritance of some congenital heart defects. This study was done to find out the risk factors for CHD. A case-control study was done on pediatric patients at a tertiary care hospital, Aga Khan University Hospital, located in Karachi, Pakistan. A total of 500 patients, 250 cases and 250 controls were included in the study. Amongst the 250 cases (i.e. those diagnosed with CHD), 122 patients (48.8%) were born of consanguineous marriages while in the controls (i.e. non-CHD) only 72 patients (28.9%) showed a consanguinity amongst parents. On multivariate analysis, consanguinity emerged as an independent risk factor for CHD; adjusted odds ratio 2.59 (95% C. I. 1.73 - 3.87). Other risk factors included low birth weight, maternal co-morbidities, family history of CHD and first born child. On the other hand, medications used by the mother during the index pregnancy, maternal age and gender of the child did not significantly increase the risk of developing CHD. Analyses of our results show that parental consanguinity, family history of CHD, maternal co-morbidities, first born child and low birth weight are independent risk factors for CHD
Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis
Directory of Open Access Journals (Sweden)
SU, H.
2011-08-01
Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.
International Nuclear Information System (INIS)
Huang He; Qu Yuzhong; Li Hanxiong
2005-01-01
With the development of intelligent control, switched systems have been widely studied. Here we try to introduce some ideas of the switched systems into the field of neural networks. In this Letter, a class of switched Hopfield neural networks with time-varying delay is investigated. The parametric uncertainty is considered and assumed to be norm bounded. Firstly, the mathematical model of the switched Hopfield neural networks is established in which a set of Hopfield neural networks are used as the individual subsystems and an arbitrary switching rule is assumed; Secondly, robust stability analysis for such switched Hopfield neural networks is addressed based on the Lyapunov-Krasovskii approach. Some criteria are given to guarantee the switched Hopfield neural networks to be globally exponentially stable for all admissible parametric uncertainties. These conditions are expressed in terms of some strict linear matrix inequalities (LMIs). Finally, a numerical example is provided to illustrate our results
Directory of Open Access Journals (Sweden)
Gill R. Tsouri
2009-01-01
Full Text Available A method of overloading subcarriers by multiple transmitters to secure OFDM in wireless time-varying channels is proposed and analyzed. The method is based on reverse piloting, superposition modulation, and joint decoding. It makes use of channel randomness, reciprocity, and fast decorrelation in space to secure OFDM with low overheads on encryption, decryption, and key distribution. These properties make it a good alternative to traditional software-based information security algorithms in systems where the costs associated with such algorithms are an implementation obstacle. A necessary and sufficient condition for achieving information theoretic security in accordance with channel and system parameters is derived. Security by complexity is assessed for cases where the condition for information theoretic security is not satisfied. In addition, practical means for implementing the method are derived including generating robust joint constellations, decoding data with low complexity, and mitigating the effects of imperfections due to mobility, power control errors, and synchronization errors.
Directory of Open Access Journals (Sweden)
Cao Jinde
2011-01-01
Full Text Available Abstract In this paper, an integral sliding mode control approach is presented to investigate synchronization of nonidentical chaotic neural networks with discrete and distributed time-varying delays as well as leakage delay. By considering a proper sliding surface and constructing Lyapunov-Krasovskii functional, as well as employing a combination of the free-weighting matrix method, Newton-Leibniz formulation and inequality technique, a sliding mode controller is designed to achieve the asymptotical synchronization of the addressed nonidentical neural networks. Moreover, a sliding mode control law is also synthesized to guarantee the reachability of the specified sliding surface. The provided conditions are expressed in terms of linear matrix inequalities, and are dependent on the discrete and distributed time delays as well as leakage delay. A simulation example is given to verify the theoretical results.
Decentralized H∞ Control of Interconnected Systems with Time-varying Delays
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Amal Zouhri
2017-01-01
Full Text Available This paper focuses on the problem of delay dependent stability/stabilization of interconnected systems with time-varying delays. The approach is based on a new Lyapunov-Krasovskii functional. A decentralized delay-dependent stability analysis is performed to characterize linear matrix inequalities (LMIs based on the conditions under which every local subsystem of the linear interconnected delay system is asymptotically stable. Then we design a decentralized state-feedback stabilization scheme such that the family of closedloop feedback subsystems enjoys the delay-dependent asymptotic stability for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example and compared with some recent previous ones.
Zhang, Langwen; Xie, Wei; Wang, Jingcheng
2017-11-01
In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.
A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain
2017-07-25
This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.
Almost Periodic Solution for Memristive Neural Networks with Time-Varying Delays
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Huaiqin Wu
2013-01-01
Full Text Available This paper is concerned with the dynamical stability analysis for almost periodic solution of memristive neural networks with time-varying delays. Under the framework of Filippov solutions, by applying the inequality analysis techniques, the existence and asymptotically almost periodic behavior of solutions are discussed. Based on the differential inclusions theory and Lyapunov functional approach, the stability issues of almost periodic solution are investigated, and a sufficient condition for the existence, uniqueness, and global exponential stability of the almost periodic solution is established. Moreover, as a special case, the condition which ensures the global exponential stability of a unique periodic solution is also presented for the considered memristive neural networks. Two examples are given to illustrate the validity of the theoretical results.
On-line statistical processing of radiation detector pulse trains with time-varying count rates
International Nuclear Information System (INIS)
Apostolopoulos, G.
2008-01-01
Statistical analysis is of primary importance for the correct interpretation of nuclear measurements, due to the inherent random nature of radioactive decay processes. This paper discusses the application of statistical signal processing techniques to the random pulse trains generated by radiation detectors. The aims of the presented algorithms are: (i) continuous, on-line estimation of the underlying time-varying count rate θ(t) and its first-order derivative dθ/dt; (ii) detection of abrupt changes in both of these quantities and estimation of their new value after the change point. Maximum-likelihood techniques, based on the Poisson probability distribution, are employed for the on-line estimation of θ and dθ/dt. Detection of abrupt changes is achieved on the basis of the generalized likelihood ratio statistical test. The properties of the proposed algorithms are evaluated by extensive simulations and possible applications for on-line radiation monitoring are discussed
The co-movement of monetary policy and its time-varying nature: A DCCA approach
Rohit, Abhishek; Mitra, Subrata Kumar
2018-02-01
Employing a novel methodology of DCCA cross-correlation coefficient (ρDCCA), this study attempts to provide fresh evidences for the co-movement of monetary policies of the advanced (AEs) as well as the emerging economies (EMEs) vis-à-vis the United States. A higher degree of monetary co-movement as measured by ρDCCA values, is identified for the AEs as compared to the EMEs. Lower co-movement of monetary policy is especially noticeable in the short run for EMEs. We further investigate the time-varying nature of such co-movements for the AEs by splitting the period (1980-2014) into four sub periods and also by performing a rolling window estimation for the entire period to reveal smoother dynamics. Significant evidence of higher monetary coordination is revealed for sub-periods with stronger trade and financial linkages.
Time-varying predictability in crude-oil markets: the case of GCC countries
International Nuclear Information System (INIS)
El Hedi Arouri, Mohamed; Thanh Huong Dinh; Duc Khuong Nguyen
2010-01-01
This paper uses a time-varying parameter model with generalized autoregressive conditional heteroscedasticity effects to examine the dynamic behavior of crude-oil prices for the period February 7, 1997-January 8, 2010. Using data from four countries of the Gulf Cooperation Council, we find evidence of short-term predictability in oil-price changes over time, except for several short sub-periods. However, the hypothesis of convergence towards weak-form informational efficiency is rejected for all markets. In addition, we explore the possibility of structural breaks in the time-paths of the estimated predictability indices and detect only one breakpoint, for the oil markets in Qatar and the United Arab Emirates. Our empirical results therefore call for new empirical research to further gauge the predictability characteristics and the determinants of oil-price changes.
Ghumare, Eshwar; Schrooten, Maarten; Vandenberghe, Rik; Dupont, Patrick
2015-08-01
Kalman filter approaches are widely applied to derive time varying effective connectivity from electroencephalographic (EEG) data. For multi-trial data, a classical Kalman filter (CKF) designed for the estimation of single trial data, can be implemented by trial-averaging the data or by averaging single trial estimates. A general linear Kalman filter (GLKF) provides an extension for multi-trial data. In this work, we studied the performance of the different Kalman filtering approaches for different values of signal-to-noise ratio (SNR), number of trials and number of EEG channels. We used a simulated model from which we calculated scalp recordings. From these recordings, we estimated cortical sources. Multivariate autoregressive model parameters and partial directed coherence was calculated for these estimated sources and compared with the ground-truth. The results showed an overall superior performance of GLKF except for low levels of SNR and number of trials.
A Comparison of Evolutionary Algorithms for Tracking Time-Varying Recursive Systems
Directory of Open Access Journals (Sweden)
White Michael S
2003-01-01
Full Text Available A comparison is made of the behaviour of some evolutionary algorithms in time-varying adaptive recursive filter systems. Simulations show that an algorithm including random immigrants outperforms a more conventional algorithm using the breeder genetic algorithm as the mutation operator when the time variation is discontinuous, but neither algorithm performs well when the time variation is rapid but smooth. To meet this deficit, a new hybrid algorithm which uses a hill climber as an additional genetic operator, applied for several steps at each generation, is introduced. A comparison is made of the effect of applying the hill climbing operator a few times to all members of the population or a larger number of times solely to the best individual; it is found that applying to the whole population yields the better results, substantially improved compared with those obtained using earlier methods.
Measurement of speech levels in the presence of time varying background noise
Pearsons, K. S.; Horonjeff, R.
1982-01-01
Short-term speech level measurements which could be used to note changes in vocal effort in a time varying noise environment were studied. Knowing the changes in speech level would in turn allow prediction of intelligibility in the presence of aircraft flyover noise. Tests indicated that it is possible to use two second samples of speech to estimate long term root mean square speech levels. Other tests were also performed in which people read out loud during aircraft flyover noise. Results of these tests indicate that people do indeed raise their voice during flyovers at a rate of about 3-1/2 dB for each 10 dB increase in background level. This finding is in agreement with other tests of speech levels in the presence of steady state background noise.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Directory of Open Access Journals (Sweden)
Tomoaki Chiba
Full Text Available In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
The time-varying correlation between policy uncertainty and stock returns: Evidence from China
Xiong, Xiong; Bian, Yuxiang; Shen, Dehua
2018-06-01
In this paper, we use a new policy uncertainty index to investigate the time-varying correlation between economic policy uncertainty (EPU) and Chinese stock market returns. The correlation is examined in the period from January 1995 to December 2016. We show that absolute changes in EPU have a significant impact on stock market returns. Specifically, empirical results based on the DCC-GARCH model reveal that the correlation between EPU and stock returns has large fluctuations, especially during a financial crisis; in addition, the impact of EPU on the Shanghai stock market is greater than on the Shenzhen stock market. Robustness results reveal that the impact of EPU on state-owned enterprises is larger than on non-state enterprises. All of these results highlight the important role of EPU in the Chinese stock market, and shed light on such issues for future research.
Off-Line Robust Constrained MPC for Linear Time-Varying Systems with Persistent Disturbances
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P. Bumroongsri
2014-01-01
Full Text Available An off-line robust constrained model predictive control (MPC algorithm for linear time-varying (LTV systems is developed. A novel feature is the fact that both model uncertainty and bounded additive disturbance are explicitly taken into account in the off-line formulation of MPC. In order to reduce the on-line computational burdens, a sequence of explicit control laws corresponding to a sequence of positively invariant sets is computed off-line. At each sampling time, the smallest positively invariant set containing the measured state is determined and the corresponding control law is implemented in the process. The proposed MPC algorithm can guarantee robust stability while ensuring the satisfaction of input and output constraints. The effectiveness of the proposed MPC algorithm is illustrated by two examples.
H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.
Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir
2018-03-01
This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.
Multistability and instability analysis of recurrent neural networks with time-varying delays.
Zhang, Fanghai; Zeng, Zhigang
2018-01-01
This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n-neuronal recurrent neural networks have exactly [Formula: see text] equilibria, [Formula: see text] of which are locally exponentially stable and the others are unstable, where k 0 is a nonnegative integer such that k 0 ≤n. By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Pinning synchronization of memristor-based neural networks with time-varying delays.
Yang, Zhanyu; Luo, Biao; Liu, Derong; Li, Yueheng
2017-09-01
In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Passivity analysis of memristor-based impulsive inertial neural networks with time-varying delays.
Wan, Peng; Jian, Jigui
2018-03-01
This paper focuses on delay-dependent passivity analysis for a class of memristive impulsive inertial neural networks with time-varying delays. By choosing proper variable transformation, the memristive inertial neural networks can be rewritten as first-order differential equations. The memristive model presented here is regarded as a switching system rather than employing the theory of differential inclusion and set-value map. Based on matrix inequality and Lyapunov-Krasovskii functional method, several delay-dependent passivity conditions are obtained to ascertain the passivity of the addressed networks. In addition, the results obtained here contain those on the passivity for the addressed networks without impulse effects as special cases and can also be generalized to other neural networks with more complex pulse interference. Finally, one numerical example is presented to show the validity of the obtained results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Estimating time-varying conditional correlations between stock and foreign exchange markets
Tastan, Hüseyin
2006-02-01
This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.
Parameter Estimation of a Closed Loop Coupled Tank Time Varying System using Recursive Methods
International Nuclear Information System (INIS)
Basir, Siti Nora; Yussof, Hanafiah; Shamsuddin, Syamimi; Selamat, Hazlina; Zahari, Nur Ismarrubie
2013-01-01
This project investigates the direct identification of closed loop plant using discrete-time approach. The uses of Recursive Least Squares (RLS), Recursive Instrumental Variable (RIV) and Recursive Instrumental Variable with Centre-Of-Triangle (RIV + COT) in the parameter estimation of closed loop time varying system have been considered. The algorithms were applied in a coupled tank system that employs covariance resetting technique where the time of parameter changes occur is unknown. The performances of all the parameter estimation methods, RLS, RIV and RIV + COT were compared. The estimation of the system whose output was corrupted with white and coloured noises were investigated. Covariance resetting technique successfully executed when the parameters change. RIV + COT gives better estimates than RLS and RIV in terms of convergence and maximum overshoot
Time-varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article
Grinstead, Jay Henderson; Venkatapathy, Ethiraj; Noyes, Eric A.; Mach, Jeffrey J.; Empey, Daniel M.; White, Todd R.
2014-01-01
A new approach for arc jet testing of thermal protection materials at conditions approximating the time-varying conditions of atmospheric entry was developed and demonstrated. The approach relies upon the spatial variation of heat flux and pressure over a cylindrical test model. By slowly rotating a cylindrical arc jet test model during exposure to an arc jet stream, each point on the test model will experience constantly changing applied heat flux. The predicted temporal profile of heat flux at a point on a vehicle can be replicated by rotating the cylinder at a prescribed speed and direction. An electromechanical test model mechanism was designed, built, and operated during an arc jet test to demonstrate the technique.
Horner, Andrew B; Beauchamp, James W; So, Richard H Y
2009-01-01
Gradated spectral interpolations between musical instrument tone pairs were used to investigate discrimination as a function of time-averaged spectral difference. All possible nonidentical pairs taken from a collection of eight musical instrument sounds consisting of bassoon, clarinet, flute, horn, oboe, saxophone, trumpet, and violin were tested. For each pair, several tones were generated with different balances between the primary and secondary instruments, where the balance was fixed across the duration of each tone. Among primary instruments it was found that changes to horn and bassoon [corrected] were most easily discriminable, while changes to saxophone and trumpet timbres were least discriminable. Among secondary instruments, the clarinet had the strongest effect on discrimination, whereas the bassoon had the least effect. For primary instruments, strong negative correlations were found between discrimination and their spectral incoherences, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting time-varying alterations such as spectral interpolation.
Fault Detection for Non-Gaussian Stochastic Systems with Time-Varying Delay
Directory of Open Access Journals (Sweden)
Tao Li
2013-01-01
Full Text Available Fault detection (FD for non-Gaussian stochastic systems with time-varying delay is studied. The available information for the addressed problem is the input and the measured output probability density functions (PDFs of the system. In this framework, firstly, by constructing an augmented Lyapunov functional, which involves some slack variables and a tuning parameter, a delay-dependent condition for the existence of FD observer is derived in terms of linear matrix inequality (LMI and the fault can be detected through a threshold. Secondly, in order to improve the detection sensitivity performance, the optimal algorithm is applied to minimize the threshold value. Finally, paper-making process example is given to demonstrate the applicability of the proposed approach.
A topological approach to migration and visualization of time-varying volume data
International Nuclear Information System (INIS)
Fujishiro, Issei; Otsuka, Rieko; Hamaoka, Aya; Takeshima, Yuriko; Takahashi, Shigeo
2004-01-01
Rapid advance in high performance computing and measurement technologies has recently made it possible to produce a stupendous amount of time-varying volume datasets in various disciplines. However, there exist a few known visual exploration tools which allow us to investigate the core of their complex behavior effectively. In this article, our previous approach to topological volume skeletonization is extended to capture the topological skeleton of a 4D volumetric field in terms of critical timing. A cyclic information drilldown scheme, termed T-map, is presented, where a wide choice of information visualization techniques are deployed so that the users are allowed to repeatedly squeeze partial spatiotemporal domains of interest until the size gets fitted into an available computing storage space, prior to topologically-accentuated visualization of the pinpointed volumetric domains. A case study with datasets from atomic collision research is performed to illustrate the feasibility of the present method. (author)
Efficiency or speculation? A time-varying analysis of European sovereign debt
Ferreira, Paulo
2018-01-01
The outbreak of the Greek debt crisis caused turmoil in European markets and drew attention to the problem of public debt and its consequences. The increase in the return rates of sovereign debts was one of these consequences. However, like any other asset, sovereign debt returns are expected to have a memoryless behaviour. Analysing a total of 15 European countries (Eurozone and non-Eurozone), and applying a time-varying analysis of the Hurst exponent, we found evidence of long-range memory in sovereign bonds. When analysing the spreads between each bond and the German one, it is possible to conclude that Eurozone countries' spreads show more evidence of long-range dependence. Considering the Eurozone countries most affected by the Eurozone crisis, that long-range dependence is more evident, but started before the crisis, which could be interpreted as possible speculation by investors.
The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory
DEFF Research Database (Denmark)
Govindan, Kannan
2015-01-01
A Vendor Managed Inventory (VMI) partnership places the responsibility on the vendor (rather than on buyers) to schedule purchase orders for inventory replenishment in the supply chain system. In this research, the supply chain network considers the Silver-Meal heuristic with an augmentation...... quantity replenishment policy between both traditional and VMI systems. We consider time-varying stochastic demand in two-echelon (one vendor, multiple retailers) supply chains. This paper seeks to find the supply chain that minimizes system cost through comparing performance between traditional and VMI...... systems. A mathematical model is developed, and total supply chain cost is used as the measure of comparison. The models are applied in both traditional and VMI supply chains based on pharmaceutical industry data, and we focus on total cost difference compared through the use of Adjusted Silver-Meal (ASM...
Linear response approach to active Brownian particles in time-varying activity fields
Merlitz, Holger; Vuijk, Hidde D.; Brader, Joseph; Sharma, Abhinav; Sommer, Jens-Uwe
2018-05-01
In a theoretical and simulation study, active Brownian particles (ABPs) in three-dimensional bulk systems are exposed to time-varying sinusoidal activity waves that are running through the system. A linear response (Green-Kubo) formalism is applied to derive fully analytical expressions for the torque-free polarization profiles of non-interacting particles. The activity waves induce fluxes that strongly depend on the particle size and may be employed to de-mix mixtures of ABPs or to drive the particles into selected areas of the system. Three-dimensional Langevin dynamics simulations are carried out to verify the accuracy of the linear response formalism, which is shown to work best when the particles are small (i.e., highly Brownian) or operating at low activity levels.
Cai, Shuiming; Hao, Junjun; Liu, Zengrong
2011-06-01
This paper studies the synchronization of coupled chaotic systems with time-varying delays in the presence of parameter mismatches by means of periodically intermittent control. Some novel and useful quasisynchronization criteria are obtained by using the methods which are different from the techniques employed in the existing works, and the derived results are less conservative. Especially, a strong constraint on the control width that the control width should be larger than the time delay imposed by the current references is released in this paper. Moreover, our results show that the synchronization criteria depend on the ratio of control width to control period, but not the control width or the control period. Finally, some numerical simulations are given to show the effectiveness of the theoretical results.
Weighted H∞ Filtering for a Class of Switched Linear Systems with Additive Time-Varying Delays
Directory of Open Access Journals (Sweden)
Li-li Li
2015-01-01
Full Text Available This paper is concerned with the problem of weighted H∞ filtering for a class of switched linear systems with two additive time-varying delays, which represent a general class of switched time-delay systems with strong practical background. Combining average dwell time (ADT technique with piecewise Lyapunov functionals, sufficient conditions are established to guarantee the exponential stability and weighted H∞ performance for the filtering error systems. The parameters of the designed switched filters are obtained by solving linear matrix inequalities (LMIs. A modification of Jensen integral inequality is exploited to derive results with less theoretical conservatism and computational complexity. Finally, two examples are given to demonstrate the effectiveness of the proposed method.
Synchronization criterion for Lur'e type complex dynamical networks with time-varying delay
International Nuclear Information System (INIS)
Ji, D.H.; Park, Ju H.; Yoo, W.J.; Won, S.C.; Lee, S.M.
2010-01-01
In this Letter, the synchronization problem for a class of complex dynamical networks in which every identical node is a Lur'e system with time-varying delay is considered. A delay-dependent synchronization criterion is derived for the synchronization of complex dynamical network that represented by Lur'e system with sector restricted nonlinearities. The derived criterion is a sufficient condition for absolute stability of error dynamics between the each nodes and the isolated node. Using a convex representation of the nonlinearity for error dynamics, the stability condition based on the discretized Lyapunov-Krasovskii functional is obtained via LMI formulation. The proposed delay-dependent synchronization criterion is less conservative than the existing ones. The effectiveness of our work is verified through numerical examples.
Directory of Open Access Journals (Sweden)
I PUTU GEDE DIAN GERRY SUWEDAYANA
2016-08-01
Full Text Available The purpose of this research is to forecast the number of Australian tourists arrival to Bali using Time Varying Parameter (TVP model based on inflation of Indonesia and exchange rate AUD to IDR from January 2010 – December 2015 as explanatory variables. TVP model is specified in a state space model and estimated by Kalman filter algorithm. The result shows that the TVP model can be used to forecast the number of Australian tourists arrival to Bali because it satisfied the assumption that the residuals are distributed normally and the residuals in the measurement and transition equations are not correlated. The estimated TVP model is . This model has a value of mean absolute percentage error (MAPE is equal to dan root mean square percentage error (RMSPE is equal to . The number of Australian tourists arrival to Bali for the next five periods is predicted: ; ; ; ; and (January - May 2016.
International Nuclear Information System (INIS)
Xu Shengyuan; Lam, James; Ho, Daniel W.C.
2005-01-01
This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method
Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis
International Nuclear Information System (INIS)
Liu, Yurong; Wang, Zidong; Serrano, Alan; Liu, Xiaohui
2007-01-01
This Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a Lyapunov-Krasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition
An Explicit MOT-TD-VIE Solver for Time Varying Media
Sayed, Sadeed Bin
2016-03-15
An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i.e., flux density and field intensity, are discretized using full and half Schaubert-Wilton-Glisson functions in space. Temporal interpolation is carried out using band limited approximate prolate spherical wave functions. The discretized coupled system of integral equation and constitutive relation is integrated in time using a PE(CE)m type linear multistep scheme. Unlike the existing MOT methods, the resulting explicit MOT scheme allows for straightforward incorporation of the time variation in the dielectric permittivity.
Periodic solution for state-dependent impulsive shunting inhibitory CNNs with time-varying delays.
Şaylı, Mustafa; Yılmaz, Enes
2015-08-01
In this paper, we consider existence and global exponential stability of periodic solution for state-dependent impulsive shunting inhibitory cellular neural networks with time-varying delays. By means of B-equivalence method, we reduce these state-dependent impulsive neural networks system to an equivalent fix time impulsive neural networks system. Further, by using Mawhin's continuation theorem of coincide degree theory and employing a suitable Lyapunov function some new sufficient conditions for existence and global exponential stability of periodic solution are obtained. Previous results are improved and extended. Finally, we give an illustrative example with numerical simulations to demonstrate the effectiveness of our theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
Energy Technology Data Exchange (ETDEWEB)
Yin, Youbing, E-mail: youbing-yin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Choi, Jiwoong, E-mail: jiwoong-choi@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Tawhai, Merryn H., E-mail: m.tawhai@auckland.ac.nz [Auckland Bioengineering Institute, The University of Auckland, Auckland (New Zealand); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States)
2013-07-01
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
Evolution of colloidal dispersions in novel time-varying optical potentials
Koss, Brian Alan
Optical traps use forces exerted by a tightly focused light beam to trap objects from tens of nanometers to tens of micrometers in size. Since their introduction in 1986, optical tweezers have become very useful to biology, chemistry, and soft condensed-matter physics. Work presented here, promises to advance optical tweezers not only in fundamental scientific research, but also in applications outside of the laboratory and into the mainstream of miniaturized manufacturing and diagnostics. By providing unprecedented access to the mesoscopic world, a new generation of optical traps, called Dynamic Holographic Optical Tweezers (HOTs) offers revolutionary new opportunities for fundamental and applied research. To demonstrate this technique, HOTs will be used to pump particles via a new method of transport called Optical Peristalsis (OP). OP is efficient method for transporting mesoscopic objects in three dimensions using short repetitive sequences of holographic optical trapping patterns. Transport in this process is analogous to peristaltic pumping, with the configurations of optical traps mimicking states of a peristaltic pump. While not limited to the deterministic particle transport, OP, can also be a platform to investigate the stochastic limit of particle transport. Advances in recent years have demonstrated that a variety of time-varying perturbations can induce drift in a diffusive system without exerting an overall force. Among these, are thermal ratchet models in which the system is subjected to time-varying energy landscapes that break spatiotemporal symmetry and thereby induce drift. Typically, the potential energy landscape is chosen to be the sawtooth potential. This work describes an alternate class of symmetric thermal ratchet models, that are not sawtooth, and demonstrates their efficacy in biasing the diffusion of colloidal spheres in both the stochastic and deterministic limits. Unlike previous models, each state in this thermal ratchet consists of
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long
2012-01-01
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. PMID:23794749
A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis.
Directory of Open Access Journals (Sweden)
Jessica M Conway
2014-08-01
Full Text Available Simple models of therapy for viral diseases such as hepatitis C virus (HCV or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time.
Toward the integration of European natural gas markets:A time-varying approach
International Nuclear Information System (INIS)
Renou-Maissant, Patricia
2012-01-01
Over the past fifteen years, European gas markets have radically changed. In order to build a single European gas market, a new regulatory framework has been established through three European Gas Directives. The purpose of this article is to investigate the impact of the reforms in the natural gas industry on consumer prices, with a specific focus on gas prices for industrial use. The strength of the relationship between the industrial gas prices of six western European countries is studied by testing the Law of One Price for the period 1991–2009. Estimations were carried out using both cointegration analysis and time-varying parameter models. Results highlight an emerging and on-going process of convergence between the industrial gas prices in western Europe since 2001 for the six EU member states. The strength and the level of convergence differ widely between countries. Strong integration of gas markets in continental Europe, except for the Belgian market, has been established. It appears that the convergence process between continental countries and the UK is not completed. Thus, the integration of European gas markets remains an open issue and the question of how far integration will proceed will still be widely discussed in the coming years. - Highlights: ► We investigate the integration of European natural gas markets. ► We use both cointegration analysis and time-varying parameter models. ► We show the failure of cointegration techniques to take account of evolving processes. ► An emerging and on-going process of convergence between the industrial gas prices is at work. ► Strong integration of gas markets in continental Europe has been established.
Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.
Zheng, Lingxiao; Hedrick, Tyson L; Mittal, Rajat
2013-01-01
Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.
Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.
Directory of Open Access Journals (Sweden)
Lingxiao Zheng
Full Text Available Insect wings can undergo significant chordwise (camber as well as spanwise (twist deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.
Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay
Chunodkar, Apurva A.; Akella, Maruthi R.
2013-12-01
This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.
Time-Varying Distortions of Binaural Information by Bilateral Hearing Aids
Rodriguez, Francisco A.; Portnuff, Cory D. F.; Goupell, Matthew J.; Tollin, Daniel J.
2016-01-01
In patients with bilateral hearing loss, the use of two hearing aids (HAs) offers the potential to restore the benefits of binaural hearing, including sound source localization and segregation. However, existing evidence suggests that bilateral HA users’ access to binaural information, namely interaural time and level differences (ITDs and ILDs), can be compromised by device processing. Our objective was to characterize the nature and magnitude of binaural distortions caused by modern digital behind-the-ear HAs using a variety of stimuli and HA program settings. Of particular interest was a common frequency-lowering algorithm known as nonlinear frequency compression, which has not previously been assessed for its effects on binaural information. A binaural beamforming algorithm was also assessed. Wide dynamic range compression was enabled in all programs. HAs were placed on a binaural manikin, and stimuli were presented from an arc of loudspeakers inside an anechoic chamber. Stimuli were broadband noise bursts, 10-Hz sinusoidally amplitude-modulated noise bursts, or consonant–vowel–consonant speech tokens. Binaural information was analyzed in terms of ITDs, ILDs, and interaural coherence, both for whole stimuli and in a time-varying sense (i.e., within a running temporal window) across four different frequency bands (1, 2, 4, and 6 kHz). Key findings were: (a) Nonlinear frequency compression caused distortions of high-frequency envelope ITDs and significantly reduced interaural coherence. (b) For modulated stimuli, all programs caused time-varying distortion of ILDs. (c) HAs altered the relationship between ITDs and ILDs, introducing large ITD–ILD conflicts in some cases. Potential perceptual consequences of measured distortions are discussed. PMID:27698258
Charbonneau, Jeremy
As the perceived quality of a product is becoming more important in the manufacturing industry, more emphasis is being placed on accurately predicting the sound quality of everyday objects. This study was undertaken to improve upon current prediction techniques with regard to the psychoacoustic descriptor of loudness and an improved binaural summation technique. The feasibility of this project was first investigated through a loudness matching experiment involving thirty-one subjects and pure tones of constant sound pressure level. A dependence of binaural summation on frequency was observed which had previously not been a subject of investigation in the reviewed literature. A follow-up investigation was carried out with forty-eight volunteers and pure tones of constant sensation level. Contrary to existing theories in literature the resulting loudness matches revealed an amplitude versus frequency relationship which confirmed the perceived increase in loudness when a signal was presented to both ears simultaneously as opposed to one ear alone. The resulting trend strongly indicated that the higher the frequency of the presented signal, the greater the increase in observed binaural summation. The results from each investigation were summarized into a single binaural summation algorithm and inserted into an improved time-varying loudness model. Using experimental techniques, it was demonstrated that the updated binaural summation algorithm was a considerable improvement over the state of the art approach for predicting the perceived binaural loudness. The improved function retained the ease of use from the original model while additionally providing accurate estimates of diotic listening conditions from monaural WAV files. It was clearly demonstrated using a validation jury test that the revised time-varying loudness model was a significant improvement over the previously standardized approach.
Local inertial oscillations in the surface ocean generated by time-varying winds
Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing
2015-12-01
A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.
Fluctuating interaction network and time-varying stability of a natural fish community
Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio
2018-02-01
Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.
Atrial fibrillation and bleeding complication - risk factors and risk marker
Breithardt, G.; Ravens, U.; Kirchhof, P.; van Gelder, I. C.
2012-01-01
The development of atrial fibrillation (AF) is closely linked to risk factors like hypertension and heart failure, diabetes mellitus, myocardial infarction and valvular heart disease. These factors partly overlap with those which determine the progression of atrial fibrillation and the incidence of
Hamlyn, Jess; Duhig, Michael; McGrath, John; Scott, James
2013-05-01
Schizophrenia and autism are two poorly understood clinical syndromes that differ in age of onset and clinical profile. However, recent genetic and epidemiological research suggests that these two neurodevelopmental disorders share certain risk factors. The aims of this review are to describe modifiable risk factors that have been identified in both disorders, and, where available, collate salient systematic reviews and meta-analyses that have examined shared risk factors. Based on searches of Medline, Embase and PsycINFO, inspection of review articles and expert opinion, we first compiled a set of candidate modifiable risk factors associated with autism. Where available, we next collated systematic-reviews (with or without meta-analyses) related to modifiable risk factors associated with both autism and schizophrenia. We identified three modifiable risk factors that have been examined in systematic reviews for both autism and schizophrenia. Advanced paternal age was reported as a risk factor for schizophrenia in a single meta-analysis and as a risk factor in two meta-analyses for autism. With respect to pregnancy and birth complications, for autism one meta-analysis identified maternal diabetes and bleeding during pregnancy as risks factors for autism whilst a meta-analysis of eight studies identified obstetric complications as a risk factor for schizophrenia. Migrant status was identified as a risk factor for both autism and schizophrenia. Two separate meta-analyses were identified for each disorder. Despite distinct clinical phenotypes, the evidence suggests that at least some non-genetic risk factors are shared between these two syndromes. In particular, exposure to drugs, nutritional excesses or deficiencies and infectious agents lend themselves to public health interventions. Studies are now needed to quantify any increase in risk of either autism or schizophrenia that is associated with these modifiable environmental factors. Copyright © 2012 Elsevier Inc
Risk factors in neuroleptic malignant syndrome.
Gupta, Vinay; Magon, Rakesh; Mishra, B P; Sidhu, G B S; Mahajan, Ranjiv
2003-01-01
Neuroleptic malignant syndrome (NMS) is an uncommon but potentially serious idiosyncratic response to neuroleptic antipsychotics. It usually affects young males, but the risk has been seen to increase with certain factors including the administration practices of antipsychotic neuroleptics in these individuals. Even though no predictors for NMS are yet known, this article highlights the findings on certain risk factors as seen from a series of fifteen patients who developed NMS. Cautious use of neuroleptics in those at risk, early recognition and institution of immediate management is important.
Epidemiology and risk factors of schizophrenia
Czech Academy of Sciences Publication Activity Database
Janoutová, J.; Janáčková, P.; Šerý, Omar; Zeman, T.; Ambrož, P.; Kovalová, M.; Vařechová, K.; Hosák, L.; Jiřík, V.; Janout, V.
2016-01-01
Roč. 37, č. 1 (2016), s. 1-8 ISSN 0172-780X R&D Projects: GA MZd NT14504 Institutional support: RVO:67985904 Keywords : schizophrenia * risk factors * epidemiology Subject RIV: FQ - Public Health Care, Social Medicine Impact factor: 0.918, year: 2016
Osteonecrosis. Part 1. Risk factors and pathogenesis
Directory of Open Access Journals (Sweden)
Ekaterina Valeriyevna Ilyinykh
2013-01-01
Full Text Available The paper considers different risk factors for osteonecrosis (ON and some aspects of its pathogenesis: impairments in the differentiation of stromal cells, the vascular provision of intraand extravasal genesis, the quality of proper bone tissue due to generalized or local osteoporosis, intravascular coagulation factors contributing to microthrombogenesis. The basic types of ON are identified.
Cardiovascular risk factors and collateral artery formation.
de Groot, D; Pasterkamp, G; Hoefer, I E
2009-12-01
Arterial lumen narrowing and vascular occlusion is the actual cause of morbidity and mortality in atherosclerotic disease. Collateral artery formation (arteriogenesis) refers to an active remodelling of non-functional vascular anastomoses to functional collateral arteries, capable to bypass the site of obstruction and preserve the tissue that is jeopardized by ischaemia. Hemodynamic forces such as shear stress and wall stress play a pivotal role in collateral artery formation, accompanied by the expression of various cytokines and invasion of circulating leucocytes. Arteriogenesis hence represents an important compensatory mechanism for atherosclerotic vessel occlusion. As arteriogenesis mostly occurs when lumen narrowing by atherosclerotic plaques takes place, presence of cardiovascular risk factors (e.g. hypertension, hypercholesterolaemia and diabetes) is highly likely. Risk factors for atherosclerotic disease affect collateral artery growth directly and indirectly by altering hemodynamic forces or influencing cellular function and proliferation. Adequate collateralization varies significantly among atherosclerotic patients, some profit from the presence of extensive collateral networks, whereas others do not. Cardiovascular risk factors could increase the risk of adverse cardiovascular events in certain patients because of the reduced protection through an alternative vascular network. Likewise, drugs primarily thought to control cardiovascular risk factors might contribute or counteract collateral artery growth. This review summarizes current knowledge on the influence of cardiovascular risk factors and the effects of cardiovascular medication on the development of collateral vessels in experimental and clinical studies.
Predictive risk factors for persistent postherniotomy pain
DEFF Research Database (Denmark)
Aasvang, Eske K; Gmaehle, Eliza; Hansen, Jeanette B
2010-01-01
BACKGROUND: Persistent postherniotomy pain (PPP) affects everyday activities in 5-10% of patients. Identification of predisposing factors may help to identify the risk groups and guide anesthetic or surgical procedures in reducing risk for PPP. METHODS: A prospective study was conducted in 464...... patients undergoing open or laparoscopic transabdominal preperitoneal elective groin hernia repair. Primary outcome was identification of risk factors for substantial pain-related functional impairment at 6 months postoperatively assessed by the validated Activity Assessment Scale (AAS). Data on potential...... risk factors for PPP were collected preoperatively (pain from the groin hernia, preoperative AAS score, pain from other body regions, and psychometric assessment). Pain scores were collected on days 7 and 30 postoperatively. Sensory functions including pain response to tonic heat stimulation were...
Prevalence of health risk factors among fishermen
DEFF Research Database (Denmark)
Frantzeskou, Elpida; Jensen, Olaf; Linos, Athena
2014-01-01
Background Studies have shown that fishermen have a higher mortality from cardiovascular diseases, cancer and accidents. The majority of cardiovascular disease is caused by external risk factors such as the diet, tobacco, alcohol and lack of physical activity. The purpose of this paper...... was to review the available information on the prevalence of these preventable risk factors in order to strengthen the preventive strategies. Methods A search for the last decade was done via Medline, Google and Google Scholar with the keywords "diet, tobacco, alcohol, physical exercise, overweight....... Of the Danish fishermen 25%-, 34% and 37% were obese in the 18-24, 25-44 and 45-64 years age groups. Conclusion Health risk factors among fishermen need to be highlighted and further investigated as they represent occupational risks of major impact to chronic diseases prevalence with projections to quality...
Van der Velden, U.; Abbas, F.; Armand, S.; Loos, B. G.; Timmerman, M. F.; Van der Weijden, G. A.; Van Winkelhoff, A. J.; Winkel, E. G.
Objective: To identify risk factors, risk predictors and risk determinants for onset and progression of periodontitis. Material and Methods: For this longitudinal, prospective study all subjects in the age range 15-25 years living in a village of approximately 2000 inhabitants at a tea estate on
Cardiovascular disease risk factors and cognitive impairment.
Nash, David T; Fillit, Howard
2006-04-15
The role of cardiovascular disease risk factors in the occurrence and progression of cognitive impairment has been the subject of a significant number of publications but has not achieved widespread recognition among many physicians and educated laymen. It is apparent that the active treatment of certain of these cardiovascular disease risk factors is accompanied by a reduced risk for cognitive impairment. Patients with hypertension who are treated experience fewer cardiovascular disease events as well as less cognitive impairment than similar untreated patients. Patients who exercise may present with less cognitive impairment, and obesity may increase the risk for cognitive impairment. Lipid abnormalities and genetic markers are associated with an increased risk for cardiovascular disease and cognitive impairment. Autopsy studies have demonstrated a correlation between elevated levels of cholesterol and amyloid deposition in the brain. Research has demonstrated a relation between atherosclerotic obstruction lesions in the circle of Willis and dementia. Diabetes mellitus is associated with an increased risk for cardiovascular disease and cognitive impairment. A number of nonpharmacologic factors have a role in reducing the risk for cognitive impairment. Antioxidants, fatty acids, and micronutrients may have a role, and diets rich in fruits and vegetables and other dietary approaches may improve the outlook for patients considered at risk for cognitive impairment.
[Environmental risk factors for schizophrenia: a review].
Vilain, J; Galliot, A-M; Durand-Roger, J; Leboyer, M; Llorca, P-M; Schürhoff, F; Szöke, A
2013-02-01
Evidence of variations in schizophrenia incidence rates has been found in genetically homogenous populations, depending on changes within time or space of certain environmental characteristics. The consideration of the impact of environmental risk factors in etiopathogenic studies has put the environment in the forefront of research regarding psychotic illnesses. Various environmental factors such as urbanicity, migration, cannabis, childhood traumas, infectious agents, obstetrical complications and psychosocial factors have been associated with the risk of developing schizophrenia. These risk factors can be biological, physical, psychological as well as social and may operate at different times in an individual's life (fetal period, childhood, adolescence and early adulthood). Whilst some of these factors act on an individual level, others act on a populational level, modulating the individual risk. These factors can have a direct action on the development of schizophrenia, or on the other hand act as markers for directly implicated factors that have not yet been identified. This article summarizes the current knowledge on this subject. An extensive literature search was conducted via the search engine Pubmed. Eight risk factors were selected and developed in the following paper: urbanicity (or living in an urban area), cannabis, migration (and ethnic density), obstetrical complications, seasonality of birth, infectious agents (and inflammatory responses), socio-demographic factors and childhood traumas. For each of these factors, we provide information on the importance of the risk, the vulnerability period, hypotheses made on the possible mechanisms behind the factors and the level of proof the current research offers (good, medium, or insufficient) according to the amount, type, quality and concordance of the studies at hand. Some factors, such as cannabis, are "unique" in their influence on the development of schizophrenia since it labels only one risk factor
Cardiovascular risk factors and disease in women.
Gill, Sharon K
2015-05-01
Coronary artery disease and stroke predominantly affect older women as opposed to younger women, but the risk factors that contribute to atherosclerotic cardiovascular disease risk often start in young women. Young women with polycystic ovary syndrome (PCOS), with migraine, and who use oral contraceptive pills (OCPs) have short-term increases in thrombotic complications that can result in coronary events or stroke. Attention should be focused on risk reduction in women of all ages. Screening for and discussing diabetes, hypertension, obesity, smoking, migraine, PCOS, and pregnancy complication history and discussing the pros and cons of hormone and statin medications are part of reducing cardiovascular risk for women. Published by Elsevier Inc.
Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide
DEFF Research Database (Denmark)
Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete
2017-01-01
trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during......People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time...... admission. Most studies are based on low power, thus compromising quality and generalisability. The few studies with sufficient statistical power mainly identified non-modifiable risk predictors such as male gender, diagnosis, or recent deliberate self-harm. Also, the predictive value of these predictors...
Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide
DEFF Research Database (Denmark)
Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete
2017-01-01
People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time...... trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during...... is low. It would be of great benefit if future studies would be based on large samples while focusing on modifiable predictors over the course of an admission, such as hopelessness, depressive symptoms, and family/social situations. This would improve our chances of developing better risk assessment...
Risk factors for recurrent spontaneous epistaxis.
Abrich, Victor; Brozek, Annabelle; Boyle, Timothy R; Chyou, Po-Huang; Yale, Steven H
2014-12-01
To identify risk factors associated with spontaneous recurrent epistaxis. This was a retrospective cohort study assessing patients in the Marshfield Clinic system diagnosed as having epistaxis between January 1, 1991, and January 1, 2011. There were 461 cases with at least 2 episodes of spontaneous epistaxis within 3 years and 912 controls with only 1 episode in the same time frame. More than 50 potential risk factors were investigated, including demographic features, substance use, nasal anatomical abnormalities, nasal infectious and inflammatory processes, medical comorbidities, medications, and laboratory values. A Cox proportional hazards regression modeling approach was used to calculate hazard ratios of epistaxis recurrence. Traditional risk factors for epistaxis, including nasal perforation, nasal septum deviation, rhinitis, sinusitis, and upper respiratory tract infection, did not increase the risk of recurrence. Significant risk factors for recurrent epistaxis included congestive heart failure, diabetes mellitus, hypertension, and a history of anemia. Warfarin use increased the risk of recurrence, independent of international normalized ratio. Aspirin and clopidogrel were not found to increase the risk of recurrence. Few major adverse cardiovascular events were observed within 30 days of the first epistaxis event. Congestive heart failure is an underappreciated risk factor for recurrent epistaxis. Hypertension and diabetes mellitus may induce atherosclerotic changes in the nasal vessels, making them friable and more at risk for bleeding. Patients with recurrent epistaxis may also be more susceptible to developing anemia. Physicians should promote antiplatelet and antithrombotic medication adherence despite an increased propensity for recurrent epistaxis to prevent major adverse cardiovascular events. Copyright © 2014 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
External risk factors affecting construction costs
Mubarak, Husin, Saiful; Oktaviati, Mutia
2017-11-01
Some risk factors can have impacts on the cost, time, and performance. Results of previous studies indicated that the external conditions are among the factors which give effect to the contractor in the completion of the project. The analysis in the study carried out by considering the conditions of the project in the last 15 years in Aceh province, divided into military conflict phase (2000-2004), post tsunami disaster rehabilitation and reconstruction phase (2005-2009), and post-rehabilitation and reconstruction phase (2010-present). This study intended to analyze the impact of external risk factors, primarily related to the impact on project costs and to investigate the influence of the risk factors and construction phases impacted the project cost. Data was collected by using a questionnaire distributed in 15 large companies qualification contractors in Aceh province. Factors analyzed consisted of socio-political, government policies, natural disasters, and monetary conditions. Data were analyzed using statistical application of severity index to measure the level of risk impact. The analysis results presented the tendency of impact on cost can generally be classified as low. There is only one variable classified as high-impact, variable `fuel price increases', which appear on the military conflict and post tsunami disaster rehabilitation and reconstruction periods. The risk impact on costs from the factors and variables classified with high intensity needs a serious attention, especially when the high level impact is followed by the high frequency of occurrences.
[Identification of risk factors for congenital malformations].
Canals C, Andrea; Cavada C, Gabriel; Nazer H, Julio
2014-11-01
The relative importance of congenital malformations as a cause of death in the first year of life is increasing along with the control of preventable causes of perinatal mortality. To identify risk factors for congenital malformations. Retrospective case-control study of births registered in the database of The Latin American Collaborative Study of Congenital Malformations (ECLAMC), in the period 2001-2010. Birth weight and gestational age were significantly lower in cases than controls, behaving as risk factors and associated with a greater severity of congenital malformations. The risk and severity of congenital malformations increased along with mother's age. Fetal growth retardation, a history of congenital malformations in the family, physical factors and acute illnesses of the mother in the first trimester of pregnancy were also significant risk factors for congenital malformations and their severity. The educational level of the mother was a protective factor for congenital malformations and their severity. Variables previously identified as risk factors for congenital malformations, were significantly related with the occurrence of congenital malformations and their severity.
Biological risk factors for deep vein trombosis.
Vayá, Amparo; Mira, Yolanda; Martínez, Marcial; Villa, Piedad; Ferrando, Fernando; Estellés, Amparo; Corella, Dolores; Aznar, Justo
2002-01-01
Hypercoagulable states due either to inherited or acquired thrombotic risk factors are only present in approximately half of cases of DVT, but the causes in the other half, remain unknown. The importance of biological risk factors such as hyperlipidemia, hypofibrinolysis and hemorheological alterations in the pathogenesis of DVT has not been well established. In order to ascertain whether the above mentioned biological factors are associated with DVT and could constitute independent risk factors, we carried out a case-control study in 109 first DVT patients in whom inherited or acquired thrombophilic risk factors had been ruled out and 121 healthy controls age (42+/-15 years) and sex matched. From all the biological variables analyzed (cholesterol, triglycerides, glucose, fibrinogen, erythrocyte aggregation, hematocrit, plasma viscosity and PAI-1) only fibrinogen concentration reached a statistically significant difference on the comparison of means (290+/-73 mg/dl in cases vs 268+/-58 mg/dl in controls, p220 mg/dl, hematocrit >45% and fibrinogen >300 mg/dl was higher in cases than in controls: 38% vs 22%; p30 ng/ml, 37% vs 25% was borderline significant; p=0.055. Multivariate logistic regression analysis showed that cholesterolemia >220 mg/dl and fibrinogen >300 mg/dl constitute independent predictors of venous thrombotic risk. The adjusted OR's were 2.03 (95% CI; 1.12-3.70) for cholesterolemia and 1.94 (95% CI; 1.07-3.55) for fibrinogen. When these two variables combined DVT risk rose about fourfold (3.96; p<0.05). Our results suggest that hypercholesterolemia and hyperfibrinogenemia should be added to the list of known DVT risk factors and we recommend adopting measures to decrease these variables in the population with a high risk of DVT.
Industrial risk factors for colorectal cancer
International Nuclear Information System (INIS)
Lashner, B.A.; Epstein, S.S.
1990-01-01
Colorectal cancer is the second most common malignancy in the United States, and its incidence rates have sharply increased recently, especially in males. Industrial exposures, both occupational and environmental, are important colorectal cancer risk factors that are generally unrecognized by clinicians. Migration studies have documented that colorectal cancer is strongly associated with environmental risk factors. The causal role of occupational exposures is evidenced by a substantial literature associating specific work practices with increased colorectal cancer risks. Industrially related environmental exposures, including polluted drinking water and ionizing radiation, have also been associated with excess risks. Currently, there is a tendency to attribute colorectal cancer, largely or exclusively, to dietary and other lifestyle factors, thus neglecting these industrially related effects. Concerted efforts are needed to recognize the causal role of industrial risk factors and to encourage government and industry to reduce carcinogenic exposures. Furthermore, cost-effective screening programs for high-risk population groups are critically needed to further reduce deaths from colorectal cancer. 143 references
Directory of Open Access Journals (Sweden)
Islam S.M. Khalil
2016-06-01
Full Text Available Targeted therapy using magnetic microparticles and nanoparticles has the potential to mitigate the negative side-effects associated with conventional medical treatment. Major technological challenges still need to be addressed in order to translate these particles into in vivo applications. For example, magnetic particles need to be navigated controllably in vessels against flowing streams of body fluid. This paper describes the motion control of paramagnetic microparticles in the flowing streams of fluidic channels with time-varying flow rates (maximum flow is 35 ml.hr−1. This control is designed using a magnetic-based proportional-derivative (PD control system to compensate for the time-varying flow inside the channels (with width and depth of 2 mm and 1.5 mm, respectively. First, we achieve point-to-point motion control against and along flow rates of 4 ml.hr−1, 6 ml.hr−1, 17 ml.hr−1, and 35 ml.hr−1. The average speeds of single microparticle (with average diameter of 100 μm against flow rates of 6 ml.hr−1 and 30 ml.hr−1 are calculated to be 45 μm.s−1 and 15 μm.s−1, respectively. Second, we implement PD control with disturbance estimation and compensation. This control decreases the steady-state error by 50%, 70%, 73%, and 78% at flow rates of 4 ml.hr−1, 6 ml.hr−1, 17 ml.hr−1, and 35 ml.hr−1, respectively. Finally, we consider the problem of finding the optimal path (minimal kinetic energy between two points using calculus of variation, against the mentioned flow rates. Not only do we find that an optimal path between two collinear points with the direction of maximum flow (middle of the fluidic channel decreases the rise time of the microparticles, but we also decrease the input current that is supplied to the electromagnetic coils by minimizing the kinetic energy of the microparticles, compared to a PD control with disturbance compensation.
Mass Redistribution in the Core and Time-varying Gravity at the Earth's Surface
Kuang, Wei-Jia; Chao, Benjamin F.; Fang, Ming
2003-01-01
The Earth's liquid outer core is in convection, as suggested by the existence of the geomagnetic field in much of the Earth's history. One consequence of the convection is the redistribution of mass resulting from relative motion among fluid parcels with slightly different densities. This time dependent mass redistribution inside the core produces a small perturbation on the gravity field of the Earth. With our numerical dynamo solutions, we find that the mass redistribution (and the resultant gravity field) symmetric about the equator is much stronger than that anti-symmetric about the equator. In particular, J(sub 2) component is the strongest. In addition, the gravity field variation increases with the Rayleigh number that measures the driving force for the geodynamo in the core. With reasonable scaling from the current dynamo solutions, we could expect that at the surface of the Earth, the J(sub 2) variation from the core is on the order of l0(exp -16)/year relative to the mean (i.e. spherically symmetric) gravity field of the Earth. The possible shielding effect due to core-mantle boundary pressure variation loading is likely much smaller and is therefore negligible. Our results suggest that time-varying gravity field perturbation due to core mass redistribution may be measured with modem space geodetic observations, which will result a new means of detecting dynamical processes in the Earth's deep interior.
Replicability of time-varying connectivity patterns in large resting state fMRI samples.
Abrol, Anees; Damaraju, Eswar; Miller, Robyn L; Stephen, Julia M; Claus, Eric D; Mayer, Andrew R; Calhoun, Vince D
2017-12-01
The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Solution to the monoenergetic time-dependent neutron transport equation with a time-varying source
International Nuclear Information System (INIS)
Ganapol, B.D.
1986-01-01
Even though fundamental time-dependent neutron transport problems have existed since the inception of neutron transport theory, it has only been recently that a reliable numerical solution to one of the basic problems has been obtained. Experience in generating numerical solutions to time-dependent transport equations has indicated that the multiple collision formulation is the most versatile numerical technique for model problems. The formulation coupled with a moment reconstruction of each collided flux component has led to benchmark-quality (four- to five-digit accuracy) numerical evaluation of the neutron flux in plane infinite geometry for any degree of scattering anisotropy and for both pulsed isotropic and beam sources. As will be shown in this presentation, this solution can serve as a Green's function, thus extending the previous results to more complicated source situations. Here we will be concerned with a time-varying source at the center of an infinite medium. If accurate, such solutions have both pedagogical and practical uses as benchmarks against which other more approximate solutions designed for a wider class of problems can be compared
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields
Wang, B.
2013-06-01
Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.
Connelly, Blair C.
In order to reduce the emission of pollutants such as soot and NO x from combustion systems, a detailed understanding of pollutant formation is required. In addition to environmental concerns, this is important for a fundamental understanding of flame behavior as significant quantities of soot lower local flame temperatures, increase overall flame length and affect the formation of such temperature-dependent species as NOx. This problem is investigated by carrying out coupled computational and experimental studies of steady and time-varying sooting, coflow diffusion flames. Optical diagnostic techniques are a powerful tool for characterizing combustion systems, as they provide a noninvasive method of probing the environment. Laser diagnostic techniques have added advantages, as systems can be probed with high spectral, temporal and spatial resolution, and with species selectivity. Experimental soot volume fractions were determined by using two-dimensional laser-induced incandescence (LII), calibrated with an on-line extinction measurement, and soot pyrometry. Measurements of soot particle size distributions are made using time-resolved LII (TR-LII). Laser-induced fluorescence measurements are made of NO and formaldehyde. These experimental measurements, and others, are compared with computational results in an effort to understand and model soot formation and to examine the coupled relationship of soot and NO x formation.
Directory of Open Access Journals (Sweden)
Surafel Luleseged Tilahun
2017-01-01
Full Text Available Traffic congestion is one of the main issues in the study of transportation planning and management. It creates different problems including environmental pollution and health problem and incurs a cost which is increasing through years. One-third of this congestion is created by cars searching for parking places. Drivers may be aware that parking places are fully occupied but will drive around hoping that a parking place may become vacant. Opportunistic services, involving learning, predicting, and exploiting Internet of Things scenarios, are able to adapt to dynamic unforeseen situations and have the potential to ease parking search issues. Hence, in this paper, a cooperative dynamic prediction mechanism between multiple agents for parking space availability in the neighborhood, integrating foreseen and unforeseen events and adapting for long-term changes, is proposed. An agent in each parking place will use a dynamic and time varying Markov chain to predict the parking availability and these agents will communicate to produce the parking availability prediction in the whole neighborhood. Furthermore, a learning approach is proposed where the system can adapt to different changes in the parking demand including long-term changes. Simulation results, using synthesized data based on an actual parking lot data from a shopping mall in Geneva, show that the proposed model is promising based on the learning accuracy with service adaptation and performance in different cases.
St-Onge, Guillaume; Young, Jean-Gabriel; Laurence, Edward; Murphy, Charles; Dubé, Louis J.
2018-02-01
We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework on a given degree distribution, we provide a detailed analysis of the stationary state using the rewiring rate to explore the whole range of the time variation of the structure relative to that of the SIS process. This analysis is suitable for the characterization of the phase transition and leads to three main contributions: (1) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (2) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (3) We obtain bounds for the critical exponents of a number of quantities in the stationary state. This allows us to reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon: observables for different degree classes have a different scaling with the infection rate. This phenomenon is followed by the successive activation of the degree classes beyond the epidemic threshold.
Time-varying span efficiency through the wingbeat of desert locusts.
Henningsson, Per; Bomphrey, Richard J
2012-06-07
The flight performance of animals depends greatly on the efficacy with which they generate aerodynamic forces. Accordingly, maximum range, load-lifting capacity and peak accelerations during manoeuvres are all constrained by the efficiency of momentum transfer to the wake. Here, we use high-speed particle image velocimetry (1 kHz) to record flow velocities in the near wake of desert locusts (Schistocerca gregaria, Forskål). We use the measured flow fields to calculate time-varying span efficiency throughout the wing stroke cycle. The locusts are found to operate at a maximum span efficiency of 79 per cent, typically at a plateau of about 60 per cent for the majority of the downstroke, but at lower values during the upstroke. Moreover, the calculated span efficiencies are highest when the largest lift forces are being generated (90% of the total lift is generated during the plateau of span efficiency) suggesting that the combination of wing kinematics and morphology in locust flight perform most efficiently when doing the most work.
Optimum Control for Nonlinear Dynamic Radial Deformation of Turbine Casing with Time-Varying LSSVM
Directory of Open Access Journals (Sweden)
Cheng-Wei Fei
2015-01-01
Full Text Available With the development of the high performance and high reliability of aeroengine, the blade-tip radial running clearance (BTRRC of high pressure turbine seriously influences the reliability and performance of aeroengine, wherein the radial deformation control of turbine casing has to be concerned in BTRRC design. To improve BTRRC design, the optimum control-based probabilistic optimization of turbine casing radial deformation was implemented using time-varying least square support vector machine (T-LSSVM by considering nonlinear material properties and dynamic thermal load. First the T-LSSVM method was proposed and its mathematical model was established. And then the nonlinear dynamic optimal control model of casing radial deformation was constructed with T-LSSVM. Thirdly, through the numerical experiments, the T-LSSVM method is demonstrated to be a promising approach in reducing additional design samples and improving computational efficiency with acceptable computational precision. Through the optimum control-based probabilistic optimization for nonlinear dynamic radial turbine casing deformation, the optimum radial deformation is 7.865 × 10−4 m with acceptable reliability degree 0.995 6, which is reduced by 7.86 × 10−5 m relative to that before optimization. These results validate the effectiveness and feasibility of the proposed T-LSSVM method, which provides a useful insight into casing radial deformation, BTRRC control, and the development of gas turbine with high performance and high reliability.
Robust Stability of Scaled-Four-Channel Teleoperation with Internet Time-Varying Delays
Directory of Open Access Journals (Sweden)
Emma Delgado
2016-04-01
Full Text Available We describe the application of a generic stability framework for a teleoperation system under time-varying delay conditions, as addressed in a previous work, to a scaled-four-channel (γ-4C control scheme. Described is how varying delays are dealt with by means of dynamic encapsulation, giving rise to mu-test conditions for robust stability and offering an appealing frequency technique to deal with the stability robustness of the architecture. We discuss ideal transparency problems and we adapt classical solutions so that controllers are proper, without single or double differentiators, and thus avoid the negative effects of noise. The control scheme was fine-tuned and tested for complete stability to zero of the whole state, while seeking a practical solution to the trade-off between stability and transparency in the Internet-based teleoperation. These ideas were tested on an Internet-based application with two Omni devices at remote laboratory locations via simulations and real remote experiments that achieved robust stability, while performing well in terms of position synchronization and force transparency.
Interactive exploration of large-scale time-varying data using dynamic tracking graphs
Widanagamaachchi, W.
2012-10-01
Exploring and analyzing the temporal evolution of features in large-scale time-varying datasets is a common problem in many areas of science and engineering. One natural representation of such data is tracking graphs, i.e., constrained graph layouts that use one spatial dimension to indicate time and show the "tracks" of each feature as it evolves, merges or disappears. However, for practical data sets creating the corresponding optimal graph layouts that minimize the number of intersections can take hours to compute with existing techniques. Furthermore, the resulting graphs are often unmanageably large and complex even with an ideal layout. Finally, due to the cost of the layout, changing the feature definition, e.g. by changing an iso-value, or analyzing properly adjusted sub-graphs is infeasible. To address these challenges, this paper presents a new framework that couples hierarchical feature definitions with progressive graph layout algorithms to provide an interactive exploration of dynamically constructed tracking graphs. Our system enables users to change feature definitions on-the-fly and filter features using arbitrary attributes while providing an interactive view of the resulting tracking graphs. Furthermore, the graph display is integrated into a linked view system that provides a traditional 3D view of the current set of features and allows a cross-linked selection to enable a fully flexible spatio-temporal exploration of data. We demonstrate the utility of our approach with several large-scale scientific simulations from combustion science. © 2012 IEEE.
Design and implementation of multi-signal and time-varying neural reconstructions.
Nanda, Sumit; Chen, Hanbo; Das, Ravi; Bhattacharjee, Shatabdi; Cuntz, Hermann; Torben-Nielsen, Benjamin; Peng, Hanchuan; Cox, Daniel N; De Schutter, Erik; Ascoli, Giorgio A
2018-01-23
Several efficient procedures exist to digitally trace neuronal structure from light microscopy, and mature community resources have emerged to store, share, and analyze these datasets. In contrast, the quantification of intracellular distributions and morphological dynamics is not yet standardized. Current widespread descriptions of neuron morphology are static and inadequate for subcellular characterizations. We introduce a new file format to represent multichannel information as well as an open-source Vaa3D plugin to acquire this type of data. Next we define a novel data structure to capture morphological dynamics, and demonstrate its application to different time-lapse experiments. Importantly, we designed both innovations as judicious extensions of the classic SWC format, thus ensuring full back-compatibility with popular visualization and modeling tools. We then deploy the combined multichannel/time-varying reconstruction system on developing neurons in live Drosophila larvae by digitally tracing fluorescently labeled cytoskeletal components along with overall dendritic morphology as they changed over time. This same design is also suitable for quantifying dendritic calcium dynamics and tracking arbor-wide movement of any subcellular substrate of interest.
Robust Stability of Scaled-Four-Channel Teleoperation with Internet Time-Varying Delays.
Delgado, Emma; Barreiro, Antonio; Falcón, Pablo; Díaz-Cacho, Miguel
2016-04-26
We describe the application of a generic stability framework for a teleoperation system under time-varying delay conditions, as addressed in a previous work, to a scaled-four-channel (γ-4C) control scheme. Described is how varying delays are dealt with by means of dynamic encapsulation, giving rise to mu-test conditions for robust stability and offering an appealing frequency technique to deal with the stability robustness of the architecture. We discuss ideal transparency problems and we adapt classical solutions so that controllers are proper, without single or double differentiators, and thus avoid the negative effects of noise. The control scheme was fine-tuned and tested for complete stability to zero of the whole state, while seeking a practical solution to the trade-off between stability and transparency in the Internet-based teleoperation. These ideas were tested on an Internet-based application with two Omni devices at remote laboratory locations via simulations and real remote experiments that achieved robust stability, while performing well in terms of position synchronization and force transparency.
International Nuclear Information System (INIS)
Wang, Zuo-Cai; Ren, Wei-Xin; Chen, Gen-Da
2012-01-01
This paper presents a recursive Hilbert transform method for the time-varying property identification of large-scale shear-type buildings with limited sensor deployments. An observer technique is introduced to estimate the building responses from limited available measurements. For an n-story shear-type building with l measurements (l ≤ n), the responses of other stories without measurements can be estimated based on the first r mode shapes (r ≤ l) as-built conditions and l measurements. Both the measured responses and evaluated responses and their Hilbert transforms are then used to track any variation of structural parameters of a multi-story building over time. Given floor masses, both the stiffness and damping coefficients of the building are identified one-by-one from the top to the bottom story. When variations of parameters are detected, a new developed branch-and-bound technique can be used to update the first r mode shapes with the identified parameters. A 60-story shear building with abruptly varying stiffness at different floors is simulated as an example. The numerical results indicate that the proposed method can detect variations of the parameters of large-scale shear-type buildings with limited sensor deployments at appropriate locations. (paper)
International Nuclear Information System (INIS)
Kumar, V.; Mukherjee, S.
1977-01-01
In the present paper a general time-dependent inelastic analysis procedure for three-dimensional bodies subjected to arbitrary time varying mechanical and thermal loads using these state variable theories is presented. For the purpose of illustrations, the problems of hollow spheres, cylinders and solid circular shafts subjected to various combinations of internal and external pressures, axial force (or constraint) and torque are analyzed using the proposed solution procedure. Various cyclic thermal and mechanical loading histories with rectangular or sawtooth type waves with or without hold-time are considered. Numerical results for these geometrical shapes for various such loading histories are presented using Hart's theory (Journal of Engineering Materials and Technology 1976). The calculations are performed for nickel in the temperature range of 25 0 C to 400 0 C. For integrating forward in time, a method of solving a stiff system of ordinary differential equations is employed which corrects the step size and order of the method automatically. The limit loads for hollow spheres and cylinders are calculated using the proposed method and Hart's theory, and comparisons are made against the known theoretical results. The numerical results for other loading histories are discussed in the context of Hart's state variable type constitutive relations. The significance of phenomena such as strain rate sensitivity, Bauschinger's effect, crep recovery, history dependence and material softening with regard to these multiaxial problems are discussed in the context of Hart's theory
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields
Wang, B.; Rosen, P.; Skraba, P.; Bhatia, H.; Pascucci, V.
2013-01-01
Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.
From dynamical systems with time-varying delay to circle maps and Koopman operators
Müller, David; Otto, Andreas; Radons, Günter
2017-06-01
In this paper, we investigate the influence of the retarded access by a time-varying delay on the dynamics of delay systems. We show that there are two universality classes of delays, which lead to fundamental differences in dynamical quantities such as the Lyapunov spectrum. Therefore, we introduce an operator theoretic framework, where the solution operator of the delay system is decomposed into the Koopman operator describing the delay access and an operator similar to the solution operator known from systems with constant delay. The Koopman operator corresponds to an iterated map, called access map, which is defined by the iteration of the delayed argument of the delay equation. The dynamics of this one-dimensional iterated map determines the universality classes of the infinite-dimensional state dynamics governed by the delay differential equation. In this way, we connect the theory of time-delay systems with the theory of circle maps and the framework of the Koopman operator. In this paper, we extend our previous work [A. Otto, D. Müller, and G. Radons, Phys. Rev. Lett. 118, 044104 (2017), 10.1103/PhysRevLett.118.044104] by elaborating the mathematical details and presenting further results also on the Lyapunov vectors.
Noise level estimation in weakly nonlinear slowly time-varying systems
International Nuclear Information System (INIS)
Aerts, J R M; Dirckx, J J J; Lataire, J; Pintelon, R
2008-01-01
Recently, a method using multisine excitation was proposed for estimating the frequency response, the nonlinear distortions and the disturbing noise of weakly nonlinear time-invariant systems. This method has been demonstrated on the measurement of nonlinear distortions in the vibration of acoustically driven systems such as a latex membrane, which is a good example of a time-invariant system [1]. However, not all systems are perfectly time invariant, e.g. biomechanical systems. This time variation can be misinterpreted as an elevated noise floor, and the classical noise estimation method gives a wrong result. Two improved methods to retrieve the correct noise information from the measurements are presented. Both of them make use of multisine excitations. First, it is demonstrated that the improved methods give the same result as the classical noise estimation method when applied to a time-invariant system (high-quality microphone membrane). Next, it is demonstrated that the new methods clearly give an improved estimate of the noise level on time-varying systems. As an application example results for the vibration response of an eardrum are shown
Energy Technology Data Exchange (ETDEWEB)
Alexander S. Rattner; Donna Post Guillen; Alark Joshi
2012-12-01
Photo- and physically-realistic techniques are often insufficient for visualization of simulation results, especially for 3D and time-varying datasets. Substantial research efforts have been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. While these efforts have yielded valuable visualization results, a great deal of work has been reproduced in studies as individual research groups often develop purpose-built platforms. Additionally, interoperability between illustrative visualization software is limited due to specialized processing and rendering architectures employed in different studies. In this investigation, a generalized framework for illustrative visualization is proposed, and implemented in marmotViz, a ParaView plugin, enabling its use on variety of computing platforms with various data file formats and mesh geometries. Detailed descriptions of the region-of-interest identification and feature-tracking algorithms incorporated into this tool are provided. Additionally, implementations of multiple illustrative effect algorithms are presented to demonstrate the use and flexibility of this framework. By providing a framework and useful underlying functionality, the marmotViz tool can act as a springboard for future research in the field of illustrative visualization.
Cao, Jiguo; Huang, Jianhua Z.; Wu, Hulin
2012-01-01
Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online.
Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.
Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis
2018-01-01
Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.
Coded throughput performance simulations for the time-varying satellite channel. M.S. Thesis
Han, LI
1995-01-01
The design of a reliable satellite communication link involving the data transfer from a small, low-orbit satellite to a ground station, but through a geostationary satellite, was examined. In such a scenario, the received signal power to noise density ratio increases as the transmitting low-orbit satellite comes into view, and then decreases as it then departs, resulting in a short-duration, time-varying communication link. The optimal values of the small satellite antenna beamwidth, signaling rate, modulation scheme and the theoretical link throughput (in bits per day) have been determined. The goal of this thesis is to choose a practical coding scheme which maximizes the daily link throughput while satisfying a prescribed probability of error requirement. We examine the throughput of both fixed rate and variable rate concatenated forward error correction (FEC) coding schemes for the additive white Gaussian noise (AWGN) channel, and then examine the effect of radio frequency interference (RFI) on the best coding scheme among them. Interleaving is used to mitigate degradation due to RFI. It was found that the variable rate concatenated coding scheme could achieve 74 percent of the theoretical throughput, equivalent to 1.11 Gbits/day based on the cutoff rate R(sub 0). For comparison, 87 percent is achievable for AWGN-only case.
Reusable Launch Vehicle Attitude Control Using a Time-Varying Sliding Mode Control Technique
Shtessel, Yuri B.; Zhu, J. Jim; Daniels, Dan; Jackson, Scott (Technical Monitor)
2002-01-01
In this paper we present a time-varying sliding mode control (TVSMC) technique for reusable launch vehicle (RLV) attitude control in ascent and entry flight phases. In ascent flight the guidance commands Euler roll, pitch and yaw angles, and in entry flight it commands the aerodynamic angles of bank, attack and sideslip. The controller employs a body rate inner loop and the attitude outer loop, which are separated in time-scale by the singular perturbation principle. The novelty of the TVSMC is that both the sliding surface and the boundary layer dynamics can be varied in real time using the PD-eigenvalue assignment technique. This salient feature is used to cope with control command saturation and integrator windup in the presence of severe disturbance or control effector failure, which enhances the robustness and fault tolerance of the controller. The TV-SMC ascent and descent designs are currently being tested with high fidelity, 6-DOF dispersion simulations. The test results will be presented in the final version of this paper.
Dziak, John J; Li, Runze; Tan, Xianming; Shiffman, Saul; Shiyko, Mariya P
2015-12-01
Behavioral scientists increasingly collect intensive longitudinal data (ILD), in which phenomena are measured at high frequency and in real time. In many such studies, it is of interest to describe the pattern of change over time in important variables as well as the changing nature of the relationship between variables. Individuals' trajectories on variables of interest may be far from linear, and the predictive relationship between variables of interest and related covariates may also change over time in a nonlinear way. Time-varying effect models (TVEMs; see Tan, Shiyko, Li, Li, & Dierker, 2012) address these needs by allowing regression coefficients to be smooth, nonlinear functions of time rather than constants. However, it is possible that not only observed covariates but also unknown, latent variables may be related to the outcome. That is, regression coefficients may change over time and also vary for different kinds of individuals. Therefore, we describe a finite mixture version of TVEM for situations in which the population is heterogeneous and in which a single trajectory would conceal important, interindividual differences. This extended approach, MixTVEM, combines finite mixture modeling with non- or semiparametric regression modeling, to describe a complex pattern of change over time for distinct latent classes of individuals. The usefulness of the method is demonstrated in an empirical example from a smoking cessation study. We provide a versatile SAS macro and R function for fitting MixTVEMs. (c) 2015 APA, all rights reserved).
The Fast Simulation of Scattering Characteristics from a Simplified Time Varying Sea Surface
Directory of Open Access Journals (Sweden)
Yiwen Wei
2015-01-01
Full Text Available This paper aims at applying a simplified sea surface model into the physical optics (PO method to accelerate the scattering calculation from 1D time varying sea surface. To reduce the number of the segments and make further improvement on the efficiency of PO method, a simplified sea surface is proposed. In this simplified sea surface, the geometry of long waves is locally approximated by tilted facets that are much longer than the electromagnetic wavelength. The capillary waves are considered to be sinusoidal line superimposing on the long waves. The wavenumber of the sinusoidal waves is supposed to satisfy the resonant condition of Bragg waves which is dominant in all the scattered short wave components. Since the capillary wave is periodical within one facet, an analytical integration of the PO term can be performed. The backscattering coefficient obtained from a simplified sea surface model agrees well with that obtained from a realistic sea surface. The Doppler shifts and width also agree well with the realistic model since the capillary waves are taken into consideration. The good agreements indicate that the simplified model is reasonable and valid in predicting both the scattering coefficients and the Doppler spectra.
Soni, V.; Hadjadj, A.; Roussel, O.
2017-12-01
In this paper, a fully adaptive multiresolution (MR) finite difference scheme with a time-varying tolerance is developed to study compressible fluid flows containing shock waves in interaction with solid obstacles. To ensure adequate resolution near rigid bodies, the MR algorithm is combined with an immersed boundary method based on a direct-forcing approach in which the solid object is represented by a continuous solid-volume fraction. The resulting algorithm forms an efficient tool capable of solving linear and nonlinear waves on arbitrary geometries. Through a one-dimensional scalar wave equation, the accuracy of the MR computation is, as expected, seen to decrease in time when using a constant MR tolerance considering the accumulation of error. To overcome this problem, a variable tolerance formulation is proposed, which is assessed through a new quality criterion, to ensure a time-convergence solution for a suitable quality resolution. The newly developed algorithm coupled with high-resolution spatial and temporal approximations is successfully applied to shock-bluff body and shock-diffraction problems solving Euler and Navier-Stokes equations. Results show excellent agreement with the available numerical and experimental data, thereby demonstrating the efficiency and the performance of the proposed method.
A Class of Prediction-Correction Methods for Time-Varying Convex Optimization
Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro
2016-09-01
This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.
Detection of random alterations to time-varying musical instrument spectra.
Horner, Andrew; Beauchamp, James; So, Richard
2004-09-01
The time-varying spectra of eight musical instrument sounds were randomly altered by a time-invariant process to determine how detection of spectral alteration varies with degree of alteration, instrument, musical experience, and spectral variation. Sounds were resynthesized with centroids equalized to the original sounds, with frequencies harmonically flattened, and with average spectral error levels of 8%, 16%, 24%, 32%, and 48%. Listeners were asked to discriminate the randomly altered sounds from reference sounds resynthesized from the original data. For all eight instruments, discrimination was very good for the 32% and 48% error levels, moderate for the 16% and 24% error levels, and poor for the 8% error levels. When the error levels were 16%, 24%, and 32%, the scores of musically experienced listeners were found to be significantly better than the scores of listeners with no musical experience. Also, in this same error level range, discrimination was significantly affected by the instrument tested. For error levels of 16% and 24%, discrimination scores were significantly, but negatively correlated with measures of spectral incoherence and normalized centroid deviation on unaltered instrument spectra, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting spectral alterations. Correlation between discrimination and a measure of spectral irregularity was comparatively low.
Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert
2018-05-01
Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.
Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.
Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W
2014-11-26
Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.
Zhang, Hongjie; Hou, Yanyan; Yang, Tao; Zhang, Qian; Zhao, Jian
2018-05-01
In the spot welding process, a high alternating current is applied, resulting in a time-varying electromagnetic field surrounding the welder. When measuring the welding voltage signal, the impedance of the measuring circuit consists of two parts: dynamic resistance relating to weld nugget nucleation event and inductive reactance caused by mutual inductance. The aim of this study is to develop a method to acquire the dynamic reactance signal and to discuss the possibility of using this signal to evaluate the weld quality. For this purpose, a series of experiments were carried out. The reactance signals under different welding conditions were compared and the results showed that the morphological feature of the reactance signal was closely related to the welding current and it was also significantly influenced by some abnormal welding conditions. Some features were extracted from the reactance signal and combined to construct weld nugget strength and diameter prediction models based on the radial basis function (RBF) neural network. In addition, several features were also used to monitor the expulsion in the welding process by using Fisher linear discriminant analysis. The results indicated that using the dynamic reactance signal to evaluate weld quality is possible and feasible.
Directory of Open Access Journals (Sweden)
Lan Liu
2017-01-01
Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when q
Propagation of a laser beam in a time-varying waveguide. [plasma heating for controlled fusion
Chapman, J. M.; Kevorkian, J.
1978-01-01
The propagation of an axisymmetric laser beam in a plasma column having a radially parabolic electron density distribution is reported. For the case of an axially uniform waveguide it is found that the basic characteristics of alternating focusing and defocusing beams are maintained. However, the intensity distribution is changed at the foci and outer-beam regions. The features of paraxial beam propagation are discussed with reference to axially varying waveguides. Laser plasma coupling is considered noting the case where laser heating produces a density distribution radially parabolic near the axis and the energy absorbed over the focal length of the plasma is small. It is found that: (1) beam-propagation stability is governed by the relative magnitude of the density fluctuations existing in the axial variation of the waveguides due to laser heating, and (2) for beam propagation in a time-varying waveguide, the global instability of the propagation is a function of the initial fluctuation growth rate as compared to the initial time rate of change in the radial curvature of the waveguide.
Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks
Directory of Open Access Journals (Sweden)
Charalambous Charalambos D
2006-01-01
Full Text Available A new time-varying (TV long-term fading (LTF channel model which captures both the space and time variations of wireless systems is developed. The proposed TV LTF model is based on a stochastic differential equation driven by Brownian motion. This model is more realistic than the static models usually encountered in the literature. It allows viewing the wireless channel as a dynamical system, thus enabling well-developed tools of adaptive and nonadaptive estimation and identification techniques to be applied to this class of problems. In contrast with the traditional models, the statistics of the proposed model are shown to be TV, but converge in steady state to their static counterparts. Moreover, optimal power control algorithms (PCAs based on the new model are proposed. A centralized PCA is shown to reduce to a simple linear programming problem if predictable power control strategies (PPCS are used. In addition, an iterative distributed stochastic PCA is used to solve for the optimization problem using stochastic approximations. The latter solely requires each mobile to know its received signal-to-interference ratio. Generalizations of the power control problem based on convex optimization techniques are provided if PPCS are not assumed. Numerical results show that there are potentially large gains to be achieved by using TV stochastic models, and the distributed stochastic PCA provides better power stability and consumption than the distributed deterministic PCA.
Directory of Open Access Journals (Sweden)
Johann A. Briffa
2014-06-01
Full Text Available In this study, the authors consider time-varying block (TVB codes, which generalise a number of previous synchronisation error-correcting codes. They also consider various practical issues related to maximum a posteriori (MAP decoding of these codes. Specifically, they give an expression for the expected distribution of drift between transmitter and receiver because of synchronisation errors. They determine an appropriate choice for state space limits based on the drift probability distribution. In turn, they obtain an expression for the decoder complexity under given channel conditions in terms of the state space limits used. For a given state space, they also give a number of optimisations that reduce the algorithm complexity with no further loss of decoder performance. They also show how the MAP decoder can be used in the absence of known frame boundaries, and demonstrate that an appropriate choice of decoder parameters allows the decoder to approach the performance when frame boundaries are known, at the expense of some increase in complexity. Finally, they express some existing constructions as TVB codes, comparing performance with published results and showing that improved performance is possible by taking advantage of the flexibility of TVB codes.
Knowledge diffusion in complex networks by considering time-varying information channels
Zhu, He; Ma, Jing
2018-03-01
In this article, based on a model of epidemic spreading, we explore the knowledge diffusion process with an innovative mechanism for complex networks by considering time-varying information channels. To cover the knowledge diffusion process in homogeneous and heterogeneous networks, two types of networks (the BA network and the ER network) are investigated. The mean-field theory is used to theoretically draw the knowledge diffusion threshold. Numerical simulation demonstrates that the knowledge diffusion threshold is almost linearly correlated with the mean of the activity rate. In addition, under the influence of the activity rate and distinct from the classic Susceptible-Infected-Susceptible (SIS) model, the density of knowers almost linearly grows with the spreading rate. Finally, in consideration of the ubiquitous mechanism of innovation, we further study the evolution of knowledge in our proposed model. The results suggest that compared with the effect of the spreading rate, the average knowledge version of the population is affected more by the innovation parameter and the mean of the activity rate. Furthermore, in the BA network, the average knowledge version of individuals with higher degree is always newer than those with lower degree.
Psychosocial risk factors and heart failure hospitalization
DEFF Research Database (Denmark)
Rod, Naja Hulvej; Andersen, Ingelise; Prescott, Eva
2011-01-01
Prospective studies on the role of psychosocial factors in heart failure development are virtually nonexistent. The authors aimed to address the effect of psychosocial factors on the risk of heart failure hospitalization in men and women free of cardiovascular disease. In 1991-1993, the 8......-fourth of the population reported some degree of vital exhaustion. The vital exhaustion score was associated with a higher risk of heart failure in a dose-response manner (P risk of heart failure in both men (hazard ratio = 1.93, 95% confidence...... in the population, even a modestly higher risk of heart failure associated with vital exhaustion may be of importance in the planning of future preventive strategies for heart failure....
Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei
2018-01-01
Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.
EVALUATION OF RISK FACTORS IN ACUTE STROKE
Directory of Open Access Journals (Sweden)
Putta
2015-03-01
Full Text Available Introduction: Cerebrovascular disease is the third most common cause of death in the developed world after cancer and ischemic heart disease. In India, community surveys have shown a crude prevalence rate of 200 per 100000 population for hemiplegia. Aims and objectives: Identification of risk factors for c erebrovascular disease. Materials and Methods: Inclusion Criteria: Cases of acute stroke admitted in S.V.R.R.G.G.H, Tirupati were taken for the study. Exclusion Criteria: Head injury cases, neoplasm cases producing cerebrovascular disease were excluded. Re sults: Stroke was more common in male, 54% patients were male 46% were female. It was more common in 6 th and 7 th decade. More common risk factors were hypertension followed by smoking, diabetes mellitus. More common pathology was infarction. Conclusion: Com mon risk factors for acute stroke are hypertension, smoking, diabetes mellitus, alcoholism, obesity, cardiac disease. Stroke was confirmed by CT scan of brain.
Vitamin D, cardiovascular disease and risk factors
DEFF Research Database (Denmark)
Skaaby, Tea; Thuesen, Betina H.; Linneberg, Allan
2017-01-01
of vitamin D effects from a cardiovascular health perspective. It focuses on vitamin D in relation to cardiovascular disease, i.e. ischemic heart disease, and stroke; the traditional cardiovascular risk factors hypertension, abnormal blood lipids, obesity; and the emerging risk factors hyperparathyroidism......, microalbuminuria, chronic obstructive pulmonary diseases, and non-alcoholic fatty liver disease. Meta-analyses of observational studies have largely found vitamin D levels to be inversely associated with cardiovascular risk and disease. However, Mendelian randomization studies and randomized, controlled trials...... (RCTs) have not been able to consistently replicate the observational findings. Several RCTs are ongoing, and the results from these are needed to clarify whether vitamin D deficiency is a causal and reversible factor to prevent cardiovascular disease....
Preoperative modifiable risk factors in colorectal surgery
DEFF Research Database (Denmark)
van Rooijen, Stefanus; Carli, Francesco; Dalton, Susanne O
2017-01-01
in higher mortality rates and greater hospital costs. The number and severity of complications is closely related to patients' preoperative performance status. The aim of this study was to identify the most important preoperative modifiable risk factors that could be part of a multimodal prehabilitation...... program. METHODS: Prospectively collected data of a consecutive series of Dutch CRC patients undergoing colorectal surgery were analyzed. Modifiable risk factors were correlated to the Comprehensive Complication Index (CCI) and compared within two groups: none or mild complications (CCI ... complications (CCI ≥20). Multivariate logistic regression analysis was done to explore the combined effect of individual risk factors. RESULTS: In this 139 patient cohort, smoking, malnutrition, alcohol consumption, neoadjuvant therapy, higher age, and male sex, were seen more frequently in the severe...
Psychosocial risk factors for the metabolic syndrome
DEFF Research Database (Denmark)
Pedersen, Jolene Masters; Lund, Rikke; Andersen, Ingelise
2016-01-01
Background/Objectives: Metabolic deregulations and development of metabolic syndrome may be an important pathway underlying the relationship between stress and cardiovascular disease. We aim to estimate the effect of a comprehensive range of psychosocial factors on the risk of developing metabolic.......11) to be risk factors for developing the metabolic syndrome in women, while vital exhaustion (OR 2.09, 95% CI 0.95 to 4.59) and intake of sleep medications (OR 2.54, 95% CI 0.92 to 5.96) may play a more important role in men. Conclusions: Experiencing major life events in work and adult life and....../or dysfunctional social networks is a risk factor for metabolic syndrome in women, and stress reactions such as vital exhaustion and intake of sleep medications may play a more important role in the development of metabolic syndrome men....
Cardiovascular risk factors in subjects with psoriasis
DEFF Research Database (Denmark)
Jensen, Peter; Thyssen, Jacob P; Zachariae, Claus
2013-01-01
Background Epidemiological data have established an association between cardiovascular disease and psoriasis. Only one general population study has so far compared prevalences of cardiovascular risk factors among subjects with psoriasis and control subjects. We aimed to determine the prevalence...... of cardiovascular risk factors in subjects with and without psoriasis in the general population. Methods During 2006-2008, a cross-sectional study was performed in the general population in Copenhagen, Denmark. A total of 3471 subjects participated in a general health examination that included assessment of current...... between subjects with and without psoriasis with regard to traditional cardiovascular risk factors. Conclusions Our results contrast with the hitherto-reported increased prevalence of metabolic syndrome in subjects with psoriasis in the general US population. However, our results agree with those of other...
Early life risk factors for testicular cancer
DEFF Research Database (Denmark)
Piltoft, Johanne Spanggaard; Larsen, Signe Benzon; Dalton, Susanne Oksbjerg
2017-01-01
of this study is to utilize data from the Copenhagen School Health Records Register (CSHRR) to evaluate cryptorchidism, birth weight and birth order as risk factors for testicular cancer. METHODS: The study population consisted of 408 cases of testicular cancer identified by a government issued identification...... in crude analyses [hazard ratio (HR) = 3.60, 95% CI 2.79-4.65]. Birth weight was inversely associated with testicular cancer and no clear association with birth order was observed. The positive association between cryptorchidism and testicular cancer was only slightly attenuated controlling for birth......PURPOSE: One established risk factors for testicular cancer is cryptorchidism. However, it remains unclear whether cryptorchidism is a risk factor in itself or whether the two conditions share common causes in early life (estrogen hypothesis), such as birth weight and birth order. The objective...
Cardiovascular disease risk factors: a childhood perspective.
Praveen, Pradeep A; Roy, Ambuj; Prabhakaran, Dorairaj
2013-03-01
Atherosclerotic cardiovascular disease (CVD) is one of the leading causes of death and disability worldwide including in developing countries like India. Indians are known to be predisposed to CVD, which occur almost a decade earlier in them. Though these diseases manifest in the middle age and beyond, it is now clear that the roots of CVD lie in childhood and adolescence. Many of the conventional risk factors of CVD such as high blood pressure, dyslipidemia, tobacco use, unhealthy diet and obesity have their beginnings in childhood and then track overtime. It is thus important to screen and identify these risk factors early and treat them to prevent onset of CVD. Similarly community based strategies to prevent onset of these risk factors is imperative to tackle this burgeoning public health crisis especially in countries like ours with limited resources.