WorldWideScience

Sample records for dependent random variables

  1. Benford's law and continuous dependent random variables

    Science.gov (United States)

    Becker, Thealexa; Burt, David; Corcoran, Taylor C.; Greaves-Tunnell, Alec; Iafrate, Joseph R.; Jing, Joy; Miller, Steven J.; Porfilio, Jaclyn D.; Ronan, Ryan; Samranvedhya, Jirapat; Strauch, Frederick W.; Talbut, Blaine

    2018-01-01

    Many mathematical, man-made and natural systems exhibit a leading-digit bias, where a first digit (base 10) of 1 occurs not 11% of the time, as one would expect if all digits were equally likely, but rather 30%. This phenomenon is known as Benford's Law. Analyzing which datasets adhere to Benford's Law and how quickly Benford behavior sets in are the two most important problems in the field. Most previous work studied systems of independent random variables, and relied on the independence in their analyses. Inspired by natural processes such as particle decay, we study the dependent random variables that emerge from models of decomposition of conserved quantities. We prove that in many instances the distribution of lengths of the resulting pieces converges to Benford behavior as the number of divisions grow, and give several conjectures for other fragmentation processes. The main difficulty is that the resulting random variables are dependent. We handle this by using tools from Fourier analysis and irrationality exponents to obtain quantified convergence rates as well as introducing and developing techniques to measure and control the dependencies. The construction of these tools is one of the major motivations of this work, as our approach can be applied to many other dependent systems. As an example, we show that the n ! entries in the determinant expansions of n × n matrices with entries independently drawn from nice random variables converges to Benford's Law.

  2. Hoeffding’s Inequality for Sums of Dependent Random Variables

    Czech Academy of Sciences Publication Activity Database

    Pelekis, Christos; Ramon, J.

    2017-01-01

    Roč. 14, č. 6 (2017), č. článku 243. ISSN 1660-5446 Institutional support: RVO:67985807 Keywords : dependent random variables * Hoeffding’s inequality * k-wise independent random variables * martingale differences Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 0.868, year: 2016

  3. How a dependent's variable non-randomness affects taper equation ...

    African Journals Online (AJOL)

    In order to apply the least squares method in regression analysis, the values of the dependent variable Y should be random. In an example of regression analysis linear and nonlinear taper equations, which estimate the diameter of the tree dhi at any height of the tree hi, were compared. For each tree the diameter at the ...

  4. Non-uniform approximations for sums of discrete m-dependent random variables

    OpenAIRE

    Vellaisamy, P.; Cekanavicius, V.

    2013-01-01

    Non-uniform estimates are obtained for Poisson, compound Poisson, translated Poisson, negative binomial and binomial approximations to sums of of m-dependent integer-valued random variables. Estimates for Wasserstein metric also follow easily from our results. The results are then exemplified by the approximation of Poisson binomial distribution, 2-runs and $m$-dependent $(k_1,k_2)$-events.

  5. Maximal Inequalities for Dependent Random Variables

    DEFF Research Database (Denmark)

    Hoffmann-Jorgensen, Jorgen

    2016-01-01

    Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X-k. Then a......Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X......-k. Then a maximal inequality gives conditions ensuring that the maximal partial sum M-n = max(1) (...

  6. Central limit theorem for the Banach-valued weakly dependent random variables

    International Nuclear Information System (INIS)

    Dmitrovskij, V.A.; Ermakov, S.V.; Ostrovskij, E.I.

    1983-01-01

    The central limit theorem (CLT) for the Banach-valued weakly dependent random variables is proved. In proving CLT convergence of finite-measured (i.e. cylindrical) distributions is established. A weak compactness of the family of measures generated by a certain sequence is confirmed. The continuity of the limiting field is checked

  7. Equivalent conditions of complete moment convergence for extended negatively dependent random variables

    Directory of Open Access Journals (Sweden)

    Qunying Wu

    2017-05-01

    Full Text Available Abstract In this paper, we study the equivalent conditions of complete moment convergence for sequences of identically distributed extended negatively dependent random variables. As a result, we extend and generalize some results of complete moment convergence obtained by Chow (Bull. Inst. Math. Acad. Sin. 16:177-201, 1988 and Li and Spătaru (J. Theor. Probab. 18:933-947, 2005 from the i.i.d. case to extended negatively dependent sequences.

  8. An edgeworth expansion for a sum of M-Dependent random variables

    Directory of Open Access Journals (Sweden)

    Wan Soo Rhee

    1985-01-01

    Full Text Available Given a sequence X1,X2,…,Xn of m-dependent random variables with moments of order 3+α (0<α≦1, we give an Edgeworth expansion of the distribution of Sσ−1(S=X1+X2+…+Xn, σ2=ES2 under the assumption that E[exp(it Sσ1] is small away from the origin. The result is of the best possible order.

  9. Contextuality is about identity of random variables

    International Nuclear Information System (INIS)

    Dzhafarov, Ehtibar N; Kujala, Janne V

    2014-01-01

    Contextual situations are those in which seemingly ‘the same’ random variable changes its identity depending on the conditions under which it is recorded. Such a change of identity is observed whenever the assumption that the variable is one and the same under different conditions leads to contradictions when one considers its joint distribution with other random variables (this is the essence of all Bell-type theorems). In our Contextuality-by-Default approach, instead of asking why or how the conditions force ‘one and the same’ random variable to change ‘its’ identity, any two random variables recorded under different conditions are considered different ‘automatically.’ They are never the same, nor are they jointly distributed, but one can always impose on them a joint distribution (probabilistic coupling). The special situations when there is a coupling in which these random variables are equal with probability 1 are considered noncontextual. Contextuality means that such couplings do not exist. We argue that the determination of the identity of random variables by conditions under which they are recorded is not a causal relationship and cannot violate laws of physics. (paper)

  10. Polynomial chaos expansion with random and fuzzy variables

    Science.gov (United States)

    Jacquelin, E.; Friswell, M. I.; Adhikari, S.; Dessombz, O.; Sinou, J.-J.

    2016-06-01

    A dynamical uncertain system is studied in this paper. Two kinds of uncertainties are addressed, where the uncertain parameters are described through random variables and/or fuzzy variables. A general framework is proposed to deal with both kinds of uncertainty using a polynomial chaos expansion (PCE). It is shown that fuzzy variables may be expanded in terms of polynomial chaos when Legendre polynomials are used. The components of the PCE are a solution of an equation that does not depend on the nature of uncertainty. Once this equation is solved, the post-processing of the data gives the moments of the random response when the uncertainties are random or gives the response interval when the variables are fuzzy. With the PCE approach, it is also possible to deal with mixed uncertainty, when some parameters are random and others are fuzzy. The results provide a fuzzy description of the response statistical moments.

  11. PaCAL: A Python Package for Arithmetic Computations with Random Variables

    Directory of Open Access Journals (Sweden)

    Marcin Korze?

    2014-05-01

    Full Text Available In this paper we present PaCAL, a Python package for arithmetical computations on random variables. The package is capable of performing the four arithmetic operations: addition, subtraction, multiplication and division, as well as computing many standard functions of random variables. Summary statistics, random number generation, plots, and histograms of the resulting distributions can easily be obtained and distribution parameter ?tting is also available. The operations are performed numerically and their results interpolated allowing for arbitrary arithmetic operations on random variables following practically any probability distribution encountered in practice. The package is easy to use, as operations on random variables are performed just as they are on standard Python variables. Independence of random variables is, by default, assumed on each step but some computations on dependent random variables are also possible. We demonstrate on several examples that the results are very accurate, often close to machine precision. Practical applications include statistics, physical measurements or estimation of error distributions in scienti?c computations.

  12. Partial summations of stationary sequences of non-Gaussian random variables

    DEFF Research Database (Denmark)

    Mohr, Gunnar; Ditlevsen, Ove Dalager

    1996-01-01

    The distribution of the sum of a finite number of identically distributed random variables is in many cases easily determined given that the variables are independent. The moments of any order of the sum can always be expressed by the moments of the single term without computational problems...... of convergence of the distribution of a sum (or an integral) of mutually dependent random variables to the Gaussian distribution. The paper is closely related to the work in Ditlevsen el al. [Ditlevsen, O., Mohr, G. & Hoffmeyer, P. Integration of non-Gaussian fields. Prob. Engng Mech 11 (1996) 15-23](2)....... lognormal variables or polynomials of standard Gaussian variables. The dependency structure is induced by specifying the autocorrelation structure of the sequence of standard Gaussian variables. Particularly useful polynomials are the Winterstein approximations that distributionally fit with non...

  13. Strong Decomposition of Random Variables

    DEFF Research Database (Denmark)

    Hoffmann-Jørgensen, Jørgen; Kagan, Abram M.; Pitt, Loren D.

    2007-01-01

    A random variable X is stongly decomposable if X=Y+Z where Y=Φ(X) and Z=X-Φ(X) are independent non-degenerated random variables (called the components). It is shown that at least one of the components is singular, and we derive a necessary and sufficient condition for strong decomposability...... of a discrete random variable....

  14. Strong Laws of Large Numbers for Arrays of Rowwise NA and LNQD Random Variables

    Directory of Open Access Journals (Sweden)

    Jiangfeng Wang

    2011-01-01

    Full Text Available Some strong laws of large numbers and strong convergence properties for arrays of rowwise negatively associated and linearly negative quadrant dependent random variables are obtained. The results obtained not only generalize the result of Hu and Taylor to negatively associated and linearly negative quadrant dependent random variables, but also improve it.

  15. Reduction of the Random Variables of the Turbulent Wind Field

    DEFF Research Database (Denmark)

    Sichani, Mahdi Teimouri; Nielsen, Søren R.K.

    2012-01-01

    .e. Importance Sampling (IS) or Subset Simulation (SS), will be deteriorated on problems with many random variables. The problem with PDEM is that a multidimensional integral has to be carried out over the space defined by the random variables of the system. The numerical procedure requires discretization......Applicability of the Probability Density Evolution Method (PDEM) for realizing evolution of the probability density for the wind turbines has rather strict bounds on the basic number of the random variables involved in the model. The efficiency of most of the Advanced Monte Carlo (AMC) methods, i...... of the integral domain; this becomes increasingly difficult as the dimensions of the integral domain increase. On the other hand efficiency of the AMC methods is closely dependent on the design points of the problem. Presence of many random variables may increase the number of the design points, hence affects...

  16. Convergence Analysis of Semi-Implicit Euler Methods for Solving Stochastic Age-Dependent Capital System with Variable Delays and Random Jump Magnitudes

    Directory of Open Access Journals (Sweden)

    Qinghui Du

    2014-01-01

    Full Text Available We consider semi-implicit Euler methods for stochastic age-dependent capital system with variable delays and random jump magnitudes, and investigate the convergence of the numerical approximation. It is proved that the numerical approximate solutions converge to the analytical solutions in the mean-square sense under given conditions.

  17. Ordered random variables theory and applications

    CERN Document Server

    Shahbaz, Muhammad Qaiser; Hanif Shahbaz, Saman; Al-Zahrani, Bander M

    2016-01-01

    Ordered Random Variables have attracted several authors. The basic building block of Ordered Random Variables is Order Statistics which has several applications in extreme value theory and ordered estimation. The general model for ordered random variables, known as Generalized Order Statistics has been introduced relatively recently by Kamps (1995).

  18. Compound Poisson Approximations for Sums of Random Variables

    OpenAIRE

    Serfozo, Richard F.

    1986-01-01

    We show that a sum of dependent random variables is approximately compound Poisson when the variables are rarely nonzero and, given they are nonzero, their conditional distributions are nearly identical. We give several upper bounds on the total-variation distance between the distribution of such a sum and a compound Poisson distribution. Included is an example for Markovian occurrences of a rare event. Our bounds are consistent with those that are known for Poisson approximations for sums of...

  19. New Results On the Sum of Two Generalized Gaussian Random Variables

    KAUST Repository

    Soury, Hamza

    2015-01-01

    We propose in this paper a new method to compute the characteristic function (CF) of generalized Gaussian (GG) random variable in terms of the Fox H function. The CF of the sum of two independent GG random variables is then deduced. Based on this results, the probability density function (PDF) and the cumulative distribution function (CDF) of the sum distribution are obtained. These functions are expressed in terms of the bivariate Fox H function. Next, the statistics of the distribution of the sum, such as the moments, the cumulant, and the kurtosis, are analyzed and computed. Due to the complexity of bivariate Fox H function, a solution to reduce such complexity is to approximate the sum of two independent GG random variables by one GG random variable with suitable shape factor. The approximation method depends on the utility of the system so three methods of estimate the shape factor are studied and presented.

  20. New Results on the Sum of Two Generalized Gaussian Random Variables

    KAUST Repository

    Soury, Hamza

    2016-01-06

    We propose in this paper a new method to compute the characteristic function (CF) of generalized Gaussian (GG) random variable in terms of the Fox H function. The CF of the sum of two independent GG random variables is then deduced. Based on this results, the probability density function (PDF) and the cumulative distribution function (CDF) of the sum distribution are obtained. These functions are expressed in terms of the bivariate Fox H function. Next, the statistics of the distribution of the sum, such as the moments, the cumulant, and the kurtosis, are analyzed and computed. Due to the complexity of bivariate Fox H function, a solution to reduce such complexity is to approximate the sum of two independent GG random variables by one GG random variable with suitable shape factor. The approximation method depends on the utility of the system so three methods of estimate the shape factor are studied and presented [1].

  1. New Results on the Sum of Two Generalized Gaussian Random Variables

    KAUST Repository

    Soury, Hamza; Alouini, Mohamed-Slim

    2016-01-01

    We propose in this paper a new method to compute the characteristic function (CF) of generalized Gaussian (GG) random variable in terms of the Fox H function. The CF of the sum of two independent GG random variables is then deduced. Based on this results, the probability density function (PDF) and the cumulative distribution function (CDF) of the sum distribution are obtained. These functions are expressed in terms of the bivariate Fox H function. Next, the statistics of the distribution of the sum, such as the moments, the cumulant, and the kurtosis, are analyzed and computed. Due to the complexity of bivariate Fox H function, a solution to reduce such complexity is to approximate the sum of two independent GG random variables by one GG random variable with suitable shape factor. The approximation method depends on the utility of the system so three methods of estimate the shape factor are studied and presented [1].

  2. A comparison of random walks in dependent random environments

    NARCIS (Netherlands)

    Scheinhardt, Willem R.W.; Kroese, Dirk

    We provide exact computations for the drift of random walks in dependent random environments, including $k$-dependent and moving average environments. We show how the drift can be characterized and evaluated using Perron–Frobenius theory. Comparing random walks in various dependent environments, we

  3. Contextuality in canonical systems of random variables

    Science.gov (United States)

    Dzhafarov, Ehtibar N.; Cervantes, Víctor H.; Kujala, Janne V.

    2017-10-01

    Random variables representing measurements, broadly understood to include any responses to any inputs, form a system in which each of them is uniquely identified by its content (that which it measures) and its context (the conditions under which it is recorded). Two random variables are jointly distributed if and only if they share a context. In a canonical representation of a system, all random variables are binary, and every content-sharing pair of random variables has a unique maximal coupling (the joint distribution imposed on them so that they coincide with maximal possible probability). The system is contextual if these maximal couplings are incompatible with the joint distributions of the context-sharing random variables. We propose to represent any system of measurements in a canonical form and to consider the system contextual if and only if its canonical representation is contextual. As an illustration, we establish a criterion for contextuality of the canonical system consisting of all dichotomizations of a single pair of content-sharing categorical random variables. This article is part of the themed issue `Second quantum revolution: foundational questions'.

  4. A random number generator for continuous random variables

    Science.gov (United States)

    Guerra, V. M.; Tapia, R. A.; Thompson, J. R.

    1972-01-01

    A FORTRAN 4 routine is given which may be used to generate random observations of a continuous real valued random variable. Normal distribution of F(x), X, E(akimas), and E(linear) is presented in tabular form.

  5. Probability, random variables, and random processes theory and signal processing applications

    CERN Document Server

    Shynk, John J

    2012-01-01

    Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app

  6. Higher order moments of a sum of random variables: remarks and applications.

    Directory of Open Access Journals (Sweden)

    Luisa Tibiletti

    1996-02-01

    Full Text Available The moments of a sum of random variables depend on both the pure moments of each random addendum and on the addendum mixed moments. In this note we introduce a simple measure to evaluate the relative impedance to attach to the latter. Once the pure moments are fixed, the functional relation between the random addenda leading to the extreme values is also provided. Applications to Finance, Decision Theory and Actuarial Sciences are also suggested.

  7. Inference for binomial probability based on dependent Bernoulli random variables with applications to meta‐analysis and group level studies

    Science.gov (United States)

    Bakbergenuly, Ilyas; Morgenthaler, Stephan

    2016-01-01

    We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group‐level studies or in meta‐analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log‐odds and arcsine transformations of the estimated probability p^, both for single‐group studies and in combining results from several groups or studies in meta‐analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta‐analysis and result in abysmal coverage of the combined effect for large K. We also propose bias‐correction for the arcsine transformation. Our simulations demonstrate that this bias‐correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta‐analyses of prevalence. PMID:27192062

  8. On Complex Random Variables

    Directory of Open Access Journals (Sweden)

    Anwer Khurshid

    2012-07-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE In this paper, it is shown that a complex multivariate random variable  is a complex multivariate normal random variable of dimensionality if and only if all nondegenerate complex linear combinations of  have a complex univariate normal distribution. The characteristic function of  has been derived, and simpler forms of some theorems have been given using this characterization theorem without assuming that the variance-covariance matrix of the vector  is Hermitian positive definite. Marginal distributions of  have been given. In addition, a complex multivariate t-distribution has been defined and the density derived. A characterization of the complex multivariate t-distribution is given. A few possible uses of this distribution have been suggested.

  9. Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

    Science.gov (United States)

    Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

    2016-07-01

    We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  10. Generating variable and random schedules of reinforcement using Microsoft Excel macros.

    Science.gov (United States)

    Bancroft, Stacie L; Bourret, Jason C

    2008-01-01

    Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time. Generating schedule values for variable and random reinforcement schedules can be difficult. The present article describes the steps necessary to write macros in Microsoft Excel that will generate variable-ratio, variable-interval, variable-time, random-ratio, random-interval, and random-time reinforcement schedule values.

  11. Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

    NARCIS (Netherlands)

    Elhorst, J. Paul

    2001-01-01

    This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

  12. Future-dependent Flow Policies with Prophetic Variables

    DEFF Research Database (Denmark)

    Li, Ximeng; Nielson, Flemming; Nielson, Hanne Riis

    2016-01-01

    future-dependent flow policies- policies that can depend on not only the current values of variables, but also their final values. The final values are referred to using what we call prophetic variables, just as the initial values can be referenced using logical variables in Hoare logic. We develop...... and enforce a notion of future-dependent security for open systems, in the spirit of "non-deducibility on strategies". We also illustrate our approach in scenarios where future-dependency has advantages over present-dependency and avoids mixtures of upgradings and downgradings....

  13. Asymptotic theory of weakly dependent random processes

    CERN Document Server

    Rio, Emmanuel

    2017-01-01

    Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for sequences of random variables that are strongly mixing in the sense of Rosenblatt, or absolutely regular. The first chapter introduces covariance inequalities under strong mixing or absolute regularity. These covariance inequalities are applied in Chapters 2, 3 and 4 to moment inequalities, rates of convergence in the strong law, and central limit theorems. Chapter 5 concerns coupling. In Chapter 6 new deviation inequalities and new moment inequalities for partial sums via the coupling lemmas of Chapter 5 are derived and applied to the bounded law of the iterated logarithm. Chapters 7 and 8 deal with the theory of empirical processes under weak dependence. Lastly, Chapter 9 describes links between ergodicity, return times and rates of mixing in the case of irreducible Markov chains. Each chapter ends with a set of exercises. The book is an updated and extended ...

  14. THE COVARIATION FUNCTION FOR SYMMETRIC &ALPHA;-STABLE RANDOM VARIABLES WITH FINITE FIRST MOMENTS

    Directory of Open Access Journals (Sweden)

    Dedi Rosadi

    2012-05-01

    Full Text Available In this paper, we discuss a generalized dependence measure which is designed to measure dependence of two symmetric α-stable random variables with finite mean(1<α<=2 and contains the covariance function as the special case (when α=2. Weshortly discuss some basic properties of the function and consider several methods to estimate the function and further investigate the numerical properties of the estimatorusing the simulated data. We show how to apply this function to measure dependence of some stock returns on the composite index LQ45 in Indonesia Stock Exchange.

  15. Reward-dependent modulation of movement variability.

    Science.gov (United States)

    Pekny, Sarah E; Izawa, Jun; Shadmehr, Reza

    2015-03-04

    Movement variability is often considered an unwanted byproduct of a noisy nervous system. However, variability can signal a form of implicit exploration, indicating that the nervous system is intentionally varying the motor commands in search of actions that yield the greatest success. Here, we investigated the role of the human basal ganglia in controlling reward-dependent motor variability as measured by trial-to-trial changes in performance during a reaching task. We designed an experiment in which the only performance feedback was success or failure and quantified how reach variability was modulated as a function of the probability of reward. In healthy controls, reach variability increased as the probability of reward decreased. Control of variability depended on the history of past rewards, with the largest trial-to-trial changes occurring immediately after an unrewarded trial. In contrast, in participants with Parkinson's disease, a known example of basal ganglia dysfunction, reward was a poor modulator of variability; that is, the patients showed an impaired ability to increase variability in response to decreases in the probability of reward. This was despite the fact that, after rewarded trials, reach variability in the patients was comparable to healthy controls. In summary, we found that movement variability is partially a form of exploration driven by the recent history of rewards. When the function of the human basal ganglia is compromised, the reward-dependent control of movement variability is impaired, particularly affecting the ability to increase variability after unsuccessful outcomes. Copyright © 2015 the authors 0270-6474/15/354015-10$15.00/0.

  16. Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

  17. On the product and ratio of Bessel random variables

    Directory of Open Access Journals (Sweden)

    Saralees Nadarajah

    2005-01-01

    Full Text Available The distributions of products and ratios of random variables are of interest in many areas of the sciences. In this paper, the exact distributions of the product |XY| and the ratio |X/Y| are derived when X and Y are independent Bessel function random variables. An application of the results is provided by tabulating the associated percentage points.

  18. Designing neural networks that process mean values of random variables

    International Nuclear Information System (INIS)

    Barber, Michael J.; Clark, John W.

    2014-01-01

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

  19. Designing neural networks that process mean values of random variables

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

    2014-06-13

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

  20. A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Jae-Hee Hur

    2017-01-01

    Full Text Available Recently, the importance of mobile cloud computing has increased. Mobile devices can collect personal data from various sensors within a shorter period of time and sensor-based data consists of valuable information from users. Advanced computation power and data analysis technology based on cloud computing provide an opportunity to classify massive sensor data into given labels. Random forest algorithm is known as black box model which is hardly able to interpret the hidden process inside. In this paper, we propose a method that analyzes the variable impact in random forest algorithm to clarify which variable affects classification accuracy the most. We apply Shapley Value with random forest to analyze the variable impact. Under the assumption that every variable cooperates as players in the cooperative game situation, Shapley Value fairly distributes the payoff of variables. Our proposed method calculates the relative contributions of the variables within its classification process. In this paper, we analyze the influence of variables and list the priority of variables that affect classification accuracy result. Our proposed method proves its suitability for data interpretation in black box model like a random forest so that the algorithm is applicable in mobile cloud computing environment.

  1. Exponential Inequalities for Positively Associated Random Variables and Applications

    Directory of Open Access Journals (Sweden)

    Yang Shanchao

    2008-01-01

    Full Text Available Abstract We establish some exponential inequalities for positively associated random variables without the boundedness assumption. These inequalities improve the corresponding results obtained by Oliveira (2005. By one of the inequalities, we obtain the convergence rate for the case of geometrically decreasing covariances, which closes to the optimal achievable convergence rate for independent random variables under the Hartman-Wintner law of the iterated logarithm and improves the convergence rate derived by Oliveira (2005 for the above case.

  2. Bias in random forest variable importance measures: Illustrations, sources and a solution

    Directory of Open Access Journals (Sweden)

    Hothorn Torsten

    2007-01-01

    Full Text Available Abstract Background Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related scientific fields, for instance to select a subset of genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories. This is particularly important in genomics and computational biology, where predictors often include variables of different types, for example when predictors include both sequence data and continuous variables such as folding energy, or when amino acid sequence data show different numbers of categories. Results Simulation studies are presented illustrating that, when random forest variable importance measures are used with data of varying types, the results are misleading because suboptimal predictor variables may be artificially preferred in variable selection. The two mechanisms underlying this deficiency are biased variable selection in the individual classification trees used to build the random forest on one hand, and effects induced by bootstrap sampling with replacement on the other hand. Conclusion We propose to employ an alternative implementation of random forests, that provides unbiased variable selection in the individual classification trees. When this method is applied using subsampling without replacement, the resulting variable importance measures can be used reliably for variable selection even in situations where the potential predictor variables vary in their scale of measurement or their number of categories. The usage of both random forest algorithms and their variable importance measures in the R system for statistical computing is illustrated and

  3. Development of a localized probabilistic sensitivity method to determine random variable regional importance

    International Nuclear Information System (INIS)

    Millwater, Harry; Singh, Gulshan; Cortina, Miguel

    2012-01-01

    There are many methods to identify the important variable out of a set of random variables, i.e., “inter-variable” importance; however, to date there are no comparable methods to identify the “region” of importance within a random variable, i.e., “intra-variable” importance. Knowledge of the critical region of an input random variable (tail, near-tail, and central region) can provide valuable information towards characterizing, understanding, and improving a model through additional modeling or testing. As a result, an intra-variable probabilistic sensitivity method was developed and demonstrated for independent random variables that computes the partial derivative of a probabilistic response with respect to a localized perturbation in the CDF values of each random variable. These sensitivities are then normalized in absolute value with respect to the largest sensitivity within a distribution to indicate the region of importance. The methodology is implemented using the Score Function kernel-based method such that existing samples can be used to compute sensitivities for negligible cost. Numerical examples demonstrate the accuracy of the method through comparisons with finite difference and numerical integration quadrature estimates. - Highlights: ► Probabilistic sensitivity methodology. ► Determines the “region” of importance within random variables such as left tail, near tail, center, right tail, etc. ► Uses the Score Function approach to reuse the samples, hence, negligible cost. ► No restrictions on the random variable types or limit states.

  4. Selection for altruism through random drift in variable size populations

    Directory of Open Access Journals (Sweden)

    Houchmandzadeh Bahram

    2012-05-01

    Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.

  5. Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering

    Institute of Scientific and Technical Information of China (English)

    FENG Yu-hu

    2005-01-01

    By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.

  6. Statistics for Ratios of Rayleigh, Rician, Nakagami-m, and Weibull Distributed Random Variables

    Directory of Open Access Journals (Sweden)

    Dragana Č. Pavlović

    2013-01-01

    Full Text Available The distributions of ratios of random variables are of interest in many areas of the sciences. In this brief paper, we present the joint probability density function (PDF and PDF of maximum of ratios μ1=R1/r1 and μ2=R2/r2 for the cases where R1, R2, r1, and r2 are Rayleigh, Rician, Nakagami-m, and Weibull distributed random variables. Random variables R1 and R2, as well as random variables r1 and r2, are correlated. Ascertaining on the suitability of the Weibull distribution to describe fading in both indoor and outdoor environments, special attention is dedicated to the case of Weibull random variables. For this case, analytical expressions for the joint PDF, PDF of maximum, PDF of minimum, and product moments of arbitrary number of ratios μi=Ri/ri, i=1,…,L are obtained. Random variables in numerator, Ri, as well as random variables in denominator, ri, are exponentially correlated. To the best of the authors' knowledge, analytical expressions for the PDF of minimum and product moments of {μi}i=1L are novel in the open technical literature. The proposed mathematical analysis is complemented by various numerical results. An application of presented theoretical results is illustrated with respect to performance assessment of wireless systems.

  7. Population and prehistory III: food-dependent demography in variable environments.

    Science.gov (United States)

    Lee, Charlotte T; Puleston, Cedric O; Tuljapurkar, Shripad

    2009-11-01

    The population dynamics of preindustrial societies depend intimately on their surroundings, and food is a primary means through which environment influences population size and individual well-being. Food production requires labor; thus, dependence of survival and fertility on food involves dependence of a population's future on its current state. We use a perturbation approach to analyze the effects of random environmental variation on this nonlinear, age-structured system. We show that in expanding populations, direct environmental effects dominate induced population fluctuations, so environmental variability has little effect on mean hunger levels, although it does decrease population growth. The growth rate determines the time until population is limited by space. This limitation introduces a tradeoff between population density and well-being, so population effects become more important than the direct effects of the environment: environmental fluctuation increases mortality, releasing density dependence and raising average well-being for survivors. We discuss the social implications of these findings for the long-term fate of populations as they transition from expansion into limitation, given that conditions leading to high well-being during growth depress well-being during limitation.

  8. Validity of a Residualized Dependent Variable after Pretest Covariance Adjustments: Still the Same Variable?

    Science.gov (United States)

    Nimon, Kim; Henson, Robin K.

    2015-01-01

    The authors empirically examined whether the validity of a residualized dependent variable after covariance adjustment is comparable to that of the original variable of interest. When variance of a dependent variable is removed as a result of one or more covariates, the residual variance may not reflect the same meaning. Using the pretest-posttest…

  9. Raw and Central Moments of Binomial Random Variables via Stirling Numbers

    Science.gov (United States)

    Griffiths, Martin

    2013-01-01

    We consider here the problem of calculating the moments of binomial random variables. It is shown how formulae for both the raw and the central moments of such random variables may be obtained in a recursive manner utilizing Stirling numbers of the first kind. Suggestions are also provided as to how students might be encouraged to explore this…

  10. A review of instrumental variable estimators for Mendelian randomization.

    Science.gov (United States)

    Burgess, Stephen; Small, Dylan S; Thompson, Simon G

    2017-10-01

    Instrumental variable analysis is an approach for obtaining causal inferences on the effect of an exposure (risk factor) on an outcome from observational data. It has gained in popularity over the past decade with the use of genetic variants as instrumental variables, known as Mendelian randomization. An instrumental variable is associated with the exposure, but not associated with any confounder of the exposure-outcome association, nor is there any causal pathway from the instrumental variable to the outcome other than via the exposure. Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect of the exposure on the outcome can be estimated. There are several methods available for instrumental variable estimation; we consider the ratio method, two-stage methods, likelihood-based methods, and semi-parametric methods. Techniques for obtaining statistical inferences and confidence intervals are presented. The statistical properties of estimates from these methods are compared, and practical advice is given about choosing a suitable analysis method. In particular, bias and coverage properties of estimators are considered, especially with weak instruments. Settings particularly relevant to Mendelian randomization are prioritized in the paper, notably the scenario of a continuous exposure and a continuous or binary outcome.

  11. A note on asymptotic expansions for sums over a weakly dependent random field with application to the Poisson and Strauss processes

    DEFF Research Database (Denmark)

    Jensen, J.L.

    1993-01-01

    Previous results on Edgeworth expansions for sums over a random field are extended to the case where the strong mixing coefficient depends not only on the distance between two sets of random variables, but also on the size of the two sets. The results are applied to the Poisson and the Strauss...

  12. A Particle Swarm Optimization Algorithm with Variable Random Functions and Mutation

    Institute of Scientific and Technical Information of China (English)

    ZHOU Xiao-Jun; YANG Chun-Hua; GUI Wei-Hua; DONG Tian-Xue

    2014-01-01

    The convergence analysis of the standard particle swarm optimization (PSO) has shown that the changing of random functions, personal best and group best has the potential to improve the performance of the PSO. In this paper, a novel strategy with variable random functions and polynomial mutation is introduced into the PSO, which is called particle swarm optimization algorithm with variable random functions and mutation (PSO-RM). Random functions are adjusted with the density of the population so as to manipulate the weight of cognition part and social part. Mutation is executed on both personal best particle and group best particle to explore new areas. Experiment results have demonstrated the effectiveness of the strategy.

  13. On mean square displacement behaviors of anomalous diffusions with variable and random orders

    International Nuclear Information System (INIS)

    Sun Hongguang; Chen Wen; Sheng Hu; Chen Yangquan

    2010-01-01

    Mean square displacement (MSD) is used to characterize anomalous diffusion. Recently, models of anomalous diffusion with variable-order and random-order were proposed, but no MSD analysis has been given so far. The purpose of this Letter is to offer a concise derivation of MSD functions for the variable-order model and the random-order model. Numerical results are presented to illustrate the analytical results. In addition, we show how to establish a variable-random-order model for a given MSD function which has clear application potentials.

  14. Exercise training improves heart rate variability after methamphetamine dependency.

    Science.gov (United States)

    Dolezal, Brett Andrew; Chudzynski, Joy; Dickerson, Daniel; Mooney, Larissa; Rawson, Richard A; Garfinkel, Alan; Cooper, Christopher B

    2014-06-01

    Heart rate variability (HRV) reflects a healthy autonomic nervous system and is increased with physical training. Methamphetamine dependence (MD) causes autonomic dysfunction and diminished HRV. We compared recently abstinent methamphetamine-dependent participants with age-matched, drug-free controls (DF) and also investigated whether HRV can be improved with exercise training in the methamphetamine-dependent participants. In 50 participants (MD = 28; DF = 22), resting heart rate (HR; R-R intervals) was recorded over 5 min while seated using a monitor affixed to a chest strap. Previously reported time domain (SDNN, RMSSD, pNN50) and frequency domain (LFnu, HFnu, LF/HF) parameters of HRV were calculated with customized software. MD were randomized to thrice-weekly exercise training (ME = 14) or equal attention without training (MC = 14) over 8 wk. Groups were compared using paired and unpaired t-tests. Statistical significance was set at P ≤ 0.05. Participant characteristics were matched between groups (mean ± SD): age = 33 ± 6 yr; body mass = 82.7 ± 12 kg, body mass index = 26.8 ± 4.1 kg·min. Compared with DF, the MD group had significantly higher resting HR (P HRV indices were similar between ME and MC groups. However, after training, the ME group significantly (all P HRV, based on several conventional indices, was diminished in recently abstinent, methamphetamine-dependent individuals. Moreover, physical training yielded a marked increase in HRV, representing increased vagal modulation or improved autonomic balance.

  15. A random energy model for size dependence : recurrence vs. transience

    NARCIS (Netherlands)

    Külske, Christof

    1998-01-01

    We investigate the size dependence of disordered spin models having an infinite number of Gibbs measures in the framework of a simplified 'random energy model for size dependence'. We introduce two versions (involving either independent random walks or branching processes), that can be seen as

  16. Limit theorems for multi-indexed sums of random variables

    CERN Document Server

    Klesov, Oleg

    2014-01-01

    Presenting the first unified treatment of limit theorems for multiple sums of independent random variables, this volume fills an important gap in the field. Several new results are introduced, even in the classical setting, as well as some new approaches that are simpler than those already established in the literature. In particular, new proofs of the strong law of large numbers and the Hajek-Renyi inequality are detailed. Applications of the described theory include Gibbs fields, spin glasses, polymer models, image analysis and random shapes. Limit theorems form the backbone of probability theory and statistical theory alike. The theory of multiple sums of random variables is a direct generalization of the classical study of limit theorems, whose importance and wide application in science is unquestionable. However, to date, the subject of multiple sums has only been treated in journals. The results described in this book will be of interest to advanced undergraduates, graduate students and researchers who ...

  17. Probability densities and the radon variable transformation theorem

    International Nuclear Information System (INIS)

    Ramshaw, J.D.

    1985-01-01

    D. T. Gillespie recently derived a random variable transformation theorem relating to the joint probability densities of functionally dependent sets of random variables. The present author points out that the theorem can be derived as an immediate corollary of a simpler and more fundamental relation. In this relation the probability density is represented as a delta function averaged over an unspecified distribution of unspecified internal random variables. The random variable transformation is derived from this relation

  18. Randomized trial of intermittent or continuous amnioinfusion for variable decelerations.

    Science.gov (United States)

    Rinehart, B K; Terrone, D A; Barrow, J H; Isler, C M; Barrilleaux, P S; Roberts, W E

    2000-10-01

    To determine whether continuous or intermittent bolus amnioinfusion is more effective in relieving variable decelerations. Patients with repetitive variable decelerations were randomized to an intermittent bolus or continuous amnioinfusion. The intermittent bolus infusion group received boluses of 500 mL of normal saline, each over 30 minutes, with boluses repeated if variable decelerations recurred. The continuous infusion group received a bolus infusion of 500 mL of normal saline over 30 minutes and then 3 mL per minute until delivery occurred. The ability of the amnioinfusion to abolish variable decelerations was analyzed, as were maternal demographic and pregnancy outcome variables. Power analysis indicated that 64 patients would be required. Thirty-five patients were randomized to intermittent infusion and 30 to continuous infusion. There were no differences between groups in terms of maternal demographics, gestational age, delivery mode, neonatal outcome, median time to resolution of variable decelerations, or the number of times variable decelerations recurred. The median volume infused in the intermittent infusion group (500 mL) was significantly less than that in the continuous infusion group (905 mL, P =.003). Intermittent bolus amnioinfusion is as effective as continuous infusion in relieving variable decelerations in labor. Further investigation is necessary to determine whether either of these techniques is associated with increased occurrence of rare complications such as cord prolapse or uterine rupture.

  19. Uniqueness conditions for finitely dependent random fields

    International Nuclear Information System (INIS)

    Dobrushin, R.L.; Pecherski, E.A.

    1981-01-01

    The authors consider a random field for which uniqueness and some additional conditions guaranteeing that the correlations between the variables of the field decrease rapidly enough with the distance between the values of the parameter occur. The main result of the paper states that in such a case uniqueness is true for any other field with transition probabilities sufficiently close to those of the original field. Then they apply this result to some ''degenerate'' classes of random fields for which one can check this condition of correlation to decay, and thus obtain some new conditions of uniqueness. (Auth.)

  20. ESEARCH OF THE LAW OF DISTRIBUTION OF THE RANDOM VARIABLE OF THE COMPRESSION

    Directory of Open Access Journals (Sweden)

    I. Sarayeva

    2011-01-01

    Full Text Available At research of diagnosing the process of modern automobile engines by means of methods of mathematical statistics the experimental data of the random variable of compression are analysed and it is proved that the random variable of compression has the form of the normal law of distribution.

  1. Characteristics of quantum open systems: free random variables approach

    International Nuclear Information System (INIS)

    Gudowska-Nowak, E.; Papp, G.; Brickmann, J.

    1998-01-01

    Random Matrix Theory provides an interesting tool for modelling a number of phenomena where noises (fluctuations) play a prominent role. Various applications range from the theory of mesoscopic systems in nuclear and atomic physics to biophysical models, like Hopfield-type models of neural networks and protein folding. Random Matrix Theory is also used to study dissipative systems with broken time-reversal invariance providing a setup for analysis of dynamic processes in condensed, disordered media. In the paper we use the Random Matrix Theory (RMT) within the formalism of Free Random Variables (alias Blue's functions), which allows to characterize spectral properties of non-Hermitean ''Hamiltonians''. The relevance of using the Blue's function method is discussed in connection with application of non-Hermitean operators in various problems of physical chemistry. (author)

  2. Zero Distribution of System with Unknown Random Variables Case Study: Avoiding Collision Path

    Directory of Open Access Journals (Sweden)

    Parman Setyamartana

    2014-07-01

    Full Text Available This paper presents the stochastic analysis of finding the feasible trajectories of robotics arm motion at obstacle surrounding. Unknown variables are coefficients of polynomials joint angle so that the collision-free motion is achieved. ãk is matrix consisting of these unknown feasible polynomial coefficients. The pattern of feasible polynomial in the obstacle environment shows as random. This paper proposes to model the pattern of this randomness values using random polynomial with unknown variables as coefficients. The behavior of the system will be obtained from zero distribution as the characteristic of such random polynomial. Results show that the pattern of random polynomial of avoiding collision can be constructed from zero distribution. Zero distribution is like building block of the system with obstacles as uncertainty factor. By scale factor k, which has range, the random coefficient pattern can be predicted.

  3. Problems Identifying Independent and Dependent Variables

    Science.gov (United States)

    Leatham, Keith R.

    2012-01-01

    This paper discusses one step from the scientific method--that of identifying independent and dependent variables--from both scientific and mathematical perspectives. It begins by analyzing an episode from a middle school mathematics classroom that illustrates the need for students and teachers alike to develop a robust understanding of…

  4. Random paths with curvature dependent action

    International Nuclear Information System (INIS)

    Ambjoern, J.; Durhuus, B.

    1986-11-01

    We study discretized random paths with a curvature dependent action. The scaling limits of the corresponding statistical mechanical models can be constructed explicitly and are either usual Brownian motion or a theory where the correlations of tangents are nonzero and described by diffusion on the unit sphere. In the latter case the two point function has an anomalous dimension η = 1. (orig.)

  5. Variable Selection in Time Series Forecasting Using Random Forests

    Directory of Open Access Journals (Sweden)

    Hristos Tyralis

    2017-10-01

    Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

  6. Generating Variable and Random Schedules of Reinforcement Using Microsoft Excel Macros

    Science.gov (United States)

    Bancroft, Stacie L.; Bourret, Jason C.

    2008-01-01

    Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time.…

  7. CONVERGENCE OF THE FRACTIONAL PARTS OF THE RANDOM VARIABLES TO THE TRUNCATED EXPONENTIAL DISTRIBUTION

    Directory of Open Access Journals (Sweden)

    Bogdan Gheorghe Munteanu

    2013-01-01

    Full Text Available Using the stochastic approximations, in this paper it was studiedthe convergence in distribution of the fractional parts of the sum of random variables to the truncated exponential distribution with parameter lambda. This fact is feasible by means of the Fourier-Stieltjes sequence (FSS of the random variable.

  8. Random sets and random fuzzy sets as ill-perceived random variables an introduction for Ph.D. students and practitioners

    CERN Document Server

    Couso, Inés; Sánchez, Luciano

    2014-01-01

    This short book provides a unified view of the history and theory of random sets and fuzzy random variables, with special emphasis on its use for representing higher-order non-statistical uncertainty about statistical experiments. The authors lay bare the existence of two streams of works using the same mathematical ground, but differing form their use of sets, according to whether they represent objects of interest naturally taking the form of sets, or imprecise knowledge about such objects. Random (fuzzy) sets can be used in many fields ranging from mathematical morphology, economics, artificial intelligence, information processing and statistics per se, especially in areas where the outcomes of random experiments cannot be observed with full precision. This book also emphasizes the link between random sets and fuzzy sets with some techniques related to the theory of imprecise probabilities. This small book is intended for graduate and doctoral students in mathematics or engineering, but also provides an i...

  9. Output variability caused by random seeds in a multi-agent transport simulation model

    DEFF Research Database (Denmark)

    Paulsen, Mads; Rasmussen, Thomas Kjær; Nielsen, Otto Anker

    2018-01-01

    Dynamic transport simulators are intended to support decision makers in transport-related issues, and as such it is valuable that the random variability of their outputs is as small as possible. In this study we analyse the output variability caused by random seeds of a multi-agent transport...... simulator (MATSim) when applied to a case study of Santiago de Chile. Results based on 100 different random seeds shows that the relative accuracies of estimated link loads tend to increase with link load, but that relative errors of up to 10 % do occur even for links with large volumes. Although...

  10. Extended q -Gaussian and q -exponential distributions from gamma random variables

    Science.gov (United States)

    Budini, Adrián A.

    2015-05-01

    The family of q -Gaussian and q -exponential probability densities fit the statistical behavior of diverse complex self-similar nonequilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained by maximizing Tsallis "nonextensive" entropy under appropriate constraints, as well as from superstatistical models. In this paper we provide an alternative and complementary scheme for deriving these objects. We show that q -Gaussian and q -exponential random variables can always be expressed as a function of two statistically independent gamma random variables with the same scale parameter. Their shape index determines the complexity q parameter. This result also allows us to define an extended family of asymmetric q -Gaussian and modified q -exponential densities, which reduce to the standard ones when the shape parameters are the same. Furthermore, we demonstrate that a simple change of variables always allows relating any of these distributions with a beta stochastic variable. The extended distributions are applied in the statistical description of different complex dynamics such as log-return signals in financial markets and motion of point defects in a fluid flow.

  11. A Preliminary Investigation of a Randomized Dependent Group Contingency for Hallway Transitions

    Science.gov (United States)

    Deshais, Meghan A.; Fisher, Alyssa B.; Kahng, SungWoo

    2018-01-01

    We conducted a preliminary investigation of a randomized dependent group contingency to decrease disruptive behavior during hallway transitions. Two first-graders, identified by their classroom teacher, participated in this study. A multiple baseline across transitions was used to evaluate the effects of the randomized dependent group contingency…

  12. Piecewise linearisation of the first order loss function for families of arbitrarily distributed random variables

    NARCIS (Netherlands)

    Rossi, R.; Hendrix, E.M.T.

    2014-01-01

    We discuss the problem of computing optimal linearisation parameters for the first order loss function of a family of arbitrarily distributed random variable. We demonstrate that, in contrast to the problem in which parameters must be determined for the loss function of a single random variable,

  13. An infinite-dimensional weak KAM theory via random variables

    KAUST Repository

    Gomes, Diogo A.

    2016-08-31

    We develop several aspects of the infinite-dimensional Weak KAM theory using a random variables\\' approach. We prove that the infinite-dimensional cell problem admits a viscosity solution that is a fixed point of the Lax-Oleinik semigroup. Furthermore, we show the existence of invariant minimizing measures and calibrated curves defined on R.

  14. An infinite-dimensional weak KAM theory via random variables

    KAUST Repository

    Gomes, Diogo A.; Nurbekyan, Levon

    2016-01-01

    We develop several aspects of the infinite-dimensional Weak KAM theory using a random variables' approach. We prove that the infinite-dimensional cell problem admits a viscosity solution that is a fixed point of the Lax-Oleinik semigroup. Furthermore, we show the existence of invariant minimizing measures and calibrated curves defined on R.

  15. Extensions of von Neumann's method for generating random variables

    International Nuclear Information System (INIS)

    Monahan, J.F.

    1979-01-01

    Von Neumann's method of generating random variables with the exponential distribution and Forsythe's method for obtaining distributions with densities of the form e/sup -G//sup( x/) are generalized to apply to certain power series representations. The flexibility of the power series methods is illustrated by algorithms for the Cauchy and geometric distributions

  16. Variable screening and ranking using sampling-based sensitivity measures

    International Nuclear Information System (INIS)

    Wu, Y-T.; Mohanty, Sitakanta

    2006-01-01

    This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

  17. Spherically symmetric random walks. II. Dimensionally dependent critical behavior

    International Nuclear Information System (INIS)

    Bender, C.M.; Boettcher, S.; Meisinger, P.N.

    1996-01-01

    A recently developed model of random walks on a D-dimensional hyperspherical lattice, where D is not restricted to integer values, is extended to include the possibility of creating and annihilating random walkers. Steady-state distributions of random walkers are obtained for all dimensions D approx-gt 0 by solving a discrete eigenvalue problem. These distributions exhibit dimensionally dependent critical behavior as a function of the birth rate. This remarkably simple model exhibits a second-order phase transition with a universal, nontrivial critical exponent for all dimensions D approx-gt 0. copyright 1996 The American Physical Society

  18. SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

    International Nuclear Information System (INIS)

    Cox, N. D.; Miller, C. F.

    1985-01-01

    1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

  19. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Ahmed, Sajid

    2016-01-13

    Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

  20. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Ahmed, Sajid; Alouini, Mohamed-Slim; Jardak, Seifallah

    2016-01-01

    Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

  1. Random recurrence equations and ruin in a Markov-dependent stochastic economic environment

    DEFF Research Database (Denmark)

    Collamore, Jeffrey F.

    2009-01-01

    series models.  Our results build upon work of Goldie, who has developed tail asymptotics applicable for independent sequences of random variables subject to a random recurrence equation.  In contrast, we adopt a general approach based on the theory of Harris recurrent Markov chains and the associated...

  2. Fixed transaction costs and modelling limited dependent variables

    NARCIS (Netherlands)

    Hempenius, A.L.

    1994-01-01

    As an alternative to the Tobit model, for vectors of limited dependent variables, I suggest a model, which follows from explicitly using fixed costs, if appropriate of course, in the utility function of the decision-maker.

  3. Quadratic time dependent Hamiltonians and separation of variables

    International Nuclear Information System (INIS)

    Anzaldo-Meneses, A.

    2017-01-01

    Time dependent quantum problems defined by quadratic Hamiltonians are solved using canonical transformations. The Green’s function is obtained and a comparison with the classical Hamilton–Jacobi method leads to important geometrical insights like exterior differential systems, Monge cones and time dependent Gaussian metrics. The Wei–Norman approach is applied using unitary transformations defined in terms of generators of the associated Lie groups, here the semi-direct product of the Heisenberg group and the symplectic group. A new explicit relation for the unitary transformations is given in terms of a finite product of elementary transformations. The sequential application of adequate sets of unitary transformations leads naturally to a new separation of variables method for time dependent Hamiltonians, which is shown to be related to the Inönü–Wigner contraction of Lie groups. The new method allows also a better understanding of interacting particles or coupled modes and opens an alternative way to analyze topological phases in driven systems. - Highlights: • Exact unitary transformation reducing time dependent quadratic quantum Hamiltonian to zero. • New separation of variables method and simultaneous uncoupling of modes. • Explicit examples of transformations for one to four dimensional problems. • New general evolution equation for quadratic form in the action, respectively Green’s function.

  4. Random and systematic spatial variability of 137Cs inventories at reference sites in South-Central Brazil

    Directory of Open Access Journals (Sweden)

    Correchel Vladia

    2005-01-01

    Full Text Available The precision of the 137Cs fallout redistribution technique for the evaluation of soil erosion rates is strongly dependent on the quality of an average inventory taken at a representative reference site. The knowledge of the sources and of the degree of variation of the 137Cs fallout spatial distribution plays an important role on its use. Four reference sites were selected in the South-Central region of Brazil which were characterized in terms of soil chemical, physical and mineralogical aspects as well as the spatial variability of 137Cs inventories. Some important differences in the patterns of 137Cs depth distribution in the soil profiles of the different sites were found. They are probably associated to chemical, physical, mineralogical and biological differences of the soils but many questions still remain open for future investigation, mainly those regarding the adsorption and dynamics of the 137Cs ions in soil profiles under tropical conditions. The random spatial variability (inside each reference site was higher than the systematic spatial variability (between reference sites but their causes were not clearly identified as possible consequences of chemical, physical, mineralogical variability, and/or precipitation.

  5. Tolerance limits and tolerance intervals for ratios of normal random variables using a bootstrap calibration.

    Science.gov (United States)

    Flouri, Marilena; Zhai, Shuyan; Mathew, Thomas; Bebu, Ionut

    2017-05-01

    This paper addresses the problem of deriving one-sided tolerance limits and two-sided tolerance intervals for a ratio of two random variables that follow a bivariate normal distribution, or a lognormal/normal distribution. The methodology that is developed uses nonparametric tolerance limits based on a parametric bootstrap sample, coupled with a bootstrap calibration in order to improve accuracy. The methodology is also adopted for computing confidence limits for the median of the ratio random variable. Numerical results are reported to demonstrate the accuracy of the proposed approach. The methodology is illustrated using examples where ratio random variables are of interest: an example on the radioactivity count in reverse transcriptase assays and an example from the area of cost-effectiveness analysis in health economics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

    Directory of Open Access Journals (Sweden)

    Hideki Katagiri

    2017-10-01

    Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.

  7. The mesoscopic conductance of disordered rings, its random matrix theory and the generalized variable range hopping picture

    International Nuclear Information System (INIS)

    Stotland, Alexander; Peer, Tal; Cohen, Doron; Budoyo, Rangga; Kottos, Tsampikos

    2008-01-01

    The calculation of the conductance of disordered rings requires a theory that goes beyond the Kubo-Drude formulation. Assuming 'mesoscopic' circumstances the analysis of the electro-driven transitions shows similarities with a percolation problem in energy space. We argue that the texture and the sparsity of the perturbation matrix dictate the value of the conductance, and study its dependence on the disorder strength, ranging from the ballistic to the Anderson localization regime. An improved sparse random matrix model is introduced to capture the essential ingredients of the problem, and leads to a generalized variable range hopping picture. (fast track communication)

  8. A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

    KAUST Repository

    Babuška, Ivo; Nobile, Fabio; Tempone, Raul

    2010-01-01

    This work proposes and analyzes a stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms. These input data are assumed to depend on a finite number of random variables. The method consists of a Galerkin approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space, and naturally leads to the solution of uncoupled deterministic problems as in the Monte Carlo approach. It treats easily a wide range of situations, such as input data that depend nonlinearly on the random variables, diffusivity coefficients with unbounded second moments, and random variables that are correlated or even unbounded. We provide a rigorous convergence analysis and demonstrate exponential convergence of the “probability error” with respect to the number of Gauss points in each direction of the probability space, under some regularity assumptions on the random input data. Numerical examples show the effectiveness of the method. Finally, we include a section with developments posterior to the original publication of this work. There we review sparse grid stochastic collocation methods, which are effective collocation strategies for problems that depend on a moderately large number of random variables.

  9. Statistical Analysis for Multisite Trials Using Instrumental Variables with Random Coefficients

    Science.gov (United States)

    Raudenbush, Stephen W.; Reardon, Sean F.; Nomi, Takako

    2012-01-01

    Multisite trials can clarify the average impact of a new program and the heterogeneity of impacts across sites. Unfortunately, in many applications, compliance with treatment assignment is imperfect. For these applications, we propose an instrumental variable (IV) model with person-specific and site-specific random coefficients. Site-specific IV…

  10. On the Wigner law in dilute random matrices

    Science.gov (United States)

    Khorunzhy, A.; Rodgers, G. J.

    1998-12-01

    We consider ensembles of N × N symmetric matrices whose entries are weakly dependent random variables. We show that random dilution can change the limiting eigenvalue distribution of such matrices. We prove that under general and natural conditions the normalised eigenvalue counting function coincides with the semicircle (Wigner) distribution in the limit N → ∞. This can be explained by the observation that dilution (or more generally, random modulation) eliminates the weak dependence (or correlations) between random matrix entries. It also supports our earlier conjecture that the Wigner distribution is stable to random dilution and modulation.

  11. Sums and Products of Jointly Distributed Random Variables: A Simplified Approach

    Science.gov (United States)

    Stein, Sheldon H.

    2005-01-01

    Three basic theorems concerning expected values and variances of sums and products of random variables play an important role in mathematical statistics and its applications in education, business, the social sciences, and the natural sciences. A solid understanding of these theorems requires that students be familiar with the proofs of these…

  12. Free random variables

    CERN Document Server

    Voiculescu, Dan; Nica, Alexandru

    1992-01-01

    This book presents the first comprehensive introduction to free probability theory, a highly noncommutative probability theory with independence based on free products instead of tensor products. Basic examples of this kind of theory are provided by convolution operators on free groups and by the asymptotic behavior of large Gaussian random matrices. The probabilistic approach to free products has led to a recent surge of new results on the von Neumann algebras of free groups. The book is ideally suited as a textbook for an advanced graduate course and could also provide material for a seminar. In addition to researchers and graduate students in mathematics, this book will be of interest to physicists and others who use random matrices.

  13. Modelling comonotonic group-life under dependent decrement causes

    OpenAIRE

    Wang, Dabuxilatu

    2011-01-01

    Comonotonicity had been a extreme case of dependency between random variables. This article consider an extension of single life model under multiple dependent decrement causes to the case of comonotonic group-life.

  14. Statistical Dependence of Pipe Breaks on Explanatory Variables

    Directory of Open Access Journals (Sweden)

    Patricia Gómez-Martínez

    2017-02-01

    Full Text Available Aging infrastructure is the main challenge currently faced by water suppliers. Estimation of assets lifetime requires reliable criteria to plan assets repair and renewal strategies. To do so, pipe break prediction is one of the most important inputs. This paper analyzes the statistical dependence of pipe breaks on explanatory variables, determining their optimal combination and quantifying their influence on failure prediction accuracy. A large set of registered data from Madrid water supply network, managed by Canal de Isabel II, has been filtered, classified and studied. Several statistical Bayesian models have been built and validated from the available information with a technique that combines reference periods of time as well as geographical location. Statistical models of increasing complexity are built from zero up to five explanatory variables following two approaches: a set of independent variables or a combination of two joint variables plus an additional number of independent variables. With the aim of finding the variable combination that provides the most accurate prediction, models are compared following an objective validation procedure based on the model skill to predict the number of pipe breaks in a large set of geographical locations. As expected, model performance improves as the number of explanatory variables increases. However, the rate of improvement is not constant. Performance metrics improve significantly up to three variables, but the tendency is softened for higher order models, especially in trunk mains where performance is reduced. Slight differences are found between trunk mains and distribution lines when selecting the most influent variables and models.

  15. Goodness-of-fit tests with dependent observations

    International Nuclear Information System (INIS)

    Chicheportiche, Rémy; Bouchaud, Jean-Philippe

    2011-01-01

    We revisit the Kolmogorov–Smirnov and Cramér–von Mises goodness-of-fit (GoF) tests and propose a generalization to identically distributed, but dependent univariate random variables. We show that the dependence leads to a reduction of the 'effective' number of independent observations. The generalized GoF tests are not distribution-free but rather depend on all the lagged bivariate copulas. These objects, that we call 'self-copulas', encode all the non-linear temporal dependences. We introduce a specific, log-normal model for these self-copulas, for which a number of analytical results are derived. An application to financial time series is provided. As is well known, the dependence is to be long-ranged in this case, a finding that we confirm using self-copulas. As a consequence, the acceptance rates for GoF tests are substantially higher than if the returns were iid random variables

  16. AUTOCLASSIFICATION OF THE VARIABLE 3XMM SOURCES USING THE RANDOM FOREST MACHINE LEARNING ALGORITHM

    International Nuclear Information System (INIS)

    Farrell, Sean A.; Murphy, Tara; Lo, Kitty K.

    2015-01-01

    In the current era of large surveys and massive data sets, autoclassification of astrophysical sources using intelligent algorithms is becoming increasingly important. In this paper we present the catalog of variable sources in the Third XMM-Newton Serendipitous Source catalog (3XMM) autoclassified using the Random Forest machine learning algorithm. We used a sample of manually classified variable sources from the second data release of the XMM-Newton catalogs (2XMMi-DR2) to train the classifier, obtaining an accuracy of ∼92%. We also evaluated the effectiveness of identifying spurious detections using a sample of spurious sources, achieving an accuracy of ∼95%. Manual investigation of a random sample of classified sources confirmed these accuracy levels and showed that the Random Forest machine learning algorithm is highly effective at automatically classifying 3XMM sources. Here we present the catalog of classified 3XMM variable sources. We also present three previously unidentified unusual sources that were flagged as outlier sources by the algorithm: a new candidate supergiant fast X-ray transient, a 400 s X-ray pulsar, and an eclipsing 5 hr binary system coincident with a known Cepheid.

  17. [Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

    Science.gov (United States)

    Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

    2018-04-01

    Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

  18. Common characterization of variability and forecast errors of variable energy sources and their mitigation using reserves in power system integration studies

    Energy Technology Data Exchange (ETDEWEB)

    Menemenlis, N.; Huneault, M. [IREQ, Varennes, QC (Canada); Robitaille, A. [Dir. Plantif. de la Production Eolienne, Montreal, QC (Canada). HQ Production; Holttinen, H. [VTT Technical Research Centre of Finland, VTT (Finland)

    2012-07-01

    This In this paper we define and characterize the two random variables, variability and forecast error, over which uncertainty in power systems operations is characterized and mitigated. We show that the characterization of both these variables can be carried out with the same mathematical tools. Furthermore, this common characterization of random variables lends itself to a common methodology for the calculation of non-contingency reserves required to mitigate their effects. A parallel comparison of these two variables demonstrates similar inherent statistical properties. They depend on imminent conditions, evolve with time and can be asymmetric. Correlation is an important factor when aggregating individual wind farm characteristics in forming the distribution of the total wind generation for imminent conditions. (orig.)

  19. The quotient of normal random variables and application to asset price fat tails

    Science.gov (United States)

    Caginalp, Carey; Caginalp, Gunduz

    2018-06-01

    The quotient of random variables with normal distributions is examined and proven to have power law decay, with density f(x) ≃f0x-2, with the coefficient depending on the means and variances of the numerator and denominator and their correlation. We also obtain the conditional probability densities for each of the four quadrants given by the signs of the numerator and denominator for arbitrary correlation ρ ∈ [ - 1 , 1) . For ρ = - 1 we obtain a particularly simple closed form solution for all x ∈ R. The results are applied to a basic issue in economics and finance, namely the density of relative price changes. Classical finance stipulates a normal distribution of relative price changes, though empirical studies suggest a power law at the tail end. By considering the supply and demand in a basic price change model, we prove that the relative price change has density that decays with an x-2 power law. Various parameter limits are established.

  20. Variability in response to albuminuria-lowering drugs

    DEFF Research Database (Denmark)

    Petrykiv, Sergei I; de Zeeuw, Dick; Persson, Frederik

    2017-01-01

    AIMS: Albuminuria-lowering drugs have shown different effect size in different individuals. Since urine albumin levels are known to vary considerably from day-to-day, we questioned whether the between-individual variability in albuminuria response after therapy initiation reflects a random...... variability or a true response variation to treatment. In addition, we questioned whether the response variability is drug dependent. METHODS: To determine whether the response to treatment is random or a true drug response, we correlated in six clinical trials the change in albuminuria during placebo...... or active treatment (on-treatment) with the change in albuminuria during wash-out (off-treatment). If these responses correlate during active treatment, it suggests that at least part of the response variability can be attributed to drug response variability. We tested this for enalapril, losartan...

  1. Continuous-time random walks on networks with vertex- and time-dependent forcing.

    Science.gov (United States)

    Angstmann, C N; Donnelly, I C; Henry, B I; Langlands, T A M

    2013-08-01

    We have investigated the transport of particles moving as random walks on the vertices of a network, subject to vertex- and time-dependent forcing. We have derived the generalized master equations for this transport using continuous time random walks, characterized by jump and waiting time densities, as the underlying stochastic process. The forcing is incorporated through a vertex- and time-dependent bias in the jump densities governing the random walking particles. As a particular case, we consider particle forcing proportional to the concentration of particles on adjacent vertices, analogous to self-chemotactic attraction in a spatial continuum. Our algebraic and numerical studies of this system reveal an interesting pair-aggregation pattern formation in which the steady state is composed of a high concentration of particles on a small number of isolated pairs of adjacent vertices. The steady states do not exhibit this pair aggregation if the transport is random on the vertices, i.e., without forcing. The manifestation of pair aggregation on a transport network may thus be a signature of self-chemotactic-like forcing.

  2. Testing serial dependence by Random-shuffle surrogates and the Wayland method

    Energy Technology Data Exchange (ETDEWEB)

    Hirata, Yoshito [Department of Mathematical Informatics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Aihara Complexity Modelling Project, ERATO, JST (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)], E-mail: yoshito@sat.t.u-tokyo.ac.jp; Horai, Shunsuke [Aihara Complexity Modelling Project, ERATO, JST (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Suzuki, Hideyuki [Department of Mathematical Informatics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Aihara, Kazuyuki [Department of Mathematical Informatics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Aihara Complexity Modelling Project, ERATO, JST (Japan); Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

    2007-10-22

    Given time series, a primary concern is existence of serial dependence and determinism. They are often tested with Random-shuffle surrogates, which totally break serial dependence, and the Wayland method. Since the statistic of the Wayland method fundamentally shows a smaller value for a more deterministic time series, for real-world data, we usually expect that the statistic for the original data is smaller than or equal to those of Random-shuffle surrogates. However, we show herewith an opposite result with wind data in high time resolution. We argue that this puzzling phenomenon can be produced by observational or dynamical noise, both of which may be produced by a low-dimensional deterministic system. Thus the one-sided test is dangerous.

  3. Testing serial dependence by Random-shuffle surrogates and the Wayland method

    International Nuclear Information System (INIS)

    Hirata, Yoshito; Horai, Shunsuke; Suzuki, Hideyuki; Aihara, Kazuyuki

    2007-01-01

    Given time series, a primary concern is existence of serial dependence and determinism. They are often tested with Random-shuffle surrogates, which totally break serial dependence, and the Wayland method. Since the statistic of the Wayland method fundamentally shows a smaller value for a more deterministic time series, for real-world data, we usually expect that the statistic for the original data is smaller than or equal to those of Random-shuffle surrogates. However, we show herewith an opposite result with wind data in high time resolution. We argue that this puzzling phenomenon can be produced by observational or dynamical noise, both of which may be produced by a low-dimensional deterministic system. Thus the one-sided test is dangerous

  4. Subgeometric Ergodicity Analysis of Continuous-Time Markov Chains under Random-Time State-Dependent Lyapunov Drift Conditions

    Directory of Open Access Journals (Sweden)

    Mokaedi V. Lekgari

    2014-01-01

    Full Text Available We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs. We are mainly concerned with making use of the available results on deterministic state-dependent drift conditions for CTMCs and on random-time state-dependent drift conditions for discrete-time Markov chains and transferring them to CTMCs.

  5. Stable Graphical Model Estimation with Random Forests for Discrete, Continuous, and Mixed Variables

    OpenAIRE

    Fellinghauer, Bernd; Bühlmann, Peter; Ryffel, Martin; von Rhein, Michael; Reinhardt, Jan D.

    2011-01-01

    A conditional independence graph is a concise representation of pairwise conditional independence among many variables. Graphical Random Forests (GRaFo) are a novel method for estimating pairwise conditional independence relationships among mixed-type, i.e. continuous and discrete, variables. The number of edges is a tuning parameter in any graphical model estimator and there is no obvious number that constitutes a good choice. Stability Selection helps choosing this parameter with respect to...

  6. On lower limits and equivalences for distribution tails of randomly stopped sums

    NARCIS (Netherlands)

    Denisov, D.E.; Foss, S.G.; Korshunov, D.A.

    2008-01-01

    For a distribution F*t of a random sum St=¿1+¿+¿t of i.i.d. random variables with a common distribution F on the half-line [0, 8), we study the limits of the ratios of tails as x¿8 (here, t is a counting random variable which does not depend on {¿n}n=1). We also consider applications of the results

  7. A cellular automata model of traffic flow with variable probability of randomization

    International Nuclear Information System (INIS)

    Zheng Wei-Fan; Zhang Ji-Ye

    2015-01-01

    Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow–density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. (paper)

  8. On bounds in Poisson approximation for distributions of independent negative-binomial distributed random variables.

    Science.gov (United States)

    Hung, Tran Loc; Giang, Le Truong

    2016-01-01

    Using the Stein-Chen method some upper bounds in Poisson approximation for distributions of row-wise triangular arrays of independent negative-binomial distributed random variables are established in this note.

  9. Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables

    Directory of Open Access Journals (Sweden)

    S. K. Barik

    2012-01-01

    Full Text Available Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.

  10. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Jardak, Seifallah

    2014-09-01

    Correlated waveforms have a number of applications in different fields, such as radar and communication. It is very easy to generate correlated waveforms using infinite alphabets, but for some of the applications, it is very challenging to use them in practice. Moreover, to generate infinite alphabet constant envelope correlated waveforms, the available research uses iterative algorithms, which are computationally very expensive. In this work, we propose simple novel methods to generate correlated waveforms using finite alphabet constant and non-constant-envelope symbols. To generate finite alphabet waveforms, the proposed method map the Gaussian random variables onto the phase-shift-keying, pulse-amplitude, and quadrature-amplitude modulation schemes. For such mapping, the probability-density-function of Gaussian random variables is divided into M regions, where M is the number of alphabets in the corresponding modulation scheme. By exploiting the mapping function, the relationship between the cross-correlation of Gaussian and finite alphabet symbols is derived. To generate equiprobable symbols, the area of each region is kept same. If the requirement is to have each symbol with its own unique probability, the proposed scheme allows us that as well. Although, the proposed scheme is general, the main focus of this paper is to generate finite alphabet waveforms for multiple-input multiple-output radar, where correlated waveforms are used to achieve desired beampatterns. © 2014 IEEE.

  11. Energy decay of a variable-coefficient wave equation with nonlinear time-dependent localized damping

    Directory of Open Access Journals (Sweden)

    Jieqiong Wu

    2015-09-01

    Full Text Available We study the energy decay for the Cauchy problem of the wave equation with nonlinear time-dependent and space-dependent damping. The damping is localized in a bounded domain and near infinity, and the principal part of the wave equation has a variable-coefficient. We apply the multiplier method for variable-coefficient equations, and obtain an energy decay that depends on the property of the coefficient of the damping term.

  12. Using randomized variable practice in the treatment of childhood apraxia of speech.

    Science.gov (United States)

    Skelton, Steven L; Hagopian, Aubrie Lynn

    2014-11-01

    The purpose of this study was to determine if randomized variable practice, a central component of concurrent treatment, would be effective and efficient in treating childhood apraxia of speech (CAS). Concurrent treatment is a treatment program that takes the speech task hierarchy and randomizes it so that all tasks are worked on in one session. Previous studies have shown the treatment program to be effective and efficient in treating phonological and articulation disorders. The program was adapted to be used with children with CAS. A research design of multiple baselines across participants was used. Probes of generalization to untaught words were administered every fifth session. Three children, ranging in age from 4 to 6 years old, were the participants. Data were collected as percent correct productions during baseline, treatment, and probes of generalization of target sounds to untaught words and three-word phrases. All participants showed an increase in correct productions during treatment and during probes. Effect sizes (standard mean difference) for treatment were 3.61-5.00, and for generalization probes, they were 3.15-8.51. The results obtained from this study suggest that randomized variable practice as used in concurrent treatment can be adapted for use in treating children with CAS. Replication of this study with other children presenting CAS will be needed to establish generality of the findings.

  13. Problems of variance reduction in the simulation of random variables

    International Nuclear Information System (INIS)

    Lessi, O.

    1987-01-01

    The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced

  14. Quadratic time dependent Hamiltonians and separation of variables

    Science.gov (United States)

    Anzaldo-Meneses, A.

    2017-06-01

    Time dependent quantum problems defined by quadratic Hamiltonians are solved using canonical transformations. The Green's function is obtained and a comparison with the classical Hamilton-Jacobi method leads to important geometrical insights like exterior differential systems, Monge cones and time dependent Gaussian metrics. The Wei-Norman approach is applied using unitary transformations defined in terms of generators of the associated Lie groups, here the semi-direct product of the Heisenberg group and the symplectic group. A new explicit relation for the unitary transformations is given in terms of a finite product of elementary transformations. The sequential application of adequate sets of unitary transformations leads naturally to a new separation of variables method for time dependent Hamiltonians, which is shown to be related to the Inönü-Wigner contraction of Lie groups. The new method allows also a better understanding of interacting particles or coupled modes and opens an alternative way to analyze topological phases in driven systems.

  15. A Realization of a Quasi-Random Walk for Atoms in Time-Dependent Optical Potentials

    Directory of Open Access Journals (Sweden)

    Torsten Hinkel

    2015-09-01

    Full Text Available We consider the time dependent dynamics of an atom in a two-color pumped cavity, longitudinally through a side mirror and transversally via direct driving of the atomic dipole. The beating of the two driving frequencies leads to a time dependent effective optical potential that forces the atom into a non-trivial motion, strongly resembling a discrete random walk behavior between lattice sites. We provide both numerical and analytical analysis of such a quasi-random walk behavior.

  16. On the Distribution of Indefinite Quadratic Forms in Gaussian Random Variables

    KAUST Repository

    Al-Naffouri, Tareq Y.

    2015-10-30

    © 2015 IEEE. In this work, we propose a unified approach to evaluating the CDF and PDF of indefinite quadratic forms in Gaussian random variables. Such a quantity appears in many applications in communications, signal processing, information theory, and adaptive filtering. For example, this quantity appears in the mean-square-error (MSE) analysis of the normalized least-meansquare (NLMS) adaptive algorithm, and SINR associated with each beam in beam forming applications. The trick of the proposed approach is to replace inequalities that appear in the CDF calculation with unit step functions and to use complex integral representation of the the unit step function. Complex integration allows us then to evaluate the CDF in closed form for the zero mean case and as a single dimensional integral for the non-zero mean case. Utilizing the saddle point technique allows us to closely approximate such integrals in non zero mean case. We demonstrate how our approach can be extended to other scenarios such as the joint distribution of quadratic forms and ratios of such forms, and to characterize quadratic forms in isotropic distributed random variables.We also evaluate the outage probability in multiuser beamforming using our approach to provide an application of indefinite forms in communications.

  17. Homogenization for rigid suspensions with random velocity-dependent interfacial forces

    KAUST Repository

    Gorb, Yuliya

    2014-12-01

    We study suspensions of solid particles in a viscous incompressible fluid in the presence of random velocity-dependent interfacial forces. The flow at a small Reynolds number is modeled by the Stokes equations, coupled with the motion of rigid particles arranged in a periodic array. The objective is to perform homogenization for the given suspension and obtain an equivalent description of a homogeneous (effective) medium, the macroscopic effect of the interfacial forces and the effective viscosity are determined using the analysis on a periodicity cell. In particular, the solutions uωε to a family of problems corresponding to the size of microstructure ε and describing suspensions of rigid particles with random surface forces imposed on the interface, converge H1-weakly as ε→0 a.s. to a solution of a Stokes homogenized problem, with velocity dependent body forces. A corrector to a homogenized solution that yields a strong H1-convergence is also determined. The main technical construction is built upon the Γ-convergence theory. © 2014 Elsevier Inc.

  18. Using mi impute chained to fit ANCOVA models in randomized trials with censored dependent and independent variables

    DEFF Research Database (Denmark)

    Andersen, Andreas; Rieckmann, Andreas

    2016-01-01

    In this article, we illustrate how to use mi impute chained with intreg to fit an analysis of covariance analysis of censored and nondetectable immunological concentrations measured in a randomized pretest–posttest design.......In this article, we illustrate how to use mi impute chained with intreg to fit an analysis of covariance analysis of censored and nondetectable immunological concentrations measured in a randomized pretest–posttest design....

  19. Attention Measures of Accuracy, Variability, and Fatigue Detect Early Response to Donepezil in Alzheimer's Disease: A Randomized, Double-blind, Placebo-Controlled Pilot Trial.

    Science.gov (United States)

    Vila-Castelar, Clara; Ly, Jenny J; Kaplan, Lillian; Van Dyk, Kathleen; Berger, Jeffrey T; Macina, Lucy O; Stewart, Jennifer L; Foldi, Nancy S

    2018-04-09

    Donepezil is widely used to treat Alzheimer's disease (AD), but detecting early response remains challenging for clinicians. Acetylcholine is known to directly modulate attention, particularly under high cognitive conditions, but no studies to date test whether measures of attention under high load can detect early effects of donepezil. We hypothesized that load-dependent attention tasks are sensitive to short-term treatment effects of donepezil, while global and other domain-specific cognitive measures are not. This longitudinal, randomized, double-blind, placebo-controlled pilot trial (ClinicalTrials.gov Identifier: NCT03073876) evaluated 23 participants newly diagnosed with AD initiating de novo donepezil treatment (5 mg). After baseline assessment, participants were randomized into Drug (n = 12) or Placebo (n = 11) groups, and retested after approximately 6 weeks. Cognitive assessment included: (a) attention tasks (Foreperiod Effect, Attentional Blink, and Covert Orienting tasks) measuring processing speed, top-down accuracy, orienting, intra-individual variability, and fatigue; (b) global measures (Alzheimer's Disease Assessment Scale-Cognitive Subscale, Mini-Mental Status Examination, Dementia Rating Scale); and (c) domain-specific measures (memory, language, visuospatial, and executive function). The Drug but not the Placebo group showed benefits of treatment at high-load measures by preserving top-down accuracy, improving intra-individual variability, and averting fatigue. In contrast, other global or cognitive domain-specific measures could not detect treatment effects over the same treatment interval. The pilot-study suggests that attention measures targeting accuracy, variability, and fatigue under high-load conditions could be sensitive to short-term cholinergic treatment. Given the central role of acetylcholine in attentional function, load-dependent attentional measures may be valuable cognitive markers of early treatment response.

  20. Analysis of Secret Key Randomness Exploiting the Radio Channel Variability

    Directory of Open Access Journals (Sweden)

    Taghrid Mazloum

    2015-01-01

    Full Text Available A few years ago, physical layer based techniques have started to be considered as a way to improve security in wireless communications. A well known problem is the management of ciphering keys, both regarding the generation and distribution of these keys. A way to alleviate such difficulties is to use a common source of randomness for the legitimate terminals, not accessible to an eavesdropper. This is the case of the fading propagation channel, when exact or approximate reciprocity applies. Although this principle has been known for long, not so many works have evaluated the effect of radio channel properties in practical environments on the degree of randomness of the generated keys. To this end, we here investigate indoor radio channel measurements in different environments and settings at either 2.4625 GHz or 5.4 GHz band, of particular interest for WIFI related standards. Key bits are extracted by quantizing the complex channel coefficients and their randomness is evaluated using the NIST test suite. We then look at the impact of the carrier frequency, the channel variability in the space, time, and frequency degrees of freedom used to construct a long secret key, in relation to the nature of the radio environment such as the LOS/NLOS character.

  1. The discovery of timescale-dependent color variability of quasars

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yu-Han; Wang, Jun-Xian; Chen, Xiao-Yang [CAS Key Laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science and Technology of China, Hefei, Anhui 230026 (China); Zheng, Zhen-Ya, E-mail: sunyh92@mail.ustc.edu.cn, E-mail: jxw@ustc.edu.cn [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 (United States)

    2014-09-01

    Quasars are variable on timescales from days to years in UV/optical and generally appear bluer while they brighten. The physics behind the variations in fluxes and colors remains unclear. Using Sloan Digital Sky Survey g- and r-band photometric monitoring data for quasars in Stripe 82, we find that although the flux variation amplitude increases with timescale, the color variability exhibits the opposite behavior. The color variability of quasars is prominent at timescales as short as ∼10 days, but gradually reduces toward timescales up to years. In other words, the variable emission at shorter timescales is bluer than that at longer timescales. This timescale dependence is clearly and consistently detected at all redshifts from z = 0 to 3.5; thus, it cannot be due to contamination to broadband photometry from emission lines that do not respond to fast continuum variations. The discovery directly rules out the possibility that simply attributes the color variability to contamination from a non-variable redder component such as the host galaxy. It cannot be interpreted as changes in global accretion rate either. The thermal accretion disk fluctuation model is favored in the sense that fluctuations in the inner, hotter region of the disk are responsible for short-term variations, while longer-term and stronger variations are expected from the larger and cooler disk region. An interesting implication is that one can use quasar variations at different timescales to probe disk emission at different radii.

  2. A simulation study on estimating biomarker-treatment interaction effects in randomized trials with prognostic variables.

    Science.gov (United States)

    Haller, Bernhard; Ulm, Kurt

    2018-02-20

    To individualize treatment decisions based on patient characteristics, identification of an interaction between a biomarker and treatment is necessary. Often such potential interactions are analysed using data from randomized clinical trials intended for comparison of two treatments. Tests of interactions are often lacking statistical power and we investigated if and how a consideration of further prognostic variables can improve power and decrease the bias of estimated biomarker-treatment interactions in randomized clinical trials with time-to-event outcomes. A simulation study was performed to assess how prognostic factors affect the estimate of the biomarker-treatment interaction for a time-to-event outcome, when different approaches, like ignoring other prognostic factors, including all available covariates or using variable selection strategies, are applied. Different scenarios regarding the proportion of censored observations, the correlation structure between the covariate of interest and further potential prognostic variables, and the strength of the interaction were considered. The simulation study revealed that in a regression model for estimating a biomarker-treatment interaction, the probability of detecting a biomarker-treatment interaction can be increased by including prognostic variables that are associated with the outcome, and that the interaction estimate is biased when relevant prognostic variables are not considered. However, the probability of a false-positive finding increases if too many potential predictors are included or if variable selection is performed inadequately. We recommend undertaking an adequate literature search before data analysis to derive information about potential prognostic variables and to gain power for detecting true interaction effects and pre-specifying analyses to avoid selective reporting and increased false-positive rates.

  3. MODELING THE TIME VARIABILITY OF SDSS STRIPE 82 QUASARS AS A DAMPED RANDOM WALK

    International Nuclear Information System (INIS)

    MacLeod, C. L.; Ivezic, Z.; Bullock, E.; Kimball, A.; Sesar, B.; Westman, D.; Brooks, K.; Gibson, R.; Becker, A. C.; Kochanek, C. S.; Kozlowski, S.; Kelly, B.; De Vries, W. H.

    2010-01-01

    We model the time variability of ∼9000 spectroscopically confirmed quasars in SDSS Stripe 82 as a damped random walk (DRW). Using 2.7 million photometric measurements collected over 10 yr, we confirm the results of Kelly et al. and Kozlowski et al. that this model can explain quasar light curves at an impressive fidelity level (0.01-0.02 mag). The DRW model provides a simple, fast (O(N) for N data points), and powerful statistical description of quasar light curves by a characteristic timescale (τ) and an asymptotic rms variability on long timescales (SF ∞ ). We searched for correlations between these two variability parameters and physical parameters such as luminosity and black hole mass, and rest-frame wavelength. Our analysis shows SF ∞ to increase with decreasing luminosity and rest-frame wavelength as observed previously, and without a correlation with redshift. We find a correlation between SF ∞ and black hole mass with a power-law index of 0.18 ± 0.03, independent of the anti-correlation with luminosity. We find that τ increases with increasing wavelength with a power-law index of 0.17, remains nearly constant with redshift and luminosity, and increases with increasing black hole mass with a power-law index of 0.21 ± 0.07. The amplitude of variability is anti-correlated with the Eddington ratio, which suggests a scenario where optical fluctuations are tied to variations in the accretion rate. However, we find an additional dependence on luminosity and/or black hole mass that cannot be explained by the trend with Eddington ratio. The radio-loudest quasars have systematically larger variability amplitudes by about 30%, when corrected for the other observed trends, while the distribution of their characteristic timescale is indistinguishable from that of the full sample. We do not detect any statistically robust differences in the characteristic timescale and variability amplitude between the full sample and the small subsample of quasars detected

  4. Random Matrices for Information Processing – A Democratic Vision

    DEFF Research Database (Denmark)

    Cakmak, Burak

    The thesis studies three important applications of random matrices to information processing. Our main contribution is that we consider probabilistic systems involving more general random matrix ensembles than the classical ensembles with iid entries, i.e. models that account for statistical...... dependence between the entries. Specifically, the involved matrices are invariant or fulfill a certain asymptotic freeness condition as their dimensions grow to infinity. Informally speaking, all latent variables contribute to the system model in a democratic fashion – there are no preferred latent variables...

  5. ABCB1 genetic variability and methadone dosage requirements in opioid-dependent individuals.

    Science.gov (United States)

    Coller, Janet K; Barratt, Daniel T; Dahlen, Karianne; Loennechen, Morten H; Somogyi, Andrew A

    2006-12-01

    The most common treatment for opioid dependence is substitution therapy with another opioid such as methadone. The methadone dosage is individualized but highly variable, and program retention rates are low due in part to nonoptimal dosing resulting in withdrawal symptoms and further heroin craving and use. Methadone is a substrate for the P-glycoprotein transporter, encoded by the ABCB1 gene, which regulates central nervous system exposure. This retrospective study aimed to investigate the influence of ABCB1 genetic variability on methadone dose requirements. Genomic deoxyribonucleic acid was isolated from opioid-dependent subjects (n = 60) and non-opioid-dependent control subjects (n = 60), and polymerase chain reaction-restriction fragment length polymorphism and allele-specific polymerase chain reaction were used to determine the presence of single nucleotide polymorphisms at positions 61, 1199, 1236, 2677, and 3435. ABCB1 haplotypes were inferred with PHASE software (version 2.1). There were no significant differences in the allele or genotype frequencies of the individual single nucleotide polymorphisms or haplotypes between the 2 populations. ABCB1 genetic variability influenced daily methadone dose requirements, such that subjects carrying 2 copies of the wild-type haplotype required higher doses compared with those with 1 copy and those with no copies (98.3 +/- 10.4, 58.6 +/- 20.9, and 55.4 +/- 26.1 mg/d, respectively; P = .029). In addition, carriers of the AGCTT haplotype required significantly lower doses than noncarriers (38.0 +/- 16.8 and 61.3 +/- 24.6 mg/d, respectively; P = .04). Although ABCB1 genetic variability is not related to the development of opioid dependence, identification of variant haplotypes may, after larger prospective studies have been performed, provide clinicians with a tool for methadone dosage individualization.

  6. A comparison of random walks in dependent random environments

    NARCIS (Netherlands)

    Scheinhardt, Willem R.W.; Kroese, Dirk

    2015-01-01

    Although the theoretical behavior of one-dimensional random walks in random environments is well understood, the actual evaluation of various characteristics of such processes has received relatively little attention. This paper develops new methodology for the exact computation of the drift in such

  7. Nutrition education intervention for dependent patients: protocol of a randomized controlled trial

    OpenAIRE

    Arija Victoria; Martín Núria; Canela Teresa; Anguera Carme; Castelao Ana I; García-Barco Montserrat; García-Campo Antoni; González-Bravo Ana I; Lucena Carme; Martínez Teresa; Fernández-Barrés Silvia; Pedret Roser; Badia Waleska; Basora Josep

    2012-01-01

    Abstract Background Malnutrition in dependent patients has a high prevalence and can influence the prognosis associated with diverse pathologic processes, decrease quality of life, and increase morbidity-mortality and hospital admissions. The aim of the study is to assess the effect of an educational intervention for caregivers on the nutritional status of dependent patients at risk of malnutrition. Methods/Design Intervention study with control group, randomly allocated, of 200 patients of t...

  8. Strong result for real zeros of random algebraic polynomials

    Directory of Open Access Journals (Sweden)

    T. Uno

    2001-01-01

    Full Text Available An estimate is given for the lower bound of real zeros of random algebraic polynomials whose coefficients are non-identically distributed dependent Gaussian random variables. Moreover, our estimated measure of the exceptional set, which is independent of the degree of the polynomials, tends to zero as the degree of the polynomial tends to infinity.

  9. Analytic regularity and collocation approximation for elliptic PDEs with random domain deformations

    KAUST Repository

    Castrillon, Julio; Nobile, Fabio; Tempone, Raul

    2016-01-01

    In this work we consider the problem of approximating the statistics of a given Quantity of Interest (QoI) that depends on the solution of a linear elliptic PDE defined over a random domain parameterized by N random variables. The elliptic problem

  10. Random effects coefficient of determination for mixed and meta-analysis models.

    Science.gov (United States)

    Demidenko, Eugene; Sargent, James; Onega, Tracy

    2012-01-01

    The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.

  11. On discrete stochastic processes with long-lasting time dependence in the variance

    Science.gov (United States)

    Queirós, S. M. D.

    2008-11-01

    In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.

  12. A new reliability measure based on specified minimum distances before the locations of random variables in a finite interval

    International Nuclear Information System (INIS)

    Todinov, M.T.

    2004-01-01

    A new reliability measure is proposed and equations are derived which determine the probability of existence of a specified set of minimum gaps between random variables following a homogeneous Poisson process in a finite interval. Using the derived equations, a method is proposed for specifying the upper bound of the random variables' number density which guarantees that the probability of clustering of two or more random variables in a finite interval remains below a maximum acceptable level. It is demonstrated that even for moderate number densities the probability of clustering is substantial and should not be neglected in reliability calculations. In the important special case where the random variables are failure times, models have been proposed for determining the upper bound of the hazard rate which guarantees a set of minimum failure-free operating intervals before the random failures, with a specified probability. A model has also been proposed for determining the upper bound of the hazard rate which guarantees a minimum availability target. Using the models proposed, a new strategy, models and reliability tools have been developed for setting quantitative reliability requirements which consist of determining the intersection of the hazard rate envelopes (hazard rate upper bounds) which deliver a minimum failure-free operating period before random failures, a risk of premature failure below a maximum acceptable level and a minimum required availability. It is demonstrated that setting reliability requirements solely based on an availability target does not necessarily mean a low risk of premature failure. Even at a high availability level, the probability of premature failure can be substantial. For industries characterised by a high cost of failure, the reliability requirements should involve a hazard rate envelope limiting the risk of failure below a maximum acceptable level

  13. History dependent quantum random walks as quantum lattice gas automata

    Energy Technology Data Exchange (ETDEWEB)

    Shakeel, Asif, E-mail: asif.shakeel@gmail.com, E-mail: dmeyer@math.ucsd.edu, E-mail: plove@haverford.edu; Love, Peter J., E-mail: asif.shakeel@gmail.com, E-mail: dmeyer@math.ucsd.edu, E-mail: plove@haverford.edu [Department of Physics, Haverford College, Haverford, Pennsylvania 19041 (United States); Meyer, David A., E-mail: asif.shakeel@gmail.com, E-mail: dmeyer@math.ucsd.edu, E-mail: plove@haverford.edu [Department of Mathematics, University of California/San Diego, La Jolla, California 92093-0112 (United States)

    2014-12-15

    Quantum Random Walks (QRW) were first defined as one-particle sectors of Quantum Lattice Gas Automata (QLGA). Recently, they have been generalized to include history dependence, either on previous coin (internal, i.e., spin or velocity) states or on previous position states. These models have the goal of studying the transition to classicality, or more generally, changes in the performance of quantum walks in algorithmic applications. We show that several history dependent QRW can be identified as one-particle sectors of QLGA. This provides a unifying conceptual framework for these models in which the extra degrees of freedom required to store the history information arise naturally as geometrical degrees of freedom on the lattice.

  14. A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

    Science.gov (United States)

    Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

    2012-01-01

    The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

  15. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

    Science.gov (United States)

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

  16. Generating Correlated QPSK Waveforms By Exploiting Real Gaussian Random Variables

    KAUST Repository

    Jardak, Seifallah

    2012-11-01

    The design of waveforms with specified auto- and cross-correlation properties has a number of applications in multiple-input multiple-output (MIMO) radar, one of them is the desired transmit beampattern design. In this work, an algorithm is proposed to generate quadrature phase shift- keying (QPSK) waveforms with required cross-correlation properties using real Gaussian random-variables (RV’s). This work can be considered as the extension of what was presented in [1] to generate BPSK waveforms. This work will be extended for the generation of correlated higher-order phase shift-keying (PSK) and quadrature amplitude modulation (QAM) schemes that can better approximate the desired beampattern.

  17. Generating Correlated QPSK Waveforms By Exploiting Real Gaussian Random Variables

    KAUST Repository

    Jardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim

    2012-01-01

    The design of waveforms with specified auto- and cross-correlation properties has a number of applications in multiple-input multiple-output (MIMO) radar, one of them is the desired transmit beampattern design. In this work, an algorithm is proposed to generate quadrature phase shift- keying (QPSK) waveforms with required cross-correlation properties using real Gaussian random-variables (RV’s). This work can be considered as the extension of what was presented in [1] to generate BPSK waveforms. This work will be extended for the generation of correlated higher-order phase shift-keying (PSK) and quadrature amplitude modulation (QAM) schemes that can better approximate the desired beampattern.

  18. Time-dependent reliability sensitivity analysis of motion mechanisms

    International Nuclear Information System (INIS)

    Wei, Pengfei; Song, Jingwen; Lu, Zhenzhou; Yue, Zhufeng

    2016-01-01

    Reliability sensitivity analysis aims at identifying the source of structure/mechanism failure, and quantifying the effects of each random source or their distribution parameters on failure probability or reliability. In this paper, the time-dependent parametric reliability sensitivity (PRS) analysis as well as the global reliability sensitivity (GRS) analysis is introduced for the motion mechanisms. The PRS indices are defined as the partial derivatives of the time-dependent reliability w.r.t. the distribution parameters of each random input variable, and they quantify the effect of the small change of each distribution parameter on the time-dependent reliability. The GRS indices are defined for quantifying the individual, interaction and total contributions of the uncertainty in each random input variable to the time-dependent reliability. The envelope function method combined with the first order approximation of the motion error function is introduced for efficiently estimating the time-dependent PRS and GRS indices. Both the time-dependent PRS and GRS analysis techniques can be especially useful for reliability-based design. This significance of the proposed methods as well as the effectiveness of the envelope function method for estimating the time-dependent PRS and GRS indices are demonstrated with a four-bar mechanism and a car rack-and-pinion steering linkage. - Highlights: • Time-dependent parametric reliability sensitivity analysis is presented. • Time-dependent global reliability sensitivity analysis is presented for mechanisms. • The proposed method is especially useful for enhancing the kinematic reliability. • An envelope method is introduced for efficiently implementing the proposed methods. • The proposed method is demonstrated by two real planar mechanisms.

  19. A Generalized Random Regret Minimization Model

    NARCIS (Netherlands)

    Chorus, C.G.

    2013-01-01

    This paper presents, discusses and tests a generalized Random Regret Minimization (G-RRM) model. The G-RRM model is created by replacing a fixed constant in the attribute-specific regret functions of the RRM model, by a regret-weight variable. Depending on the value of the regret-weights, the G-RRM

  20. Frequency and temperature dependent mobility of a charged carrier and randomly interrupted strand

    International Nuclear Information System (INIS)

    Kumar, N.; Jayannavar, A.M.

    1981-05-01

    Randomly interrupted strand model of a one-dimensional conductor is considered. Exact analytical expression is obtained for the temperature dependent as mobility for a finite segment drawn at random, taking into account the reflecting barriers at the two open ends. The real part of mobility shows a broad resonance as a function of both frequency and tempeature, and vanishes quadratically in the dc limit. The frequency (temperature) maximum shifts to higher values for higher temperatures (frequencies). (author)

  1. The 'emergent scaling' phenomenon and the dielectric properties of random resistor-capacitor networks

    CERN Document Server

    Bouamrane, R

    2003-01-01

    An efficient algorithm, based on the Frank-Lobb reduction scheme, for calculating the equivalent dielectric properties of very large random resistor-capacitor (R-C) networks has been developed. It has been used to investigate the network size and composition dependence of dielectric properties and their statistical variability. The dielectric properties of 256 samples of random networks containing: 512, 2048, 8192 and 32 768 components distributed randomly in the ratios 60% R-40% C, 50% R-50% C and 40% R-60% C have been computed. It has been found that these properties exhibit the anomalous power law dependences on frequency known as the 'universal dielectric response' (UDR). Attention is drawn to the contrast between frequency ranges across which percolation determines dielectric response, where considerable variability is found amongst the samples, and those across which power laws define response where very little variability is found between samples. It is concluded that the power law UDRs are emergent pr...

  2. The limit distribution of the maximum increment of a random walk with dependent regularly varying jump sizes

    DEFF Research Database (Denmark)

    Mikosch, Thomas Valentin; Moser, Martin

    2013-01-01

    We investigate the maximum increment of a random walk with heavy-tailed jump size distribution. Here heavy-tailedness is understood as regular variation of the finite-dimensional distributions. The jump sizes constitute a strictly stationary sequence. Using a continuous mapping argument acting...... on the point processes of the normalized jump sizes, we prove that the maximum increment of the random walk converges in distribution to a Fréchet distributed random variable....

  3. Behaviors Predicting Foot Lesions in Patients with Non-Insulin-Dependent Diabetes Mellitus

    OpenAIRE

    Suico, Jeffrey G; Marriott, Deanna J; Vinicor, Frank; Litzelman, Debra K

    1998-01-01

    Associations between specific foot-care behaviors and foot lesions in patients with non-insulin-dependent diabetes mellitus were prospectively investigated. Data from a randomized controlled trial for preventing diabetic foot lesions were analyzed as a prospective cohort using logistic regression. Independent variables included foot-care behaviors, patient self-foot examination, going barefoot, availability of foot-care assistance, and visits to health-care providers. The dependent variable w...

  4. Effect of short-term heart rate variability biofeedback on long-term abstinence in alcohol dependent patients - a one-year follow-up.

    Science.gov (United States)

    Penzlin, Ana Isabel; Barlinn, Kristian; Illigens, Ben Min-Woo; Weidner, Kerstin; Siepmann, Martin; Siepmann, Timo

    2017-09-06

    A randomized controlled study (RCT) recently showed that short-term heart rate variability (HRV) biofeedback in addition to standard rehabilitation care for alcohol dependence can reduce craving, anxiety and improve cardiovascular autonomic function. In this one-year follow-up study we aimed to explore whether completion of 2-week HRV-Biofeedback training is associated with long-term abstinence. Furthermore, we sought to identify potential predictors of post-treatment abstinence. We conducted a survey on abstinence in patients with alcohol dependence 1 year after completion of an RCT comparing HRV-biofeedback in addition to inpatient rehabilitation treatment alone (controls). Abstinence rates were compared and analysed for association with demographic data as well as psychometric and autonomic cardiac assessment before and after completion of the biofeedback training using bivariate and multivariate regression analyses. Out of 48 patients who participated in the RCT, 27 patients (9 females, ages 42.9 ± 8.6, mean ± SD) completed our one-year follow-up. When including in the analysis only patients who completed follow-up, the rate of abstinence tended to be higher in patients who underwent HRV-biofeedback 1 year earlier compared to those who received rehabilitative treatment alone (66.7% vs 50%, p = ns). This non-significant trend was also observed in the intention-to-treat analysis where patients who did not participate in the follow-up were assumed to have relapsed (46,7% biofeedback vs. 33.3% controls, p = ns). Neither cardiac autonomic function nor psychometric variables were associated with abstinence 1 year after HRV-biofeedback. Our follow-up study provide a first indication of possible increase in long-term abstinence after HRV-biofeedback for alcohol dependence in addition to rehabilitation. The original randomized controlled trial was registered in the German Clinical Trials Register ( DRKS00004618 ). This one-year follow-up survey has not been

  5. Spontaneous temporal changes and variability of peripheral nerve conduction analyzed using a random effects model

    DEFF Research Database (Denmark)

    Krøigård, Thomas; Gaist, David; Otto, Marit

    2014-01-01

    SUMMARY: The reproducibility of variables commonly included in studies of peripheral nerve conduction in healthy individuals has not previously been analyzed using a random effects regression model. We examined the temporal changes and variability of standard nerve conduction measures in the leg...... reexamined after 2 and 26 weeks. There was no change in the variables except for a minor decrease in sural nerve sensory action potential amplitude and a minor increase in tibial nerve minimal F-wave latency. Reproducibility was best for peroneal nerve distal motor latency and motor conduction velocity......, sural nerve sensory conduction velocity, and tibial nerve minimal F-wave latency. Between-subject variability was greater than within-subject variability. Sample sizes ranging from 21 to 128 would be required to show changes twice the magnitude of the spontaneous changes observed in this study. Nerve...

  6. Surface effects of electrode-dependent switching behavior of resistive random-access memory

    KAUST Repository

    Ke, Jr Jian

    2016-09-26

    The surface effects of ZnO-based resistive random-access memory (ReRAM) were investigated using various electrodes. Pt electrodes were found to have better performance in terms of the device\\'s switching functionality. A thermodynamic model of the oxygen chemisorption process was proposed to explain this electrode-dependent switching behavior. The temperature-dependent switching voltage demonstrates that the ReRAM devices fabricated with Pt electrodes have a lower activation energy for the chemisorption process, resulting in a better resistive switching performance. These findings provide an in-depth understanding of electrode-dependent switching behaviors and can serve as design guidelines for future ReRAM devices.

  7. Automatic Probabilistic Program Verification through Random Variable Abstraction

    Directory of Open Access Journals (Sweden)

    Damián Barsotti

    2010-06-01

    Full Text Available The weakest pre-expectation calculus has been proved to be a mature theory to analyze quantitative properties of probabilistic and nondeterministic programs. We present an automatic method for proving quantitative linear properties on any denumerable state space using iterative backwards fixed point calculation in the general framework of abstract interpretation. In order to accomplish this task we present the technique of random variable abstraction (RVA and we also postulate a sufficient condition to achieve exact fixed point computation in the abstract domain. The feasibility of our approach is shown with two examples, one obtaining the expected running time of a probabilistic program, and the other the expected gain of a gambling strategy. Our method works on general guarded probabilistic and nondeterministic transition systems instead of plain pGCL programs, allowing us to easily model a wide range of systems including distributed ones and unstructured programs. We present the operational and weakest precondition semantics for this programs and prove its equivalence.

  8. The Distribution of Minimum of Ratios of Two Random Variables and Its Application in Analysis of Multi-hop Systems

    Directory of Open Access Journals (Sweden)

    A. Stankovic

    2012-12-01

    Full Text Available The distributions of random variables are of interest in many areas of science. In this paper, ascertaining on the importance of multi-hop transmission in contemporary wireless communications systems operating over fading channels in the presence of cochannel interference, the probability density functions (PDFs of minimum of arbitrary number of ratios of Rayleigh, Rician, Nakagami-m, Weibull and α-µ random variables are derived. These expressions can be used to study the outage probability as an important multi-hop system performance measure. Various numerical results complement the proposed mathematical analysis.

  9. Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters

    Science.gov (United States)

    Galea, Joseph M.; Ruge, Diane; Buijink, Arthur; Bestmann, Sven; Rothwell, John C.

    2013-01-01

    Action selection describes the high-level process which selects between competing movements. In animals, behavioural variability is critical for the motor exploration required to select the action which optimizes reward and minimizes cost/punishment, and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioural and neurophysiological variability on DA, and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant’s behaviour but pre-determined. Blocks highly-biased towards punishment were associated with increased MA variability relative to blocks with either reward or without feedback. This increase in behavioural variability was positively correlated with neurophysiological variability, as measured by changes in cortico-spinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA-antagonist, the variability associated with punishment diminished and the correlation between behavioural and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a pre-determined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioural variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes. PMID:23447607

  10. Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

    Energy Technology Data Exchange (ETDEWEB)

    Romero, Vicente [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bonney, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Schroeder, Benjamin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weirs, V. Gregory [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a class of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10-4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.

  11. Mindfulness Therapy for Maladaptive Interpersonal Dependency: A Preliminary Randomized Controlled Trial.

    Science.gov (United States)

    McClintock, Andrew S; Anderson, Timothy; Cranston, Saryn

    2015-11-01

    Existing treatments for maladaptive interpersonal dependency and dependent personality disorder do not meet basic scientific standards for effectiveness. The present investigation tested the efficacy of a mindfulness-based approach: mindfulness therapy for maladaptive interpersonal dependency (MT-MID). Forty-eight participants who reported consistently high levels of maladaptive dependency (i.e., scored higher than 1 standard deviation above the mean on the Interpersonal Dependency Inventory at two separate assessments) were randomized to either 5 sessions of MT-MID or a minimal contact control. Five self-reported outcomes (mindfulness, maladaptive interpersonal dependency, helplessness, fears of negative evaluation, and excessive reassurance seeking) were assessed at pretreatment, posttreatment, and a 4-week follow-up. Intent-to-treat analyses indicated that MT-MID yielded greater improvements than the control on all 5 outcomes at posttreatment (median d=1.61) and follow-up (median d=1.51). Participants assigned to MT-MID were more likely than control participants to meet criteria for clinically significant change at posttreatment (56.5% vs. 0%) and follow-up (42.9% vs. 0%). There was also evidence that increases in mindfulness mediated the dependency-related improvements. These results provide preliminary support for the efficacy of a mindfulness-based approach for treating the symptoms of maladaptive dependency. Copyright © 2015. Published by Elsevier Ltd.

  12. Construction of adjoint operators for coupled equations depending on different variables

    International Nuclear Information System (INIS)

    Hoogenboom, J.E.

    1986-01-01

    A procedure is described for the construction of the adjoint operator matrix in case of coupled equations defining quantities that depend on different sets of variables. This case is not properly treated in the literature. From this procedure a simple rule can be deduced for the construction of such adjoint operator matrices

  13. Size-dependent mechanical properties of 2D random nanofibre networks

    International Nuclear Information System (INIS)

    Lu, Zixing; Zhu, Man; Liu, Qiang

    2014-01-01

    The mechanical properties of nanofibre networks (NFNs) are size dependent with respect to different fibre diameters. In this paper, a continuum model is developed to reveal the size-dependent mechanical properties of 2D random NFNs. Since such size-dependent behaviours are attributed to different micromechanical mechanisms, the surface effects and the strain gradient (SG) effects are, respectively, introduced into the mechanical analysis of NFNs. Meanwhile, a modified fibre network model is proposed, in which the axial, bending and shearing deformations are incorporated. The closed-form expressions of effective modulus and Poisson's ratio are obtained for NFNs. Different from the results predicted by conventional fibre network model, the present model predicts the size-dependent mechanical properties of NFNs. It is found that both surface effects and SG effects have significant influences on the effective mechanical properties. Moreover, the present results show that the shearing deformation of fibre segment is also crucial to precisely evaluate the effective mechanical properties of NFNs. This work mainly aims to provide an insight into the micromechanical mechanisms of NFNs. Besides, this work is also expected to provide a more accurate theoretical model for 2D fibre networks. (paper)

  14. Algebraic polynomials with random coefficients

    Directory of Open Access Journals (Sweden)

    K. Farahmand

    2002-01-01

    Full Text Available This paper provides an asymptotic value for the mathematical expected number of points of inflections of a random polynomial of the form a0(ω+a1(ω(n11/2x+a2(ω(n21/2x2+…an(ω(nn1/2xn when n is large. The coefficients {aj(w}j=0n, w∈Ω are assumed to be a sequence of independent normally distributed random variables with means zero and variance one, each defined on a fixed probability space (A,Ω,Pr. A special case of dependent coefficients is also studied.

  15. Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

    Directory of Open Access Journals (Sweden)

    Thandi Kapwata

    2016-11-01

    Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

  16. Value of Construction Company and its Dependence on Significant Variables

    Science.gov (United States)

    Vítková, E.; Hromádka, V.; Ondrušková, E.

    2017-10-01

    The paper deals with the value of the construction company assessment respecting usable approaches and determinable variables. The reasons of the value of the construction company assessment are different, but the most important reasons are the sale or the purchase of the company, the liquidation of the company, the fusion of the company with another subject or the others. According the reason of the value assessment it is possible to determine theoretically different approaches for valuation, mainly it concerns about the yield method of valuation and the proprietary method of valuation. Both approaches are dependant of detailed input variables, which quality will influence the final assessment of the company´s value. The main objective of the paper is to suggest, according to the analysis, possible ways of input variables, mainly in the form of expected cash-flows or the profit, determination. The paper is focused mainly on methods of time series analysis, regression analysis and mathematical simulation utilization. As the output, the results of the analysis on the case study will be demonstrated.

  17. Physical activity, mindfulness meditation, or heart rate variability biofeedback for stress reduction: a randomized controlled trial

    NARCIS (Netherlands)

    van der Zwan, J.E.; de Vente, W.; Huizink, A.C.; Bögels, S.M.; de Bruin, E.I.

    2015-01-01

    In contemporary western societies stress is highly prevalent, therefore the need for stress-reducing methods is great. This randomized controlled trial compared the efficacy of self-help physical activity (PA), mindfulness meditation (MM), and heart rate variability biofeedback (HRV-BF) in reducing

  18. An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

    KAUST Repository

    Nam, Sungsik; Alouini, Mohamed-Slim; Yang, Hongchuan

    2010-01-01

    Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs

  19. Variable versus conventional lung protective mechanical ventilation during open abdominal surgery: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Spieth, Peter M; Güldner, Andreas; Uhlig, Christopher; Bluth, Thomas; Kiss, Thomas; Schultz, Marcus J; Pelosi, Paolo; Koch, Thea; Gama de Abreu, Marcelo

    2014-05-02

    General anesthesia usually requires mechanical ventilation, which is traditionally accomplished with constant tidal volumes in volume- or pressure-controlled modes. Experimental studies suggest that the use of variable tidal volumes (variable ventilation) recruits lung tissue, improves pulmonary function and reduces systemic inflammatory response. However, it is currently not known whether patients undergoing open abdominal surgery might benefit from intraoperative variable ventilation. The PROtective VARiable ventilation trial ('PROVAR') is a single center, randomized controlled trial enrolling 50 patients who are planning for open abdominal surgery expected to last longer than 3 hours. PROVAR compares conventional (non-variable) lung protective ventilation (CV) with variable lung protective ventilation (VV) regarding pulmonary function and inflammatory response. The primary endpoint of the study is the forced vital capacity on the first postoperative day. Secondary endpoints include further lung function tests, plasma cytokine levels, spatial distribution of ventilation assessed by means of electrical impedance tomography and postoperative pulmonary complications. We hypothesize that VV improves lung function and reduces systemic inflammatory response compared to CV in patients receiving mechanical ventilation during general anesthesia for open abdominal surgery longer than 3 hours. PROVAR is the first randomized controlled trial aiming at intra- and postoperative effects of VV on lung function. This study may help to define the role of VV during general anesthesia requiring mechanical ventilation. Clinicaltrials.gov NCT01683578 (registered on September 3 3012).

  20. Distribution of peak expiratory flow variability by age, gender and smoking habits in a random population sample aged 20-70 yrs

    NARCIS (Netherlands)

    Boezen, H M; Schouten, J. P.; Postma, D S; Rijcken, B

    1994-01-01

    Peak expiratory flow (PEF) variability can be considered as an index of bronchial lability. Population studies on PEF variability are few. The purpose of the current paper is to describe the distribution of PEF variability in a random population sample of adults with a wide age range (20-70 yrs),

  1. An MGF-based unified framework to determine the joint statistics of partial sums of ordered i.n.d. random variables

    KAUST Repository

    Nam, Sungsik

    2014-08-01

    The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distributed (i.n.d.). More specifically, we extend the previous analysis and introduce a new more general unified analytical framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE receivers operating over frequency-selective fading channels with a non-uniform power delay profile. © 1991-2012 IEEE.

  2. The supremuim of a negative drift random walk with dependent heavy-tailed steps

    NARCIS (Netherlands)

    Mikosch, T; Smorodnitsky, G

    Many important probabilistic models in queuing theory, insurance and finance deal with partial sums of a negative mean stationary process (a negative drift random walk), and the law of the supremum of such a process is used to calculate, depending on the context, the ruin probability, the steady

  3. Using k-dependence causal forest to mine the most significant dependency relationships among clinical variables for thyroid disease diagnosis.

    Directory of Open Access Journals (Sweden)

    LiMin Wang

    Full Text Available Numerous data mining models have been proposed to construct computer-aided medical expert systems. Bayesian network classifiers (BNCs are more distinct and understandable than other models. To graphically describe the dependency relationships among clinical variables for thyroid disease diagnosis and ensure the rationality of the diagnosis results, the proposed k-dependence causal forest (KCF model generates a series of submodels in the framework of maximum spanning tree (MST and demonstrates stronger dependence representation. Friedman test on 12 UCI datasets shows that KCF has classification accuracy advantage over the other state-of-the-art BNCs, such as Naive Bayes, tree augmented Naive Bayes, and k-dependence Bayesian classifier. Our extensive experimental comparison on 4 medical datasets also proves the feasibility and effectiveness of KCF in terms of sensitivity and specificity.

  4. Residual and Past Entropy for Concomitants of Ordered Random Variables of Morgenstern Family

    Directory of Open Access Journals (Sweden)

    M. M. Mohie EL-Din

    2015-01-01

    Full Text Available For a system, which is observed at time t, the residual and past entropies measure the uncertainty about the remaining and the past life of the distribution, respectively. In this paper, we have presented the residual and past entropy of Morgenstern family based on the concomitants of the different types of generalized order statistics (gos and give the linear transformation of such model. Characterization results for these dynamic entropies for concomitants of ordered random variables have been considered.

  5. Analytic regularity and collocation approximation for elliptic PDEs with random domain deformations

    KAUST Repository

    Castrillon, Julio

    2016-03-02

    In this work we consider the problem of approximating the statistics of a given Quantity of Interest (QoI) that depends on the solution of a linear elliptic PDE defined over a random domain parameterized by N random variables. The elliptic problem is remapped onto a corresponding PDE with a fixed deterministic domain. We show that the solution can be analytically extended to a well defined region in CN with respect to the random variables. A sparse grid stochastic collocation method is then used to compute the mean and variance of the QoI. Finally, convergence rates for the mean and variance of the QoI are derived and compared to those obtained in numerical experiments.

  6. A general symplectic method for the response analysis of infinitely periodic structures subjected to random excitations

    Directory of Open Access Journals (Sweden)

    You-Wei Zhang

    Full Text Available A general symplectic method for the random response analysis of infinitely periodic structures subjected to stationary/non-stationary random excitations is developed using symplectic mathematics in conjunction with variable separation and the pseudo-excitation method (PEM. Starting from the equation of motion for a single loaded substructure, symplectic analysis is firstly used to eliminate the dependent degrees of the freedom through condensation. A Fourier expansion of the condensed equation of motion is then applied to separate the variables of time and wave number, thus enabling the necessary recurrence scheme to be developed. The random response is finally determined by implementing PEM. The proposed method is justified by comparison with results available in the literature and is then applied to a more complicated time-dependent coupled system.

  7. On the strong law of large numbers for $\\varphi$-subgaussian random variables

    OpenAIRE

    Zajkowski, Krzysztof

    2016-01-01

    For $p\\ge 1$ let $\\varphi_p(x)=x^2/2$ if $|x|\\le 1$ and $\\varphi_p(x)=1/p|x|^p-1/p+1/2$ if $|x|>1$. For a random variable $\\xi$ let $\\tau_{\\varphi_p}(\\xi)$ denote $\\inf\\{a\\ge 0:\\;\\forall_{\\lambda\\in\\mathbb{R}}\\; \\ln\\mathbb{E}\\exp(\\lambda\\xi)\\le\\varphi_p(a\\lambda)\\}$; $\\tau_{\\varphi_p}$ is a norm in a space $Sub_{\\varphi_p}=\\{\\xi:\\;\\tau_{\\varphi_p}(\\xi)1$) there exist positive constants $c$ and $\\alpha$ such that for every natural number $n$ the following inequality $\\tau_{\\varphi_p}(\\sum_{i=1...

  8. Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2017-10-01

    Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

  9. Double-blind, randomized placebo-controlled clinical trial of benfotiamine for severe alcohol dependence.

    Science.gov (United States)

    Manzardo, Ann M; He, Jianghua; Poje, Albert; Penick, Elizabeth C; Campbell, Jan; Butler, Merlin G

    2013-12-01

    Alcohol dependence is associated with severe nutritional and vitamin deficiency. Vitamin B1 (thiamine) deficiency erodes neurological pathways that may influence the ability to drink in moderation. The present study examines tolerability of supplementation using the high-potency thiamine analog, benfotiamine (BF), and BF's effects on alcohol consumption in severely affected, self-identified, alcohol dependent subjects. A randomized, double-blind, placebo-controlled trial was conducted on 120 non-treatment seeking, actively drinking, alcohol dependent men and women volunteers (mean age=47 years) from the Kansas City area who met DSM-IV-TR criteria for current alcohol dependence. Subjects were randomized to receive 600 mg benfotiamine or placebo (PL) once daily by mouth for 24 weeks with 6 follow-up assessments scheduled at 4 week intervals. Side effects and daily alcohol consumption were recorded. Seventy (58%) subjects completed 24 weeks of study (N=21 women; N=49 men) with overall completion rates of 55% (N=33) for PL and 63% (N=37) for BF groups. No significant adverse events were noted and alcohol consumption decreased significantly for both treatment groups. Alcohol consumption decreased from baseline levels for 9 of 10 BF treated women after 1 month of treatment compared with 2 of 11 on PL. Reductions in total alcohol consumption over 6 months were significantly greater for BF treated women (BF: N=10, -611 ± 380 standard drinks; PL: N=11, -159 ± 562 standard drinks, p-value=0.02). BF supplementation of actively drinking alcohol dependent men and women was well-tolerated and may discourage alcohol consumption among women. The results do support expanded studies of BF treatment in alcoholism. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  10. Distance and Azimuthal Dependence of Ground‐Motion Variability for Unilateral Strike‐Slip Ruptures

    KAUST Repository

    Vyas, Jagdish Chandra

    2016-06-21

    We investigate near‐field ground‐motion variability by computing the seismic wavefield for five kinematic unilateral‐rupture models of the 1992 Mw 7.3 Landers earthquake, eight simplified unilateral‐rupture models based on the Landers event, and a large Mw 7.8 ShakeOut scenario. We include the geometrical fault complexity and consider different 1D velocity–density profiles for the Landers simulations and a 3D heterogeneous Earth structure for the ShakeOut scenario. For the Landers earthquake, the computed waveforms are validated using strong‐motion recordings. We analyze the simulated ground‐motion data set in terms of distance and azimuth dependence of peak ground velocity (PGV). Our simulations reveal that intraevent ground‐motion variability Graphic is higher in close distances to the fault (<20  km) and decreases with increasing distance following a power law. This finding is in stark contrast to constant sigma‐values used in empirical ground‐motion prediction equations. The physical explanation of a large near‐field Graphic is the presence of strong directivity and rupture complexity. High values of Graphic occur in the rupture‐propagation direction, but small values occur in the direction perpendicular to it. We observe that the power‐law decay of Graphic is primarily controlled by slip heterogeneity. In addition, Graphic, as function of azimuth, is sensitive to variations in both rupture speed and slip heterogeneity. The azimuth dependence of the ground‐motion mean μln(PGV) is well described by a Cauchy–Lorentz function that provides a novel empirical quantification to model the spatial dependency of ground motion. Online Material: Figures of slip distributions, residuals to ground‐motion prediction equations (GMPEs), distance and azimuthal dependence, and directivity predictor of ground‐motion variability for different source models.

  11. Convolutions of Heavy Tailed Random Variables and Applications to Portfolio Diversification and MA(1) Time Series

    NARCIS (Netherlands)

    J.L. Geluk (Jaap); L. Peng (Liang); C.G. de Vries (Casper)

    1999-01-01

    textabstractThe paper characterizes first and second order tail behavior of convolutions of i.i.d. heavy tailed random variables with support on the real line. The result is applied to the problem of risk diversification in portfolio analysis and to the estimation of the parameter in a MA(1) model.

  12. Lead-position dependent regular oscillations and random fluctuations of conductance in graphene quantum dots

    International Nuclear Information System (INIS)

    Huang Liang; Yang Rui; Lai Yingcheng; Ferry, David K

    2013-01-01

    Quantum interference causes a wavefunction to have sensitive spatial dependence, and this has a significant effect on quantum transport. For example, in a quantum-dot system, the conductance can depend on the lead positions. We investigate, for graphene quantum dots, the conductance variations with the lead positions. Since for graphene the types of boundaries, e.g., zigzag and armchair, can fundamentally affect the quantum transport characteristics, we focus on rectangular graphene quantum dots, for which the effects of boundaries can be systematically studied. For both zigzag and armchair horizontal boundaries, we find that changing the positions of the leads can induce significant conductance variations. Depending on the Fermi energy, the variations can be either regular oscillations or random conductance fluctuations. We develop a physical theory to elucidate the origin of the conductance oscillation/fluctuation patterns. In particular, quantum interference leads to standing-wave-like-patterns in the quantum dot which, in the absence of leads, are regulated by the energy-band structure of the corresponding vertical graphene ribbon. The observed ‘coexistence’ of regular oscillations and random fluctuations in the conductance can be exploited for the development of graphene-based nanodevices. (paper)

  13. Tail asymptotics for dependent subexponential differences

    DEFF Research Database (Denmark)

    Albrecher, H; Asmussen, Søren; Kortschak, D.

    We study the asymptotic behavior of P(X − Y > u) as u → ∞, where X is subexponential and X, Y are positive random variables that may be dependent. We give criteria under which the subtraction of Y does not change the tail behavior of X. It is also studied under which conditions the comonotonic co...

  14. Dealing with Dependent Uncertainty in Modelling: A Comparative Study Case through the Airy Equation

    Directory of Open Access Journals (Sweden)

    J.-C. Cortés

    2013-01-01

    Full Text Available The consideration of uncertainty in differential equations leads to the emergent area of random differential equations. Under this approach, inputs become random variables and/or stochastic processes. Often one assumes that inputs are independent, a hypothesis that simplifies the mathematical treatment although it could not be met in applications. In this paper, we analyse, through the Airy equation, the influence of statistical dependence of inputs on the output, computing its expectation and standard deviation by Fröbenius and Polynomial Chaos methods. The results are compared with Monte Carlo sampling. The analysis is conducted by the Airy equation since, as in the deterministic scenario its solutions are highly oscillatory, it is expected that differences will be better highlighted. To illustrate our study, and motivated by the ubiquity of Gaussian random variables in numerous practical problems, we assume that inputs follow a multivariate Gaussian distribution throughout the paper. The application of Fröbenius method to solve Airy equation is based on an extension of the method to the case where inputs are dependent. The numerical results show that the existence of statistical dependence among the inputs and its magnitude entails changes on the variability of the output.

  15. Human Performance Technology (HPT): An Examination of Definitions through Dependent and Independent Variables.

    Science.gov (United States)

    Irlbeck, Sonja A.

    2002-01-01

    Provides a chronological perspective of human performance technology (HPT) definitions and an evaluation of them in terms of independent and dependent variables. Discusses human competence and performance technology and compares the definitions with the goals that have been articulated for HPT. (Author/LRW)

  16. Topiramate for the management of methamphetamine dependence: a pilot randomized, double-blind, placebo-controlled trial.

    Science.gov (United States)

    Rezaei, Farzin; Ghaderi, Ebrahim; Mardani, Roya; Hamidi, Seiran; Hassanzadeh, Kambiz

    2016-06-01

    To date, no medication has been approved as an effective treatment for methamphetamine dependence. Topiramate has attracted considerable attention as a treatment for the dependence on alcohol and stimulants. Therefore, this study aimed to evaluate the effect of topiramate for methamphetamine dependence. This study was a double-blind, randomized, placebo-controlled trial. In the present investigation, 62 methamphetamine-dependent adults were enrolled and randomized into two groups, and received topiramate or a placebo for 10 weeks in escalating doses from 50 mg/day to the target maintenance dose of 200 mg/day. Addiction severity index (ASI) and craving scores were registered every week. The Beck questionnaire was also given to each participant at baseline and every 2 weeks during the treatment. Urine samples were collected at baseline and every 2 weeks during the treatment. Fifty-seven patients completed 10 weeks of the trial. There was no significant difference between both groups in the mean percentage of prescribed capsules taken by the participants. At week six, the topiramate group showed a significantly lower proportion of methamphetamine-positive urine tests in comparison with the placebo group (P = 0.01). In addition, there were significantly lower scores in the topiramate group in comparison with the placebo group in two domains of ASI: drug use severity (P methamphetamine dependence. © 2016 Société Française de Pharmacologie et de Thérapeutique.

  17. Nutrition education intervention for dependent patients: protocol of a randomized controlled trial.

    Science.gov (United States)

    Arija, Victoria; Martín, Núria; Canela, Teresa; Anguera, Carme; Castelao, Ana I; García-Barco, Montserrat; García-Campo, Antoni; González-Bravo, Ana I; Lucena, Carme; Martínez, Teresa; Fernández-Barrés, Silvia; Pedret, Roser; Badia, Waleska; Basora, Josep

    2012-05-24

    Malnutrition in dependent patients has a high prevalence and can influence the prognosis associated with diverse pathologic processes, decrease quality of life, and increase morbidity-mortality and hospital admissions.The aim of the study is to assess the effect of an educational intervention for caregivers on the nutritional status of dependent patients at risk of malnutrition. Intervention study with control group, randomly allocated, of 200 patients of the Home Care Program carried out in 8 Primary Care Centers (Spain). These patients are dependent and at risk of malnutrition, older than 65, and have caregivers. The socioeconomic and educational characteristics of the patient and the caregiver are recorded. On a schedule of 0-6-12 months, patients are evaluated as follows: Mini Nutritional Assessment (MNA), food intake, dentures, degree of dependency (Barthel test), cognitive state (Pfeiffer test), mood status (Yesavage test), and anthropometric and serum parameters of nutritional status: albumin, prealbumin, transferrin, haemoglobin, lymphocyte count, iron, and ferritin.Prior to the intervention, the educational procedure and the design of educational material are standardized among nurses. The nurses conduct an initial session for caregivers and then monitor the education impact at home every month (4 visits) up to 6 months. The North American Nursing Diagnosis Association (NANDA) methodology will be used. The investigators will study the effect of the intervention with caregivers on the patient's nutritional status using the MNA test, diet, anthropometry, and biochemical parameters.Bivariate normal test statistics and multivariate models will be created to adjust the effect of the intervention.The SPSS/PC program will be used for statistical analysis. The nutritional status of dependent patients has been little studied. This study allows us to know nutritional risk from different points of view: diet, anthropometry and biochemistry in dependent patients at

  18. Nutrition education intervention for dependent patients: protocol of a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Arija Victoria

    2012-05-01

    Full Text Available Abstract Background Malnutrition in dependent patients has a high prevalence and can influence the prognosis associated with diverse pathologic processes, decrease quality of life, and increase morbidity-mortality and hospital admissions. The aim of the study is to assess the effect of an educational intervention for caregivers on the nutritional status of dependent patients at risk of malnutrition. Methods/Design Intervention study with control group, randomly allocated, of 200 patients of the Home Care Program carried out in 8 Primary Care Centers (Spain. These patients are dependent and at risk of malnutrition, older than 65, and have caregivers. The socioeconomic and educational characteristics of the patient and the caregiver are recorded. On a schedule of 0–6–12 months, patients are evaluated as follows: Mini Nutritional Assessment (MNA, food intake, dentures, degree of dependency (Barthel test, cognitive state (Pfeiffer test, mood status (Yesavage test, and anthropometric and serum parameters of nutritional status: albumin, prealbumin, transferrin, haemoglobin, lymphocyte count, iron, and ferritin. Prior to the intervention, the educational procedure and the design of educational material are standardized among nurses. The nurses conduct an initial session for caregivers and then monitor the education impact at home every month (4 visits up to 6 months. The North American Nursing Diagnosis Association (NANDA methodology will be used. The investigators will study the effect of the intervention with caregivers on the patient’s nutritional status using the MNA test, diet, anthropometry, and biochemical parameters. Bivariate normal test statistics and multivariate models will be created to adjust the effect of the intervention. The SPSS/PC program will be used for statistical analysis. Discussion The nutritional status of dependent patients has been little studied. This study allows us to know nutritional risk from different points of

  19. Motivation as an independent and a dependent variable in medical education: a review of the literature.

    Science.gov (United States)

    Kusurkar, R A; Ten Cate, Th J; van Asperen, M; Croiset, G

    2011-01-01

    Motivation in learning behaviour and education is well-researched in general education, but less in medical education. To answer two research questions, 'How has the literature studied motivation as either an independent or dependent variable? How is motivation useful in predicting and understanding processes and outcomes in medical education?' in the light of the Self-determination Theory (SDT) of motivation. A literature search performed using the PubMed, PsycINFO and ERIC databases resulted in 460 articles. The inclusion criteria were empirical research, specific measurement of motivation and qualitative research studies which had well-designed methodology. Only studies related to medical students/school were included. Findings of 56 articles were included in the review. Motivation as an independent variable appears to affect learning and study behaviour, academic performance, choice of medicine and specialty within medicine and intention to continue medical study. Motivation as a dependent variable appears to be affected by age, gender, ethnicity, socioeconomic status, personality, year of medical curriculum and teacher and peer support, all of which cannot be manipulated by medical educators. Motivation is also affected by factors that can be influenced, among which are, autonomy, competence and relatedness, which have been described as the basic psychological needs important for intrinsic motivation according to SDT. Motivation is an independent variable in medical education influencing important outcomes and is also a dependent variable influenced by autonomy, competence and relatedness. This review finds some evidence in support of the validity of SDT in medical education.

  20. The behaviour of random forest permutation-based variable importance measures under predictor correlation.

    Science.gov (United States)

    Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

    2010-02-27

    Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

  1. Simple, efficient estimators of treatment effects in randomized trials using generalized linear models to leverage baseline variables.

    Science.gov (United States)

    Rosenblum, Michael; van der Laan, Mark J

    2010-04-01

    Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation.

  2. Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

    Science.gov (United States)

    Rosenblum, Michael; van der Laan, Mark J.

    2010-01-01

    Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

  3. Relativistic Random-Phase Approximation with Density-dependent Meson-nucleon Couplings at Finite Temperature

    International Nuclear Information System (INIS)

    Niu, Y.; Paar, N.; Vretenar, D.; Meng, J.

    2009-01-01

    The fully self-consistent relativistic random-phase approximation (RRPA) framework based on effective interactions with a phenomenological density dependence is extended to finite temperatures. The RRPA configuration space is built from the spectrum of single-nucleon states at finite temperature obtained by the temperature dependent relativistic mean field (RMF-T) theory based on effective Lagrangian with density dependent meson-nucleon vertex functions. As an illustration, the dependence of binding energy, radius, entropy and single particle levels on temperature for spherical nucleus 2 08P b is investigated in RMF-T theory. The finite temperature RRPA has been employed in studies of giant monopole and dipole resonances, and the evolution of resonance properties has been studied as a function of temperature. In addition, exotic modes of excitation have been systematically explored at finite temperatures, with an emphasis on the case of pygmy dipole resonances.(author)

  4. The use of random amplified polymorphic DNA to evaluate the genetic variability of Ponkan mandarin (Citrus reticulata Blanco accessions

    Directory of Open Access Journals (Sweden)

    Coletta Filho Helvécio Della

    2000-01-01

    Full Text Available RAPD analysis of 19 Ponkan mandarin accessions was performed using 25 random primers. Of 112 amplification products selected, only 32 were polymorphic across five accessions. The absence of genetic variability among the other 14 accessions suggested that they were either clonal propagations with different local names, or that they had undetectable genetic variability, such as point mutations which cannot be detected by RAPD.

  5. Phase dependence of transport-aperture coordination variability reveals control strategy of reach-to-grasp movements.

    Science.gov (United States)

    Rand, Miya K; Shimansky, Y P; Hossain, Abul B M I; Stelmach, George E

    2010-11-01

    Based on an assumption of movement control optimality in reach-to-grasp movements, we have recently developed a mathematical model of transport-aperture coordination (TAC), according to which the hand-target distance is a function of hand velocity and acceleration, aperture magnitude, and aperture velocity and acceleration (Rand et al. in Exp Brain Res 188:263-274, 2008). Reach-to-grasp movements were performed by young adults under four different reaching speeds and two different transport distances. The residual error magnitude of fitting the above model to data across different trials and subjects was minimal for the aperture-closure phase, but relatively much greater for the aperture-opening phase, indicating considerable difference in TAC variability between those phases. This study's goal is to identify the main reasons for that difference and obtain insights into the control strategy of reach-to-grasp movements. TAC variability within the aperture-opening phase of a single trial was found minimal, indicating that TAC variability between trials was not due to execution noise, but rather a result of inter-trial and inter-subject variability of motor plan. At the same time, the dependence of the extent of trial-to-trial variability of TAC in that phase on the speed of hand transport was sharply inconsistent with the concept of speed-accuracy trade-off: the lower the speed, the larger the variability. Conversely, the dependence of the extent of TAC variability in the aperture-closure phase on hand transport speed was consistent with that concept. Taking into account recent evidence that the cost of neural information processing is substantial for movement planning, the dependence of TAC variability in the aperture-opening phase on task performance conditions suggests that it is not the movement time that the CNS saves in that phase, but the cost of neuro-computational resources and metabolic energy required for TAC regulation in that phase. Thus, the CNS

  6. How Far Is Quasar UV/Optical Variability from a Damped Random Walk at Low Frequency?

    Energy Technology Data Exchange (ETDEWEB)

    Guo Hengxiao; Wang Junxian; Cai Zhenyi; Sun Mouyuan, E-mail: hengxiaoguo@gmail.com, E-mail: jxw@ustc.edu.cn [CAS Key Laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science and Technology of China, Hefei 230026 (China)

    2017-10-01

    Studies have shown that UV/optical light curves of quasars can be described using the prevalent damped random walk (DRW) model, also known as the Ornstein–Uhlenbeck process. A white noise power spectral density (PSD) is expected at low frequency in this model; however, a direct observational constraint to the low-frequency PSD slope is difficult due to the limited lengths of the light curves available. Meanwhile, quasars show scatter in their DRW parameters that is too large to be attributed to uncertainties in the measurements and dependence on the variation of known physical factors. In this work we present simulations showing that, if the low-frequency PSD deviates from the DRW, the red noise leakage can naturally produce large scatter in the variation parameters measured from simulated light curves. The steeper the low-frequency PSD slope, the larger scatter we expect. Based on observations of SDSS Stripe 82 quasars, we find that the low-frequency PSD slope should be no steeper than −1.3. The actual slope could be flatter, which consequently requires that the quasar variabilities should be influenced by other unknown factors. We speculate that the magnetic field and/or metallicity could be such additional factors.

  7. TWO MEASURES OF THE DEPENDENCE OF PREFERENTIAL RANKINGS ON CATEGORICAL VARIABLES

    Directory of Open Access Journals (Sweden)

    Lissowski Grzegorz

    2017-06-01

    Full Text Available The aim of this paper is to apply a general methodology for constructing statistical methods, which is based on decision theory, to give a statistical description of preferential rankings, with a focus on the rankings’ dependence on categorical variables. In the paper, I use functions of description errors that are based on the Kemeny and Hamming distances between preferential orderings, but the proposed methodology can also be applied to other methods of estimating description errors.

  8. Effects of dependence in high-dimensional multiple testing problems

    Directory of Open Access Journals (Sweden)

    van de Wiel Mark A

    2008-02-01

    Full Text Available Abstract Background We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices. Results We study the robustness against dependence of several FDR procedures that are popular in microarray studies, such as Benjamin-Hochberg FDR, Storey's q-value, SAM and resampling based FDR procedures. False Non-discovery Rates and estimates of the number of null hypotheses are computed from those methods and compared. Our simulation study shows that methods such as SAM and the q-value do not adequately control the FDR to the level claimed under dependence conditions. On the other hand, the adaptive Benjamini-Hochberg procedure seems to be most robust while remaining conservative. Finally, the estimates of the number of true null hypotheses under various dependence conditions are variable. Conclusion We discuss a new method for efficient guided simulation of dependent data, which satisfy imposed network constraints as conditional independence structures. Our simulation set-up allows for a structural study of the effect of dependencies on multiple testing criterions and is useful for testing a potentially new method on π0 or FDR estimation in a dependency context.

  9. Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

    Science.gov (United States)

    Wang, Wei; Griswold, Michael E

    2016-11-30

    The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  10. Determination of spatially dependent transfer function of zero power reactor by using pseudo-random incentive

    International Nuclear Information System (INIS)

    Kostic, Lj.

    1973-01-01

    Specially constructed fast reactivity oscillator was stimulating the zero power reactor by a stimulus which caused pseudo-random reactivity changes. Measuring system included stochastic oscillator BCR-1 supplied by pseudo-random pulses from noise generator GBS-16, instrumental tape-recorder, system for data acquisition and digital computer ZUSE-Z-23. For measuring the spatially dependent transfer function, reactor response was measured at a number of different positions of stochastic oscillator and ionization chamber. In order to keep the reactor system linear, experiment was limited to small reactivity fluctuations. Experimental results were compared to theoretical ones

  11. A Method of Approximating Expectations of Functions of Sums of Independent Random Variables

    OpenAIRE

    Klass, Michael J.

    1981-01-01

    Let $X_1, X_2, \\cdots$ be a sequence of independent random variables with $S_n = \\sum^n_{i = 1} X_i$. Fix $\\alpha > 0$. Let $\\Phi(\\cdot)$ be a continuous, strictly increasing function on $\\lbrack 0, \\infty)$ such that $\\Phi(0) = 0$ and $\\Phi(cx) \\leq c^\\alpha\\Phi(x)$ for all $x > 0$ and all $c \\geq 2$. Suppose $a$ is a real number and $J$ is a finite nonempty subset of the positive integers. In this paper we are interested in approximating $E \\max_{j \\in J} \\Phi(|a + S_j|)$. We construct a nu...

  12. Gaussian Mixture Random Coefficient model based framework for SHM in structures with time-dependent dynamics under uncertainty

    Science.gov (United States)

    Avendaño-Valencia, Luis David; Fassois, Spilios D.

    2017-12-01

    The problem of vibration-based damage diagnosis in structures characterized by time-dependent dynamics under significant environmental and/or operational uncertainty is considered. A stochastic framework consisting of a Gaussian Mixture Random Coefficient model of the uncertain time-dependent dynamics under each structural health state, proper estimation methods, and Bayesian or minimum distance type decision making, is postulated. The Random Coefficient (RC) time-dependent stochastic model with coefficients following a multivariate Gaussian Mixture Model (GMM) allows for significant flexibility in uncertainty representation. Certain of the model parameters are estimated via a simple procedure which is founded on the related Multiple Model (MM) concept, while the GMM weights are explicitly estimated for optimizing damage diagnostic performance. The postulated framework is demonstrated via damage detection in a simple simulated model of a quarter-car active suspension with time-dependent dynamics and considerable uncertainty on the payload. Comparisons with a simpler Gaussian RC model based method are also presented, with the postulated framework shown to be capable of offering considerable improvement in diagnostic performance.

  13. Ruin Probabilities in a Dependent Discrete-Time Risk Model With Gamma-Like Tailed Insurance Risks

    Directory of Open Access Journals (Sweden)

    Xing-Fang Huang

    2017-03-01

    Full Text Available This paper considered a dependent discrete-time risk model, in which the insurance risks are represented by a sequence of independent and identically distributed real-valued random variables with a common Gamma-like tailed distribution; the financial risks are denoted by another sequence of independent and identically distributed positive random variables with a finite upper endpoint, but a general dependence structure exists between each pair of the insurance risks and the financial risks. Following the works of Yang and Yuen in 2016, we derive some asymptotic relations for the finite-time and infinite-time ruin probabilities. As a complement, we demonstrate our obtained result through a Crude Monte Carlo (CMC simulation with asymptotics.

  14. Random walk in degree space and the time-dependent Watts-Strogatz model

    OpenAIRE

    Grande, H. L. Casa; Cotacallapa, M.; Hase, M. O.

    2016-01-01

    In this work, we propose a scheme that provides an analytical estimate for the time-dependent degree distribution of some networks. This scheme maps the problem into a random walk in degree space, and then we choose the paths that are responsible for the dominant contributions. The method is illustrated on the dynamical versions of the Erd\\"os-R\\'enyi and Watts-Strogatz graphs, which were introduced as static models in the original formulation. We have succeeded in obtaining an analytical for...

  15. Uncertainty Quantification in Scale-Dependent Models of Flow in Porous Media: SCALE-DEPENDENT UQ

    Energy Technology Data Exchange (ETDEWEB)

    Tartakovsky, A. M. [Computational Mathematics Group, Pacific Northwest National Laboratory, Richland WA USA; Panzeri, M. [Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Milano Italy; Tartakovsky, G. D. [Hydrology Group, Pacific Northwest National Laboratory, Richland WA USA; Guadagnini, A. [Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Milano Italy

    2017-11-01

    Equations governing flow and transport in heterogeneous porous media are scale-dependent. We demonstrate that it is possible to identify a support scale $\\eta^*$, such that the typically employed approximate formulations of Moment Equations (ME) yield accurate (statistical) moments of a target environmental state variable. Under these circumstances, the ME approach can be used as an alternative to the Monte Carlo (MC) method for Uncertainty Quantification in diverse fields of Earth and environmental sciences. MEs are directly satisfied by the leading moments of the quantities of interest and are defined on the same support scale as the governing stochastic partial differential equations (PDEs). Computable approximations of the otherwise exact MEs can be obtained through perturbation expansion of moments of the state variables in orders of the standard deviation of the random model parameters. As such, their convergence is guaranteed only for the standard deviation smaller than one. We demonstrate our approach in the context of steady-state groundwater flow in a porous medium with a spatially random hydraulic conductivity.

  16. Size-dependent piezoelectric energy-harvesting analysis of micro/nano bridges subjected to random ambient excitations

    Science.gov (United States)

    Radgolchin, Moeen; Moeenfard, Hamid

    2018-02-01

    The construction of self-powered micro-electro-mechanical units by converting the mechanical energy of the systems into electrical power has attracted much attention in recent years. While power harvesting from deterministic external excitations is state of the art, it has been much more difficult to derive mathematical models for scavenging electrical energy from ambient random vibrations, due to the stochastic nature of the excitations. The current research concerns analytical modeling of micro-bridge energy harvesters based on random vibration theory. Since classical elasticity fails to accurately predict the mechanical behavior of micro-structures, strain gradient theory is employed as a powerful tool to increase the accuracy of the random vibration modeling of the micro-harvester. Equations of motion of the system in the time domain are derived using the Lagrange approach. These are then utilized to determine the frequency and impulse responses of the structure. Assuming the energy harvester to be subjected to a combination of broadband and limited-band random support motion and transverse loading, closed-form expressions for mean, mean square, correlation and spectral density of the output power are derived. The suggested formulation is further exploited to investigate the effect of the different design parameters, including the geometric properties of the structure as well as the properties of the electrical circuit on the resulting power. Furthermore, the effect of length scale parameters on the harvested energy is investigated in detail. It is observed that the predictions of classical and even simple size-dependent theories (such as couple stress) appreciably differ from the findings of strain gradient theory on the basis of random vibration. This study presents a first-time modeling of micro-scale harvesters under stochastic excitations using a size-dependent approach and can be considered as a reliable foundation for future research in the field of

  17. Self-produced Time Intervals Are Perceived as More Variable and/or Shorter Depending on Temporal Context in Subsecond and Suprasecond Ranges

    Directory of Open Access Journals (Sweden)

    Keita eMitani

    2016-06-01

    Full Text Available The processing of time intervals is fundamental for sensorimotor and cognitive functions. Perceptual and motor timing are often performed concurrently (e.g., playing a musical instrument. Although previous studies have shown the influence of body movements on time perception, how we perceive self-produced time intervals has remained unclear. Furthermore, it has been suggested that the timing mechanisms are distinct for the sub- and suprasecond ranges. Here, we compared perceptual performances for self-produced and passively presented time intervals in random contexts (i.e., multiple target intervals presented in a session across the sub- and suprasecond ranges (Experiment 1 and within the sub- (Experiment 2 and suprasecond (Experiment 3 ranges, and in a constant context (i.e., a single target interval presented in a session in the sub- and suprasecond ranges (Experiment 4. We show that self-produced time intervals were perceived as shorter and more variable across the sub- and suprasecond ranges and within the suprasecond range but not within the subsecond range in a random context. In a constant context, the self-produced time intervals were perceived as more variable in the suprasecond range but not in the subsecond range. The impairing effects indicate that motor timing interferes with perceptual timing. The dependence of impairment on temporal contexts suggests multiple timing mechanisms for the subsecond and suprasecond ranges. In addition, violation of the scalar property (i.e., a constant variability to target interval ratio was observed between the sub- and suprasecond ranges. The violation was clearer for motor timing than for perceptual timing. This suggests that the multiple timing mechanisms for the sub- and suprasecond ranges overlap more for perception than for motor. Moreover, the central tendency effect (i.e., where shorter base intervals are overestimated and longer base intervals are underestimated disappeared with subsecond

  18. Variable dead time counters: 2. A computer simulation

    International Nuclear Information System (INIS)

    Hooton, B.W.; Lees, E.W.

    1980-09-01

    A computer model has been developed to give a pulse train which simulates that generated by a variable dead time counter (VDC) used in safeguards determination of Pu mass. The model is applied to two algorithms generally used for VDC analysis. It is used to determine their limitations at high counting rates and to investigate the effects of random neutrons from (α,n) reactions. Both algorithms are found to be deficient for use with masses of 240 Pu greater than 100g and one commonly used algorithm is shown, by use of the model and also by theory, to yield a result which is dependent on the random neutron intensity. (author)

  19. Random phenomena fundamentals of probability and statistics for engineers

    CERN Document Server

    Ogunnaike, Babatunde A

    2009-01-01

    PreludeApproach PhilosophyFour Basic PrinciplesI FoundationsTwo Motivating ExamplesYield Improvement in a Chemical ProcessQuality Assurance in a Glass Sheet Manufacturing ProcessOutline of a Systematic ApproachRandom Phenomena, Variability, and UncertaintyTwo Extreme Idealizations of Natural PhenomenaRandom Mass PhenomenaIntroducing ProbabilityThe Probabilistic FrameworkII ProbabilityFundamentals of Probability TheoryBuilding BlocksOperationsProbabilityConditional ProbabilityIndependenceRandom Variables and DistributionsDistributionsMathematical ExpectationCharacterizing DistributionsSpecial Derived Probability FunctionsMultidimensional Random VariablesDistributions of Several Random VariablesDistributional Characteristics of Jointly Distributed Random VariablesRandom Variable TransformationsSingle Variable TransformationsBivariate TransformationsGeneral Multivariate TransformationsApplication Case Studies I: ProbabilityMendel and HeredityWorld War II Warship Tactical Response Under AttackIII DistributionsIde...

  20. A message-passing approach to random constraint satisfaction problems with growing domains

    International Nuclear Information System (INIS)

    Zhao, Chunyan; Zheng, Zhiming; Zhou, Haijun; Xu, Ke

    2011-01-01

    Message-passing algorithms based on belief propagation (BP) are implemented on a random constraint satisfaction problem (CSP) referred to as model RB, which is a prototype of hard random CSPs with growing domain size. In model RB, the number of candidate discrete values (the domain size) of each variable increases polynomially with the variable number N of the problem formula. Although the satisfiability threshold of model RB is exactly known, finding solutions for a single problem formula is quite challenging and attempts have been limited to cases of N ∼ 10 2 . In this paper, we propose two different kinds of message-passing algorithms guided by BP for this problem. Numerical simulations demonstrate that these algorithms allow us to find a solution for random formulas of model RB with constraint tightness slightly less than p cr , the threshold value for the satisfiability phase transition. To evaluate the performance of these algorithms, we also provide a local search algorithm (random walk) as a comparison. Besides this, the simulated time dependence of the problem size N and the entropy of the variables for growing domain size are discussed

  1. BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios, E-mail: junhankim@email.arizona.edu [Department of Astronomy and Steward Observatory, University of Arizona, 933 N. Cherry Avenue, Tucson, AZ 85721 (United States)

    2016-12-01

    The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

  2. Investigating Factorial Invariance of Latent Variables Across Populations When Manifest Variables Are Missing Completely.

    Science.gov (United States)

    Widaman, Keith F; Grimm, Kevin J; Early, Dawnté R; Robins, Richard W; Conger, Rand D

    2013-07-01

    Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group.

  3. Anomalous transport in fluid field with random waiting time depending on the preceding jump length

    International Nuclear Information System (INIS)

    Zhang Hong; Li Guo-Hua

    2016-01-01

    Anomalous (or non-Fickian) transport behaviors of particles have been widely observed in complex porous media. To capture the energy-dependent characteristics of non-Fickian transport of a particle in flow fields, in the present paper a generalized continuous time random walk model whose waiting time probability distribution depends on the preceding jump length is introduced, and the corresponding master equation in Fourier–Laplace space for the distribution of particles is derived. As examples, two generalized advection-dispersion equations for Gaussian distribution and lévy flight with the probability density function of waiting time being quadratic dependent on the preceding jump length are obtained by applying the derived master equation. (paper)

  4. Testing concordance of instrumental variable effects in generalized linear models with application to Mendelian randomization

    Science.gov (United States)

    Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li

    2014-01-01

    Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158

  5. Simulation-based production planning for engineer-to-order systems with random yield

    NARCIS (Netherlands)

    Akcay, Alp; Martagan, Tugce

    2018-01-01

    We consider an engineer-to-order production system with unknown yield. We model the yield as a random variable which represents the percentage output obtained from one unit of production quantity. We develop a beta-regression model in which the mean value of the yield depends on the unique

  6. Asymptotics for Associated Random Variables

    CERN Document Server

    Oliveira, Paulo Eduardo

    2012-01-01

    The book concerns the notion of association in probability and statistics. Association and some other positive dependence notions were introduced in 1966 and 1967 but received little attention from the probabilistic and statistics community. The interest in these dependence notions increased in the last 15 to 20 years, and many asymptotic results were proved and improved. Despite this increased interest, characterizations and results remained essentially scattered in the literature published in different journals. The goal of this book is to bring together the bulk of these results, presenting

  7. Multivariate normal maximum likelihood with both ordinal and continuous variables, and data missing at random.

    Science.gov (United States)

    Pritikin, Joshua N; Brick, Timothy R; Neale, Michael C

    2018-04-01

    A novel method for the maximum likelihood estimation of structural equation models (SEM) with both ordinal and continuous indicators is introduced using a flexible multivariate probit model for the ordinal indicators. A full information approach ensures unbiased estimates for data missing at random. Exceeding the capability of prior methods, up to 13 ordinal variables can be included before integration time increases beyond 1 s per row. The method relies on the axiom of conditional probability to split apart the distribution of continuous and ordinal variables. Due to the symmetry of the axiom, two similar methods are available. A simulation study provides evidence that the two similar approaches offer equal accuracy. A further simulation is used to develop a heuristic to automatically select the most computationally efficient approach. Joint ordinal continuous SEM is implemented in OpenMx, free and open-source software.

  8. Convolutions of Heavy Tailed Random Variables and Applications to Portfolio Diversification and MA(1) Time Series

    OpenAIRE

    Geluk, Jaap; Peng, Liang; de Vries, Casper G.

    1999-01-01

    Suppose X1,X2 are independent random variables satisfying a second-order regular variation condition on the tail-sum and a balance condition on the tails. In this paper we give a description of the asymptotic behaviour as t → ∞ for P(X1 + X2 > t). The result is applied to the problem of risk diversification in portfolio analysis and to the estimation of the parameter in a MA(1) model.

  9. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  10. Comparison of structured and unstructured physical activity training on predicted VO2max and heart rate variability in adolescents - a randomized control trial.

    Science.gov (United States)

    Sharma, Vivek Kumar; Subramanian, Senthil Kumar; Radhakrishnan, Krishnakumar; Rajendran, Rajathi; Ravindran, Balasubramanian Sulur; Arunachalam, Vinayathan

    2017-05-01

    Physical inactivity contributes to many health issues. The WHO-recommended physical activity for adolescents encompasses aerobic, resistance, and bone strengthening exercises aimed at achieving health-related physical fitness. Heart rate variability (HRV) and maximal aerobic capacity (VO2max) are considered as noninvasive measures of cardiovascular health. The objective of this study is to compare the effect of structured and unstructured physical training on maximal aerobic capacity and HRV among adolescents. We designed a single blinded, parallel, randomized active-controlled trial (Registration No. CTRI/2013/08/003897) to compare the physiological effects of 6 months of globally recommended structured physical activity (SPA), with that of unstructured physical activity (USPA) in healthy school-going adolescents. We recruited 439 healthy student volunteers (boys: 250, girls: 189) in the age group of 12-17 years. Randomization across the groups was done using age and gender stratified randomization method, and the participants were divided into two groups: SPA (n=219, boys: 117, girls: 102) and USPA (n=220, boys: 119, girls: 101). Depending on their training status and gender the participants in both SPA and USPA groups were further subdivided into the following four sub-groups: SPA athlete boys (n=22) and girls (n=17), SPA nonathlete boys (n=95) and girls (n=85), USPA athlete boys (n=23) and girls (n=17), and USPA nonathlete boys (n=96) and girls (n=84). We recorded HRV, body fat%, and VO2 max using Rockport Walk Fitness test before and after the intervention. Maximum aerobic capacity and heart rate variability increased significantly while heart rate, systolic blood pressure, diastolic blood pressure, and body fat percentage decreased significantly after both SPA and USPA intervention. However, the improvement was more in SPA as compared to USPA. SPA is more beneficial for improving cardiorespiratory fitness, HRV, and reducing body fat percentage in terms of

  11. Application of a random network with a variable geometry of links to the kinetics of drug elimination in healthy and diseased livers

    Science.gov (United States)

    Chelminiak, P.; Dixon, J. M.; Tuszyński, J. A.; Marsh, R. E.

    2006-05-01

    This paper discusses an application of a random network with a variable number of links and traps to the elimination of drug molecules from the body by the liver. The nodes and links represent the transport vessels, and the traps represent liver cells with metabolic enzymes that eliminate drug molecules. By varying the number and configuration of links and nodes, different disease states of the liver related to vascular damage have been simulated, and the effects on the rate of elimination of a drug have been investigated. Results of numerical simulations show the prevalence of exponential decay curves with rates that depend on the concentration of links. In the case of fractal lattices at the percolation threshold, we find that the decay of the concentration is described by exponential functions for high trap concentrations but transitions to stretched exponential behavior at low trap concentrations.

  12. Vertical random variability of the distribution coefficient in the soil and its effect on the migration of fallout radionuclides

    International Nuclear Information System (INIS)

    Bunzl, K.

    2002-01-01

    In the field, the distribution coefficient, K d , for the sorption of a radionuclide by the soil cannot be expected to be constant. Even in a well defined soil horizon, K d will vary stochastically in horizontal as well as in vertical direction around a mean value. The horizontal random variability of K d produce a pronounced tailing effect in the concentration depth profile of a fallout radionuclide, much less is known on the corresponding effect of the vertical random variability. To analyze this effect theoretically, the classical convection-dispersion model in combination with the random-walk particle method was applied. The concentration depth profile of a radionuclide was calculated one year after deposition assuming constant values of the pore water velocity, the diffusion/dispersion coefficient, and the distribution coefficient (K d = 100 cm 3 x g -1 ) and exhibiting a vertical variability for K d according to a log-normal distribution with a geometric mean of 100 cm 3 x g -1 and a coefficient of variation of CV 0.53. The results show that these two concentration depth profiles are only slightly different, the location of the peak is shifted somewhat upwards, and the dispersion of the concentration depth profile is slightly larger. A substantial tailing effect of the concentration depth profile is not perceivable. Especially with respect to the location of the peak, a very good approximation of the concentration depth profile is obtained if the arithmetic mean of the K d -values (K d = 113 cm 3 x g -1 ) and a slightly increased dispersion coefficient are used in the analytical solution of the classical convection-dispersion equation with constant K d . The evaluation of the observed concentration depth profile with the analytical solution of the classical convection-dispersion equation with constant parameters will, within the usual experimental limits, hardly reveal the presence of a log-normal random distribution of K d in the vertical direction in

  13. Uncovering state-dependent relationships in shallow lakes using Bayesian latent variable regression.

    Science.gov (United States)

    Vitense, Kelsey; Hanson, Mark A; Herwig, Brian R; Zimmer, Kyle D; Fieberg, John

    2018-03-01

    Ecosystems sometimes undergo dramatic shifts between contrasting regimes. Shallow lakes, for instance, can transition between two alternative stable states: a clear state dominated by submerged aquatic vegetation and a turbid state dominated by phytoplankton. Theoretical models suggest that critical nutrient thresholds differentiate three lake types: highly resilient clear lakes, lakes that may switch between clear and turbid states following perturbations, and highly resilient turbid lakes. For effective and efficient management of shallow lakes and other systems, managers need tools to identify critical thresholds and state-dependent relationships between driving variables and key system features. Using shallow lakes as a model system for which alternative stable states have been demonstrated, we developed an integrated framework using Bayesian latent variable regression (BLR) to classify lake states, identify critical total phosphorus (TP) thresholds, and estimate steady state relationships between TP and chlorophyll a (chl a) using cross-sectional data. We evaluated the method using data simulated from a stochastic differential equation model and compared its performance to k-means clustering with regression (KMR). We also applied the framework to data comprising 130 shallow lakes. For simulated data sets, BLR had high state classification rates (median/mean accuracy >97%) and accurately estimated TP thresholds and state-dependent TP-chl a relationships. Classification and estimation improved with increasing sample size and decreasing noise levels. Compared to KMR, BLR had higher classification rates and better approximated the TP-chl a steady state relationships and TP thresholds. We fit the BLR model to three different years of empirical shallow lake data, and managers can use the estimated bifurcation diagrams to prioritize lakes for management according to their proximity to thresholds and chance of successful rehabilitation. Our model improves upon

  14. Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

    Science.gov (United States)

    You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

    2011-02-01

    The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure

  15. An AUC-based permutation variable importance measure for random forests.

    Science.gov (United States)

    Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure

    2013-04-05

    The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html.

  16. Random walk in degree space and the time-dependent Watts-Strogatz model

    Science.gov (United States)

    Casa Grande, H. L.; Cotacallapa, M.; Hase, M. O.

    2017-01-01

    In this work, we propose a scheme that provides an analytical estimate for the time-dependent degree distribution of some networks. This scheme maps the problem into a random walk in degree space, and then we choose the paths that are responsible for the dominant contributions. The method is illustrated on the dynamical versions of the Erdős-Rényi and Watts-Strogatz graphs, which were introduced as static models in the original formulation. We have succeeded in obtaining an analytical form for the dynamics Watts-Strogatz model, which is asymptotically exact for some regimes.

  17. Variability of interconnected wind plants: correlation length and its dependence on variability time scale

    Science.gov (United States)

    St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

    2015-04-01

    The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. But how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer ‘how far is far enough,’ we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25-2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high

  18. Method of nuclear reactor control using a variable temperature load dependent set point

    International Nuclear Information System (INIS)

    Kelly, J.J.; Rambo, G.E.

    1982-01-01

    A method and apparatus for controlling a nuclear reactor in response to a variable average reactor coolant temperature set point is disclosed. The set point is dependent upon percent of full power load demand. A manually-actuated ''droop mode'' of control is provided whereby the reactor coolant temperature is allowed to drop below the set point temperature a predetermined amount wherein the control is switched from reactor control rods exclusively to feedwater flow

  19. Natural variability of biochemical biomarkers in the macro-zoobenthos: Dependence on life stage and environmental factors.

    Science.gov (United States)

    Scarduelli, Lucia; Giacchini, Roberto; Parenti, Paolo; Migliorati, Sonia; Di Brisco, Agnese Maria; Vighi, Marco

    2017-11-01

    Biomarkers are widely used in ecotoxicology as indicators of exposure to toxicants. However, their ability to provide ecologically relevant information remains controversial. One of the major problems is understanding whether the measured responses are determined by stress factors or lie within the natural variability range. In a previous work, the natural variability of enzymatic levels in invertebrates sampled in pristine rivers was proven to be relevant across both space and time. In the present study, the experimental design was improved by considering different life stages of the selected taxa and by measuring more environmental parameters. The experimental design considered sampling sites in 2 different rivers, 8 sampling dates covering the whole seasonal cycle, 4 species from 3 different taxonomic groups (Plecoptera, Perla grandis; Ephemeroptera, Baetis alpinus and Epeorus alpicula; Tricoptera, Hydropsyche pellucidula), different life stages for each species, and 4 enzymes (acetylcholinesterase, glutathione S-transferase, alkaline phosphatase, and catalase). Biomarker levels were related to environmental (physicochemical) parameters to verify any kind of dependence. Data were statistically elaborated using hierarchical multilevel Bayesian models. Natural variability was found to be relevant across both space and time. The results of the present study proved that care should be paid when interpreting biomarker results. Further research is needed to better understand the dependence of the natural variability on environmental parameters. Environ Toxicol Chem 2017;36:3158-3167. © 2017 SETAC. © 2017 SETAC.

  20. On a randomly imperfect spherical cap pressurized by a random ...

    African Journals Online (AJOL)

    In this paper, we investigate a dynamical system in a random setting of dual randomness in space and time variables in which both the imperfection of the structure and the load function are considered random , each with a statistical zero-mean .The auto- covariance of the load is correlated as an exponentially decaying ...

  1. Dimensions of dependence and their influence on the outcome of cognitive behaviour therapy for health anxiety: randomized controlled trial.

    Science.gov (United States)

    Tyrer, Peter; Wang, Duolao; Tyrer, Helen; Crawford, Mike; Cooper, Sylvia

    2016-05-01

    The personality trait of dependence is common in health-seeking behaviour. We therefore examined its impact in a large randomized controlled trial of psychological treatment for health anxiety. To test whether dependent personality traits were positive or negative in determining the outcome of an adapted form of cognitive behaviour therapy for health anxiety (CBT-HA) over the course of 5 years and whether dependent personality dysfunction could be viewed dimensionally in a similar way to the new ICD-11 diagnostic system for general personality disorder. Dependent personality dysfunction was assessed using a self-rated questionnaire, the Dependent Personality Questionnaire, at baseline in a randomized controlled trial of 444 patients from medical clinics with pathological health anxiety treated with a modified form of CBT-HA or standard treatment in the medical clinics, with assessment on five occasions over 5 years. Dependent personality dysfunction was assessed using four severity groups. Patients with mild and moderate dependent personality disorder treated with CBT-HA showed the greatest reduction in health anxiety compared with standard care, and those with no dependent dysfunction showed the least benefit. Patients with higher dependent traits received significantly more treatment sessions (8.6) than those with low trait levels (5.4) (p dependent personality. The reasons for this may be related to better adherence to psychological treatment and greater negative effects of frequent reassurance and excessive consultation in those treated in standard care. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  2. r2VIM: A new variable selection method for random forests in genome-wide association studies.

    Science.gov (United States)

    Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

    2016-01-01

    Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

  3. Assessment of variability in the hydrological cycle of the Loess Plateau, China: examining dependence structures of hydrological processes

    Science.gov (United States)

    Guo, A.; Wang, Y.

    2017-12-01

    Investigating variability in dependence structures of hydrological processes is of critical importance for developing an understanding of mechanisms of hydrological cycles in changing environments. In focusing on this topic, present work involves the following: (1) identifying and eliminating serial correlation and conditional heteroscedasticity in monthly streamflow (Q), precipitation (P) and potential evapotranspiration (PE) series using the ARMA-GARCH model (ARMA: autoregressive moving average; GARCH: generalized autoregressive conditional heteroscedasticity); (2) describing dependence structures of hydrological processes using partial copula coupled with the ARMA-GARCH model and identifying their variability via copula-based likelihood-ratio test method; and (3) determining conditional probability of annual Q under different climate scenarios on account of above results. This framework enables us to depict hydrological variables in the presence of conditional heteroscedasticity and to examine dependence structures of hydrological processes while excluding the influence of covariates by using partial copula-based ARMA-GARCH model. Eight major catchments across the Loess Plateau (LP) are used as study regions. Results indicate that (1) The occurrence of change points in dependence structures of Q and P (PE) varies across the LP. Change points of P-PE dependence structures in all regions almost fully correspond to the initiation of global warming, i.e., the early 1980s. (3) Conditional probabilities of annual Q under various P and PE scenarios are estimated from the 3-dimensional joint distribution of (Q, P and PE) based on the above change points. These findings shed light on mechanisms of the hydrological cycle and can guide water supply planning and management, particularly in changing environments.

  4. The dependence of J/ψ-nucleon inelastic cross section on the Feynman variable

    International Nuclear Information System (INIS)

    Duan Chungui; Liu Na; Miao Wendan

    2011-01-01

    By means of two typical sets of nuclear parton distribution functions, meanwhile taking account of the energy loss of the beam proton and the nuclear absorption of the charmonium states traversing the nuclear matter in the uniform framework of the Glauber model, a leading order phenomenological analysis is given in the color evaporation model of the E866 experimental data on J/ψ production differential cross section ratios R Fe/Be (x F ). It is shown that the energy loss effect of beam proton on R Fe/Be (x F ) is more important than the nuclear effects on parton distribution functions in the high Feynman variable x F region. It is found that the J/ψ-nucleon inelastic cross section depends on the Feynman variable x F and increases linearly with x F in the region x F > 0.2. (authors)

  5. Effects of Variable Production Rate and Time-Dependent Holding Cost for Complementary Products in Supply Chain Model

    Directory of Open Access Journals (Sweden)

    Mitali Sarkar

    2017-01-01

    Full Text Available Recently, a major trend is going to redesign a production system by controlling or making variable the production rate within some fixed interval to maintain the optimal level. This strategy is more effective when the holding cost is time-dependent as it is interrelated with holding duration of products and rate of production. An effort is made to make a supply chain model (SCM to show the joint effect of variable production rate and time-varying holding cost for specific type of complementary products, where those products are made by two different manufacturers and a common retailer makes them bundle and sells bundles to end customers. Demand of each product is specified by stochastic reservation prices with a known potential market size. Those players of the SCM are considered with unequal power. Stackelberg game approach is employed to obtain global optimum solution of the model. An illustrative numerical example, graphical representation, and managerial insights are given to illustrate the model. Results prove that variable production rate and time-dependent holding cost save more than existing literature.

  6. Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

    Directory of Open Access Journals (Sweden)

    Juliana Petrini

    2012-12-01

    Full Text Available The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567, yearling weight (n=58,124, and scrotal circumference (n=20,371 of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

  7. Building the nodal nuclear data dependences in a many-dimensional state-variable space

    International Nuclear Information System (INIS)

    Dufek, Jan

    2011-01-01

    Highlights: → The Abstract and Introduction are revised to reflect reviewers' comments. → Section is revised and simplified. → The third paragraph in Section is revised. → All typos are fixed. - Abstract: We present new methods for building the polynomial-regression based nodal nuclear data models. The data models can reflect dependences on a large number of state variables, and they can consider various history effects. Suitable multivariate polynomials that approximate the nodal data dependences are identified efficiently in an iterative manner. The history effects are analysed using a new sampling scheme for lattice calculations where the traditional base burnup and branch calculations are replaced by a large number of diverse burnup histories. The total number of lattice calculations is controlled so that the data models are built to a required accuracy.

  8. Resistance controllability and variability improvement in a TaO{sub x}-based resistive memory for multilevel storage application

    Energy Technology Data Exchange (ETDEWEB)

    Prakash, A., E-mail: amitknp@postech.ac.kr, E-mail: amit.knp02@gmail.com, E-mail: hwanghs@postech.ac.kr; Song, J.; Hwang, H., E-mail: amitknp@postech.ac.kr, E-mail: amit.knp02@gmail.com, E-mail: hwanghs@postech.ac.kr [Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), 77 Cheongam-ro, Nam-gu, Pohang, 790-784 (Korea, Republic of); Deleruyelle, D.; Bocquet, M. [Im2np, UMR CNRS 7334, Aix-Marseille Université, Marseille (France)

    2015-06-08

    In order to obtain reliable multilevel cell (MLC) characteristics, resistance controllability between the different resistance levels is required especially in resistive random access memory (RRAM), which is prone to resistance variability mainly due to its intrinsic random nature of defect generation and filament formation. In this study, we have thoroughly investigated the multilevel resistance variability in a TaO{sub x}-based nanoscale (<30 nm) RRAM operated in MLC mode. It is found that the resistance variability not only depends on the conductive filament size but also is a strong function of oxygen vacancy concentration in it. Based on the gained insights through experimental observations and simulation, it is suggested that forming thinner but denser conductive filament may greatly improve the temporal resistance variability even at low operation current despite the inherent stochastic nature of resistance switching process.

  9. Randomized controlled trial of attention bias modification in a racially diverse, socially anxious, alcohol dependent sample.

    Science.gov (United States)

    Clerkin, Elise M; Magee, Joshua C; Wells, Tony T; Beard, Courtney; Barnett, Nancy P

    2016-12-01

    Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Adult participants (N = 86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Randomized Controlled Trial of Attention Bias Modification in a Racially Diverse, Socially Anxious, Alcohol Dependent Sample

    Science.gov (United States)

    Clerkin, Elise M.; Magee, Joshua C.; Wells, Tony T.; Beard, Courtney; Barnett, Nancy P.

    2016-01-01

    Objective Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Method Adult participants (N=86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Results Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. Conclusions These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. PMID:27591918

  11. Stochastic methods for uncertainty treatment of functional variables in computer codes: application to safety studies

    International Nuclear Information System (INIS)

    Nanty, Simon

    2015-01-01

    This work relates to the framework of uncertainty quantification for numerical simulators, and more precisely studies two industrial applications linked to the safety studies of nuclear plants. These two applications have several common features. The first one is that the computer code inputs are functional and scalar variables, functional ones being dependent. The second feature is that the probability distribution of functional variables is known only through a sample of their realizations. The third feature, relative to only one of the two applications, is the high computational cost of the code, which limits the number of possible simulations. The main objective of this work was to propose a complete methodology for the uncertainty analysis of numerical simulators for the two considered cases. First, we have proposed a methodology to quantify the uncertainties of dependent functional random variables from a sample of their realizations. This methodology enables to both model the dependency between variables and their link to another variable, called co-variate, which could be, for instance, the output of the considered code. Then, we have developed an adaptation of a visualization tool for functional data, which enables to simultaneously visualize the uncertainties and features of dependent functional variables. Second, a method to perform the global sensitivity analysis of the codes used in the two studied cases has been proposed. In the case of a computationally demanding code, the direct use of quantitative global sensitivity analysis methods is intractable. To overcome this issue, the retained solution consists in building a surrogate model or meta model, a fast-running model approximating the computationally expensive code. An optimized uniform sampling strategy for scalar and functional variables has been developed to build a learning basis for the meta model. Finally, a new approximation approach for expensive codes with functional outputs has been

  12. Drop Spreading with Random Viscosity

    Science.gov (United States)

    Xu, Feng; Jensen, Oliver

    2016-11-01

    Airway mucus acts as a barrier to protect the lung. However as a biological material, its physical properties are known imperfectly and can be spatially heterogeneous. In this study we assess the impact of these uncertainties on the rate of spreading of a drop (representing an inhaled aerosol) over a mucus film. We model the film as Newtonian, having a viscosity that depends linearly on the concentration of a passive solute (a crude proxy for mucin proteins). Given an initial random solute (and hence viscosity) distribution, described as a Gaussian random field with a given correlation structure, we seek to quantify the uncertainties in outcomes as the drop spreads. Using lubrication theory, we describe the spreading of the drop in terms of a system of coupled nonlinear PDEs governing the evolution of film height and the vertically-averaged solute concentration. We perform Monte Carlo simulations to predict the variability in the drop centre location and width (1D) or area (2D). We show how simulation results are well described (at much lower computational cost) by a low-order model using a weak disorder expansion. Our results show for example how variability in the drop location is a non-monotonic function of the solute correlation length increases. Engineering and Physical Sciences Research Council.

  13. Continuous-Time Random Walk with multi-step memory: an application to market dynamics

    Science.gov (United States)

    Gubiec, Tomasz; Kutner, Ryszard

    2017-11-01

    An extended version of the Continuous-Time Random Walk (CTRW) model with memory is herein developed. This memory involves the dependence between arbitrary number of successive jumps of the process while waiting times between jumps are considered as i.i.d. random variables. This dependence was established analyzing empirical histograms for the stochastic process of a single share price on a market within the high frequency time scale. Then, it was justified theoretically by considering bid-ask bounce mechanism containing some delay characteristic for any double-auction market. Our model appeared exactly analytically solvable. Therefore, it enables a direct comparison of its predictions with their empirical counterparts, for instance, with empirical velocity autocorrelation function. Thus, the present research significantly extends capabilities of the CTRW formalism. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

  14. A preliminary, randomized trial of aerobic exercise for alcohol dependence.

    Science.gov (United States)

    Brown, Richard A; Abrantes, Ana M; Minami, Haruka; Read, Jennifer P; Marcus, Bess H; Jakicic, John M; Strong, David R; Dubreuil, Mary Ella; Gordon, Alan A; Ramsey, Susan E; Kahler, Christopher W; Stuart, Gregory L

    2014-07-01

    Interventions targeting physical activity may be valuable as an adjunct to alcohol treatment, but have been relatively untested. In the current study, alcohol dependent, physically sedentary patients were randomized to: a 12-week moderate-intensity, group aerobic exercise intervention (AE; n=25) or a brief advice to exercise intervention (BA-E; n=23). Results showed that individuals in AE reported significantly fewer drinking and heavy drinking days, relative to BA-E during treatment. Furthermore adherence to AE strengthened the beneficial effect of intervention on alcohol use outcomes. While high levels of moderate-intensity exercise appeared to facilitate alcohol recovery regardless of intervention arm, attending the group-based AE intervention seemed to further enhance the positive effects of exercise on alcohol use. Study findings indicate that a moderate intensity, group aerobic exercise intervention is an efficacious adjunct to alcohol treatment. Improving adherence to the intervention may enhance its beneficial effects on alcohol use. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Human phoneme recognition depending on speech-intrinsic variability.

    Science.gov (United States)

    Meyer, Bernd T; Jürgens, Tim; Wesker, Thorsten; Brand, Thomas; Kollmeier, Birger

    2010-11-01

    The influence of different sources of speech-intrinsic variation (speaking rate, effort, style and dialect or accent) on human speech perception was investigated. In listening experiments with 16 listeners, confusions of consonant-vowel-consonant (CVC) and vowel-consonant-vowel (VCV) sounds in speech-weighted noise were analyzed. Experiments were based on the OLLO logatome speech database, which was designed for a man-machine comparison. It contains utterances spoken by 50 speakers from five dialect/accent regions and covers several intrinsic variations. By comparing results depending on intrinsic and extrinsic variations (i.e., different levels of masking noise), the degradation induced by variabilities can be expressed in terms of the SNR. The spectral level distance between the respective speech segment and the long-term spectrum of the masking noise was found to be a good predictor for recognition rates, while phoneme confusions were influenced by the distance to spectrally close phonemes. An analysis based on transmitted information of articulatory features showed that voicing and manner of articulation are comparatively robust cues in the presence of intrinsic variations, whereas the coding of place is more degraded. The database and detailed results have been made available for comparisons between human speech recognition (HSR) and automatic speech recognizers (ASR).

  16. Managing the Newsvendor Modeled Product System with Random Capacity and Capacity-Dependent Price

    Directory of Open Access Journals (Sweden)

    Qingying Li

    2015-01-01

    Full Text Available We consider a newsvendor modeled product system, where the firm provides products to the market. The supply capacity of the product is random, so the firm receives either the amount of order quantity or the realized capacity, whichever is smaller. The market price is capacity dependent. We consider two types of production cost structures: the procurement case and the in-house production case. The firm pays for the received quantity in the former case and for the ordered quantity in the latter case. We obtain the optimal order quantities for both cases. Comparing with the traditional newsvendor model, we find that the optimal order quantity in both the procurement case and the in-house production case are no greater than that in the traditional newsvendor model with a fixed selling price. We also find that the optimal order quantity for the procurement case is greater than that for the in-house production case. Numerical study is conducted to investigate the sensitivity of the optimal solution versus the distribution of the random capacity/demand.

  17. Dissociable effects of practice variability on learning motor and timing skills.

    Science.gov (United States)

    Caramiaux, Baptiste; Bevilacqua, Frédéric; Wanderley, Marcelo M; Palmer, Caroline

    2018-01-01

    Motor skill acquisition inherently depends on the way one practices the motor task. The amount of motor task variability during practice has been shown to foster transfer of the learned skill to other similar motor tasks. In addition, variability in a learning schedule, in which a task and its variations are interweaved during practice, has been shown to help the transfer of learning in motor skill acquisition. However, there is little evidence on how motor task variations and variability schedules during practice act on the acquisition of complex motor skills such as music performance, in which a performer learns both the right movements (motor skill) and the right time to perform them (timing skill). This study investigated the impact of rate (tempo) variability and the schedule of tempo change during practice on timing and motor skill acquisition. Complete novices, with no musical training, practiced a simple musical sequence on a piano keyboard at different rates. Each novice was assigned to one of four learning conditions designed to manipulate the amount of tempo variability across trials (large or small tempo set) and the schedule of tempo change (randomized or non-randomized order) during practice. At test, the novices performed the same musical sequence at a familiar tempo and at novel tempi (testing tempo transfer), as well as two novel (but related) sequences at a familiar tempo (testing spatial transfer). We found that practice conditions had little effect on learning and transfer performance of timing skill. Interestingly, practice conditions influenced motor skill learning (reduction of movement variability): lower temporal variability during practice facilitated transfer to new tempi and new sequences; non-randomized learning schedule improved transfer to new tempi and new sequences. Tempo (rate) and the sequence difficulty (spatial manipulation) affected performance variability in both timing and movement. These findings suggest that there is a

  18. Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

    Directory of Open Access Journals (Sweden)

    Christophe Coupé

    2018-04-01

    Full Text Available As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM, which address grouping of observations, and generalized linear mixed-effects models (GLMM, which offer a family of distributions for the dependent variable. Generalized additive models (GAM are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS. We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships

  19. Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

    Science.gov (United States)

    Coupé, Christophe

    2018-01-01

    As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we

  20. On the fluctuations of sums of independent random variables.

    Science.gov (United States)

    Feller, W

    1969-07-01

    If X(1), X(2),... are independent random variables with zero expectation and finite variances, the cumulative sums S(n) are, on the average, of the order of magnitude S(n), where S(n) (2) = E(S(n) (2)). The occasional maxima of the ratios S(n)/S(n) are surprisingly large and the problem is to estimate the extent of their probable fluctuations.Specifically, let S(n) (*) = (S(n) - b(n))/a(n), where {a(n)} and {b(n)}, two numerical sequences. For any interval I, denote by p(I) the probability that the event S(n) (*) epsilon I occurs for infinitely many n. Under mild conditions on {a(n)} and {b(n)}, it is shown that p(I) equals 0 or 1 according as a certain series converges or diverges. To obtain the upper limit of S(n)/a(n), one has to set b(n) = +/- epsilon a(n), but finer results are obtained with smaller b(n). No assumptions concerning the under-lying distributions are made; the criteria explain structurally which features of {X(n)} affect the fluctuations, but for concrete results something about P{S(n)>a(n)} must be known. For example, a complete solution is possible when the X(n) are normal, replacing the classical law of the iterated logarithm. Further concrete estimates may be obtained by combining the new criteria with some recently developed limit theorems.

  1. Anomalous transport in fluid field with random waiting time depending on the preceding jump length

    Science.gov (United States)

    Zhang, Hong; Li, Guo-Hua

    2016-11-01

    Anomalous (or non-Fickian) transport behaviors of particles have been widely observed in complex porous media. To capture the energy-dependent characteristics of non-Fickian transport of a particle in flow fields, in the present paper a generalized continuous time random walk model whose waiting time probability distribution depends on the preceding jump length is introduced, and the corresponding master equation in Fourier-Laplace space for the distribution of particles is derived. As examples, two generalized advection-dispersion equations for Gaussian distribution and lévy flight with the probability density function of waiting time being quadratic dependent on the preceding jump length are obtained by applying the derived master equation. Project supported by the Foundation for Young Key Teachers of Chengdu University of Technology, China (Grant No. KYGG201414) and the Opening Foundation of Geomathematics Key Laboratory of Sichuan Province, China (Grant No. scsxdz2013009).

  2. A Comparison of the Prognostic Value of Early PSA Test-Based Variables Following External Beam Radiotherapy, With or Without Preceding Androgen Deprivation: Analysis of Data From the TROG 96.01 Randomized Trial

    International Nuclear Information System (INIS)

    Lamb, David S.; Denham, James W.; Joseph, David; Matthews, John; Atkinson, Chris; Spry, Nigel A.; Duchesne, Gillian; Ebert, Martin; Steigler, Allison; Delahunt, Brett; D'Este, Catherine

    2011-01-01

    Purpose: We sought to compare the prognostic value of early prostate-specific antigen (PSA) test-based variables for the 802 eligible patients treated in the Trans-Tasman Radiation Oncology Group 96.01 randomized trial. Methods and Materials: Patients in this trial had T2b, T2c, T3, and T4 N0 prostate cancer and were randomized to 0, 3, or 6 months of neoadjuvant androgen deprivation therapy (NADT) prior to and during radiation treatment at 66 Gy to the prostate and seminal vesicles. The early PSA test-based variables evaluated were the pretreatment initial PSA (iPSA) value, PSA values at 2 and 4 months into NADT, the PSA nadir (nPSA) value after radiation in all patients, and PSA response signatures in men receiving radiation. Comparisons of endpoints were made using Cox models of local progression-free survival, distant failure-free survival, biochemical failure-free survival, and prostate cancer-specific survival. Results: The nPSA value was a powerful predictor of all endpoints regardless of whether NADT was given before radiation. PSA response signatures also predicted all endpoints in men treated by radiation alone. iPSA and PSA results at 2 and 4 months into NADT predicted biochemical failure-free survival but not any of the clinical endpoints. nPSA values correlated with those of iPSA, Gleason grade, and T stage and were significantly higher in men receiving radiation alone than in those receiving NADT. Conclusions: The postradiation nPSA value is the strongest prognostic indicator of all early PSA-based variables. However, its use as a surrogate endpoint needs to take into account its dependence on pretreatment variables and treatment method.

  3. Neutron Transport in Finite Random Media with Pure-Triplet Scattering

    International Nuclear Information System (INIS)

    Sallaha, M.; Hendi, A.A.

    2008-01-01

    The solution of the one-speed neutron transport equation in a finite slab random medium with pure-triplet anisotropic scattering is studied. The stochastic medium is assumed to consist of two randomly mixed immiscible fluids. The cross section and the scattering kernel are treated as discrete random variables, which obey the same statistics as Markovian processes and exponential chord length statistics. The medium boundaries are considered to have specular reflectivities with angular-dependent externally incident flux. The deterministic solution is obtained by using Pomraning-Eddington approximation. Numerical results are calculated for the average reflectivity and average transmissivity for different values of the single scattering albedo and varying the parameters which characterize the random medium. Compared to the results obtained by Adams et al. in case of isotropic scattering that based on the Monte Carlo technique, it can be seen that we have good comparable data

  4. Shape dependency of the extinction and absorption cross sections of dust aerosols modeled as randomly oriented spheroids

    Directory of Open Access Journals (Sweden)

    R. Wagner

    2011-09-01

    Full Text Available We present computational results on the shape dependency of the extinction and absorption cross sections of dustlike aerosol particles that were modeled as randomly oriented spheroids. Shape dependent variations in the extinction cross sections are largest in the size regime that is governed by the interference structure. Elongated spheroids best fitted measured extinction spectra of re-dispersed Saharan dust samples. For dust particles smaller than 1.5 μm in diameter and low absorption potential, shape effects on the absorption cross sections are very small.

  5. Concurrence of Quantum States: Algebraic Dynamical Method Study XXX Models in a Time-Depending Random External Field

    International Nuclear Information System (INIS)

    Fu Chuanji; Zhu Qinsheng; Wu Shaoyi

    2010-01-01

    Based on algebraic dynamics and the concept of the concurrence of the entanglement, we investigate the evolutive properties of the two-qubit entanglement that formed by Heisenberg XXX models under a time-depending external held. For this system, the property of the concurrence that is only dependent on the coupling constant J and total values of the external field is proved. Furthermore, we found that the thermal concurrence of the system under a static random external field is a function of the coupling constant J, temperature T, and the magnitude of external held. (general)

  6. The Relationship of Field Dependent/Independent Cognitive Styles, Stimuli Variability and Time Factor on Student Achievement.

    Science.gov (United States)

    Atang, Christopher I.

    The effects of black and white and color illustrations on student achievement were studied to investigate the relationships between cognitive styles and instructional design. Field dependence (FD) and field independence (FI) were chosen as the cognitive style variables. Subjects were 85 freshman students in the Iowa State University Psychology…

  7. The Initial Regression Statistical Characteristics of Intervals Between Zeros of Random Processes

    Directory of Open Access Journals (Sweden)

    V. K. Hohlov

    2014-01-01

    Full Text Available The article substantiates the initial regression statistical characteristics of intervals between zeros of realizing random processes, studies their properties allowing the use these features in the autonomous information systems (AIS of near location (NL. Coefficients of the initial regression (CIR to minimize the residual sum of squares of multiple initial regression views are justified on the basis of vector representations associated with a random vector notion of analyzed signal parameters. It is shown that even with no covariance-based private CIR it is possible to predict one random variable through another with respect to the deterministic components. The paper studies dependences of CIR interval sizes between zeros of the narrowband stationary in wide-sense random process with its energy spectrum. Particular CIR for random processes with Gaussian and rectangular energy spectra are obtained. It is shown that the considered CIRs do not depend on the average frequency of spectra, are determined by the relative bandwidth of the energy spectra, and weakly depend on the type of spectrum. CIR properties enable its use as an informative parameter when implementing temporary regression methods of signal processing, invariant to the average rate and variance of the input implementations. We consider estimates of the average energy spectrum frequency of the random stationary process by calculating the length of the time interval corresponding to the specified number of intervals between zeros. It is shown that the relative variance in estimation of the average energy spectrum frequency of stationary random process with increasing relative bandwidth ceases to depend on the last process implementation in processing above ten intervals between zeros. The obtained results can be used in the AIS NL to solve the tasks of detection and signal recognition, when a decision is made in conditions of unknown mathematical expectations on a limited observation

  8. Neuronal variability during handwriting: lognormal distribution.

    Directory of Open Access Journals (Sweden)

    Valery I Rupasov

    Full Text Available We examined time-dependent statistical properties of electromyographic (EMG signals recorded from intrinsic hand muscles during handwriting. Our analysis showed that trial-to-trial neuronal variability of EMG signals is well described by the lognormal distribution clearly distinguished from the Gaussian (normal distribution. This finding indicates that EMG formation cannot be described by a conventional model where the signal is normally distributed because it is composed by summation of many random sources. We found that the variability of temporal parameters of handwriting--handwriting duration and response time--is also well described by a lognormal distribution. Although, the exact mechanism of lognormal statistics remains an open question, the results obtained should significantly impact experimental research, theoretical modeling and bioengineering applications of motor networks. In particular, our results suggest that accounting for lognormal distribution of EMGs can improve biomimetic systems that strive to reproduce EMG signals in artificial actuators.

  9. Contribution to the application of the random vibration theory to the seismic analysis of structures via state variables

    International Nuclear Information System (INIS)

    Maestrini, A.P.

    1979-04-01

    Several problems related to the application of the theory of random by means of state variables are studied. The well-known equations that define the propagation of the mean and the variance for linear and non-linear systems are first presented. The Monte Carlo method is next resorted to in order to determine the applicability of the hypothesis of a normally distributed output in case of linear systems subjected to non-Gaussian excitations. Finally, attention is focused on the properties of linear filters and modulation functions proposed to simulate seismic excitations as non stationary random processes. Acceleration spectra obtained by multiplying rms spectra by a constant factor are compared with design spectra suggested by several authors for various soil conditions. In every case, filter properties are given. (Author) [pt

  10. Pure-Triplet Scattering for Radiative Transfer in Semi-infinite Random Media with Refractive-Index Dependent Boundary

    International Nuclear Information System (INIS)

    Sallah, M.; Degheidy, A.R.

    2013-01-01

    Radiative transfer problem for pure-triplet scattering, in participating half-space random medium is proposed. The medium is assumed to be random with binary Markovian mixtures (e.g. radiation transfer in astrophysical contexts where the clouds and clear sky play and two-phase medium) described by Markovian statistics. The specular reflectivity of the boundary is angular-dependent described by the Fresnel's reflection probability function. The problem is solved at first in the deterministic case, and then the solution is averaged using the formalism developed by Levermore and Pomraning, to treat particles transport problems in statistical mixtures. Some physical quantities of interest such as the reflectivity of the boundary, average radiant energy, and average net flux are computed for various values of refractive index of the boundary

  11. Dose-Dependent Effects of the Cimicifuga racemosa Extract Ze 450 in the Treatment of Climacteric Complaints: A Randomized, Placebo-Controlled Study

    Directory of Open Access Journals (Sweden)

    Ruediger Schellenberg

    2012-01-01

    Full Text Available Extracts from Cimicifuga racemosa (CR, synonym Actaea racemosa have shown efficacy in trials in women with menopausal symptoms. Yet, dose dependency remains unclear. Therefore, 180 female outpatients with climacteric complaints were treated for 12 weeks in a randomized, double-blind, placebo-controlled, 3-armed trial (CR extract Ze 450 in 6.5 mg or 13.0 mg, or placebo. Primary outcome was the difference in menopausal symptoms (vasomotor, psychological, and somatic, assessed by the Kupperman Menopausal Index between baseline and week 12. Secondary efficacy variables were patients’ self-assessments of general quality of life (QoL, responder rates, and safety. Compared to placebo, patients receiving Ze 450 showed a significant reduction in the severity of menopausal symptoms in a dose-dependent manner from baseline to endpoint (mean absolute differences 17.0 (95% CI 14.65–19.35 score points, P<0.0001 for 13.0 mg; mean absolute differences 8.47 (95% CI 5.55–11.39 score points, P=0.0003 for 6.5 mg. QoL and responder rates corresponded with the main endpoint. Changes in menopausal symptoms and QoL were inversely correlated. Reported adverse events and clinical laboratory testing did not raise safety concerns. The CR extract Ze 450 is an effective and well-tolerated nonhormonal alternative to hormone treatment for symptom relief in menopausal women.

  12. Randomized random walk on a random walk

    International Nuclear Information System (INIS)

    Lee, P.A.

    1983-06-01

    This paper discusses generalizations of the model introduced by Kehr and Kunter of the random walk of a particle on a one-dimensional chain which in turn has been constructed by a random walk procedure. The superimposed random walk is randomised in time according to the occurrences of a stochastic point process. The probability of finding the particle in a particular position at a certain instant is obtained explicitly in the transform domain. It is found that the asymptotic behaviour for large time of the mean-square displacement of the particle depends critically on the assumed structure of the basic random walk, giving a diffusion-like term for an asymmetric walk or a square root law if the walk is symmetric. Many results are obtained in closed form for the Poisson process case, and these agree with those given previously by Kehr and Kunter. (author)

  13. Reflectance variability of surface coatings reveals characteristic eigenvalue spectra

    Science.gov (United States)

    Medina, José M.; Díaz, José A.; Barros, Rui

    2012-10-01

    We have examined the trial-to-trial variability of the reflectance spectra of surface coatings containing effect pigments. Principal component analysis of reflectances was done at each detection angle separately. A method for classification of principal components is applied based on the eigenvalue spectra. It was found that the eigenvalue spectra follow characteristic power laws and depend on the detection angle. Three different subsets of principal components were examined to separate the relevant spectral features related to the pigments from other noise sources. Reconstruction of the reflectance spectra by taking only the first subset indicated that reflectance variability was higher at near-specular reflection, suggesting a correlation with the trial-to-trial deposition of effect pigments. Reconstruction by using the second subset indicates that variability was higher at short wavelengths. Finally, reconstruction by using only the third subset indicates that reflectance variability was not totally random as a function of the wavelength. The methods employed can be useful in the evaluation of color variability in industrial paint application processes.

  14. Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen

    2013-02-01

    In this paper, the distributed synchronization problem of networks of agent systems with controllers and nonlinearities subject to Bernoulli switchings is investigated. Controllers and adaptive updating laws injected in each vertex of networks depend on the state information of its neighborhood. Three sets of Bernoulli stochastic variables are introduced to describe the occurrence probabilities of distributed adaptive controllers, updating laws and nonlinearities, respectively. By the Lyapunov functions method, we show that the distributed synchronization of networks composed of agent systems with multiple randomly occurring nonlinearities, multiple randomly occurring controllers, and multiple randomly occurring updating laws can be achieved in mean square under certain criteria. The conditions derived in this paper can be solved by semi-definite programming. Moreover, by mathematical analysis, we find that the coupling strength, the probabilities of the Bernoulli stochastic variables, and the form of nonlinearities have great impacts on the convergence speed and the terminal control strength. The synchronization criteria and the observed phenomena are demonstrated by several numerical simulation examples. In addition, the advantage of distributed adaptive controllers over conventional adaptive controllers is illustrated.

  15. Qualitatively Assessing Randomness in SVD Results

    Science.gov (United States)

    Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

    2012-12-01

    Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

  16. Respiratory variability preceding and following sighs: a resetter hypothesis.

    Science.gov (United States)

    Vlemincx, Elke; Van Diest, Ilse; Lehrer, Paul M; Aubert, André E; Van den Bergh, Omer

    2010-04-01

    Respiratory behavior is characterized by complex variability with structured and random components. Assuming that both a lack of variability and too much randomness represent suboptimal breathing regulation, we hypothesized that sighing acts as a resetter inducing structured variability. Spontaneous breathing was measured in healthy persons (N=42) during a 20min period of quiet sitting using the LifeShirt(®) System. Four blocks of 10 breaths with a 50% window overlap were determined before and after spontaneous sighs. Total respiratory variability of minute ventilation was measured using the coefficient of variation and structured (correlated) variability was quantified using autocorrelation. Towards a sigh, total variability gradually increased without concomittant changes in correlated variability, suggesting that randomness increased. After a sigh, correlated variability increased. No changes in variability were found in comparable epochs without intermediate sighs. We conclude that a sigh resets structured respiratory variability, enhancing information processing in the respiratory system. Copyright © 2009 Elsevier B.V. All rights reserved.

  17. Some limit theorems for negatively associated random variables

    Indian Academy of Sciences (India)

    random sampling without replacement, and (i) joint distribution of ranks. ... wide applications in multivariate statistical analysis and system reliability, the ... strong law of large numbers for negatively associated sequences under the case where.

  18. Multiple cyber attacks against a target with observation errors and dependent outcomes: Characterization and optimization

    International Nuclear Information System (INIS)

    Hu, Xiaoxiao; Xu, Maochao; Xu, Shouhuai; Zhao, Peng

    2017-01-01

    In this paper we investigate a cybersecurity model: An attacker can launch multiple attacks against a target with a termination strategy that says that the attacker will stop after observing a number of successful attacks or when the attacker is out of attack resources. However, the attacker's observation of the attack outcomes (i.e., random variables indicating whether the target is compromised or not) has an observation error that is specified by both a false-negative and a false-positive probability. The novelty of the model we study is the accommodation of the dependence between the attack outcomes, because the dependence was assumed away in the literature. In this model, we characterize the monotonicity and bounds of the compromise probability (i.e., the probability that the target is compromised). In addition to extensively showing the impact of dependence on quantities such as compromise probability and attack cost, we give methods for finding the optimal strategy that leads to maximum compromise probability or minimum attack cost. This study highlights that the dependence between random variables cannot be assumed away, because the results will be misleading. - Highlights: • A novel cybersecurity model is proposed to accommodate the dependence among attack outcomes. • The monotonicity and bounds of the compromise probability are studied. • The dependence effect on the compromise probability and attack cost is discussed via simulation. • The optimal strategy that leads to maximum compromise probability or minimum attack cost is presented.

  19. Bell-Boole Inequality: Nonlocality or Probabilistic Incompatibility of Random Variables?

    Directory of Open Access Journals (Sweden)

    Andrei Khrennikov

    2008-03-01

    Full Text Available The main aim of this report is to inform the quantum information community about investigations on the problem of probabilistic compatibility of a family of random variables: a possibility to realize such a family on the basis of a single probability measure (to construct a single Kolmogorov probability space. These investigations were started hundred of years ago by J. Boole (who invented Boolean algebras. The complete solution of the problem was obtained by Soviet mathematician Vorobjev in 60th. Surprisingly probabilists and statisticians obtained inequalities for probabilities and correlations among which one can find the famous Bell’s inequality and its generalizations. Such inequalities appeared simply as constraints for probabilistic compatibility. In this framework one can not see a priori any link to such problems as nonlocality and “death of reality” which are typically linked to Bell’s type inequalities in physical literature. We analyze the difference between positions of mathematicians and quantum physicists. In particular, we found that one of the most reasonable explanations of probabilistic incompatibility is mixing in Bell’s type inequalities statistical data from a number of experiments performed under different experimental contexts.

  20. Rye-Based Evening Meals Favorably Affected Glucose Regulation and Appetite Variables at the Following Breakfast; A Randomized Controlled Study in Healthy Subjects.

    Science.gov (United States)

    Sandberg, Jonna C; Björck, Inger M E; Nilsson, Anne C

    2016-01-01

    Whole grain has shown potential to prevent obesity, cardiovascular disease and type 2 diabetes. Possible mechanism could be related to colonic fermentation of specific indigestible carbohydrates, i.e. dietary fiber (DF). The aim of this study was to investigate effects on cardiometabolic risk factors and appetite regulation the next day when ingesting rye kernel bread rich in DF as an evening meal. Whole grain rye kernel test bread (RKB) or a white wheat flour based bread (reference product, WWB) was provided as late evening meals to healthy young adults in a randomized cross-over design. The test products RKB and WWB were provided in two priming settings: as a single evening meal or as three consecutive evening meals prior to the experimental days. Test variables were measured in the morning, 10.5-13.5 hours after ingestion of RKB or WWB. The postprandial phase was analyzed for measures of glucose metabolism, inflammatory markers, appetite regulating hormones and short chain fatty acids (SCFA) in blood, hydrogen excretion in breath and subjective appetite ratings. With the exception of serum CRP, no significant differences in test variables were observed depending on length of priming (P>0.05). The RKB evening meal increased plasma concentrations of PYY (0-120 min, Pappetite ratings during the whole experimental period (Pappetite sensation could be beneficial in preventing obesity. These effects could possibly be mediated through colonic fermentation. ClinicalTrials.gov NCT02093481.

  1. Employment-Based Abstinence Reinforcement as a Maintenance Intervention for the Treatment of Cocaine Dependence: A Randomized Controlled Trial

    Science.gov (United States)

    DeFulio, Anthony; Donlin, Wendy D.; Wong, Conrad J.; Silverman, Kenneth

    2009-01-01

    Context: Due to the chronic nature of cocaine dependence, long-term maintenance treatments may be required to sustain abstinence. Abstinence reinforcement is among the most effective means of initiating cocaine abstinence. Practical and effective means of maintaining abstinence reinforcement programs over time are needed. Objective: Determine whether employment-based abstinence reinforcement can be an effective long-term maintenance intervention for cocaine dependence. Design: Participants (N=128) were enrolled in a 6-month job skills training and abstinence initiation program. Participants who initiated abstinence, attended regularly, and developed needed job skills during the first six months were hired as operators in a data entry business and randomly assigned to an employment only (Control, n = 24) or abstinence-contingent employment (n = 27) group. Setting: A nonprofit data entry business. Participants: Unemployed welfare recipients who persistently used cocaine while enrolled in methadone treatment in Baltimore. Intervention: Abstinence-contingent employment participants received one year of employment-based contingency management, in which access to employment was contingent on provision drug-free urine samples under routine and then random drug testing. If a participant provided drug-positive urine or failed to provide a mandatory sample, then that participant received a temporary reduction in pay and could not work until urinalysis confirmed recent abstinence. Main Outcome Measure: Cocaine-negative urine samples at monthly assessments across one year of employment. Results: During the one-year of employment, abstinence-contingent employment participants provided significantly more cocaine-negative urine samples than employment only participants (79.3% and 50.7%, respectively; p = 0.004, OR = 3.73, 95% CI = 1.60 – 8.69). Conclusions: Employment-based abstinence reinforcement that includes random drug testing is effective as a long-term maintenance

  2. A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

    Directory of Open Access Journals (Sweden)

    Huixin Tian

    2016-01-01

    Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.

  3. A simplified method for random vibration analysis of structures with random parameters

    International Nuclear Information System (INIS)

    Ghienne, Martin; Blanzé, Claude

    2016-01-01

    Piezoelectric patches with adapted electrical circuits or viscoelastic dissipative materials are two solutions particularly adapted to reduce vibration of light structures. To accurately design these solutions, it is necessary to describe precisely the dynamical behaviour of the structure. It may quickly become computationally intensive to describe robustly this behaviour for a structure with nonlinear phenomena, such as contact or friction for bolted structures, and uncertain variations of its parameters. The aim of this work is to propose a non-intrusive reduced stochastic method to characterize robustly the vibrational response of a structure with random parameters. Our goal is to characterize the eigenspace of linear systems with dynamic properties considered as random variables. This method is based on a separation of random aspects from deterministic aspects and allows us to estimate the first central moments of each random eigenfrequency with a single deterministic finite elements computation. The method is applied to a frame with several Young's moduli modeled as random variables. This example could be expanded to a bolted structure including piezoelectric devices. The method needs to be enhanced when random eigenvalues are closely spaced. An indicator with no additional computational cost is proposed to characterize the ’’proximity” of two random eigenvalues. (paper)

  4. Are glucose levels, glucose variability and autonomic control influenced by inspiratory muscle exercise in patients with type 2 diabetes? Study protocol for a randomized controlled trial.

    Science.gov (United States)

    Schein, Aso; Correa, Aps; Casali, Karina Rabello; Schaan, Beatriz D

    2016-01-20

    Physical exercise reduces glucose levels and glucose variability in patients with type 2 diabetes. Acute inspiratory muscle exercise has been shown to reduce these parameters in a small group of patients with type 2 diabetes, but these results have yet to be confirmed in a well-designed study. The aim of this study is to investigate the effect of acute inspiratory muscle exercise on glucose levels, glucose variability, and cardiovascular autonomic function in patients with type 2 diabetes. This study will use a randomized clinical trial crossover design. A total of 14 subjects will be recruited and randomly allocated to two groups to perform acute inspiratory muscle loading at 2 % of maximal inspiratory pressure (PImax, placebo load) or 60 % of PImax (experimental load). Inspiratory muscle training could be a novel exercise modality to be used to decrease glucose levels and glucose variability. ClinicalTrials.gov NCT02292810 .

  5. Relay model for recruiting alcohol dependent patients in general hospitals--a single-blind pragmatic randomized trial

    DEFF Research Database (Denmark)

    Schwarz, Anne-Sophie; Bilberg, Randi; Bjerregaard, Lene Berit Skov

    2016-01-01

    - The Relay Model. METHOD/DESIGN: The study is a single-blind pragmatic randomized controlled trial including patients admitted to the hospital. The study group (n = 500) will receive an intervention, and the control group (n = 500) will be referred to treatment by usual procedures. All patients complete......://register.clinicaltrials.gov/by identifier: RESCueH_Relay NCT02188043 Project Relay Model for Recruiting Alcohol Dependent Patients in General Hospitals (TRN Registration: 07/09/2014)....

  6. Time-dependence in relativistic collisionless shocks: theory of the variable

    Energy Technology Data Exchange (ETDEWEB)

    Spitkovsky, A

    2004-02-05

    We describe results from time-dependent numerical modeling of the collisionless reverse shock terminating the pulsar wind in the Crab Nebula. We treat the upstream relativistic wind as composed of ions and electron-positron plasma embedded in a toroidal magnetic field, flowing radially outward from the pulsar in a sector around the rotational equator. The relativistic cyclotron instability of the ion gyrational orbit downstream of the leading shock in the electron-positron pairs launches outward propagating magnetosonic waves. Because of the fresh supply of ions crossing the shock, this time-dependent process achieves a limit-cycle, in which the waves are launched with periodicity on the order of the ion Larmor time. Compressions in the magnetic field and pair density associated with these waves, as well as their propagation speed, semi-quantitatively reproduce the behavior of the wisp and ring features described in recent observations obtained using the Hubble Space Telescope and the Chandra X-Ray Observatory. By selecting the parameters of the ion orbits to fit the spatial separation of the wisps, we predict the period of time variability of the wisps that is consistent with the data. When coupled with a mechanism for non-thermal acceleration of the pairs, the compressions in the magnetic field and plasma density associated with the optical wisp structure naturally account for the location of X-ray features in the Crab. We also discuss the origin of the high energy ions and their acceleration in the equatorial current sheet of the pulsar wind.

  7. Bubble CPAP versus CPAP with variable flow in newborns with respiratory distress: a randomized controlled trial.

    Science.gov (United States)

    Yagui, Ana Cristina Zanon; Vale, Luciana Assis Pires Andrade; Haddad, Luciana Branco; Prado, Cristiane; Rossi, Felipe Souza; Deutsch, Alice D Agostini; Rebello, Celso Moura

    2011-01-01

    To evaluate the efficacy and safety of nasal continuous positive airway pressure (NCPAP) using devices with variable flow or bubble continuous positive airway pressure (CPAP) regarding CPAP failure, presence of air leaks, total CPAP and oxygen time, and length of intensive care unit and hospital stay in neonates with moderate respiratory distress (RD) and birth weight (BW) ≥ 1,500 g. Forty newborns requiring NCPAP were randomized into two study groups: variable flow group (VF) and continuous flow group (CF). The study was conducted between October 2008 and April 2010. Demographic data, CPAP failure, presence of air leaks, and total CPAP and oxygen time were recorded. Categorical outcomes were tested using the chi-square test or the Fisher's exact test. Continuous variables were analyzed using the Mann-Whitney test. The level of significance was set at p CPAP failure (21.1 and 20.0% for VF and CF, respectively; p = 1.000), air leak syndrome (10.5 and 5.0%, respectively; p = 0.605), total CPAP time (median: 22.0 h, interquartile range [IQR]: 8.00-31.00 h and median: 22.0 h, IQR: 6.00-32.00 h, respectively; p = 0.822), and total oxygen time (median: 24.00 h, IQR: 7.00-85.00 h and median: 21.00 h, IQR: 9.50-66.75 h, respectively; p = 0.779). In newborns with BW ≥ 1,500 g and moderate RD, the use of continuous flow NCPAP showed the same benefits as the use of variable flow NCPAP.

  8. European Randomized Study of Screening for Prostate Cancer Risk Calculator: External Validation, Variability, and Clinical Significance.

    Science.gov (United States)

    Gómez-Gómez, Enrique; Carrasco-Valiente, Julia; Blanca-Pedregosa, Ana; Barco-Sánchez, Beatriz; Fernandez-Rueda, Jose Luis; Molina-Abril, Helena; Valero-Rosa, Jose; Font-Ugalde, Pilar; Requena-Tapia, Maria José

    2017-04-01

    To externally validate the European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator (RC) and to evaluate its variability between 2 consecutive prostate-specific antigen (PSA) values. We prospectively catalogued 1021 consecutive patients before prostate biopsy for suspicion of prostate cancer (PCa). The risk of PCa and significant PCa (Gleason score ≥7) from 749 patients was calculated according to ERSPC-RC (digital rectal examination-based version 3 of 4) for 2 consecutive PSA tests per patient. The calculators' predictions were analyzed using calibration plots and the area under the receiver operating characteristic curve (area under the curve). Cohen kappa coefficient was used to compare the ability and variability. Of 749 patients, PCa was detected in 251 (33.5%) and significant PCa was detected in 133 (17.8%). Calibration plots showed an acceptable parallelism and similar discrimination ability for both PSA levels with an area under the curve of 0.69 for PCa and 0.74 for significant PCa. The ERSPC showed 226 (30.2%) unnecessary biopsies with the loss of 10 significant PCa. The variability of the RC was 16% for PCa and 20% for significant PCa, and a higher variability was associated with a reduced risk of significant PCa. We can conclude that the performance of the ERSPC-RC in the present cohort shows a high similitude between the 2 PSA levels; however, the RC variability value is associated with a decreased risk of significant PCa. The use of the ERSPC in our cohort detects a high number of unnecessary biopsies. Thus, the incorporation of ERSPC-RC could help the clinical decision to carry out a prostate biopsy. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. A large-scale study of the random variability of a coding sequence: a study on the CFTR gene.

    Science.gov (United States)

    Modiano, Guido; Bombieri, Cristina; Ciminelli, Bianca Maria; Belpinati, Francesca; Giorgi, Silvia; Georges, Marie des; Scotet, Virginie; Pompei, Fiorenza; Ciccacci, Cinzia; Guittard, Caroline; Audrézet, Marie Pierre; Begnini, Angela; Toepfer, Michael; Macek, Milan; Ferec, Claude; Claustres, Mireille; Pignatti, Pier Franco

    2005-02-01

    Coding single nucleotide substitutions (cSNSs) have been studied on hundreds of genes using small samples (n(g) approximately 100-150 genes). In the present investigation, a large random European population sample (average n(g) approximately 1500) was studied for a single gene, the CFTR (Cystic Fibrosis Transmembrane conductance Regulator). The nonsynonymous (NS) substitutions exhibited, in accordance with previous reports, a mean probability of being polymorphic (q > 0.005), much lower than that of the synonymous (S) substitutions, but they showed a similar rate of subpolymorphic (q < 0.005) variability. This indicates that, in autosomal genes that may have harmful recessive alleles (nonduplicated genes with important functions), genetic drift overwhelms selection in the subpolymorphic range of variability, making disadvantageous alleles behave as neutral. These results imply that the majority of the subpolymorphic nonsynonymous alleles of these genes are selectively negative or even pathogenic.

  10. Lower limits for distribution tails of randomly stopped sums

    NARCIS (Netherlands)

    Denisov, D.E.; Korshunov, D.A.; Foss, S.G.

    2008-01-01

    We study lower limits for the ratio $\\overline{F^{*\\tau}}(x)/\\,\\overline F(x)$ of tail distributions, where $F^{*\\tau}$ is a distribution of a sum of a random size $\\tau$ of independent identically distributed random variables having a common distribution $F$, and a random variable $\\tau$ does not

  11. Handling Time-dependent Variables : Antibiotics and Antibiotic Resistance

    NARCIS (Netherlands)

    Munoz-Price, L. Silvia; Frencken, Jos F.; Tarima, Sergey; Bonten, Marc

    2016-01-01

    Elucidating quantitative associations between antibiotic exposure and antibiotic resistance development is important. In the absence of randomized trials, observational studies are the next best alternative to derive such estimates. Yet, as antibiotics are prescribed for varying time periods,

  12. Stable limits for sums of dependent infinite variance random variables

    DEFF Research Database (Denmark)

    Bartkiewicz, Katarzyna; Jakubowski, Adam; Mikosch, Thomas

    2011-01-01

    The aim of this paper is to provide conditions which ensure that the affinely transformed partial sums of a strictly stationary process converge in distribution to an infinite variance stable distribution. Conditions for this convergence to hold are known in the literature. However, most of these...

  13. An integrated supply chain model for new products with imprecise production and supply under scenario dependent fuzzy random demand

    Science.gov (United States)

    Nagar, Lokesh; Dutta, Pankaj; Jain, Karuna

    2014-05-01

    In the present day business scenario, instant changes in market demand, different source of materials and manufacturing technologies force many companies to change their supply chain planning in order to tackle the real-world uncertainty. The purpose of this paper is to develop a multi-objective two-stage stochastic programming supply chain model that incorporates imprecise production rate and supplier capacity under scenario dependent fuzzy random demand associated with new product supply chains. The objectives are to maximise the supply chain profit, achieve desired service level and minimise financial risk. The proposed model allows simultaneous determination of optimum supply chain design, procurement and production quantities across the different plants, and trade-offs between inventory and transportation modes for both inbound and outbound logistics. Analogous to chance constraints, we have used the possibility measure to quantify the demand uncertainties and the model is solved using fuzzy linear programming approach. An illustration is presented to demonstrate the effectiveness of the proposed model. Sensitivity analysis is performed for maximisation of the supply chain profit with respect to different confidence level of service, risk and possibility measure. It is found that when one considers the service level and risk as robustness measure the variability in profit reduces.

  14. Sum of ratios of products forα-μ random variables in wireless multihop relaying and multiple scattering

    KAUST Repository

    Wang, Kezhi; Wang, Tian; Chen, Yunfei; Alouini, Mohamed-Slim

    2014-01-01

    The sum of ratios of products of independent 2642 2642α-μ random variables (RVs) is approximated by using the Generalized Gamma ratio approximation (GGRA) with Gamma ratio approximation (GRA) as a special case. The proposed approximation is used to calculate the outage probability of the equal gain combining (EGC) or maximum ratio combining (MRC) receivers for wireless multihop relaying or multiple scattering systems considering interferences. Numerical results show that the newly derived approximation works very well verified by the simulation, while GRA has a slightly worse performance than GGRA when outage probability is below 0.1 but with a more simplified form.

  15. Sum of ratios of products forα-μ random variables in wireless multihop relaying and multiple scattering

    KAUST Repository

    Wang, Kezhi

    2014-09-01

    The sum of ratios of products of independent 2642 2642α-μ random variables (RVs) is approximated by using the Generalized Gamma ratio approximation (GGRA) with Gamma ratio approximation (GRA) as a special case. The proposed approximation is used to calculate the outage probability of the equal gain combining (EGC) or maximum ratio combining (MRC) receivers for wireless multihop relaying or multiple scattering systems considering interferences. Numerical results show that the newly derived approximation works very well verified by the simulation, while GRA has a slightly worse performance than GGRA when outage probability is below 0.1 but with a more simplified form.

  16. Factor VIIa response to a fat-rich meal does not depend on fatty acid composition: A randomized controlled trial

    NARCIS (Netherlands)

    Mennen, L.; Maat, M. de; Meijer, G.; Zock, P.; Grobbee, D.; Kok, F.; Kluft, C.; Schouten, E.

    1998-01-01

    A fat-rich meal increases activated factor VII (FVIIa), but it is not clear whether this increase depends on the fatty acid composition of the meal. Therefore, we studied the FVIIa response to fat-rich meals with different fatty acid composition in a randomized controlled crossover trial and

  17. Memory effects, two color percolation, and the temperature dependence of Mott variable-range hopping

    Science.gov (United States)

    Agam, Oded; Aleiner, Igor L.

    2014-06-01

    There are three basic processes that determine hopping transport: (a) hopping between normally empty sites (i.e., having exponentially small occupation numbers at equilibrium), (b) hopping between normally occupied sites, and (c) transitions between normally occupied and unoccupied sites. In conventional theories all these processes are considered Markovian and the correlations of occupation numbers of different sites are believed to be small (i.e., not exponential in temperature). We show that, contrary to this belief, memory effects suppress the processes of type (c) and manifest themselves in a subleading exponential temperature dependence of the variable-range hopping conductivity. This temperature dependence originates from the property that sites of type (a) and (b) form two independent resistor networks that are weakly coupled to each other by processes of type (c). This leads to a two-color percolation problem which we solve in the critical region.

  18. Compositions, Random Sums and Continued Random Fractions of Poisson and Fractional Poisson Processes

    Science.gov (United States)

    Orsingher, Enzo; Polito, Federico

    2012-08-01

    In this paper we consider the relation between random sums and compositions of different processes. In particular, for independent Poisson processes N α ( t), N β ( t), t>0, we have that N_{α}(N_{β}(t)) stackrel{d}{=} sum_{j=1}^{N_{β}(t)} Xj, where the X j s are Poisson random variables. We present a series of similar cases, where the outer process is Poisson with different inner processes. We highlight generalisations of these results where the external process is infinitely divisible. A section of the paper concerns compositions of the form N_{α}(tauk^{ν}), ν∈(0,1], where tauk^{ν} is the inverse of the fractional Poisson process, and we show how these compositions can be represented as random sums. Furthermore we study compositions of the form Θ( N( t)), t>0, which can be represented as random products. The last section is devoted to studying continued fractions of Cauchy random variables with a Poisson number of levels. We evaluate the exact distribution and derive the scale parameter in terms of ratios of Fibonacci numbers.

  19. Randomized Trial of a Lifestyle Physical Activity Intervention for Breast Cancer Survivors: Effects on Transtheoretical Model Variables.

    Science.gov (United States)

    Scruggs, Stacie; Mama, Scherezade K; Carmack, Cindy L; Douglas, Tommy; Diamond, Pamela; Basen-Engquist, Karen

    2018-01-01

    This study examined whether a physical activity intervention affects transtheoretical model (TTM) variables that facilitate exercise adoption in breast cancer survivors. Sixty sedentary breast cancer survivors were randomized to a 6-month lifestyle physical activity intervention or standard care. TTM variables that have been shown to facilitate exercise adoption and progress through the stages of change, including self-efficacy, decisional balance, and processes of change, were measured at baseline, 3 months, and 6 months. Differences in TTM variables between groups were tested using repeated measures analysis of variance. The intervention group had significantly higher self-efficacy ( F = 9.55, p = .003) and perceived significantly fewer cons of exercise ( F = 5.416, p = .025) at 3 and 6 months compared with the standard care group. Self-liberation, counterconditioning, and reinforcement management processes of change increased significantly from baseline to 6 months in the intervention group, and self-efficacy and reinforcement management were significantly associated with improvement in stage of change. The stage-based physical activity intervention increased use of select processes of change, improved self-efficacy, decreased perceptions of the cons of exercise, and helped participants advance in stage of change. These results point to the importance of using a theory-based approach in interventions to increase physical activity in cancer survivors.

  20. Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients

    KAUST Repository

    Nobile, Fabio; Tempone, Raul

    2009-01-01

    We consider the problem of numerically approximating statistical moments of the solution of a time- dependent linear parabolic partial differential equation (PDE), whose coefficients and/or forcing terms are spatially correlated random fields. The stochastic coefficients of the PDE are approximated by truncated Karhunen-Loève expansions driven by a finite number of uncorrelated random variables. After approxi- mating the stochastic coefficients, the original stochastic PDE turns into a new deterministic parametric PDE of the same type, the dimension of the parameter set being equal to the number of random variables introduced. After proving that the solution of the parametric PDE problem is analytic with respect to the parameters, we consider global polynomial approximations based on tensor product, total degree or sparse polynomial spaces and constructed by either a Stochastic Galerkin or a Stochastic Collocation approach. We derive convergence rates for the different cases and present numerical results that show how these approaches are a valid alternative to the more traditional Monte Carlo Method for this class of problems. © 2009 John Wiley & Sons, Ltd.

  1. Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients

    KAUST Repository

    Nobile, Fabio

    2009-11-05

    We consider the problem of numerically approximating statistical moments of the solution of a time- dependent linear parabolic partial differential equation (PDE), whose coefficients and/or forcing terms are spatially correlated random fields. The stochastic coefficients of the PDE are approximated by truncated Karhunen-Loève expansions driven by a finite number of uncorrelated random variables. After approxi- mating the stochastic coefficients, the original stochastic PDE turns into a new deterministic parametric PDE of the same type, the dimension of the parameter set being equal to the number of random variables introduced. After proving that the solution of the parametric PDE problem is analytic with respect to the parameters, we consider global polynomial approximations based on tensor product, total degree or sparse polynomial spaces and constructed by either a Stochastic Galerkin or a Stochastic Collocation approach. We derive convergence rates for the different cases and present numerical results that show how these approaches are a valid alternative to the more traditional Monte Carlo Method for this class of problems. © 2009 John Wiley & Sons, Ltd.

  2. Variational Infinite Hidden Conditional Random Fields

    NARCIS (Netherlands)

    Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin

    2015-01-01

    Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of

  3. Effects of a Psychological Intervention in a Primary Health Care Center for Caregivers of Dependent Relatives: A Randomized Trial

    Science.gov (United States)

    Rodriguez-Sanchez, Emiliano; Patino-Alonso, Maria C.; Mora-Simon, Sara; Gomez-Marcos, Manuel A.; Perez-Penaranda, Anibal; Losada-Baltar, Andres; Garcia-Ortiz, Luis

    2013-01-01

    Purpose: To assess, in the context of Primary Health Care (PHC), the effect of a psychological intervention in mental health among caregivers (CGs) of dependent relatives. Design and Methods: Randomized multicenter, controlled clinical trial. The 125 CGs included in the trial were receiving health care in PHC. Inclusion criteria: Identifying…

  4. A Proof-of-Concept Randomized Controlled Study of Gabapentin: Effects on Cannabis Use, Withdrawal and Executive Function Deficits in Cannabis-Dependent Adults

    OpenAIRE

    Mason, Barbara J; Crean, Rebecca; Goodell, Vivian; Light, John M; Quello, Susan; Shadan, Farhad; Buffkins, Kimberly; Kyle, Mark; Adusumalli, Murali; Begovic, Adnan; Rao, Santosh

    2012-01-01

    There are no FDA-approved pharmacotherapies for cannabis dependence. Cannabis is the most widely used illicit drug in the world, and patients seeking treatment for primary cannabis dependence represent 25% of all substance use admissions. We conducted a phase IIa proof-of-concept pilot study to examine the safety and efficacy of a calcium channel/GABA modulating drug, gabapentin, for the treatment of cannabis dependence. A 12-week, randomized, double-blind, placebo-controlled clinical trial w...

  5. How to get rid of W: a latent variables approach to modelling spatially lagged variables

    NARCIS (Netherlands)

    Folmer, H.; Oud, J.

    2008-01-01

    In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

  6. How to get rid of W : a latent variables approach to modelling spatially lagged variables

    NARCIS (Netherlands)

    Folmer, Henk; Oud, Johan

    2008-01-01

    In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

  7. Alcohol-related brief intervention in patients treated for opiate or cocaine dependence: a randomized controlled study

    Directory of Open Access Journals (Sweden)

    Khan Riaz

    2011-08-01

    Full Text Available Abstract Background Despite the importance of heavy drinking and alcohol dependence among patients with opiate and cocaine dependence, few studies have evaluated specific interventions within this group. The aim of the present study was to evaluate the impact of screening with the Alcohol Use Disorders Identification Test (AUDIT and of brief intervention (BI on alcohol use in a sample of patients treated for opioid or cocaine dependence in a specialized outpatient clinic. Methods Adult outpatients treated for opioid or cocaine dependence in Switzerland were screened for excessive alcohol drinking and dependence with the AUDIT. Patients with AUDIT scores that indicated excessive drinking or dependence were randomized into two groups--treatment as usual or treatment as usual together with BI--and assessed at 3 months and 9 months. Results Findings revealed a high rate (44% of problematic alcohol use (excessive drinking and dependence among patients with opiate and cocaine dependence. The number of drinks per week decreased significantly between T0 (inclusion and T3 (month 3. A decrease in average AUDIT scores was observed between T0 and T3 and between T0 and T9 (month 9. No statistically significant difference between treatment groups was observed. Conclusions In a substance abuse specialized setting, screening for alcohol use with the AUDIT, followed by feedback on the score, and use of alcohol BI are both possibly useful strategies to induce changes in problematic alcohol use. Definitive conclusions cannot, however, be drawn from the study because of limitations such as lack of a naturalistic group. An important result of the study is the excellent internal consistency of AUDIT in a population treated for opiate or cocaine dependence.

  8. Central limit theorems for sequences with m(n)-dependent main part

    NARCIS (Netherlands)

    Nieuwenhuis, G.

    1992-01-01

    Let (Xi(n); n ϵ N, 1⩽i⩽h(n)) be a double sequence of random variables with h(n)→∞ as n→∞. Suppose that the sequence can be split into two parts: an m(n)-dependent sequence (Xi,m(n); n ϵ N, 1⩽i⩽h(n)) of main terms and a sequence (Xi,m(n); n ϵ N, 1⩽i⩽h(n)) of residual terms. Here (m(n)) may be

  9. Intervention to improve social and family support for caregivers of dependent patients: ICIAS study protocol.

    Science.gov (United States)

    Rosell-Murphy, Magdalena; Bonet-Simó, Josep M; Baena, Esther; Prieto, Gemma; Bellerino, Eva; Solé, Francesc; Rubio, Montserrat; Krier, Ilona; Torres, Pascuala; Mimoso, Sonia

    2014-03-25

    Despite the existence of formal professional support services, informal support (mainly family members) continues to be the main source of eldercare, especially for those who are dependent or disabled. Professionals on the primary health care are the ideal choice to educate, provide psychological support, and help to mobilize social resources available to the informal caregiver.Controversy remains concerning the efficiency of multiple interventions, taking a holistic approach to both the patient and caregiver, and optimum utilization of the available community resources. .For this reason our goal is to assess whether an intervention designed to improve the social support for caregivers effectively decreases caregivers burden and improves their quality of life. CONTROLled, multicentre, community intervention trial, with patients and their caregivers randomized to the intervention or control group according to their assigned Primary Health Care Team (PHCT). Primary Health Care network (9 PHCTs). Primary informal caregivers of patients receiving home health care from participating PHCTs. Required sample size is 282 caregivers (141 from PHCTs randomized to the intervention group and 141 from PHCTs randomized to the control group. a) PHCT professionals: standardized training to implement caregivers intervention. b) Caregivers: 1 individualized counselling session, 1 family session, and 4 educational group sessions conducted by participating PHCT professionals; in addition to usual home health care visits, periodic telephone follow-up contact and unlimited telephone support. Caregivers and dependent patients: usual home health care, consisting of bimonthly scheduled visits, follow-up as needed, and additional attention upon request.Data analysisDependent variables: Caregiver burden (short-form Zarit test), caregivers' social support (Medical Outcomes Study), and caregivers' reported quality of life (SF-12)INDEPENDENT VARIABLES: a) Caregiver: sociodemographic data

  10. Asymptotic distribution of products of sums of independent random ...

    Indian Academy of Sciences (India)

    integrable random variables (r.v.) are asymptotically log-normal. This fact ... the product of the partial sums of i.i.d. positive random variables as follows. .... Now define ..... by Henan Province Foundation and Frontier Technology Research Plan.

  11. A Geometrical Framework for Covariance Matrices of Continuous and Categorical Variables

    Science.gov (United States)

    Vernizzi, Graziano; Nakai, Miki

    2015-01-01

    It is well known that a categorical random variable can be represented geometrically by a simplex. Accordingly, several measures of association between categorical variables have been proposed and discussed in the literature. Moreover, the standard definitions of covariance and correlation coefficient for continuous random variables have been…

  12. BWIP-RANDOM-SAMPLING, Random Sample Generation for Nuclear Waste Disposal

    International Nuclear Information System (INIS)

    Sagar, B.

    1989-01-01

    1 - Description of program or function: Random samples for different distribution types are generated. Distribution types as required for performance assessment modeling of geologic nuclear waste disposal are provided. These are: - Uniform, - Log-uniform (base 10 or natural), - Normal, - Lognormal (base 10 or natural), - Exponential, - Bernoulli, - User defined continuous distribution. 2 - Method of solution: A linear congruential generator is used for uniform random numbers. A set of functions is used to transform the uniform distribution to the other distributions. Stratified, rather than random, sampling can be chosen. Truncated limits can be specified on many distributions, whose usual definition has an infinite support. 3 - Restrictions on the complexity of the problem: Generation of correlated random variables is not included

  13. Mycorrhizal dependency of laurel (Ocotea sp.)

    International Nuclear Information System (INIS)

    Sierra-Escobar, Jorge A; Castro Restrepo, Dagoberto; Osorio Vega, Walter

    2009-01-01

    A greenhouse experiment was carried out to determine the mycorrhizal dependency of laurel (>Ocotea sp.). In order to do this, a completely randomized experimental design was used, with six treatments in a factorial array of 3 x 2 and five repetitions. The treatments involved a combination of three Phosphorus (P) levels in soil solution (0.002, 0.02 and 0.2 mg L-1) and two levels of mycorrhizal inoculation, either inoculated or non-inoculated with Glomus aggregatum Schenck and Smith. The leaf P content as a function of time was used as an output variable. Shoot dry matter, shoot P content, mycorrhizal colonization of roots, and mycorrhizal dependence were measured at harvest. The results indicated that the leaf P content increased significantly when using the mycorrhizal inoculation in laurel at P level 0.2 mg L -1, but not in the other P levels, on some of the sampling days. Shoot dry weight and total plant P content did not increase at all levels of soil available P. Mycorrhizal dependency of laurel reached 28%, which allows this species to be classified as moderately dependent on mycorrhiza.

  14. Capturing heterogeneity in gene expression studies by surrogate variable analysis.

    Directory of Open Access Journals (Sweden)

    Jeffrey T Leek

    2007-09-01

    Full Text Available It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on gene expression levels. In addition to the measured variable(s of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of gene expression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.

  15. Random perturbations of arterial blood pressure for the assessment of dynamic cerebral autoregulation

    International Nuclear Information System (INIS)

    Katsogridakis, Emmanuel; Panerai, Ronney B; Bush, Glen; Fan, Lingke; Birch, Anthony A; Simpson, David M; Allen, Robert; Potter, John F

    2012-01-01

    The assessment of cerebral autoregulation (CA) relies mostly on methods that modulate arterial blood pressure (ABP). Despite advances, the gold standard of assessment remains elusive and clinical practicality is limited. We investigate a novel approach of assessing CA, consisting of the intermittent application of thigh cuffs using square wave sequences. Our aim was to increase ABP variability whilst minimizing volunteer discomfort, thus improving assessment acceptability. Two random square wave sequences and two maximum pressure settings (80 and 150 mmHg) were used, corresponding to four manoeuvres that were conducted in random order after a baseline recording. The intermittent application of thigh cuffs resulted in an amplitude dependent increase in ABP (p = 0.001) and cerebral blood flow velocity (CBFV) variability (p = 0.026) compared to baseline. No statistically significant differences in mean heart rate or heart rate variability were observed (p = 0.108 and p = 0.350, respectively), suggesting that no significant sympathetic response was elicited. No significant differences in the CBFV step response were observed, suggesting no distortion of autoregulatory parameters resulted from the use of thigh cuffs. We conclude that pseudorandom binary sequences are an effective and safe alternative for increasing ABP variability. This new approach shows great promise as a tool for the robust assessment of CA. (paper)

  16. The randomly renewed general item and the randomly inspected item with exponential life distribution

    International Nuclear Information System (INIS)

    Schneeweiss, W.G.

    1979-01-01

    For a randomly renewed item the probability distributions of the time to failure and of the duration of down time and the expectations of these random variables are determined. Moreover, it is shown that the same theory applies to randomly checked items with exponential probability distribution of life such as electronic items. The case of periodic renewals is treated as an example. (orig.) [de

  17. Atomoxetine Does Not Alter Cocaine Use in Cocaine Dependent Individuals: A Double Blind Randomized Trial

    Science.gov (United States)

    Middleton, Lisa S.; Wong, Conrad J.; Nuzzo, Paul A.; Campbell, Charles L.; Rush, Craig R.; Lofwall, Michelle R.

    2016-01-01

    Background Cocaine abuse continues to be a significant public health problem associated with morbidity and mortality. To date, no pharmacotherapeutic approach has proven effective for treating cocaine use disorders. Preclinical and clinical evidence suggests that noradrenergic activity may play a role in mediating some effects of cocaine and may be a rational target for treatment. Methods This double blind, placebo-controlled randomized, parallel group, 12-week outpatient clinical trial enrolled cocaine dependent individuals seeking treatment to examine the potential efficacy of the selective norepinephrine reuptake inhibitor, atomoxetine (80 mg/day; p.o.; n=25), compared to placebo (n=25). Subjects were initially stratified on cocaine use (atomoxetine and placebo groups (X2=0.2, p=.66; OR=0.89 [95% CI 0.41 – 1.74). Atomoxetine was generally well tolerated in this population. Conclusions These data provide no support for the utility of atomoxetine in the treatment of cocaine dependence. PMID:23200303

  18. Age dependant somatometric and cephalometric variables among ...

    African Journals Online (AJOL)

    Background: The process of growth passes through stages of developmental processes. This stage is the age. Age is known to affect many parameters in the body and this includes somatometric and cephalometric variables. Methods: The study was conducted with a total number of 409 students of university of Jos, ...

  19. The effects of variable practice on locomotor adaptation to a novel asymmetric gait.

    Science.gov (United States)

    Hinkel-Lipsker, Jacob W; Hahn, Michael E

    2017-09-01

    Very little is known about the effects of specific practice on motor learning of predictive balance control during novel bipedal gait. This information could provide an insight into how the direction and magnitude of predictive errors during acquisition of a novel gait task influence transfer of balance control, as well as yield a practice protocol for the restoration of balance for those with locomotor impairments. This study examined the effect of a variable practice paradigm on transfer of a novel asymmetric gait pattern in able-bodied individuals. Using a split-belt treadmill, one limb was driven at a constant velocity (constant limb) and the other underwent specific changes in velocity (variable limb) during practice according to one of three prescribed practice paradigms: serial, where the variable limb velocity increased linearly; random blocked, where variable limb underwent random belt velocity changes every 20 strides; and random practice, where the variable limb underwent random step-to-step changes in velocity. Random practice showed the highest balance control variability during acquisition compared to serial and random blocked practice which demonstrated the best transfer of balance control on one transfer test. Both random and random blocked practices showed significantly less balance control variability during a second transfer test compared to serial practice. These results indicate that random blocked practice may be best for generalizability of balance control while learning a novel gait, perhaps, indicating that individuals who underwent this practice paradigm were able to find the most optimal balance control solution during practice.

  20. Soil variability in engineering applications

    Science.gov (United States)

    Vessia, Giovanna

    2014-05-01

    Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random

  1. Time-dependent Gross-Pitaevskii equation for composite bosons as the strong-coupling limit of the fermionic broken-symmetry random-phase approximation

    International Nuclear Information System (INIS)

    Strinati, G.C.; Pieri, P.

    2004-01-01

    The linear response to a space- and time-dependent external disturbance of a system of dilute condensed composite bosons at zero temperature, as obtained from the linearized version of the time-dependent Gross-Pitaevskii equation, is shown to result also from the strong-coupling limit of the time-dependent BCS (or broken-symmetry random-phase) approximation for the constituent fermions subject to the same external disturbance. In this way, it is possible to connect excited-state properties of the bosonic and fermionic systems by placing the Gross-Pitaevskii equation in perspective with the corresponding fermionic approximations

  2. Protecting chips against hold time violations due to variability

    CERN Document Server

    Neuberger, Gustavo; Reis, Ricardo

    2013-01-01

    With the development of Very-Deep Sub-Micron technologies, process variability is becoming increasingly important and is a very important issue in the design of complex circuits. Process variability is the statistical variation of process parameters, meaning that these parameters do not have always the same value, but become a random variable, with a given mean value and standard deviation. This effect can lead to several issues in digital circuit design.The logical consequence of this parameter variation is that circuit characteristics, as delay and power, also become random variables. Becaus

  3. A combinatorial and probabilistic study of initial and end heights of descents in samples of geometrically distributed random variables and in permutations

    Directory of Open Access Journals (Sweden)

    Helmut Prodinger

    2007-01-01

    Full Text Available In words, generated by independent geometrically distributed random variables, we study the l th descent, which is, roughly speaking, the l th occurrence of a neighbouring pair ab with a>b. The value a is called the initial height, and b the end height. We study these two random variables (and some similar ones by combinatorial and probabilistic tools. We find in all instances a generating function Ψ(v,u, where the coefficient of v j u i refers to the j th descent (ascent, and i to the initial (end height. From this, various conclusions can be drawn, in particular expected values. In the probabilistic part, a Markov chain model is used, which allows to get explicit expressions for the heights of the second descent. In principle, one could go further, but the complexity of the results forbids it. This is extended to permutations of a large number of elements. Methods from q-analysis are used to simplify the expressions. This is the reason that we confine ourselves to the geometric distribution only. For general discrete distributions, no such tools are available.

  4. Addition of Granulocyte/Monocyte Apheresis to Oral Prednisone for Steroid-dependent Ulcerative Colitis: A Randomized Multicentre Clinical Trial.

    Science.gov (United States)

    Domènech, Eugeni; Panés, Julián; Hinojosa, Joaquín; Annese, Vito; Magro, Fernando; Sturniolo, Giacomo Carlo; Bossa, Fabrizio; Fernández, Francisco; González-Conde, Benito; García-Sánchez, Valle; Dignass, Axel; Herrera, José Manuel; Cabriada, José Luis; Guardiola, Jordi; Vecchi, Maurizio; Portela, Francisco; Ginard, Daniel

    2018-05-25

    Steroid-dependency occurs in up to 30% of patients with ulcerative colitis [UC]. In this setting, few drugs have demonstrated efficacy in inducing steroid-free remission. The aim of this study was to evaluate the efficacy and safety of adding granulocyte/monocyte apheresis [GMA] to oral prednisone in patients with steroid-dependent UC. This was a randomized, multicentre, open trial comparing 7 weekly sessions of GMA plus oral prednisone [40 mg/day and tapering] with prednisone alone, in patients with active, steroid-dependent UC [Mayo score 4-10 and inability to withdraw corticosteroids in 3 months or relapse within the first 3 months after discontinuation]. Patients were stratified by concomitant use of thiopurines at inclusion. A 9-week tapering schedule of prednisone was pre-established in both study groups. The primary endpoint was steroid-free remission [defined as a total Mayo score ≤2, with no subscore >1] at Week 24, with no re-introduction of corticosteroids. In all 123 patients were included [63 GMA group, 62 prednisone alone]. In the intention-to-treat analysis, steroid-free remission at Week 24 was achieved in 13% (95% confidence interval [CI] 6-24) in the GMA group and 7% [95% CI 2-16] in the control group [p = 0.11]. In the GMA group, time to relapse was significantly longer (hazard ratio [HR] 1.7 [1.16-2.48], P = 0.005) and steroid-related adverse events were significantly lower [6% vs 20%, P < 0.05]. In a randomized trial, the addition of 7 weekly sessions of GMA to a conventional course of oral prednisone did not increase the proportion of steroid-free remissions in patients with active steroid-dependent UC, though it delayed clinical relapse.

  5. Effects of cue-exposure treatment on neural cue reactivity in alcohol dependence: a randomized trial.

    Science.gov (United States)

    Vollstädt-Klein, Sabine; Loeber, Sabine; Kirsch, Martina; Bach, Patrick; Richter, Anne; Bühler, Mira; von der Goltz, Christoph; Hermann, Derik; Mann, Karl; Kiefer, Falk

    2011-06-01

    In alcohol-dependent patients, alcohol-associated cues elicit brain activation in mesocorticolimbic networks involved in relapse mechanisms. Cue-exposure based extinction training (CET) has been shown to be efficacious in the treatment of alcoholism; however, it has remained unexplored whether CET mediates its therapeutic effects via changes of activity in mesolimbic networks in response to alcohol cues. In this study, we assessed CET treatment effects on cue-induced responses using functional magnetic resonance imaging (fMRI). In a randomized controlled trial, abstinent alcohol-dependent patients were randomly assigned to a CET group (n = 15) or a control group (n = 15). All patients underwent an extended detoxification treatment comprising medically supervised detoxification, health education, and supportive therapy. The CET patients additionally received nine CET sessions over 3 weeks, exposing the patient to his/her preferred alcoholic beverage. Cue-induced fMRI activation to alcohol cues was measured at pretreatment and posttreatment. Compared with pretreatment, fMRI cue-reactivity reduction was greater in the CET relative to the control group, especially in the anterior cingulate gyrus and the insula, as well as limbic and frontal regions. Before treatment, increased cue-induced fMRI activation was found in limbic and reward-related brain regions and in visual areas. After treatment, the CET group showed less activation than the control group in the left ventral striatum. The study provides first evidence that an exposure-based psychotherapeutic intervention in the treatment of alcoholism impacts on brain areas relevant for addiction memory and attentional focus to alcohol-associated cues and affects mesocorticolimbic reward pathways suggested to be pathophysiologically involved in addiction. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Varenicline for treatment of alcohol dependence: a randomized, placebo-controlled trial.

    Science.gov (United States)

    de Bejczy, Andrea; Löf, Elin; Walther, Lisa; Guterstam, Joar; Hammarberg, Anders; Asanovska, Gulber; Franck, Johan; Isaksson, Anders; Söderpalm, Bo

    2015-11-01

    using PEth as outcome variable, together with a nonsymmetric bias associated with self-reported data, strongly argue for using the specific biomarker PEth in studies of treatments of alcohol dependence. Copyright © 2015 by the Research Society on Alcoholism.

  7. Maintaining Treatment Fidelity of Mindfulness-Based Relapse Prevention Intervention for Alcohol Dependence: A Randomized Controlled Trial Experience

    Directory of Open Access Journals (Sweden)

    Aleksandra E. Zgierska

    2017-01-01

    Full Text Available Background. Treatment fidelity is essential to methodological rigor of clinical trials evaluating behavioral interventions such as Mindfulness Meditation (MM. However, procedures for monitoring and maintenance of treatment fidelity are inconsistently applied, limiting the strength of such research. Objective. To describe the implementation and findings related to fidelity monitoring of the Mindfulness-Based Relapse Prevention for Alcohol Dependence (MBRP-A intervention in a 26-week randomized controlled trial. Methods. 123 alcohol dependent adults were randomly assigned to MM (MBRP-A and home practice, adjunctive to usual care; N=64 or control (usual care alone; N=59. Treatment fidelity assessment strategies recommended by the National Institutes of Health Behavior Change Consortium for study/intervention design, therapist training, intervention delivery, and treatment receipt and enactment were applied. Results. Ten 8-session interventions were delivered. Therapist adherence and competence, assessed using the modified MBRP Adherence and Competence Scale, were high. Among the MM group participants, 46 attended ≥4 sessions; over 90% reported at-home MM practice at 8 weeks and 72% at 26 weeks. They also reported satisfaction with and usefulness of MM for maintaining sobriety. No adverse events were reported. Conclusions. A systematic approach to assessment of treatment fidelity in behavioral clinical trials allows determination of the degree of consistency between intended and actual delivery and receipt of intervention.

  8. Precise lim sup behavior of probabilities of large deviations for sums of i.i.d. random variables

    Directory of Open Access Journals (Sweden)

    Andrew Rosalsky

    2004-12-01

    Full Text Available Let {X,Xn;n≥1} be a sequence of real-valued i.i.d. random variables and let Sn=∑i=1nXi, n≥1. In this paper, we study the probabilities of large deviations of the form P(Sn>tn1/p, P(Sntn1/p, where t>0 and 0x1/p/ϕ(x=1, then for every t>0, limsupn→∞P(|Sn|>tn1/p/(nϕ(n=tpα.

  9. Estimations of natural variability between satellite measurements of trace species concentrations

    Science.gov (United States)

    Sheese, P.; Walker, K. A.; Boone, C. D.; Degenstein, D. A.; Kolonjari, F.; Plummer, D. A.; von Clarmann, T.

    2017-12-01

    In order to validate satellite measurements of atmospheric states, it is necessary to understand the range of random and systematic errors inherent in the measurements. On occasions where the measurements do not agree within those errors, a common "go-to" explanation is that the unexplained difference can be chalked up to "natural variability". However, the expected natural variability is often left ambiguous and rarely quantified. This study will look to quantify the expected natural variability of both O3 and NO2 between two satellite instruments: ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and Infrared Imaging System). By sampling the CMAM30 (30-year specified dynamics simulation of the Canadian Middle Atmosphere Model) climate chemistry model throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements at varying coincidence criteria, height-dependent expected values of O3 and NO2 variability will be estimated and reported on. The results could also be used to better optimize the coincidence criteria used in satellite measurement validation studies.

  10. Dynamic Output Feedback Control for Nonlinear Networked Control Systems with Random Packet Dropout and Random Delay

    Directory of Open Access Journals (Sweden)

    Shuiqing Yu

    2013-01-01

    Full Text Available This paper investigates the dynamic output feedback control for nonlinear networked control systems with both random packet dropout and random delay. Random packet dropout and random delay are modeled as two independent random variables. An observer-based dynamic output feedback controller is designed based upon the Lyapunov theory. The quantitative relationship of the dropout rate, transition probability matrix, and nonlinear level is derived by solving a set of linear matrix inequalities. Finally, an example is presented to illustrate the effectiveness of the proposed method.

  11. Security of BB84 with weak randomness and imperfect qubit encoding

    Science.gov (United States)

    Zhao, Liang-Yuan; Yin, Zhen-Qiang; Li, Hong-Wei; Chen, Wei; Fang, Xi; Han, Zheng-Fu; Huang, Wei

    2018-03-01

    The main threats for the well-known Bennett-Brassard 1984 (BB84) practical quantum key distribution (QKD) systems are that its encoding is inaccurate and measurement device may be vulnerable to particular attacks. Thus, a general physical model or security proof to tackle these loopholes simultaneously and quantitatively is highly desired. Here we give a framework on the security of BB84 when imperfect qubit encoding and vulnerability of measurement device are both considered. In our analysis, the potential attacks to measurement device are generalized by the recently proposed weak randomness model which assumes the input random numbers are partially biased depending on a hidden variable planted by an eavesdropper. And the inevitable encoding inaccuracy is also introduced here. From a fundamental view, our work reveals the potential information leakage due to encoding inaccuracy and weak randomness input. For applications, our result can be viewed as a useful tool to quantitatively evaluate the security of a practical QKD system.

  12. Random Decrement

    DEFF Research Database (Denmark)

    Asmussen, J.C.; Ibrahim, S.R.; Brincker, Rune

    Abstraet Thispaper demansirates how to use the Random Decrement (RD) technique for identification o flinear structures subjected to ambient excitation. The theory behind the technique will be presented and guidelines how to choose the different variables will be given. This is done by introducing...

  13. Solute transport modelling with the variable temporally dependent ...

    Indian Academy of Sciences (India)

    Pintu Das

    2018-02-07

    Feb 7, 2018 ... in a finite domain with time-dependent sources and dis- tance-dependent dispersivities. Also, existing ... solute transport in multi-layered porous media using gen- eralized integral transform technique with .... methods for solving the fractional reaction-–sub-diffusion equation. To solve numerically the Eqs.

  14. What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

    Science.gov (United States)

    Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

    2015-07-24

    Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

  15. Correlates of blood pressure in young insulin-dependent diabetics and their families.

    Science.gov (United States)

    Tarn, A C; Thomas, J M; Drury, P L

    1990-09-01

    We compared the correlates of blood pressure in 163 young patients with insulin-dependent diabetes and in 232 of their non-diabetic siblings. A single observer recorded blood pressure in all subjects, plus all their available parents, using a standardized technique. Other variables recorded included age, weight, height, presence of diabetes and urinary albumin. The major factors accounting for over 50% of the variance of systolic blood pressure (SBP) in both groups were age, weight, paternal SBP and sex. In addition, in the diabetic group the logarithm of the random urinary albumin concentration was a significant explanatory variable. For diastolic blood pressure (DBP) approximately 16% of the variance was explained by age, weight and maternal DBP. Parental blood pressure was an important determinant of blood pressure in both the diabetic and non-diabetic sibling groups. The similarity of the correlates of blood pressure in the two groups suggests that the determinants of blood pressure in young insulin-dependent diabetic patients and in the general population are similar.

  16. Risk of dependence associated with health, social support, and lifestyle.

    Science.gov (United States)

    Alcañiz, Manuela; Brugulat, Pilar; Guillén, Montserrat; Medina-Bustos, Antonia; Mompart-Penina, Anna; Solé-Auró, Aïda

    2015-01-01

    OBJECTIVE To analyze the prevalence of individuals at risk of dependence and its associated factors. METHODS The study was based on data from the Catalan Health Survey, Spain conducted in 2010 and 2011. Logistic regression models from a random sample of 3,842 individuals aged ≥ 15 years were used to classify individuals according to the state of their personal autonomy. Predictive models were proposed to identify indicators that helped distinguish dependent individuals from those at risk of dependence. Variables on health status, social support, and lifestyles were considered. RESULTS We found that 18.6% of the population presented a risk of dependence, especially after age 65. Compared with this group, individuals who reported dependence (11.0%) had difficulties performing activities of daily living and had to receive support to perform them. Habits such as smoking, excessive alcohol consumption, and being sedentary were associated with a higher probability of dependence, particularly for women. CONCLUSIONS Difficulties in carrying out activities of daily living precede the onset of dependence. Preserving personal autonomy and function without receiving support appear to be a preventive factor. Adopting an active and healthy lifestyle helps reduce the risk of dependence.

  17. Random Decrement

    DEFF Research Database (Denmark)

    Asmussen, J. C.; Ibrahim, S. R.; Brincker, Rune

    This paper demonstrates how to use the Random Decrement (RD) technique for identification of linear structures subjected to ambient excitation. The theory behind the technique will be presented and guidelines how to choose the different variables will be given. This is done by introducing a new...

  18. Random Decrement

    DEFF Research Database (Denmark)

    Asmussen, J. C.; Ibrahim, R.; Brincker, Rune

    1998-01-01

    This paper demonstrates how to use the Random Decrement (RD) technique for identification of linear structures subjected to ambient excitation. The theory behind the technique will be presented and guidelines how to choose the different variables will be given. This is done by introducing a new...

  19. Frequency-dependent hopping conductivity in a static electric field in a random one-dimensional lattice

    International Nuclear Information System (INIS)

    Lyo, S.K.

    1986-01-01

    The frequency-dependent electrical conductivity is studied in a nearest-neighbor-hopping linear lattice with disordered site energies and barrier heights in the presence of a uniform static electric field, allowing for detailed balance between random rates. Exact expressions are obtained for the conductivity for both high and low frequencies. The results reduce to those obtained by previous authors in the absence of site-energy disorder. However, the latter is found to alter the character of the frequency dependence of the conductivity significantly at low frequencies. In this case the conductivity is expanded as sigma(ω) = sigma 0 +isigma 1 ω-sigma 2 ω 2 -isigma 3 ω 3 +.... We find that sigma 1 is nonvanishing only if both site energies and barrier heights are disordered and that sigma 2 is positive when the fluctuations in site energies are small compared with the thermal energy but becomes negative in the opposite regime. The ac response is found to vanish [i.e., sigma(ω) = 0 for ωnot =0] in the absence of disorder in barrier heights

  20. Effects of sapropterin on endothelium-dependent vasodilation in patients with CADASIL: a randomized controlled trial.

    Science.gov (United States)

    De Maria, Renata; Campolo, Jonica; Frontali, Marina; Taroni, Franco; Federico, Antonio; Inzitari, Domenico; Tavani, Alessandra; Romano, Silvia; Puca, Emanuele; Orzi, Francesco; Francia, Ada; Mariotti, Caterina; Tomasello, Chiara; Dotti, Maria Teresa; Stromillo, Maria Laura; Pantoni, Leonardo; Pescini, Francesca; Valenti, Raffaella; Pelucchi, Claudio; Parolini, Marina; Parodi, Oberdan

    2014-10-01

    Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a rare autosomal dominant disorder caused by NOTCH3 mutations, is characterized by vascular smooth muscle and endothelial cells abnormalities, altered vasoreactivity, and recurrent lacunar infarcts. Vasomotor function may represent a key factor for disease progression. Tetrahydrobiopterin, essential cofactor for nitric oxide synthesis in endothelial cells, ameliorates endothelial function. We assessed whether supplementation with sapropterin, a synthetic tetrahydrobiopterin analog, improves endothelium-dependent vasodilation in CADASIL patients. In a 24-month, multicenter randomized, double-blind, placebo-controlled trial, CADASIL patients aged 30 to 65 years were randomly assigned to receive placebo or sapropterin 200 to 400 mg BID. The primary end point was change in the reactive hyperemia index by peripheral arterial tonometry at 24 months. We also assessed the safety and tolerability of sapropterin. Analysis was done by intention-to-treat. The intention-to-treat population included 61 patients. We found no significant difference between sapropterin (n=32) and placebo (n=29) in the primary end point (mean difference in reactive hyperemia index by peripheral arterial tonometry changes 0.19 [95% confidence interval, -0.18, 0.56]). Reactive hyperemia index by peripheral arterial tonometry increased after 24 months in 37% of patients on sapropterin and in 28% on placebo; however, after adjustment for age, sex, and clinical characteristics, improvement was not associated with treatment arm. The proportion of patients with adverse events was similar on sapropterin and on placebo (50% versus 48.3%); serious adverse events occurred in 6.3% versus 13.8%, respectively. Sapropterin was safe and well-tolerated at the average dose of 5 mg/kg/day, but did not affect endothelium-dependent vasodilation in CADASIL patients. https://www.clinicaltrialsregister.eu. Unique

  1. The Attentional Dependence of Emotion Cognition is Variable with the Competing Task

    Directory of Open Access Journals (Sweden)

    Cheng Chen

    2016-11-01

    Full Text Available The relationship between emotion and attention has fascinated researchers for decades. Many previous studies have used eye-tracking, ERP, MEG and fMRI to explore this issue but have reached different conclusions: some researchers hold that emotion cognition is an automatic process and independent of attention, while some others believed that emotion cognition is modulated by attentional resources and is a type of controlled processing. The present research aimed to investigate this controversy, and we hypothesized that the attentional dependence of emotion cognition is variable with the competing task. Eye-tracking technology and a dual-task paradigm were adopted, and subjects’ attention was manipulated to fixate at the central task to investigate whether subjects could detect the emotional faces presented in the peripheral area with a decrease or near-absence of attention. The results revealed that when the peripheral task was emotional face discrimination but the central attention-demanding task was different, subjects performed well in the peripheral task, which means that emotional information can be processed in parallel with other stimuli, and there may be a specific channel in the human brain for processing emotional information. However, when the central and peripheral tasks were both emotional face discrimination, subjects could not perform well in the peripheral task, indicating that the processing of emotional information required attentional resources and that it is a type of controlled processing. Therefore, we concluded that the attentional dependence of emotion cognition varied with the competing task.

  2. The Ghent Psychotherapy Study (GPS) on the differential efficacy of supportive-expressive and cognitive behavioral interventions in dependent and self-critical depressive patients: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Meganck, Reitske; Desmet, Mattias; Bockting, Claudi; Inslegers, Ruth; Truijens, Femke; De Smet, Melissa; De Geest, Rosa; Van Nieuwenhove, Kimberly; Hennissen, Vicky; Hermans, Goedele; Loeys, Tom; Norman, Ufuoma Angelica; Baeken, Chris; Vanheule, Stijn

    2017-03-14

    Major depressive disorder is a leading cause of disease burden worldwide, indicating the importance of effective therapies. Outcome studies have shown overall efficacy of different types of psychotherapy across groups, yet large variability within groups. Although patient characteristics are considered crucial in understanding outcome, they have received limited research attention. This trial aims at investigating the interaction between therapeutic approach (pre-structured versus explorative) and the personality style of patients (dependent versus self-critical), which is considered a core underlying dimension of depressive pathology. This study is a pragmatic stratified (dependent and self-critical patients) parallel trial with equal randomization (allocation 1:1) conducted in Flanders, Belgium. One hundred and four patients will be recruited and randomized to either 16-20 sessions of cognitive behavioral therapy for depression (pre-structured approach) or 16-20 sessions of short-term psychodynamic psychotherapy for depression (explorative approach) conducted by trained psychotherapists in private practices. The primary outcome is the severity of depression as measured by the Hamilton Rating Scale for Depression at completion of therapy. Secondary outcome measures include self-reported depressive and other symptoms, interpersonal functioning, idiosyncratic complaints, and the presence of the diagnosis of depression. Additional measures include biological measures, narrative material (sessions, interviews), and health care costs. This trial presents the test of an often-described, yet hardly investigated interaction between important personality dimensions and therapeutic approach in the treatment of depression. Results could inform therapists on how to match psychotherapeutic treatments to specific personality characteristics of their patients. Isrctn.com, ISRCTN17130982 . Registered on 2 February 2015.

  3. Nasal Jet-CPAP (variable flow) versus Bubble-CPAP in preterm infants with respiratory distress: an open label, randomized controlled trial.

    Science.gov (United States)

    Bhatti, A; Khan, J; Murki, S; Sundaram, V; Saini, S S; Kumar, P

    2015-11-01

    To compare the failure rates between Jet continuous positive airway pressure device (J-CPAP-variable flow) and Bubble continuous positive airway device (B-CPAP) in preterm infants with respiratory distress. Preterm newborns CPAP (a variable flow device) or B-CPAP (continuous flow device). A standardized protocol was followed for titration, weaning and removal of CPAP. Pressure was monitored close to the nares in both the devices every 6 hours and settings were adjusted to provide desired CPAP. The primary outcome was CPAP failure rate within 72 h of life. Secondary outcomes were CPAP failure within 7 days of life, need for surfactant post-randomization, time to CPAP failure, duration of CPAP and complications of prematurity. An intention to treat analysis was done. One-hundred seventy neonates were randomized, 80 to J-CPAP and 90 to B-CPAP. CPAP failure rates within 72 h were similar in infants who received J-CPAP and in those who received B-CPAP (29 versus 21%; relative risks 1.4 (0.8 to 2.3), P=0.25). Mean (95% confidence intervals) time to CPAP failure was 59 h (54 to 64) in the Jet CPAP group in comparison with 65 h (62 to 68) in the Bubble CPAP group (log rank P=0.19). All other secondary outcomes were similar between the two groups. In preterm infants with respiratory distress starting within 6 h of life, CPAP failure rates were similar with Jet CPAP and Bubble CPAP.

  4. Random phenomena; Phenomenes aleatoires

    Energy Technology Data Exchange (ETDEWEB)

    Bonnet, G. [Commissariat a l' energie atomique et aux energies alternatives - CEA, C.E.N.G., Service d' Electronique, Section d' Electronique, Grenoble (France)

    1963-07-01

    This document gathers a set of conferences presented in 1962. A first one proposes a mathematical introduction to the analysis of random phenomena. The second one presents an axiomatic of probability calculation. The third one proposes an overview of one-dimensional random variables. The fourth one addresses random pairs, and presents basic theorems regarding the algebra of mathematical expectations. The fifth conference discusses some probability laws: binomial distribution, the Poisson distribution, and the Laplace-Gauss distribution. The last one deals with the issues of stochastic convergence and asymptotic distributions.

  5. Dependent failures of diesel generators

    International Nuclear Information System (INIS)

    Mankamo, T.; Pulkkinen, U.

    1982-01-01

    This survey of dependent failures (common-cause failures) is based on the data of diesel generator failures in U. S. nuclear power plants as reported in Licensee Event Reports. Failures were classified into random and potentially dependent failures. All failures due to design errors, manufacturing or installation errors, maintenance errors, or deviations in the operational environment were classified as potentially dependent failures.The statistical dependence between failures was estimated from the relative portion of multiple failures. Results confirm the earlier view of the significance of statistical dependence, a strong dependence on the age of the diesel generator was found in each failure class excluding random failures and maintenance errors, which had a nearly constant frequency independent of diesel generator age

  6. Multiple Scattering in Random Mechanical Systems and Diffusion Approximation

    Science.gov (United States)

    Feres, Renato; Ng, Jasmine; Zhang, Hong-Kun

    2013-10-01

    This paper is concerned with stochastic processes that model multiple (or iterated) scattering in classical mechanical systems of billiard type, defined below. From a given (deterministic) system of billiard type, a random process with transition probabilities operator P is introduced by assuming that some of the dynamical variables are random with prescribed probability distributions. Of particular interest are systems with weak scattering, which are associated to parametric families of operators P h , depending on a geometric or mechanical parameter h, that approaches the identity as h goes to 0. It is shown that ( P h - I)/ h converges for small h to a second order elliptic differential operator on compactly supported functions and that the Markov chain process associated to P h converges to a diffusion with infinitesimal generator . Both P h and are self-adjoint (densely) defined on the space of square-integrable functions over the (lower) half-space in , where η is a stationary measure. This measure's density is either (post-collision) Maxwell-Boltzmann distribution or Knudsen cosine law, and the random processes with infinitesimal generator respectively correspond to what we call MB diffusion and (generalized) Legendre diffusion. Concrete examples of simple mechanical systems are given and illustrated by numerically simulating the random processes.

  7. An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

    KAUST Repository

    Nam, Sungsik

    2010-11-01

    Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.

  8. Numerical Solution of the Time-Dependent Navier–Stokes Equation for Variable Density–Variable Viscosity. Part I

    Czech Academy of Sciences Publication Activity Database

    Axelsson, Owe; Xin, H.; Neytcheva, M.

    2015-01-01

    Roč. 20, č. 2 (2015), s. 232-260 ISSN 1392-6292 Institutional support: RVO:68145535 Keywords : variable density * phase-field model * Navier-Stokes equations * preconditioning * variable viscosity Subject RIV: BA - General Mathematics Impact factor: 0.468, year: 2015 http://www.tandfonline.com/doi/abs/10.3846/13926292.2015.1021395

  9. Decompounding random sums: A nonparametric approach

    DEFF Research Database (Denmark)

    Hansen, Martin Bøgsted; Pitts, Susan M.

    Observations from sums of random variables with a random number of summands, known as random, compound or stopped sums arise within many areas of engineering and science. Quite often it is desirable to infer properties of the distribution of the terms in the random sum. In the present paper we...... review a number of applications and consider the nonlinear inverse problem of inferring the cumulative distribution function of the components in the random sum. We review the existing literature on non-parametric approaches to the problem. The models amenable to the analysis are generalized considerably...

  10. Lack of evidence for low-dimensional chaos in heart rate variability

    DEFF Research Database (Denmark)

    Kanters, J K; Holstein-Rathlou, N H; Agner, E

    1994-01-01

    INTRODUCTION: The term chaos is used to describe erratic or apparently random time-dependent behavior in deterministic systems. It has been suggested that the variability observed in the normal heart rate may be due to chaos, but this question has not been settled. METHODS AND RESULTS: Heart rate...... in the experimental data, but the prediction error as a function of the prediction length increased at a slower rate than characteristic of a low-dimensional chaotic system. CONCLUSION: There is no evidence for low-dimensional chaos in the time series of RR intervals from healthy human subjects. However, nonlinear...

  11. Some results on convergence rates for probabilities of moderate deviations for sums of random variables

    Directory of Open Access Journals (Sweden)

    Deli Li

    1992-01-01

    Full Text Available Let X, Xn, n≥1 be a sequence of iid real random variables, and Sn=∑k=1nXk, n≥1. Convergence rates of moderate deviations are derived, i.e., the rate of convergence to zero of certain tail probabilities of the partial sums are determined. For example, we obtain equivalent conditions for the convergence of series ∑n≥1(ψ2(n/nP(|Sn|≥nφ(n only under the assumptions convergence that EX=0 and EX2=1, where φ and ψ are taken from a broad class of functions. These results generalize and improve some recent results of Li (1991 and Gafurov (1982 and some previous work of Davis (1968. For b∈[0,1] and ϵ>0, letλϵ,b=∑n≥3((loglognb/nI(|Sn|≥(2+ϵnloglogn.The behaviour of Eλϵ,b as ϵ↓0 is also studied.

  12. Integrated care for comorbid alcohol dependence and anxiety and/or depressive disorder: study protocol for an assessor-blind, randomized controlled trial.

    Science.gov (United States)

    Morley, Kirsten C; Baillie, Andrew; Sannibale, Claudia; Teesson, Maree; Haber, Paul S

    2013-11-19

    A major barrier to successful treatment in alcohol dependence is psychiatric comorbidity. During treatment, the time to relapse is shorter, the drop-out rate is increased, and long-term alcohol consumption is greater for those with comorbid major depression or anxiety disorder than those with an alcohol use disorder with no comorbid mental disorder. The treatment of alcohol dependence and psychological disorders is often the responsibility of different services, and this can hinder the treatment process. Accordingly, there is a need for an effective integrated treatment for alcohol dependence and comorbid anxiety and/or depression. We aim to assess the effectiveness of a specialized, integrated intervention for alcohol dependence with comorbid anxiety and/or mood disorder using a randomized design in an outpatient hospital setting. Following a three-week stabilization period (abstinence or significantly reduced consumption), participants will undergo complete formal assessment for anxiety and depression. Those patients with a diagnosis of an anxiety and/or depressive disorder will be randomized to either 1) integrated intervention (cognitive behavioral therapy) for alcohol, anxiety, and/or depression; or 2) usual counseling care for alcohol problems. Patients will then be followed up at weeks 12, 16, and 24. The primary outcome measure is alcohol consumption (total abstinence, time to lapse, and time to relapse). Secondary outcome measures include changes in alcohol dependence severity, depression, or anxiety symptoms and changes in clinician-rated severity of anxiety and depression. The study findings will have potential implications for clinical practice by evaluating the implementation of specialized integrated treatment for comorbid anxiety and/or depression in an alcohol outpatient service. ClinicalTrials.gov Identifier: NCT01941693.

  13. Association Splitting: A randomized controlled trial of a new method to reduce craving among inpatients with alcohol dependence.

    Science.gov (United States)

    Schneider, Brooke C; Moritz, Steffen; Hottenrott, Birgit; Reimer, Jens; Andreou, Christina; Jelinek, Lena

    2016-04-30

    Association Splitting, a novel cognitive intervention, was tested in patients with alcohol dependence as an add-on intervention in an initial randomized controlled trial. Preliminary support for Association Splitting has been found in patients with obsessive-compulsive disorder, as well as in an online pilot study of patients with alcohol use disorders. The present variant sought to reduce craving by strengthening neutral associations with alcohol-related stimuli, thus, altering cognitive networks. Eighty-four inpatients with verified diagnoses of alcohol dependence, who were currently undergoing inpatient treatment, were randomly assigned to Association Splitting or Exercise Therapy. Craving was measured at baseline, 4-week follow-up, and six months later with the Obsessive-Compulsive Drinking Scale (primary outcome) and the Alcohol Craving Questionnaire. There was no advantage for Association Splitting after three treatment sessions relative to Exercise Therapy. Among Association Splitting participants, 51.9% endorsed a subjective decline in craving and 88.9% indicated that they would use Association Splitting in the future. Despite high acceptance, an additional benefit of Association Splitting beyond standard inpatient treatment was not found. Given that participants were concurrently undergoing inpatient treatment and Association Splitting has previously shown moderate effects, modification of the study design may improve the potential to detect significant effects in future trials. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  14. A study of probabilistic fatigue crack propagation models in Mg Al Zn alloys under different specimen thickness conditions by using the residual of a random variable

    International Nuclear Information System (INIS)

    Choi, Seon Soon

    2012-01-01

    The primary aim of this paper was to evaluate several probabilistic fatigue crack propagation models using the residual of a random variable, and to present the model fit for probabilistic fatigue behavior in Mg Al Zn alloys. The proposed probabilistic models are the probabilistic Paris Erdogan model, probabilistic Walker model, probabilistic Forman model, and probabilistic modified Forman models. These models were prepared by applying a random variable to the empirical fatigue crack propagation models with these names. The best models for describing fatigue crack propagation models with these names. The best models for describing fatigue crack propagation models with these names. The best models for describing fatigue crack propagation models with these names. The best models vor describing fatigue crack propagation behavior in Mg Al Zn alloys were generally the probabilistic Paris Erdogan and probabilistic Walker models. The probabilistic Forman model was a good model only for a specimen with a thickness of 9.45mm

  15. Gamma processes and peaks-over-threshold distributions for time-dependent reliability

    International Nuclear Information System (INIS)

    Noortwijk, J.M. van; Weide, J.A.M. van der; Kallen, M.J.; Pandey, M.D.

    2007-01-01

    In the evaluation of structural reliability, a failure is defined as the event in which stress exceeds a resistance that is liable to deterioration. This paper presents a method to combine the two stochastic processes of deteriorating resistance and fluctuating load for computing the time-dependent reliability of a structural component. The deterioration process is modelled as a gamma process, which is a stochastic process with independent non-negative increments having a gamma distribution with identical scale parameter. The stochastic process of loads is generated by a Poisson process. The variability of the random loads is modelled by a peaks-over-threshold distribution (such as the generalised Pareto distribution). These stochastic processes of deterioration and load are combined to evaluate the time-dependent reliability

  16. Ratio index variables or ANCOVA? Fisher's cats revisited.

    Science.gov (United States)

    Tu, Yu-Kang; Law, Graham R; Ellison, George T H; Gilthorpe, Mark S

    2010-01-01

    Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. (c) 2009 John Wiley & Sons, Ltd.

  17. Establishment of regression dependences. Linear and nonlinear dependences

    International Nuclear Information System (INIS)

    Onishchenko, A.M.

    1994-01-01

    The main problems of determination of linear and 19 types of nonlinear regression dependences are completely discussed. It is taken into consideration that total dispersions are the sum of measurement dispersions and parameter variation dispersions themselves. Approaches to all dispersions determination are described. It is shown that the least square fit gives inconsistent estimation for industrial objects and processes. The correction methods by taking into account comparable measurement errors for both variable give an opportunity to obtain consistent estimation for the regression equation parameters. The condition of the correction technique application expediency is given. The technique for determination of nonlinear regression dependences taking into account the dependence form and comparable errors of both variables is described. 6 refs., 1 tab

  18. Comparing Young and Elderly Serial Reaction Time Task Performance on Repeated and Random Conditions

    Directory of Open Access Journals (Sweden)

    Fatemeh Ehsani

    2012-07-01

    Full Text Available Objectives: Acquisition motor skill training in elderly is at great importance. The main purpose of this study was to compare young and elderly performance in serial reaction time task on different repeated and random conditions. Methods & Materials: A serial reaction time task by using software was applied for studying motor learning in 30 young and 30 elderly. Each group divided randomly implicitly and explicitly into subgroups. A task 4 squares with different colors appeared on the monitor and subjects were asked to press its defined key immediately after observing it. Subjects practiced 8 motor blocks (4 repeated blocks, then 2 random blocks and 2 repeated blocks. Block time that was dependent variable measured and Independent-samples t- test with repeated ANOVA measures were used in this test. Results: young groups performed both repeated and random sequences significantly faster than elderly (P0.05. Explicit older subgroup performed 7,8 blocks slower than 6 block with a significant difference (P<0.05. Conclusion: Young adults discriminate high level performance than elderly in both repeated and random practice. Elderly performed random practice better than repeated practice.

  19. Unit-specific calibration of Actigraph accelerometers in a mechanical setup - is it worth the effort? The effect on random output variation caused by technical inter-instrument variability in the laboratory and in the field

    DEFF Research Database (Denmark)

    Moeller, Niels C; Korsholm, Lars; Kristensen, Peter L

    2008-01-01

    BACKGROUND: Potentially, unit-specific in-vitro calibration of accelerometers could increase field data quality and study power. However, reduced inter-unit variability would only be important if random instrument variability contributes considerably to the total variation in field data. Therefor...

  20. Individualized Anemia Management Reduces Hemoglobin Variability in Hemodialysis Patients

    OpenAIRE

    Gaweda, Adam E.; Aronoff, George R.; Jacobs, Alfred A.; Rai, Shesh N.; Brier, Michael E.

    2013-01-01

    One-size-fits-all protocol-based approaches to anemia management with erythropoiesis-stimulating agents (ESAs) may result in undesired patterns of hemoglobin variability. In this single-center, double-blind, randomized controlled trial, we tested the hypothesis that individualized dosing of ESA improves hemoglobin variability over a standard population-based approach. We enrolled 62 hemodialysis patients and followed them over a 12-month period. Patients were randomly assigned to receive ESA ...

  1. A random matrix approach to VARMA processes

    International Nuclear Information System (INIS)

    Burda, Zdzislaw; Jarosz, Andrzej; Nowak, Maciej A; Snarska, Malgorzata

    2010-01-01

    We apply random matrix theory to derive the spectral density of large sample covariance matrices generated by multivariate VMA(q), VAR(q) and VARMA(q 1 , q 2 ) processes. In particular, we consider a limit where the number of random variables N and the number of consecutive time measurements T are large but the ratio N/T is fixed. In this regime, the underlying random matrices are asymptotically equivalent to free random variables (FRV). We apply the FRV calculus to calculate the eigenvalue density of the sample covariance for several VARMA-type processes. We explicitly solve the VARMA(1, 1) case and demonstrate perfect agreement between the analytical result and the spectra obtained by Monte Carlo simulations. The proposed method is purely algebraic and can be easily generalized to q 1 >1 and q 2 >1.

  2. A Review on asymptotic normality of sums of associated random ...

    African Journals Online (AJOL)

    Association between random variables is a generalization of independence of these random variables. This concept is more and more commonly used in current trends in any research elds in Statistics. In this paper, we proceed to a simple, clear and rigorous introduction to it. We will present the fundamental asymptotic ...

  3. Psychiatric comorbidity and quality of life in patients with alcohol dependence syndrome

    Directory of Open Access Journals (Sweden)

    Sidharth Arya

    2017-01-01

    Full Text Available Context: There is a lack of literature on the relation between psychiatric comorbidities and their influence on quality of life in patients with alcohol dependence syndrome in the Indian settings. Aims: To study the relation between psychiatric comorbidity with quality of life in patients with alcohol dependence. Settings and Design: The study was carried out in a de-addiction centre of a tertiary care hospital upon randomly selected inpatients of alcohol dependence syndrome. Patients with other substance abuse except tobacco or those with severe physical impairment were excluded. Materials and Methods: Hundred in-patients were assessed between the period of August 2013 to July 2014, using a number of instruments including specially designed proforma for clinical and drinking variables, CIWA-Ar, SADD, M.I.N.I 5.0 and WHO QoL Bref. Statistics used: SPSS 19.0 was used for analysis. Significance was calculated using t-test for continuous variables and chi-square test for categorical variables. Results: Prevalence of psychiatric disorder was found to be 32% across all the tested patients, with anxiety (n = 13 and depressive disorder (n = 12 being most common. Presence of psychiatric comorbidity lead to significant lowering in overall quality, perception of general health, physical (42.12 vs 57.78, P = 0.001, psychological (40.19 vs 53.29, P = 0.002, social (43.97 vs 66.90, P = 0.000, and environment (50.47 vs 62.71, P = 0.001 domains. Conclusion: Comorbid psychiatric disorders have a significant negative impact on the quality of life in patients with alcohol dependence syndrome.

  4. An unbiased estimator of the variance of simple random sampling using mixed random-systematic sampling

    OpenAIRE

    Padilla, Alberto

    2009-01-01

    Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling without replacement is used. By means of a mixed random - systematic sample, an unbiased estimator o...

  5. Within-day variability on short and long walking tests in persons with multiple sclerosis.

    Science.gov (United States)

    Feys, Peter; Bibby, Bo; Romberg, Anders; Santoyo, Carme; Gebara, Benoit; de Noordhout, Benoit Maertens; Knuts, Kathy; Bethoux, Francois; Skjerbæk, Anders; Jensen, Ellen; Baert, Ilse; Vaney, Claude; de Groot, Vincent; Dalgas, Ulrik

    2014-03-15

    To compare within-day variability of short (10 m walking test at usual and fastest speed; 10MWT) and long (2 and 6-minute walking test; 2MWT/6MWT) tests in persons with multiple sclerosis. Observational study. MS rehabilitation and research centers in Europe and US within RIMS (European network for best practice and research in MS rehabilitation). Ambulatory persons with MS (Expanded Disability Status Scale 0-6.5). Subjects of different centers performed walking tests at 3 time points during a single day. 10MWT, 2MWT and 6MWT at fastest speed and 10MWT at usual speed. Ninety-five percent limits of agreement were computed using a random effects model with individual pwMS as random effect. Following this model, retest scores are with 95% certainty within these limits of baseline scores. In 102 subjects, within-day variability was constant in absolute units for the 10MWT, 2MWT and 6MWT at fastest speed (+/-0.26, 0.16 and 0.15m/s respectively, corresponding to +/-19.2m and +/-54 m for the 2MWT and 6MWT) independent on the severity of ambulatory dysfunction. This implies a greater relative variability with increasing disability level, often above 20% depending on the applied test. The relative within-day variability of the 10MWT at usual speed was +/-31% independent of ambulatory function. Absolute values of within-day variability on walking tests at fastest speed were independent of disability level and greater with short compared to long walking tests. Relative within-day variability remained overall constant when measured at usual speed. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

  6. Positive random variables with a discrete probability mass at the origin: Parameter estimation for left-censored samples with application to air quality monitoring data

    International Nuclear Information System (INIS)

    Gogolak, C.V.

    1986-11-01

    The concentration of a contaminant measured in a particular medium might be distributed as a positive random variable when it is present, but it may not always be present. If there is a level below which the concentration cannot be distinguished from zero by the analytical apparatus, a sample from such a population will be censored on the left. The presence of both zeros and positive values in the censored portion of such samples complicates the problem of estimating the parameters of the underlying positive random variable and the probability of a zero observation. Using the method of maximum likelihood, it is shown that the solution to this estimation problem reduces largely to that of estimating the parameters of the distribution truncated at the point of censorship. The maximum likelihood estimate of the proportion of zero values follows directly. The derivation of the maximum likelihood estimates for a lognormal population with zeros is given in detail, and the asymptotic properties of the estimates are examined. The estimation method was used to fit several different distributions to a set of severely censored 85 Kr monitoring data from six locations at the Savannah River Plant chemical separations facilities

  7. A Model for Positively Correlated Count Variables

    DEFF Research Database (Denmark)

    Møller, Jesper; Rubak, Ege Holger

    2010-01-01

    An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....

  8. Relationship between clustering and algorithmic phase transitions in the random k-XORSAT model and its NP-complete extensions

    International Nuclear Information System (INIS)

    Altarelli, F; Monasson, R; Zamponi, F

    2008-01-01

    We study the performances of stochastic heuristic search algorithms on Uniquely Extendible Constraint Satisfaction Problems with random inputs. We show that, for any heuristic preserving the Poissonian nature of the underlying instance, the (heuristic-dependent) largest ratio α a of constraints per variables for which a search algorithm is likely to find solutions is smaller than the critical ratio α d above which solutions are clustered and highly correlated. In addition we show that the clustering ratio can be reached when the number k of variables per constraints goes to infinity by the so-called Generalized Unit Clause heuristic

  9. Modified Feynman ratchet with velocity-dependent fluctuations

    Directory of Open Access Journals (Sweden)

    Jack Denur

    2004-03-01

    Full Text Available Abstract: The randomness of Brownian motion at thermodynamic equilibrium can be spontaneously broken by velocity-dependence of fluctuations, i.e., by dependence of values or probability distributions of fluctuating properties on Brownian-motional velocity. Such randomness-breaking can spontaneously obtain via interaction between Brownian-motional Doppler effects --- which manifest the required velocity-dependence --- and system geometrical asymmetry. A non random walk is thereby spontaneously superposed on Brownian motion, resulting in a systematic net drift velocity despite thermodynamic equilibrium. The time evolution of this systematic net drift velocity --- and of velocity probability density, force, and power output --- is derived for a velocity-dependent modification of Feynman's ratchet. We show that said spontaneous randomness-breaking, and consequent systematic net drift velocity, imply: bias from the Maxwellian of the system's velocity probability density, the force that tends to accelerate it, and its power output. Maximization, especially of power output, is discussed. Uncompensated decreases in total entropy, challenging the second law of thermodynamics, are thereby implied.

  10. Random survival forests for competing risks

    DEFF Research Database (Denmark)

    Ishwaran, Hemant; Gerds, Thomas A; Kogalur, Udaya B

    2014-01-01

    We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection...

  11. Baclofen for maintenance treatment of opioid dependence: A randomized double-blind placebo-controlled clinical trial [ISRCTN32121581

    Directory of Open Access Journals (Sweden)

    Ahmadi-Abhari Seyed Ali

    2003-11-01

    Full Text Available Abstract Background Results of preclinical studies suggest that the GABAB receptor agonist baclofen may be useful in treatment of opioid dependence. This study was aimed at assessing the possible efficacy of baclofen for maintenance treatment of opioid dependence. Methods A total of 40 opioid-dependent patients were detoxified and randomly assigned to receive baclofen (60 mg/day or placebo in a 12-week, double blind, parallel-group trial. Primary outcome measure was retention in treatment. Secondary outcome measures included opioids and alcohol use according to urinalysis and self-report ratings, intensity of opioid craving assessed with a visual analogue scale, opioid withdrawal symptoms as measured by the Short Opiate Withdrawal Scale and depression scores on the Hamilton inventory. Results Treatment retention was significantly higher in the baclofen group. Baclofen also showed a significant superiority over placebo in terms of opiate withdrawal syndrome and depressive symptoms. Non-significant, but generally favorable responses were seen in the baclofen group with other outcome measures including intensity of opioid craving and self-reported opioid and alcohol use. However, no significant difference was seen in the rates of opioid-positive urine tests. Additionally, the drug side effects of the two groups were not significantly different. Conclusion The results support further study of baclofen in the maintenance treatment of opioid dependence.

  12. Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

    Directory of Open Access Journals (Sweden)

    U. Mishra

    2012-09-01

    Full Text Available The direction and magnitude of soil organic carbon (SOC changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5. Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were found to be land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth system models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%, followed by discontinuous (28%, isolated (24.3%, and sporadic (23.6% permafrost areas. Our high-resolution mapping of soil carbon stock reveals the

  13. Curvature of random walks and random polygons in confinement

    International Nuclear Information System (INIS)

    Diao, Y; Ernst, C; Montemayor, A; Ziegler, U

    2013-01-01

    The purpose of this paper is to study the curvature of equilateral random walks and polygons that are confined in a sphere. Curvature is one of several basic geometric properties that can be used to describe random walks and polygons. We show that confinement affects curvature quite strongly, and in the limit case where the confinement diameter equals the edge length the unconfined expected curvature value doubles from π/2 to π. To study curvature a simple model of an equilateral random walk in spherical confinement in dimensions 2 and 3 is introduced. For this simple model we derive explicit integral expressions for the expected value of the total curvature in both dimensions. These expressions are functions that depend only on the radius R of the confinement sphere. We then show that the values obtained by numeric integration of these expressions agrees with numerical average curvature estimates obtained from simulations of random walks. Finally, we compare the confinement effect on curvature of random walks with random polygons. (paper)

  14. Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures.

    Science.gov (United States)

    Filippi, Sarah; Holmes, Chris C; Nieto-Barajas, Luis E

    2016-11-16

    In this article we propose novel Bayesian nonparametric methods using Dirichlet Process Mixture (DPM) models for detecting pairwise dependence between random variables while accounting for uncertainty in the form of the underlying distributions. A key criteria is that the procedures should scale to large data sets. In this regard we find that the formal calculation of the Bayes factor for a dependent-vs.-independent DPM joint probability measure is not feasible computationally. To address this we present Bayesian diagnostic measures for characterising evidence against a "null model" of pairwise independence. In simulation studies, as well as for a real data analysis, we show that our approach provides a useful tool for the exploratory nonparametric Bayesian analysis of large multivariate data sets.

  15. Individual Variability in Brain Activity: A Nuisance or an Opportunity?

    Science.gov (United States)

    Van Horn, John Darrell; Grafton, Scott T; Miller, Michael B

    2008-12-01

    Functional imaging research has been heavily influenced by results based on population-level inference. However, group average results may belie the unique patterns of activity present in the individual that ordinarily are considered random noise. Recent advances in the evolution of MRI hardware have led to significant improvements in the stability and reproducibility of blood oxygen level dependent (BOLD) measurements. These enhancements provide a unique opportunity for closer examination of individual patterns of brain activity. Three objectives can be accomplished by considering brain scans at the individual level; (1) Mapping functional anatomy at a fine grained analysis; (2) Determining if an individual scan is normative with respect to a reference population; and (3) Understanding the sources of intersubject variability in brain activity. In this review, we detail these objectives, briefly discuss their histories and present recent trends in the analyses of individual variability. Finally, we emphasize the unique opportunities and challenges for understanding individual differences through international collaboration among Pacific Rim investigators.

  16. Estimating the price elasticity of beer: meta-analysis of data with heterogeneity, dependence, and publication bias.

    Science.gov (United States)

    Nelson, Jon P

    2014-01-01

    Precise estimates of price elasticities are important for alcohol tax policy. Using meta-analysis, this paper corrects average beer elasticities for heterogeneity, dependence, and publication selection bias. A sample of 191 estimates is obtained from 114 primary studies. Simple and weighted means are reported. Dependence is addressed by restricting number of estimates per study, author-restricted samples, and author-specific variables. Publication bias is addressed using funnel graph, trim-and-fill, and Egger's intercept model. Heterogeneity and selection bias are examined jointly in meta-regressions containing moderator variables for econometric methodology, primary data, and precision of estimates. Results for fixed- and random-effects regressions are reported. Country-specific effects and sample time periods are unimportant, but several methodology variables help explain the dispersion of estimates. In models that correct for selection bias and heterogeneity, the average beer price elasticity is about -0.20, which is less elastic by 50% compared to values commonly used in alcohol tax policy simulations. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS.

    Science.gov (United States)

    Shalizi, Cosma Rohilla; Rinaldo, Alessandro

    2013-04-01

    The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling , or, in terms of the theory of stochastic processes, that it defines a projective family. Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact violated by many popular and scientifically appealing models, and that satisfying it drastically limits ERGM's expressive power. These results are actually special cases of more general results about exponential families of dependent random variables, which we also prove. Using such results, we offer easily checked conditions for the consistency of maximum likelihood estimation in ERGMs, and discuss some possible constructive responses.

  18. Variability in research ethics review of cluster randomized trials: a scenario-based survey in three countries

    Science.gov (United States)

    2014-01-01

    Background Cluster randomized trials (CRTs) present unique ethical challenges. In the absence of a uniform standard for their ethical design and conduct, problems such as variability in procedures and requirements by different research ethics committees will persist. We aimed to assess the need for ethics guidelines for CRTs among research ethics chairs internationally, investigate variability in procedures for research ethics review of CRTs within and among countries, and elicit research ethics chairs’ perspectives on specific ethical issues in CRTs, including the identification of research subjects. The proper identification of research subjects is a necessary requirement in the research ethics review process, to help ensure, on the one hand, that subjects are protected from harm and exploitation, and on the other, that reviews of CRTs are completed efficiently. Methods A web-based survey with closed- and open-ended questions was administered to research ethics chairs in Canada, the United States, and the United Kingdom. The survey presented three scenarios of CRTs involving cluster-level, professional-level, and individual-level interventions. For each scenario, a series of questions was posed with respect to the type of review required (full, expedited, or no review) and the identification of research subjects at cluster and individual levels. Results A total of 189 (35%) of 542 chairs responded. Overall, 144 (84%, 95% CI 79 to 90%) agreed or strongly agreed that there is a need for ethics guidelines for CRTs and 158 (92%, 95% CI 88 to 96%) agreed or strongly agreed that research ethics committees could be better informed about distinct ethical issues surrounding CRTs. There was considerable variability among research ethics chairs with respect to the type of review required, as well as the identification of research subjects. The cluster-cluster and professional-cluster scenarios produced the most disagreement. Conclusions Research ethics committees

  19. Time-dependent postural control adaptations following a neuromuscular warm-up in female handball players: a randomized controlled trial.

    Science.gov (United States)

    Steib, Simon; Zahn, Peter; Zu Eulenburg, Christine; Pfeifer, Klaus; Zech, Astrid

    2016-01-01

    Female handball athletes are at a particular risk of sustaining lower extremity injuries. The study examines time-dependent adaptations of static and dynamic balance as potential injury risk factors to a specific warm-up program focusing on neuromuscular control. Fourty one (24.0 ± 5.9 years) female handball athletes were randomized to an intervention or control group. The intervention group implemented a 15-min specific neuromuscular warm-up program, three times per week for eleven weeks, whereas the control group continued with their regular warm-up. Balance was assessed at five time points. Measures included the star excursion balance test (SEBT), and center of pressure (COP) sway velocity during single-leg standing. No baseline differences existed between groups in demographic data. Adherence to neuromuscular warm-up was 88.7 %. Mean COP sway velocity decreased significantly over time in the intervention group (-14.4 %; p  control group (-6.2 %; p  = 0.056). However, these effects did not differ significantly between groups ( p  = .098). Mean changes over time in the SEBT score were significantly greater ( p  = .014) in the intervention group (+5.48) compared to the control group (+3.45). Paired t-tests revealed that the first significant balance improvements were observed after 6 weeks of training. A neuromuscular warm-up positively influences balance variables associated with an increased risk of lower extremity injuries in female handball athletes. The course of adaptations suggests that a training volume of 15 min, three times weekly over at least six weeks produces measurable changes. Retrospectively registered on 4th October 2016. Registry: clinicaltrials.gov. Trial number: NCT02925377.

  20. Reduced plasma aldosterone concentrations in randomly selected patients with insulin-dependent diabetes mellitus.

    LENUS (Irish Health Repository)

    Cronin, C C

    2012-02-03

    Abnormalities of the renin-angiotensin system have been reported in patients with diabetes mellitus and with diabetic complications. In this study, plasma concentrations of prorenin, renin, and aldosterone were measured in a stratified random sample of 110 insulin-dependent (Type 1) diabetic patients attending our outpatient clinic. Fifty-four age- and sex-matched control subjects were also examined. Plasma prorenin concentration was higher in patients without complications than in control subjects when upright (geometric mean (95% confidence intervals (CI): 75.9 (55.0-105.6) vs 45.1 (31.6-64.3) mU I-1, p < 0.05). There was no difference in plasma prorenin concentration between patients without and with microalbuminuria and between patients without and with background retinopathy. Plasma renin concentration, both when supine and upright, was similar in control subjects, in patients without complications, and in patients with varying degrees of diabetic microangiopathy. Plasma aldosterone was suppressed in patients without complications in comparison to control subjects (74 (58-95) vs 167 (140-199) ng I-1, p < 0.001) and was also suppressed in patients with microvascular disease. Plasma potassium was significantly higher in patients than in control subjects (mean +\\/- standard deviation: 4.10 +\\/- 0.36 vs 3.89 +\\/- 0.26 mmol I-1; p < 0.001) and plasma sodium was significantly lower (138 +\\/- 4 vs 140 +\\/- 2 mmol I-1; p < 0.001). We conclude that plasma prorenin is not a useful early marker for diabetic microvascular disease. Despite apparently normal plasma renin concentrations, plasma aldosterone is suppressed in insulin-dependent diabetic patients.

  1. RNA-seq: technical variability and sampling

    Science.gov (United States)

    2011-01-01

    Background RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases. PMID:21645359

  2. Cryotherapy, Sensation, and Isometric-Force Variability

    Science.gov (United States)

    Denegar, Craig R.; Buckley, William E.; Newell, Karl M.

    2003-01-01

    Objective: To determine the changes in sensation of pressure, 2-point discrimination, and submaximal isometric-force production variability due to cryotherapy. Design and Setting: Sensation was assessed using a 2 × 2 × 2 × 3 repeated-measures factorial design, with treatment (ice immersion or control), limb (right or left), digit (finger or thumb), and sensation test time (baseline, posttreatment, or postisometric-force trials) as independent variables. Dependent variables were changes in sensation of pressure and 2-point discrimination. Isometric-force variability was tested with a 2 × 2 × 3 repeated-measures factorial design. Treatment condition (ice immersion or control), limb (right or left), and percentage (10, 25, or 40) of maximal voluntary isometric contraction (MVIC) were the independent variables. The dependent variables were the precision or variability (the standard deviation of mean isometric force) and the accuracy or targeting error (the root mean square error) of the isometric force for each percentage of MVIC. Subjects: Fifteen volunteer college students (8 men, 7 women; age = 22 ± 3 years; mass = 72 ± 21.9 kg; height = 183.4 ± 11.6 cm). Measurements: We measured sensation in the distal palmar aspect of the index finger and thumb. Sensation of pressure and 2-point discrimination were measured before treatment (baseline), after treatment (15 minutes of ice immersion or control), and at the completion of isometric testing (final). Variability (standard deviation of mean isometric force) of the submaximal isometric finger forces was measured by having the subjects exert a pinching force with the thumb and index finger for 30 seconds. Subjects performed the pinching task at the 3 submaximal levels of MVIC (10%, 25%, and 40%), with the order of trials assigned randomly. The subjects were given a target representing the submaximal percentage of MVIC and visual feedback of the force produced as they pinched the testing device. The force exerted

  3. All varieties of encoding variability are not created equal: Separating variable processing from variable tasks

    Science.gov (United States)

    Huff, Mark J.; Bodner, Glen E.

    2014-01-01

    Whether encoding variability facilitates memory is shown to depend on whether item-specific and relational processing are both performed across study blocks, and whether study items are weakly versus strongly related. Variable-processing groups studied a word list once using an item-specific task and once using a relational task. Variable-task groups’ two different study tasks recruited the same type of processing each block. Repeated-task groups performed the same study task each block. Recall and recognition were greatest in the variable-processing group, but only with weakly related lists. A variable-processing benefit was also found when task-based processing and list-type processing were complementary (e.g., item-specific processing of a related list) rather than redundant (e.g., relational processing of a related list). That performing both item-specific and relational processing across trials, or within a trial, yields encoding-variability benefits may help reconcile decades of contradictory findings in this area. PMID:25018583

  4. Benchmarking Variable Selection in QSAR.

    Science.gov (United States)

    Eklund, Martin; Norinder, Ulf; Boyer, Scott; Carlsson, Lars

    2012-02-01

    Variable selection is important in QSAR modeling since it can improve model performance and transparency, as well as reduce the computational cost of model fitting and predictions. Which variable selection methods that perform well in QSAR settings is largely unknown. To address this question we, in a total of 1728 benchmarking experiments, rigorously investigated how eight variable selection methods affect the predictive performance and transparency of random forest models fitted to seven QSAR datasets covering different endpoints, descriptors sets, types of response variables, and number of chemical compounds. The results show that univariate variable selection methods are suboptimal and that the number of variables in the benchmarked datasets can be reduced with about 60 % without significant loss in model performance when using multivariate adaptive regression splines MARS and forward selection. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift

    DEFF Research Database (Denmark)

    Lehre, Per Kristian; Witt, Carsten

    2014-01-01

    Drift analysis is one of the state-of-the-art techniques for the runtime analysis of randomized search heuristics (RSHs) such as evolutionary algorithms (EAs), simulated annealing etc. The vast majority of existing drift theorems yield bounds on the expected value of the hitting time for a target...

  6. Random walks on reductive groups

    CERN Document Server

    Benoist, Yves

    2016-01-01

    The classical theory of Random Walks describes the asymptotic behavior of sums of independent identically distributed random real variables. This book explains the generalization of this theory to products of independent identically distributed random matrices with real coefficients. Under the assumption that the action of the matrices is semisimple – or, equivalently, that the Zariski closure of the group generated by these matrices is reductive - and under suitable moment assumptions, it is shown that the norm of the products of such random matrices satisfies a number of classical probabilistic laws. This book includes necessary background on the theory of reductive algebraic groups, probability theory and operator theory, thereby providing a modern introduction to the topic.

  7. Fuzzy randomness uncertainty in civil engineering and computational mechanics

    CERN Document Server

    Möller, Bernd

    2004-01-01

    This book, for the first time, provides a coherent, overall concept for taking account of uncertainty in the analysis, the safety assessment, and the design of structures. The reader is introduced to the problem of uncertainty modeling and familiarized with particular uncertainty models. For simultaneously considering stochastic and non-stochastic uncertainty the superordinated uncertainty model fuzzy randomness, which contains real valued random variables as well as fuzzy variables as special cases, is presented. For this purpose basic mathematical knowledge concerning the fuzzy set theory and the theory of fuzzy random variables is imparted. The body of the book comprises the appropriate quantification of uncertain structural parameters, the fuzzy and fuzzy probabilistic structural analysis, the fuzzy probabilistic safety assessment, and the fuzzy cluster structural design. The completely new algorithms are described in detail and illustrated by way of demonstrative examples.

  8. Fuzziness and randomness in an optimization framework

    International Nuclear Information System (INIS)

    Luhandjula, M.K.

    1994-03-01

    This paper presents a semi-infinite approach for linear programming in the presence of fuzzy random variable coefficients. As a byproduct a way for dealing with optimization problems including both fuzzy and random data is obtained. Numerical examples are provided for the sake of illustration. (author). 13 refs

  9. Large deviations of heavy-tailed random sums with applications in insurance and finance

    NARCIS (Netherlands)

    Kluppelberg, C; Mikosch, T

    We prove large deviation results for the random sum S(t)=Sigma(i=1)(N(t)) X-i, t greater than or equal to 0, where (N(t))(t greater than or equal to 0) are non-negative integer-valued random variables and (X-n)(n is an element of N) are i.i.d. non-negative random Variables with common distribution

  10. Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables

    DEFF Research Database (Denmark)

    Burgess, Stephen; Thompson, Simon G; Thompson, Grahame

    2010-01-01

    Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context o...

  11. Multi-index Stochastic Collocation Convergence Rates for Random PDEs with Parametric Regularity

    KAUST Repository

    Haji Ali, Abdul Lateef; Nobile, Fabio; Tamellini, Lorenzo; Tempone, Raul

    2016-01-01

    We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of the solution of a partial differential equation (PDE) with random data, where the random coefficient is parametrized by means of a countable sequence of terms in a suitable expansion. MISC is a combination technique based on mixed differences of spatial approximations and quadratures over the space of random data, and naturally, the error analysis uses the joint regularity of the solution with respect to both the variables in the physical domain and parametric variables. In MISC, the number of problem solutions performed at each discretization level is not determined by balancing the spatial and stochastic components of the error, but rather by suitably extending the knapsack-problem approach employed in the construction of the quasi-optimal sparse-grids and Multi-index Monte Carlo methods, i.e., we use a greedy optimization procedure to select the most effective mixed differences to include in the MISC estimator. We apply our theoretical estimates to a linear elliptic PDE in which the log-diffusion coefficient is modeled as a random field, with a covariance similar to a Matérn model, whose realizations have spatial regularity determined by a scalar parameter. We conduct a complexity analysis based on a summability argument showing algebraic rates of convergence with respect to the overall computational work. The rate of convergence depends on the smoothness parameter, the physical dimensionality and the efficiency of the linear solver. Numerical experiments show the effectiveness of MISC in this infinite dimensional setting compared with the Multi-index Monte Carlo method and compare the convergence rate against the rates predicted in our theoretical analysis. © 2016 SFoCM

  12. Multi-index Stochastic Collocation Convergence Rates for Random PDEs with Parametric Regularity

    KAUST Repository

    Haji Ali, Abdul Lateef

    2016-08-26

    We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of the solution of a partial differential equation (PDE) with random data, where the random coefficient is parametrized by means of a countable sequence of terms in a suitable expansion. MISC is a combination technique based on mixed differences of spatial approximations and quadratures over the space of random data, and naturally, the error analysis uses the joint regularity of the solution with respect to both the variables in the physical domain and parametric variables. In MISC, the number of problem solutions performed at each discretization level is not determined by balancing the spatial and stochastic components of the error, but rather by suitably extending the knapsack-problem approach employed in the construction of the quasi-optimal sparse-grids and Multi-index Monte Carlo methods, i.e., we use a greedy optimization procedure to select the most effective mixed differences to include in the MISC estimator. We apply our theoretical estimates to a linear elliptic PDE in which the log-diffusion coefficient is modeled as a random field, with a covariance similar to a Matérn model, whose realizations have spatial regularity determined by a scalar parameter. We conduct a complexity analysis based on a summability argument showing algebraic rates of convergence with respect to the overall computational work. The rate of convergence depends on the smoothness parameter, the physical dimensionality and the efficiency of the linear solver. Numerical experiments show the effectiveness of MISC in this infinite dimensional setting compared with the Multi-index Monte Carlo method and compare the convergence rate against the rates predicted in our theoretical analysis. © 2016 SFoCM

  13. Problems in probability theory, mathematical statistics and theory of random functions

    CERN Document Server

    Sveshnikov, A A

    1979-01-01

    Problem solving is the main thrust of this excellent, well-organized workbook. Suitable for students at all levels in probability theory and statistics, the book presents over 1,000 problems and their solutions, illustrating fundamental theory and representative applications in the following fields: Random Events; Distribution Laws; Correlation Theory; Random Variables; Entropy & Information; Markov Processes; Systems of Random Variables; Limit Theorems; Data Processing; and more.The coverage of topics is both broad and deep, ranging from the most elementary combinatorial problems through lim

  14. Midazolam Plus Haloperidol as Adjuvant Analgesics to Morphine in Opium Dependent Patients: A Randomized Clinical Trial.

    Science.gov (United States)

    Afzalimoghaddam, Mohammad; Edalatifard, Maryam; Nejati, Amir; Momeni, Mehdi; Isavi, Nader; Karimialavijeh, Ehsan

    2016-01-01

    Tolerance to opioids among opium-dependent patients creates obstacles for proper pain management of these patients in the emergency department (ED). The aim of the present study was to investigate the efficacy of intramuscular (IM) haloperidol plus midazolam on morphine analgesia among opium-dependent patients. Opium-dependent adults who were admitted to the ED for new-onset severe pain in the limbs or abdomen (within 24 hours of admission and a pain score of over six, using a numerical rating scale [NRS]) were recruited. Participants were randomly assigned into two groups. Group A received morphine 0.05 mg/kg intravenously (IV) and a mixture of midazolam 2.5 mg and haloperidol 2.5 mg (diluted in 5 cc of distilled water, IM); group B received morphine 0.05 mg/kg IV and distilled water 5 cc, IM. Measured outcomes were related to: 1) pain intensity; 2) total doses of morphine; 3) changes in hemodynamic status and level of consciousness of patients. NRS scores (zero to 10) before and one, three and six hours following intervention, as well as total doses of morphine, were recorded. We recruited 68 males (78.16%) and 19 females (21.83%). The mean age was 38.28±6.59 years. The pain score in group A declined more rapidly over six hours than that in group B. Moreover, as compared to group B, the amount of morphine use decreased significantly in group A. Based on the present data, adding haloperidol plus midazolam to morphine for pain management improved pain scores and lowered morphine consumption among opium-dependent patients. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  15. Variability in colonization of arbuscular mycorrhizal fungi and its effect on mycorrhizal dependency of improved and unimproved soybean cultivars.

    Science.gov (United States)

    Salloum, M S; Guzzo, M C; Velazquez, M S; Sagadin, M B; Luna, C M

    2016-12-01

    Breeding selection of germplasm under fertilized conditions may reduce the frequency of genes that promote mycorrhizal associations. This study was developed to compare variability in mycorrhizal colonization and its effect on mycorrhizal dependency (MD) in improved soybean genotypes (I-1 and I-2) with differential tolerance to drought stress, and in unimproved soybean genotypes (UI-3 and UI-4). As inoculum, a mixed native arbuscular mycorrhizal fungi (AMF) was isolated from soybean roots, showing spores mostly of the species Funneliformis mosseae. At 20 days, unimproved genotypes followed by I-2, showed an increase in arbuscule formation, but not in I-1. At 40 days, mycorrhizal plants showed an increase in nodulation, this effect being more evident in unimproved genotypes. Mycorrhizal dependency, evaluated as growth and biochemical parameters from oxidative stress was increased in unimproved and I-2 since 20 days, whereas in I-1, MD increased at 40 days. We cannot distinguish significant differences in AMF colonization and MD between unimproved and I-2. However, variability among improved genotypes was observed. Our results suggest that selection for improved soybean genotypes with good and rapid AMF colonization, particularly high arbuscule/hyphae ratio could be a useful strategy for the development of genotypes that optimize AMF contribution to cropping systems.

  16. The Dependence of Cloud Particle Size on Non-Aerosol-Loading Related Variables

    Energy Technology Data Exchange (ETDEWEB)

    Shao, H.; Liu, G.

    2005-03-18

    An enhanced concentration of aerosol may increase the number of cloud drops by providing more cloud condensation nuclei (CCN), which in turn results in a higher cloud albedo at a constant cloud liquid water path. This process is often referred to as the aerosol indirect effect (AIE). Many in situ and remote sensing observations support this hypothesis (Ramanathan et al. 2001). However, satellite observed relations between aerosol concentration and cloud drop size are not always in agreement with the AIE. Based on global analysis of cloud effective radius (r{sub e}) and aerosol number concentration (N{sub a}) derived from satellite data, Sekiguchi et al. (2003) found that the correlations between the two variables can be either negative, or positive, or none, depending on the location of the clouds. They discovered that significantly negative r{sub e} - N{sub a} correlation can only be identified along coastal regions of the continents where abundant continental aerosols inflow from land, whereas Feingold et al. (2001) found that the response of r{sub e} to aerosol loading is the greatest in the region where aerosol optical depth ({tau}{sub a}) is the smallest. The reason for the discrepancy is likely due to the variations in cloud macroscopic properties such as geometrical thickness (Brenguier et al. 2003). Since r{sub e} is modified not only by aerosol but also by cloud geometrical thickness (H), the correlation between re and {tau}{sub a} actually reflects both the aerosol indirect effect and dependence of H. Therefore, discussing AIE based on the r{sub e}-{tau}{sub a} correlation without taking into account variations in cloud geometrical thickness may be misleading. This paper is motivated to extract aerosols' effect from overall effects using the independent measurements of cloud geometrical thickness, {tau}{sub a} and r{sub e}.

  17. A Note on the Tail Behavior of Randomly Weighted Sums with Convolution-Equivalently Distributed Random Variables

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2013-01-01

    Full Text Available We investigate the tailed asymptotic behavior of the randomly weighted sums with increments with convolution-equivalent distributions. Our obtained result can be directly applied to a discrete-time insurance risk model with insurance and financial risks and derive the asymptotics for the finite-time probability of the above risk model.

  18. Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets

    DEFF Research Database (Denmark)

    Lunde, Asger; Timmermann, Allan

    2004-01-01

    This article studies time series dependence in the direction of stock prices by modeling the (instantaneous) probability that a bull or bear market terminates as a function of its age and a set of underlying state variables, such as interest rates. A random walk model is rejected both for bull...... and bear markets. Although it . ts the data better, a generalized autoregressive conditional heteroscedasticity model is also found to be inconsistent with the very long bull markets observed in the data. The strongest effect of increasing interest rates is found to be a lower bear market hazard rate...

  19. A variable-order time-dependent neutron transport method for nuclear reactor kinetics using analytically-integrated space-time characteristics

    International Nuclear Information System (INIS)

    Hoffman, A. J.; Lee, J. C.

    2013-01-01

    A new time-dependent neutron transport method based on the method of characteristics (MOC) has been developed. Whereas most spatial kinetics methods treat time dependence through temporal discretization, this new method treats time dependence by defining the characteristics to span space and time. In this implementation regions are defined in space-time where the thickness of the region in time fulfills an analogous role to the time step in discretized methods. The time dependence of the local source is approximated using a truncated Taylor series expansion with high order derivatives approximated using backward differences, permitting the solution of the resulting space-time characteristic equation. To avoid a drastic increase in computational expense and memory requirements due to solving many discrete characteristics in the space-time planes, the temporal variation of the boundary source is similarly approximated. This allows the characteristics in the space-time plane to be represented analytically rather than discretely, resulting in an algorithm comparable in implementation and expense to one that arises from conventional time integration techniques. Furthermore, by defining the boundary flux time derivative in terms of the preceding local source time derivative and boundary flux time derivative, the need to store angularly-dependent data is avoided without approximating the angular dependence of the angular flux time derivative. The accuracy of this method is assessed through implementation in the neutron transport code DeCART. The method is employed with variable-order local source representation to model a TWIGL transient. The results demonstrate that this method is accurate and more efficient than the discretized method. (authors)

  20. Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

    Science.gov (United States)

    Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

    2005-06-01

    This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

  1. Prediction of 90Y Radioembolization Outcome from Pretherapeutic Factors with Random Survival Forests.

    Science.gov (United States)

    Ingrisch, Michael; Schöppe, Franziska; Paprottka, Karolin; Fabritius, Matthias; Strobl, Frederik F; De Toni, Enrico N; Ilhan, Harun; Todica, Andrei; Michl, Marlies; Paprottka, Philipp Marius

    2018-05-01

    Our objective was to predict the outcome of 90 Y radioembolization in patients with intrahepatic tumors from pretherapeutic baseline parameters and to identify predictive variables using a machine-learning approach based on random survival forests. Methods: In this retrospective study, 366 patients with primary ( n = 92) or secondary ( n = 274) liver tumors who had received 90 Y radioembolization were analyzed. A random survival forest was trained to predict individual risk from baseline values of cholinesterase, bilirubin, type of primary tumor, age at radioembolization, hepatic tumor burden, presence of extrahepatic disease, and sex. The predictive importance of each baseline parameter was determined using the minimal-depth concept, and the partial dependency of predicted risk on the continuous variables bilirubin level and cholinesterase level was determined. Results: Median overall survival was 11.4 mo (95% confidence interval, 9.7-14.2 mo), with 228 deaths occurring during the observation period. The random-survival-forest analysis identified baseline cholinesterase and bilirubin as the most important variables (forest-averaged lowest minimal depth, 1.2 and 1.5, respectively), followed by the type of primary tumor (1.7), age (2.4), tumor burden (2.8), and presence of extrahepatic disease (3.5). Sex had the highest forest-averaged minimal depth (5.5), indicating little predictive value. Baseline bilirubin levels above 1.5 mg/dL were associated with a steep increase in predicted mortality. Similarly, cholinesterase levels below 7.5 U predicted a strong increase in mortality. The trained random survival forest achieved a concordance index of 0.657, with an SE of 0.02, comparable to the concordance index of 0.652 and SE of 0.02 for a previously published Cox proportional hazards model. Conclusion: Random survival forests are a simple and straightforward machine-learning approach for prediction of overall survival. The predictive performance of the trained model

  2. Geometry of the q-exponential distribution with dependent competing risks and accelerated life testing

    Science.gov (United States)

    Zhang, Fode; Shi, Yimin; Wang, Ruibing

    2017-02-01

    In the information geometry suggested by Amari (1985) and Amari et al. (1987), a parametric statistical model can be regarded as a differentiable manifold with the parameter space as a coordinate system. Note that the q-exponential distribution plays an important role in Tsallis statistics (see Tsallis, 2009), this paper investigates the geometry of the q-exponential distribution with dependent competing risks and accelerated life testing (ALT). A copula function based on the q-exponential function, which can be considered as the generalized Gumbel copula, is discussed to illustrate the structure of the dependent random variable. Employing two iterative algorithms, simulation results are given to compare the performance of estimations and levels of association under different hybrid progressively censoring schemes (HPCSs).

  3. Comparison of variance estimators for metaanalysis of instrumental variable estimates

    NARCIS (Netherlands)

    Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.

    2016-01-01

    Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two

  4. Coverage dependent molecular assembly of anthraquinone on Au(111)

    Science.gov (United States)

    DeLoach, Andrew S.; Conrad, Brad R.; Einstein, T. L.; Dougherty, Daniel B.

    2017-11-01

    A scanning tunneling microscopy study of anthraquinone (AQ) on the Au(111) surface shows that the molecules self-assemble into several structures depending on the local surface coverage. At high coverages, a close-packed saturated monolayer is observed, while at low coverages, mobile surface molecules coexist with stable chiral hexamer clusters. At intermediate coverages, a disordered 2D porous network interlinking close-packed islands is observed in contrast to the giant honeycomb networks observed for the same molecule on Cu(111). This difference verifies the predicted extreme sensitivity [J. Wyrick et al., Nano Lett. 11, 2944 (2011)] of the pore network to small changes in the surface electronic structure. Quantitative analysis of the 2D pore network reveals that the areas of the vacancy islands are distributed log-normally. Log-normal distributions are typically associated with the product of random variables (multiplicative noise), and we propose that the distribution of pore sizes for AQ on Au(111) originates from random linear rate constants for molecules to either desorb from the surface or detach from the region of a nucleated pore.

  5. Reticulocyte dynamic and hemoglobin variability in hemodialysis patients treated with Darbepoetin alfa and C.E.R.A.: a randomized controlled trial.

    Science.gov (United States)

    Forni, Valentina; Bianchi, Giorgia; Ogna, Adam; Salvadé, Igor; Vuistiner, Philippe; Burnier, Michel; Gabutti, Luca

    2013-07-22

    In a simulation based on a pharmacokinetic model we demonstrated that increasing the erythropoiesis stimulating agents (ESAs) half-life or shortening their administration interval decreases hemoglobin variability. The benefit of reducing the administration interval was however lessened by the variability induced by more frequent dosage adjustments. The purpose of this study was to analyze the reticulocyte and hemoglobin kinetics and variability under different ESAs and administration intervals in a collective of chronic hemodialysis patients. The study was designed as an open-label, randomized, four-period cross-over investigation, including 30 patients under chronic hemodialysis at the regional hospital of Locarno (Switzerland) in February 2010 and lasting 2 years. Four subcutaneous treatment strategies (C.E.R.A. every 4 weeks Q4W and every 2 weeks Q2W, Darbepoetin alfa Q4W and Q2W) were compared with each other. The mean square successive difference of hemoglobin, reticulocyte count and ESAs dose was used to quantify variability. We distinguished a short- and a long-term variability based respectively on the weekly and monthly successive difference. No difference was found in the mean values of biological parameters (hemoglobin, reticulocytes, and ferritin) between the 4 strategies. ESAs type did not affect hemoglobin and reticulocyte variability, but C.E.R.A induced a more sustained reticulocytes response over time and increased the risk of hemoglobin overshooting (OR 2.7, p = 0.01). Shortening the administration interval lessened the amplitude of reticulocyte count fluctuations but resulted in more frequent ESAs dose adjustments and in amplified reticulocyte and hemoglobin variability. Q2W administration interval was however more favorable in terms of ESAs dose, allowing a 38% C.E.R.A. dose reduction, and no increase of Darbepoetin alfa. The reticulocyte dynamic was a more sensitive marker of time instability of the hemoglobin response under ESAs therapy

  6. BROAD ABSORPTION LINE VARIABILITY ON MULTI-YEAR TIMESCALES IN A LARGE QUASAR SAMPLE

    Energy Technology Data Exchange (ETDEWEB)

    Filiz Ak, N.; Brandt, W. N.; Schneider, D. P. [Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802 (United States); Hall, P. B. [Department of Physics and Astronomy, York University, 4700 Keele St., Toronto, Ontario, M3J 1P3 (Canada); Anderson, S. F. [Astronomy Department, University of Washington, Seattle, WA 98195 (United States); Hamann, F. [Department of Astronomy, University of Florida, Gainesville, FL 32611-2055 (United States); Lundgren, B. F. [Department of Astronomy, University of Wisconsin, Madison, WI 53706 (United States); Myers, Adam D. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 (United States); Pâris, I. [Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Santiago (Chile); Petitjean, P. [Universite Paris 6, Institut d' Astrophysique de Paris, 75014, Paris (France); Ross, Nicholas P. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 92420 (United States); Shen, Yue [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., MS-51, Cambridge, MA 02138 (United States); York, Don, E-mail: nfilizak@astro.psu.edu [The University of Chicago, Department of Astronomy and Astrophysics, Chicago, IL 60637 (United States)

    2013-11-10

    We present a detailed investigation of the variability of 428 C IV and 235 Si IV broad absorption line (BAL) troughs identified in multi-epoch observations of 291 quasars by the Sloan Digital Sky Survey-I/II/III. These observations primarily sample rest-frame timescales of 1-3.7 yr over which significant rearrangement of the BAL wind is expected. We derive a number of observational results on, e.g., the frequency of BAL variability, the velocity range over which BAL variability occurs, the primary observed form of BAL-trough variability, the dependence of BAL variability upon timescale, the frequency of BAL strengthening versus weakening, correlations between BAL variability and BAL-trough profiles, relations between C IV and Si IV BAL variability, coordinated multi-trough variability, and BAL variations as a function of quasar properties. We assess implications of these observational results for quasar winds. Our results support models where most BAL absorption is formed within an order-of-magnitude of the wind-launching radius, although a significant minority of BAL troughs may arise on larger scales. We estimate an average lifetime for a BAL trough along our line-of-sight of a few thousand years. BAL disappearance and emergence events appear to be extremes of general BAL variability, rather than being qualitatively distinct phenomena. We derive the parameters of a random-walk model for BAL EW variability, finding that this model can acceptably describe some key aspects of EW variability. The coordinated trough variability of BAL quasars with multiple troughs suggests that changes in 'shielding gas' may play a significant role in driving general BAL variability.

  7. Generated effect modifiers (GEM’s) in randomized clinical trials

    Science.gov (United States)

    Petkova, Eva; Tarpey, Thaddeus; Su, Zhe; Ogden, R. Todd

    2017-01-01

    In a randomized clinical trial (RCT), it is often of interest not only to estimate the effect of various treatments on the outcome, but also to determine whether any patient characteristic has a different relationship with the outcome, depending on treatment. In regression models for the outcome, if there is a non-zero interaction between treatment and a predictor, that predictor is called an “effect modifier”. Identification of such effect modifiers is crucial as we move towards precision medicine, that is, optimizing individual treatment assignment based on patient measurements assessed when presenting for treatment. In most settings, there will be several baseline predictor variables that could potentially modify the treatment effects. This article proposes optimal methods of constructing a composite variable (defined as a linear combination of pre-treatment patient characteristics) in order to generate an effect modifier in an RCT setting. Several criteria are considered for generating effect modifiers and their performance is studied via simulations. An example from a RCT is provided for illustration. PMID:27465235

  8. Stimulus-dependent state transition between synchronized oscillation and randomly repetitive burst in a model cerebellar granular layer.

    Directory of Open Access Journals (Sweden)

    Takeru Honda

    2011-07-01

    Full Text Available Information processing of the cerebellar granular layer composed of granule and Golgi cells is regarded as an important first step toward the cerebellar computation. Our previous theoretical studies have shown that granule cells can exhibit random alternation between burst and silent modes, which provides a basis of population representation of the passage-of-time (POT from the onset of external input stimuli. On the other hand, another computational study has reported that granule cells can exhibit synchronized oscillation of activity, as consistent with observed oscillation in local field potential recorded from the granular layer while animals keep still. Here we have a question of whether an identical network model can explain these distinct dynamics. In the present study, we carried out computer simulations based on a spiking network model of the granular layer varying two parameters: the strength of a current injected to granule cells and the concentration of Mg²⁺ which controls the conductance of NMDA channels assumed on the Golgi cell dendrites. The simulations showed that cells in the granular layer can switch activity states between synchronized oscillation and random burst-silent alternation depending on the two parameters. For higher Mg²⁺ concentration and a weaker injected current, granule and Golgi cells elicited spikes synchronously (synchronized oscillation state. In contrast, for lower Mg²⁺ concentration and a stronger injected current, those cells showed the random burst-silent alternation (POT-representing state. It is suggested that NMDA channels on the Golgi cell dendrites play an important role for determining how the granular layer works in response to external input.

  9. SU-F-T-113: Inherent Functional Dependence of Spinal Cord Doses of Variable Irradiated Volumes in Spine SBRT

    Energy Technology Data Exchange (ETDEWEB)

    Ma, L; Braunstein, S; Chiu, J [University of California San Francisco, San Francisco, CA (United States); Sahgal, A [Sunnybrook Health Sciences Center, University of Toronto, Toronto, Ontario (Canada)

    2016-06-15

    Purpose: Spinal cord tolerance for SBRT has been recommended for the maximum point dose level or at irradiated volumes such as 0.35 mL or 10% of contoured volumes. In this study, we investigated an inherent functional relationship that associates these dose surrogates for irradiated spinal cord volumes of up to 3.0 mL. Methods: A hidden variable termed as Effective Dose Radius (EDR) was formulated based on a dose fall-off model to correlate dose at irradiated spinal cord volumes ranging from 0 mL (point maximum) to 3.0 mL. A cohort of 15 spine SBRT cases was randomly selected to derive an EDR-parameterized formula. The mean prescription dose for the studied cases was 21.0±8.0 Gy (range, 10–40Gy) delivered in 3±1 fractions with target volumes of 39.1 ± 70.6 mL. Linear regression and variance analysis were performed for the fitting parameters of variable EDR values. Results: No direct correlation was found between the dose at maximum point and doses at variable spinal cord volumes. For example, Pearson R{sup 2} = 0.643 and R{sup 2}= 0.491 were obtained when correlating the point maximum dose with the spinal cord dose at 1 mL and 3 mL, respectively. However, near perfect correlation (R{sup 2} ≥0.99) was obtained when corresponding parameterized EDRs. Specifically, Pearson R{sup 2}= 0.996 and R{sup 2} = 0.990 were obtained when correlating EDR (maximum point dose) with EDR (dose at 1 mL) and EDR(dose at 3 mL), respectively. As a result, high confidence level look-up tables were established to correlate spinal cord doses at the maximum point to any finite irradiated volumes. Conclusion: An inherent functional relationship was demonstrated for spine SBRT. Such a relationship unifies dose surrogates at variable cord volumes and proves that a single dose surrogate (e.g. point maximum dose) is mathematically sufficient in constraining the overall spinal cord dose tolerance for SBRT.

  10. The implications of environmental variability on caribou demography: theoretical considerations

    Directory of Open Access Journals (Sweden)

    James A. Schaefer

    1991-10-01

    Full Text Available Random environmental influences, such as snow cover, are widely regarded as an integral feature of caribou population dynamics. We conducted computer simulations to explore the ramifications of such stochastic variability for caribou demography. We devised 4 models with increasing levels of complexity: Model 1, density-independence under different levels of stochasticity and r; Model 2, non-linear effect of snow cover on r; Model 3, non-linear effect of snow cover on r and stochasticity as a function of population size; and Model 4, non-linear effect of snow cover on r, stochasticity as a funciton of population size, and density-dependence according to the logistic equation. The results of Model 1 indicated that nearly all caribou populations subject only to environmental vagaries experienced either extincition or irruption. Model 2 revealed that non-linear effect of snow cover depressed the realised r as a function of population size. Finally, Model 4 suggested long-term population as previously reported in literature, but with reduced chance of overshooting K under moderate to high environmental variability.

  11. The Study of the Effectiveness of Olanzapine as a Maintenance Treatment in Opioid Dependents, a Randomized Clinical Trial

    Directory of Open Access Journals (Sweden)

    Azarekhsh Mokri

    2009-08-01

    Full Text Available Introduction: In this research, researchers want to study the effectiveness of Olanzapine on reduction of substance abuse relapse among people who are dependent to opioid material, merely. Method: A randomized clinical trial was designed. The population was opioid dependence subjects (only men that were diagnosed based on DSM-IV TR criteria, and referred to national center of addiction studies clinic. Detoxification was done by using of Clonidine, Clonazepam, Disiklomin, and NSAIDS within7 through 10 days. In second stage, the Patients who were referred to the clinic those men who had satisfied criterions selected. Demographic forms, testimonial certificate, Addiction Severity Index, Beck Depression Questionnaire, Zung Self report anxiety test administered among selected sample. Sample divided to two groups (placebo and Olanzapine the research last for 8 weeks. Results: the results showed that addiction severity reduced in both groups, but there was not significant difference in reduction of addiction severity between two groups. There was significant difference in depression and anxiety among mean scores of base line and follow up in both groups but there was not significant difference between two groups in follow up measures. Conclusion: Altogether, the results did not confirm the effectiveness of Olanzapine on maintenance treatment of opioid dependence.

  12. Non-random mating and convergence over time for alcohol consumption, smoking, and exercise: the Nord-Trøndelag Health Study.

    Science.gov (United States)

    Ask, Helga; Rognmo, Kamilla; Torvik, Fartein Ask; Røysamb, Espen; Tambs, Kristian

    2012-05-01

    Spouses tend to have similar lifestyles. We explored the degree to which spouse similarity in alcohol use, smoking, and physical exercise is caused by non-random mating or convergence. We used data collected for the Nord-Trøndelag Health Study from 1984 to 1986 and prospective registry information about when and with whom people entered marriage/cohabitation between 1970 and 2000. Our sample included 19,599 married/cohabitating couples and 1,551 future couples that were to marry/cohabitate in the 14-16 years following data collection. All couples were grouped according to the duration between data collection and entering into marriage/cohabitation. Age-adjusted polychoric spouse correlations were used as the dependent variables in non-linear segmented regression analysis; the independent variable was time. The results indicate that spouse concordance in lifestyle is due to both non-random mating and convergence. Non-random mating appeared to be strongest for smoking. Convergence in alcohol use and smoking was evident during the period prior to marriage/cohabitation, whereas convergence in exercise was evident throughout life. Reduced spouse similarity in smoking with relationship duration may reflect secular trends.

  13. Computational procedure of optimal inventory model involving controllable backorder rate and variable lead time with defective units

    Science.gov (United States)

    Lee, Wen-Chuan; Wu, Jong-Wuu; Tsou, Hsin-Hui; Lei, Chia-Ling

    2012-10-01

    This article considers that the number of defective units in an arrival order is a binominal random variable. We derive a modified mixture inventory model with backorders and lost sales, in which the order quantity and lead time are decision variables. In our studies, we also assume that the backorder rate is dependent on the length of lead time through the amount of shortages and let the backorder rate be a control variable. In addition, we assume that the lead time demand follows a mixture of normal distributions, and then relax the assumption about the form of the mixture of distribution functions of the lead time demand and apply the minimax distribution free procedure to solve the problem. Furthermore, we develop an algorithm procedure to obtain the optimal ordering strategy for each case. Finally, three numerical examples are also given to illustrate the results.

  14. A variable thickness window: Thermal and structural analyses

    International Nuclear Information System (INIS)

    Wang, Zhibi; Kuzay, T.M.

    1994-01-01

    In this paper, the finite difference formulations for variable thickness thermal analysis and variable thickness plane stress analysis are presented. In heat transfer analysis, radiation effects and temperature-dependent thermal conductivity are taken into account. While in thermal stress analysis, the thermal expansion coefficient is considered as temperature dependent. An application of the variable thickness window to an Advanced Photon Source beamline is presented

  15. Meteorological variables affect fertility rate after intrauterine artificial insemination in sheep in a seasonal-dependent manner: a 7-year study

    Science.gov (United States)

    Palacios, C.; Abecia, J. A.

    2015-05-01

    A total number of 48,088 artificial inseminations (AIs) have been controlled during seven consecutive years in 79 dairy sheep Spanish farms (41° N). Mean, maximum and minimum ambient temperatures ( Ts), temperature amplitude (TA), mean relative humidity (RH), mean solar radiation (SR) and total rainfall of each insemination day and 15 days later were recorded. Temperature-humidity index (THI) and effective temperature (ET) have been calculated. A binary logistic regression model to estimate the risk of not getting pregnant compared to getting pregnant, through the odds ratio (OR), was performed. Successful winter inseminations were carried out under higher SR ( P 1 (maximum T, ET and rainfall on AI day, and ET and rainfall on day 15), and two variables presented OR AI day and maximum T on day 15). However, the effect of meteorological factors affected fertility in opposite ways, so T becomes a protective or risk factor on fertility depending on season. In conclusion, the percentage of pregnancy after AI in sheep is significantly affected by meteorological variables in a seasonal-dependent manner, so the parameters such as temperature reverse their effects in the hot or cold seasons. A forecast of the meteorological conditions could be a useful tool when AI dates are being scheduled.

  16. Chemical Variability and Biological Activities of Brassica rapa var. rapifera Parts Essential Oils Depending on Geographic Variation and Extraction Technique.

    Science.gov (United States)

    Saka, Boualem; Djouahri, Abderrahmane; Djerrad, Zineb; Terfi, Souhila; Aberrane, Sihem; Sabaou, Nasserdine; Baaliouamer, Aoumeur; Boudarene, Lynda

    2017-06-01

    In the present work, the Brassica rapa var. rapifera parts essential oils and their antioxidant and antimicrobial activities were investigated for the first time depending on geographic origin and extraction technique. Gas-chromatography (GC) and GC/mass spectrometry (MS) analyses showed several constituents, including alcohols, aldehydes, esters, ketones, norisoprenoids, terpenic, nitrogen and sulphur compounds, totalizing 38 and 41 compounds in leaves and root essential oils, respectively. Nitrogen compounds were the main volatiles in leaves essential oils and sulphur compounds were the main volatiles in root essential oils. Qualitative and quantitative differences were found among B. rapa var. rapifera parts essential oils collected from different locations and extracted by hydrodistillation and microwave-assisted hydrodistillation techniques. Furthermore, our findings showed a high variability for both antioxidant and antimicrobial activities. The highlighted variability reflects the high impact of plant part, geographic variation and extraction technique on chemical composition and biological activities, which led to conclude that we should select essential oils to be investigated carefully depending on these factors, in order to isolate the bioactive components or to have the best quality of essential oil in terms of biological activities and preventive effects in food. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

  17. The time-dependent relativistic mean-field theory and the random phase approximation

    International Nuclear Information System (INIS)

    Ring, P.; Ma, Zhong-yu; Van Giai, Nguyen; Vretenar, D.; Wandelt, A.; Cao, Li-gang

    2001-01-01

    The Relativistic Random Phase Approximation (RRPA) is derived from the Time-Dependent Relativistic Mean-Field (TD RMF) theory in the limit of small amplitude oscillations. In the no-sea approximation of the RMF theory, the RRPA configuration space includes not only the usual particle-hole ph-states, but also αh-configurations, i.e. pairs formed from occupied states in the Fermi sea and empty negative-energy states in the Dirac sea. The contribution of the negative-energy states to the RRPA matrices is examined in a schematic model, and the large effect of Dirac-sea states on isoscalar strength distributions is illustrated for the giant monopole resonance in 116 Sn. It is shown that, because the matrix elements of the time-like component of the vector-meson fields which couple the αh-configurations with the ph-configurations are strongly reduced with respect to the corresponding matrix elements of the isoscalar scalar meson field, the inclusion of states with unperturbed energies more than 1.2 GeV below the Fermi energy has a pronounced effect on giant resonances with excitation energies in the MeV region. The influence of nuclear magnetism, i.e. the effect of the spatial components of the vector fields is examined, and the difference between the nonrelativistic and relativistic RPA predictions for the nuclear matter compression modulus is explained

  18. Perturbation Solutions for Random Linear Structural Systems subject to Random Excitation using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Köyluoglu, H.U.; Nielsen, Søren R.K.; Cakmak, A.S.

    1994-01-01

    perturbation method using stochastic differential equations. The joint statistical moments entering the perturbation solution are determined by considering an augmented dynamic system with state variables made up of the displacement and velocity vector and their first and second derivatives with respect......The paper deals with the first and second order statistical moments of the response of linear systems with random parameters subject to random excitation modelled as white-noise multiplied by an envelope function with random parameters. The method of analysis is basically a second order...... to the random parameters of the problem. Equations for partial derivatives are obtained from the partial differentiation of the equations of motion. The zero time-lag joint statistical moment equations for the augmented state vector are derived from the Itô differential formula. General formulation is given...

  19. Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

    Science.gov (United States)

    Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

    2018-07-01

    Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

  20. Extracting random numbers from quantum tunnelling through a single diode.

    Science.gov (United States)

    Bernardo-Gavito, Ramón; Bagci, Ibrahim Ethem; Roberts, Jonathan; Sexton, James; Astbury, Benjamin; Shokeir, Hamzah; McGrath, Thomas; Noori, Yasir J; Woodhead, Christopher S; Missous, Mohamed; Roedig, Utz; Young, Robert J

    2017-12-19

    Random number generation is crucial in many aspects of everyday life, as online security and privacy depend ultimately on the quality of random numbers. Many current implementations are based on pseudo-random number generators, but information security requires true random numbers for sensitive applications like key generation in banking, defence or even social media. True random number generators are systems whose outputs cannot be determined, even if their internal structure and response history are known. Sources of quantum noise are thus ideal for this application due to their intrinsic uncertainty. In this work, we propose using resonant tunnelling diodes as practical true random number generators based on a quantum mechanical effect. The output of the proposed devices can be directly used as a random stream of bits or can be further distilled using randomness extraction algorithms, depending on the application.

  1. Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships.

    Science.gov (United States)

    Rassen, Jeremy A; Brookhart, M Alan; Glynn, Robert J; Mittleman, Murray A; Schneeweiss, Sebastian

    2009-12-01

    The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of "exchangeability" between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects.

  2. Machine learning techniques to select variable stars

    Directory of Open Access Journals (Sweden)

    García-Varela Alejandro

    2017-01-01

    Full Text Available In order to perform a supervised classification of variable stars, we propose and evaluate a set of six features extracted from the magnitude density of the light curves. They are used to train automatic classification systems using state-of-the-art classifiers implemented in the R statistical computing environment. We find that random forests is the most successful method to select variables.

  3. Separating the contributions of variability and parameter uncertainty in probability distributions

    International Nuclear Information System (INIS)

    Sankararaman, S.; Mahadevan, S.

    2013-01-01

    This paper proposes a computational methodology to quantify the individual contributions of variability and distribution parameter uncertainty to the overall uncertainty in a random variable. Even if the distribution type is assumed to be known, sparse or imprecise data leads to uncertainty about the distribution parameters. If uncertain distribution parameters are represented using probability distributions, then the random variable can be represented using a family of probability distributions. The family of distributions concept has been used to obtain qualitative, graphical inference of the contributions of natural variability and distribution parameter uncertainty. The proposed methodology provides quantitative estimates of the contributions of the two types of uncertainty. Using variance-based global sensitivity analysis, the contributions of variability and distribution parameter uncertainty to the overall uncertainty are computed. The proposed method is developed at two different levels; first, at the level of a variable whose distribution parameters are uncertain, and second, at the level of a model output whose inputs have uncertain distribution parameters

  4. Exactly solvable quantum state reduction models with time-dependent coupling

    International Nuclear Information System (INIS)

    Brody, Dorje C; Constantinou, Irene C; Dear, James D C; Hughston, Lane P

    2006-01-01

    A closed-form solution to the energy-based stochastic Schroedinger equation with a time-dependent coupling is obtained. The solution is algebraic in character, and is expressed directly in terms of independent random data. The data consist of (i) a random variable H which has the distribution P(H=E i ) = π i , where π i is the transition probability vertical bar (ψ 0 vertical bar Φ i ) vertical bar 2 from the initial state vertical bar ψ 0 ) to the Lueders state vertical bar Φ i ) with energy E i , and (ii) an independent P-Brownian motion, where P is the physical probability measure associated with the dynamics of the reduction process. When the coupling is time independent, it is known that state reduction occurs asymptotically-that is to say, over an infinite time horizon. In the case of a time-dependent coupling, we show that if the magnitude of the coupling decreases sufficiently rapidly, then the energy variance will be reduced under the dynamics, but the state need not reach an energy eigenstate. This situation corresponds to the case of a 'partial' or 'incomplete' measurement of the energy. We also construct an example of a model where the opposite situation prevails, in which complete state reduction is achieved after the passage of a finite period of time

  5. Prediction of university student’s addictability based on some demographic variables, academic procrastination, and interpersonal variables

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Tavakoli

    2014-02-01

    Full Text Available Objectives: This study aimed to predict addictability among the students, based on demographic variables, academic procrastination, and interpersonal variables, and also to study the prevalence of addictability among these students. Method: The participants were 500 students (260 females, 240 males selected through a stratified random sampling among the students in Islamic Azad University Branch Abadan. The participants were assessed through Individual specification inventory, addiction potential scale and Aitken procrastination Inventory. Findings: The findings showed %23/6 of students’ readiness for addiction. Men showed higher addictability than women, but age wasn’t an issue. Also variables such as economic status, age, major, and academic procrastination predicted %13, and among interpersonal variables, the variables of having friends who use drugs and dissociated family predicted %13/2 of the variance in addictability. Conclusion: This study contains applied implications for addiction prevention.

  6. Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

    Science.gov (United States)

    Sepehry-Fard, F.; Coulthard, Maurice H.

    1995-01-01

    The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

  7. A Note on the Correlated Random Coefficient Model

    DEFF Research Database (Denmark)

    Kolodziejczyk, Christophe

    In this note we derive the bias of the OLS estimator for a correlated random coefficient model with one random coefficient, but which is correlated with a binary variable. We provide set-identification to the parameters of interest of the model. We also show how to reduce the bias of the estimator...

  8. A Core Language for Separate Variability Modeling

    DEFF Research Database (Denmark)

    Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej; Schaefer, Ina

    2014-01-01

    Separate variability modeling adds variability to a modeling language without requiring modifications of the language or the supporting tools. We define a core language for separate variability modeling using a single kind of variation point to define transformations of software artifacts in object...... hierarchical dependencies between variation points via copying and flattening. Thus, we reduce a model with intricate dependencies to a flat executable model transformation consisting of simple unconditional local variation points. The core semantics is extremely concise: it boils down to two operational rules...

  9. Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants.

    Science.gov (United States)

    Miller, Tom E X

    2007-07-01

    1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.

  10. Generated effect modifiers (GEM's) in randomized clinical trials.

    Science.gov (United States)

    Petkova, Eva; Tarpey, Thaddeus; Su, Zhe; Ogden, R Todd

    2017-01-01

    In a randomized clinical trial (RCT), it is often of interest not only to estimate the effect of various treatments on the outcome, but also to determine whether any patient characteristic has a different relationship with the outcome, depending on treatment. In regression models for the outcome, if there is a non-zero interaction between treatment and a predictor, that predictor is called an "effect modifier". Identification of such effect modifiers is crucial as we move towards precision medicine, that is, optimizing individual treatment assignment based on patient measurements assessed when presenting for treatment. In most settings, there will be several baseline predictor variables that could potentially modify the treatment effects. This article proposes optimal methods of constructing a composite variable (defined as a linear combination of pre-treatment patient characteristics) in order to generate an effect modifier in an RCT setting. Several criteria are considered for generating effect modifiers and their performance is studied via simulations. An example from a RCT is provided for illustration. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. On Direction of Dependence in Latent Variable Contexts

    Science.gov (United States)

    von Eye, Alexander; Wiedermann, Wolfgang

    2014-01-01

    Approaches to determining direction of dependence in nonexperimental data are based on the relation between higher-than second-order moments on one side and correlation and regression models on the other. These approaches have experienced rapid development and are being applied in contexts such as research on partner violence, attention deficit…

  12. Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

    Directory of Open Access Journals (Sweden)

    Zedong eBi

    2016-02-01

    Full Text Available In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis. Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e. synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons. Neurons (including the post-synaptic neuron in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1 synchronous firing and burstiness tend to increase DiffV, (2 heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3 heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our

  13. Improving tobacco dependence treatment outcomes for smokers of lower socioeconomic status: A randomized clinical trial.

    Science.gov (United States)

    Sheffer, Christine E; Bickel, Warren K; Franck, Christopher T; Panissidi, Luana; Pittman, Jami C; Stayna, Helen; Evans, Shenell

    2017-12-01

    Evidence-based treatments for tobacco dependence are significantly less effective for smokers of lower socioeconomic status which contributes to socioeconomic disparities in smoking prevalence rates and health. We aimed to reduce the socioeconomic gradient in treatment outcomes by systematically adapting evidence-based, cognitive-behavioral treatment for tobacco dependence for diverse lower socioeconomic smokers. Participants were randomized to adapted or standard treatment, received six 1-h group treatment sessions, and were followed for six months. We examined the effectiveness of the adapted treatment to improve treatment outcomes for lower socioeconomic groups. Participants (n=227) were ethnically, racially, and socioeconomically diverse. The adapted treatment significantly reduced the days to relapse for the two lowest socioeconomic groups: SES1: M=76.6 (SD 72.9) vs. 38.3 (SD 60.1) days to relapse (RR=0.63 95% CI, 0.45, 0.88, p=0.0013); SES2: M=88.2 (SD 67.3) vs. 40.1 (SD 62.6 days to relapse (RR=0.57 95% CI, 0.18, 0.70, p=0.0024). Interactions between socioeconomic status and condition were significant for initial abstinence (OR=1.26, 95% CI 1.09, 1.46, p=0.002), approached significance for 3-month abstinence (OR=0.90, 95% CI 0.80, 1.01, psocioeconomic smokers and reduce inequities in days to relapse. Novel methods of providing targeted extended support are needed to improve long-term outcomes. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Survivor bias in Mendelian randomization analysis

    DEFF Research Database (Denmark)

    Vansteelandt, Stijn; Dukes, Oliver; Martinussen, Torben

    2017-01-01

    Mendelian randomization studies employ genotypes as experimental handles to infer the effect of genetically modified exposures (e.g. vitamin D exposure) on disease outcomes (e.g. mortality). The statistical analysis of these studies makes use of the standard instrumental variables framework. Many...... of these studies focus on elderly populations, thereby ignoring the problem of left truncation, which arises due to the selection of study participants being conditional upon surviving up to the time of study onset. Such selection, in general, invalidates the assumptions on which the instrumental variables...... analysis rests. We show that Mendelian randomization studies of adult or elderly populations will therefore, in general, return biased estimates of the exposure effect when the considered genotype affects mortality; in contrast, standard tests of the causal null hypothesis that the exposure does not affect...

  15. Mitochondria and the non-genetic origins of cell-to-cell variability: More is different.

    Science.gov (United States)

    Guantes, Raúl; Díaz-Colunga, Juan; Iborra, Francisco J

    2016-01-01

    Gene expression activity is heterogeneous in a population of isogenic cells. Identifying the molecular basis of this variability will improve our understanding of phenomena like tumor resistance to drugs, virus infection, or cell fate choice. The complexity of the molecular steps and machines involved in transcription and translation could introduce sources of randomness at many levels, but a common constraint to most of these processes is its energy dependence. In eukaryotic cells, most of this energy is provided by mitochondria. A clonal population of cells may show a large variability in the number and functionality of mitochondria. Here, we discuss how differences in the mitochondrial content of each cell contribute to heterogeneity in gene products. Changes in the amount of mitochondria can also entail drastic alterations of a cell's gene expression program, which ultimately leads to phenotypic diversity. Also watch the Video Abstract. © 2015 WILEY Periodicals, Inc.

  16. Valuing travel time variability: Characteristics of the travel time distribution on an urban road

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Fukuda, Daisuke

    2012-01-01

    This paper provides a detailed empirical investigation of the distribution of travel times on an urban road for valuation of travel time variability. Our investigation is premised on the use of a theoretical model with a number of desirable properties. The definition of the value of travel time...... variability depends on certain properties of the distribution of random travel times that require empirical verification. Applying a range of nonparametric statistical techniques to data giving minute-by-minute travel times for a congested urban road over a period of five months, we show that the standardized...... travel time is roughly independent of the time of day as required by the theory. Except for the extreme right tail, a stable distribution seems to fit the data well. The travel time distributions on consecutive links seem to share a common stability parameter such that the travel time distribution...

  17. An Undergraduate Research Experience on Studying Variable Stars

    Science.gov (United States)

    Amaral, A.; Percy, J. R.

    2016-06-01

    We describe and evaluate a summer undergraduate research project and experience by one of us (AA), under the supervision of the other (JP). The aim of the project was to sample current approaches to analyzing variable star data, and topics related to the study of Mira variable stars and their astrophysical importance. This project was done through the Summer Undergraduate Research Program (SURP) in astronomy at the University of Toronto. SURP allowed undergraduate students to explore and learn about many topics within astronomy and astrophysics, from instrumentation to cosmology. SURP introduced students to key skills which are essential for students hoping to pursue graduate studies in any scientific field. Variable stars proved to be an excellent topic for a research project. For beginners to independent research, it introduces key concepts in research such as critical thinking and problem solving, while illuminating previously learned topics in stellar physics. The focus of this summer project was to compare observations with structural and evolutionary models, including modelling the random walk behavior exhibited in the (O-C) diagrams of most Mira stars. We found that the random walk could be modelled by using random fluctuations of the period. This explanation agreed well with observations.

  18. Resistor capacitor, primitive variable solution of buoyant fluid flow within an enclosure with highly temperature dependent viscosity

    Energy Technology Data Exchange (ETDEWEB)

    Burns, S.P. [Texas Univ., Austin, TX (United States); Gianoulakis, S.E. [Sandia National Labs., Albuquerque, NM (United States)

    1995-07-01

    A numerical solution for buoyant natural convection within a square enclosure containing a fluid with highly temperature dependent viscosity is presented. Although the fluid properties employed do not represent any real fluid, the large variation in the fluid viscosity with temperature is characteristic of turbulent flow modeling with eddy-viscosity concepts. Results are obtained using a primitive variable formulation and the resistor method. The results presented include velocity, temperature and pressure distributions within the enclosure as well as shear stress and heat flux distributions along the enclosure walls. Three mesh refinements were employed and uncertainty values are suggested for the final mesh refinement. These solutions are part of a contributed benchmark solution set for the subject problem.

  19. Moderate- vs high-dose methadone in the treatment of opioid dependence: a randomized trial.

    Science.gov (United States)

    Strain, E C; Bigelow, G E; Liebson, I A; Stitzer, M L

    1999-03-17

    Methadone hydrochloride treatment is the most common pharmacological intervention for opioid dependence, and recent interest has focused on expanding methadone treatment availability beyond traditional specially licensed clinics. However, despite recommendations regarding effective dosing of methadone, controlled clinical trials of higher-dose methadone have not been conducted. To compare the relative clinical efficacy of moderate- vs high-dose methadone in the treatment of opioid dependence. A 40-week randomized, double-blind clinical trial starting in June 1992 and ending in October 1995. Outpatient substance abuse treatment research clinic at the Johns Hopkins University Bayview Campus, Baltimore, Md. One hundred ninety-two eligible clinic patients. Daily oral methadone hydrochloride in the dose range of 40 to 50 mg (n = 97) or 80 to 100 mg (n = 95), with concurrent substance abuse counseling. Opioid-positive urinalysis results and retention in treatment. By intent-to-treat analysis through week 30 patients in the high-dose group had significantly lower rates of opioid-positive urine samples compared with patients in the moderate-dose group (53.0% [95% confidence interval [CI], 46.9%-59.2%] vs 61.9% [95% CI, 55.9%-68.0%]; P = .047. These differences persisted during withdrawal from methadone. Through day 210 no significant difference was evident between dose groups in treatment retention (high-dose group mean retention, 159 days; moderate-dose group mean retention, 157 days). Nineteen (33%) of 57 patients in the high-dose group and 11 (20%) of 54 patients in the moderate-dose group completed detoxification. Both moderate- and high-dose methadone treatment resulted in decreased illicit opioid use during methadone maintenance and detoxification. The high-dose group had significantly greater decreases in illicit opioid use.

  20. Client satisfaction among participants in a randomized trial comparing oral methadone and injectable diacetylmorphine for long-term opioid-dependency

    Directory of Open Access Journals (Sweden)

    Brissette Suzanne

    2011-07-01

    Full Text Available Abstract Background Substitution with opioid-agonists (e.g., methadone has shown to be an effective treatment for chronic long-term opioid dependency. Patient satisfaction with treatment has been associated with improved addiction treatment outcomes. However, there is a paucity of studies evaluating patients' satisfaction with Opioid Substitution Treatment (OST. In the present study, participants' satisfaction with OST was evaluated at 3 and 12 months. We sought to test the relationship between satisfaction and patients' characteristics, the treatment modality received and treatment outcomes. Methods Data from a randomized controlled trial, the North American Opiate Medication Initiative (NAOMI, conducted in Vancouver and Montreal (Canada between 2005-2008, was analyzed. The NAOMI study compared the effectiveness of oral methadone vs. injectable diacetylmorphine over 12 months. A small sub-group of patients received injectable hydromorphone on a double blind basis with diacetylmorphine. The Client Satisfaction Questionnaire (CSQ-8 was used to measure satisfaction with treatment. CSQ-8 scores, as well as retention and response to treatment, did not differ between those receiving hydromorphone and diacetylmorphine at 3 or 12 months assessments; therefore, these two groups were analyzed together as the 'injectable' treatment group. Results A total of 232 (92% and 237 (94% participants completed the CSQ-8 at 3 and 12 months, respectively. Participants in both groups were highly satisfied with treatment. Independent of treatment group, participants satisfied with treatment at 3 months were more likely to be retained at 12 months. Multivariate analysis indicated that satisfaction was greater among those randomized to the injection group after controlling for treatment effectiveness. Participants who were retained, responded to treatment, and had fewer psychological symptoms were more satisfied with treatment. Finally, open-ended comments were made by

  1. Demographic and psychological variables affecting test subject evaluations of ride quality

    Science.gov (United States)

    Duncan, N. C.; Conley, H. W.

    1975-01-01

    Ride-quality experiments similar in objectives, design, and procedure were conducted, one using the U.S. Air Force Total In-Flight Simulator and the other using the Langley Passenger Ride Quality Apparatus to provide the motion environments. Large samples (80 or more per experiment) of test subjects were recruited from the Tidewater Virginia area and asked to rate the comfort (on a 7-point scale) of random aircraft motion typical of that encountered during STOL flights. Test subject characteristics of age, sex, and previous flying history (number of previous airplane flights) were studied in a two by three by three factorial design. Correlations were computed between one dependent measure, the subject's mean comfort rating, and various demographic characteristics, attitudinal variables, and the scores on Spielberger's State-Trait Anxiety Inventory. An effect of sex was found in one of the studies. Males made higher (more uncomfortable) ratings of the ride than females. Age and number of previous flights were not significantly related to comfort ratings. No significant interactions between the variables of age, sex, or previous number of flights were observed.

  2. The Variability of Atmospheric Deuterium Brightness at Mars: Evidence for Seasonal Dependence

    Science.gov (United States)

    Mayyasi, Majd; Clarke, John; Bhattacharyya, Dolon; Deighan, Justin; Jain, Sonal; Chaffin, Michael; Thiemann, Edward; Schneider, Nick; Jakosky, Bruce

    2017-10-01

    The enhanced ratio of deuterium to hydrogen on Mars has been widely interpreted as indicating the loss of a large column of water into space, and the hydrogen content of the upper atmosphere is now known to be highly variable. The variation in the properties of both deuterium and hydrogen in the upper atmosphere of Mars is indicative of the dynamical processes that produce these species and propagate them to altitudes where they can escape the planet. Understanding the seasonal variability of D is key to understanding the variability of the escape rate of water from Mars. Data from a 15 month observing campaign, made by the Mars Atmosphere and Volatile Evolution Imaging Ultraviolet Spectrograph high-resolution echelle channel, are used to determine the brightness of deuterium as observed at the limb of Mars. The D emission is highly variable, with a peak in brightness just after southern summer solstice. The trends of D brightness are examined against extrinsic as well as intrinsic sources. It is found that the fluctuations in deuterium brightness in the upper atmosphere of Mars (up to 400 km), corrected for periodic solar variations, vary on timescales that are similar to those of water vapor fluctuations lower in the atmosphere (20-80 km). The observed variability in deuterium may be attributed to seasonal factors such as regional dust storm activity and subsequent circulation lower in the atmosphere.

  3. Employing online quantum random number generators for generating truly random quantum states in Mathematica

    Science.gov (United States)

    Miszczak, Jarosław Adam

    2013-01-01

    The presented package for the Mathematica computing system allows the harnessing of quantum random number generators (QRNG) for investigating the statistical properties of quantum states. The described package implements a number of functions for generating random states. The new version of the package adds the ability to use the on-line quantum random number generator service and implements new functions for retrieving lists of random numbers. Thanks to the introduced improvements, the new version provides faster access to high-quality sources of random numbers and can be used in simulations requiring large amount of random data. New version program summaryProgram title: TRQS Catalogue identifier: AEKA_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKA_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 18 134 No. of bytes in distributed program, including test data, etc.: 2 520 49 Distribution format: tar.gz Programming language: Mathematica, C. Computer: Any supporting Mathematica in version 7 or higher. Operating system: Any platform supporting Mathematica; tested with GNU/Linux (32 and 64 bit). RAM: Case-dependent Supplementary material: Fig. 1 mentioned below can be downloaded. Classification: 4.15. External routines: Quantis software library (http://www.idquantique.com/support/quantis-trng.html) Catalogue identifier of previous version: AEKA_v1_0 Journal reference of previous version: Comput. Phys. Comm. 183(2012)118 Does the new version supersede the previous version?: Yes Nature of problem: Generation of random density matrices and utilization of high-quality random numbers for the purpose of computer simulation. Solution method: Use of a physical quantum random number generator and an on-line service providing access to the source of true random

  4. Exponential gain of randomness certified by quantum contextuality

    Science.gov (United States)

    Um, Mark; Zhang, Junhua; Wang, Ye; Wang, Pengfei; Kim, Kihwan

    2017-04-01

    We demonstrate the protocol of exponential gain of randomness certified by quantum contextuality in a trapped ion system. The genuine randomness can be produced by quantum principle and certified by quantum inequalities. Recently, randomness expansion protocols based on inequality of Bell-text and Kochen-Specker (KS) theorem, have been demonstrated. These schemes have been theoretically innovated to exponentially expand the randomness and amplify the randomness from weak initial random seed. Here, we report the experimental evidence of such exponential expansion of randomness. In the experiment, we use three states of a 138Ba + ion between a ground state and two quadrupole states. In the 138Ba + ion system, we do not have detection loophole and we apply a methods to rule out certain hidden variable models that obey a kind of extended noncontextuality.

  5. Least squares estimation in a simple random coefficient autoregressive model

    DEFF Research Database (Denmark)

    Johansen, S; Lange, T

    2013-01-01

    The question we discuss is whether a simple random coefficient autoregressive model with infinite variance can create the long swings, or persistence, which are observed in many macroeconomic variables. The model is defined by yt=stρyt−1+εt,t=1,…,n, where st is an i.i.d. binary variable with p...... we prove the curious result that View the MathML source. The proof applies the notion of a tail index of sums of positive random variables with infinite variance to find the order of magnitude of View the MathML source and View the MathML source and hence the limit of View the MathML source...

  6. Effect of short-term estrogen therapy on endothelial function: a double-blinded, randomized, controlled trial.

    Science.gov (United States)

    Hurtado, R; Celani, M; Geber, S

    2016-10-01

    To evaluate the effect of short-term hormone replacement therapy with 0.625 mg conjugated estrogens daily on endothelial function of healthy postmenopausal women, using flow-mediated dilation (FMD) of the brachial artery. We performed a double-blinded, randomized, controlled trial over 3 years. Randomization was performed using computer-generated sorting. All participants were blinded to the use of conjugated equine estrogens (CEE) or placebo and FMD was assessed by a blinded examiner, before and after 28 days of medication. A total of 64 healthy postmenopausal women were selected and randomly assigned into two groups of treatment: 0.625 mg of CEE or placebo. FMD values were statistically different between the groups (p = 0.025): the group receiving CEE showed a FMD value of 0.011 compared to the placebo group (FMD = -0.082). The two groups were additionally evaluated for homogeneity through the Shapiro-Wilk test in respect to variables that could interfere with endothelial function such as age (p = 0.729), body mass index (p = 0.891), and time since menopause (p = 0.724). Other variables were excluded during selection of the participants such as chronic vascular conditions, smoking, and sedentary lifestyle. Our results demonstrate that the administration of 0.625 mg CEE for 28 days is effective in improving vascular nitric oxide-dependent dilation assessed by FMD of the brachial artery in postmenopausal women. NCT01482416.

  7. A stochastic collocation method for the second order wave equation with a discontinuous random speed

    KAUST Repository

    Motamed, Mohammad

    2012-08-31

    In this paper we propose and analyze a stochastic collocation method for solving the second order wave equation with a random wave speed and subjected to deterministic boundary and initial conditions. The speed is piecewise smooth in the physical space and depends on a finite number of random variables. The numerical scheme consists of a finite difference or finite element method in the physical space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space. This approach leads to the solution of uncoupled deterministic problems as in the Monte Carlo method. We consider both full and sparse tensor product spaces of orthogonal polynomials. We provide a rigorous convergence analysis and demonstrate different types of convergence of the probability error with respect to the number of collocation points for full and sparse tensor product spaces and under some regularity assumptions on the data. In particular, we show that, unlike in elliptic and parabolic problems, the solution to hyperbolic problems is not in general analytic with respect to the random variables. Therefore, the rate of convergence may only be algebraic. An exponential/fast rate of convergence is still possible for some quantities of interest and for the wave solution with particular types of data. We present numerical examples, which confirm the analysis and show that the collocation method is a valid alternative to the more traditional Monte Carlo method for this class of problems. © 2012 Springer-Verlag.

  8. Degree-Degree Dependencies in Random Graphs with Heavy-Tailed Degrees

    NARCIS (Netherlands)

    van der Hofstad, Remco; Litvak, Nelly

    2014-01-01

    Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, social, and biological networks are often characterized by degree-degree dependencies between neighboring nodes. In assortative networks, the degree-degree dependencies are positive (nodes with similar

  9. Statistics of α-μ Random Variables and Their Applications inWireless Multihop Relaying and Multiple Scattering Channels

    KAUST Repository

    Wang, Kezhi

    2015-06-01

    Exact results for the probability density function (PDF) and cumulative distribution function (CDF) of the sum of ratios of products (SRP) and the sum of products (SP) of independent α-μ random variables (RVs) are derived. They are in the form of 1-D integral based on the existing works on the products and ratios of α-μ RVs. In the derivation, generalized Gamma (GG) ratio approximation (GGRA) is proposed to approximate SRP. Gamma ratio approximation (GRA) is proposed to approximate SRP and the ratio of sums of products (RSP). GG approximation (GGA) and Gamma approximation (GA) are used to approximate SP. The proposed results of the SRP can be used to calculate the outage probability (OP) for wireless multihop relaying systems or multiple scattering channels with interference. The proposed results of the SP can be used to calculate the OP for these systems without interference. In addition, the proposed approximate result of the RSP can be used to calculate the OP of the signal-To-interference ratio (SIR) in a multiple scattering system with interference. © 1967-2012 IEEE.

  10. Statistics of α-μ Random Variables and Their Applications inWireless Multihop Relaying and Multiple Scattering Channels

    KAUST Repository

    Wang, Kezhi; Wang, Tian; Chen, Yunfei; Alouini, Mohamed-Slim

    2015-01-01

    Exact results for the probability density function (PDF) and cumulative distribution function (CDF) of the sum of ratios of products (SRP) and the sum of products (SP) of independent α-μ random variables (RVs) are derived. They are in the form of 1-D integral based on the existing works on the products and ratios of α-μ RVs. In the derivation, generalized Gamma (GG) ratio approximation (GGRA) is proposed to approximate SRP. Gamma ratio approximation (GRA) is proposed to approximate SRP and the ratio of sums of products (RSP). GG approximation (GGA) and Gamma approximation (GA) are used to approximate SP. The proposed results of the SRP can be used to calculate the outage probability (OP) for wireless multihop relaying systems or multiple scattering channels with interference. The proposed results of the SP can be used to calculate the OP for these systems without interference. In addition, the proposed approximate result of the RSP can be used to calculate the OP of the signal-To-interference ratio (SIR) in a multiple scattering system with interference. © 1967-2012 IEEE.

  11. Softening in Random Networks of Non-Identical Beams.

    Science.gov (United States)

    Ban, Ehsan; Barocas, Victor H; Shephard, Mark S; Picu, Catalin R

    2016-02-01

    Random fiber networks are assemblies of elastic elements connected in random configurations. They are used as models for a broad range of fibrous materials including biopolymer gels and synthetic nonwovens. Although the mechanics of networks made from the same type of fibers has been studied extensively, the behavior of composite systems of fibers with different properties has received less attention. In this work we numerically and theoretically study random networks of beams and springs of different mechanical properties. We observe that the overall network stiffness decreases on average as the variability of fiber stiffness increases, at constant mean fiber stiffness. Numerical results and analytical arguments show that for small variabilities in fiber stiffness the amount of network softening scales linearly with the variance of the fiber stiffness distribution. This result holds for any beam structure and is expected to apply to a broad range of materials including cellular solids.

  12. Time dependent variation of carrying capacity of prestressed precast beam

    Science.gov (United States)

    Le, Tuan D.; Konečný, Petr; Matečková, Pavlína

    2018-04-01

    The article deals with the evaluation of the precast concrete element time dependent carrying capacity. The variation of the resistance is inherited property of laboratory as well as in-situ members. Thus the specification of highest, yet possible, laboratory sample resistance is important with respect to evaluation of laboratory experiments based on the test machine loading capabilities. The ultimate capacity is evaluated through the bending moment resistance of a simply supported prestressed concrete beam. The probabilistic assessment is applied. Scatter of random variables of compressive strength of concrete and effective height of the cross section is considered. Monte Carlo simulation technique is used to investigate the performance of the cross section of the beam with changes of tendons’ positions and compressive strength of concrete.

  13. A Randomized Double-blind, Placebo Controlled Trial of Venlafaxine-Extended Release for Co-occurring Cannabis Dependence and Depressive Disorders

    Science.gov (United States)

    Levin, Frances R.; Mariani, John; Brooks, Daniel J.; Pavlicova, Martina; Nunes, Edward V.; Agosti, Vito; Bisaga, Adam; Sullivan, Maria A.; Carpenter, Kenneth M.

    2013-01-01

    Aim To evaluate whether venlafaxine-extended release (VEN-XR) is an effective treatment for cannabis dependence with concurrent depressive disorders. Design This was a randomized, 12 week, double-blind, placebo-controlled trial of outpatients (n = 103) with DSM-IV cannabis dependence and major depressive disorder or dysthymia. Participants received up to 375 mg VEN-XR on a fixed-flexible schedule or placebo. All patients received weekly individual cognitive-behavioral psychotherapy that primarily targeted marijuana use. Settings The trial was conducted at two university research centers in the United States. Participants One hundred and three cannabis dependent adults participated in the trial. Measurements The primary outcome measures were 1) abstinence from marijuana defined as at least two consecutive urine-confirmed abstinent weeks and 2) improvement in depressive symptoms based on the Hamilton Depression Rating Scale. Findings The proportion of patients achieving a clinically significant mood improvement [50% decrease in Hamilton Depression score from baseline] was high and did not differ between groups receiving VEN-XR (63%) and placebo (69%) (X12=0.48, p-value= 0.49). The proportion of patients achieving abstinence was low overall, but was significantly worse on VEN-XR (11.8%) compared to placebo (36.5%) (X12=7.46, p-valuemarijuana use in the placebo group (F1,179=30.49, p-valuedepressed, cannabis-dependent patients, venlafaxine-extended release does not appear to be effective at reducing depression and may lead to an increase in cannabis use. PMID:23297841

  14. High Entropy Random Selection Protocols

    NARCIS (Netherlands)

    H. Buhrman (Harry); M. Christandl (Matthias); M. Koucky (Michal); Z. Lotker (Zvi); B. Patt-Shamir; M. Charikar; K. Jansen; O. Reingold; J. Rolim

    2007-01-01

    textabstractIn this paper, we construct protocols for two parties that do not trust each other, to generate random variables with high Shannon entropy. We improve known bounds for the trade off between the number of rounds, length of communication and the entropy of the outcome.

  15. Randomized Item Response Theory Models

    NARCIS (Netherlands)

    Fox, Gerardus J.A.

    2005-01-01

    The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by

  16. Measuring and testing dependence by correlation of distances

    OpenAIRE

    Székely, Gábor J.; Rizzo, Maria L.; Bakirov, Nail K.

    2007-01-01

    Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation is zero only if the random vectors are independent. The empirical distance dependence measures are based on certain Euclidean distances between sample elements rather than sample moments, yet have a compact representation analogous to the clas...

  17. Variability of Surface Reflection Amplitudes of GPR Horn Antenna Depending on Distance between Antenna and Surface

    Directory of Open Access Journals (Sweden)

    Komačka Jozef

    2016-05-01

    Full Text Available The study focused on variability of surface reflections amplitudes of GPR horn antenna in relation to distance between an antenna and a surface is presented in the paper. The air-coupled antenna with the central frequency of 1 GHz was used in the investigation. Four types of surfaces (dry pavement, wet pavement, metal plate and composite layer from gypsum and wood were tested. The distance of antenna above the surfaces was changed in the range from 37.5 cm to 53.5 cm. The amplitudes of negative and positive peaks and their variability were analysed in relation to the distance of antenna above the surfaces. Moreover, the influence of changes in the peaks of negative and positive amplitudes on the total amplitudes was assessed. It was found out the amplitudes of negative peaks for all investigated surfaces were relatively consistent in the range from 40.5 cm to 48.5 cm and the moderate decline was identified in the case of amplitudes of positive peaks in the range of distances from 37.5 cm to 51.5 cm. This decline influences the tendency of total amplitudes. Based on the results of analysis it can be stated the distance of air-coupled antenna above the surface can influence the value of total amplitude and the differences depend on the type of surface.

  18. Rapidly variable relatvistic absorption

    Science.gov (United States)

    Parker, M.; Pinto, C.; Fabian, A.; Lohfink, A.; Buisson, D.; Alston, W.; Jiang, J.

    2017-10-01

    I will present results from the 1.5Ms XMM-Newton observing campaign on the most X-ray variable AGN, IRAS 13224-3809. We find a series of nine absorption lines with a velocity of 0.24c from an ultra-fast outflow. For the first time, we are able to see extremely rapid variability of the UFO features, and can link this to the X-ray variability from the inner accretion disk. We find a clear flux dependence of the outflow features, suggesting that the wind is ionized by increasing X-ray emission.

  19. The effect of aquatic plyometric training with and without resistance on selected physical fitness variables among volleyball players

    Directory of Open Access Journals (Sweden)

    K. KAMALAKKANNAN

    2011-06-01

    Full Text Available The purpose of this study is to analyze the effect of aquatic plyometric training with and without the use ofweights on selected physical fitness variables among volleyball players. To achieve the purpose of these study 36physically active undergraduate volleyball players between 18 and 20 years of age volunteered as participants.The participants were randomly categorized into three groups of 12 each: a control group (CG, an aquaticPlyometric training with weight group (APTWG, and an aquatic Plyometric training without weight group(APTWOG. The subjects of the control group were not exposed to any training. Both experimental groupsunderwent their respective experimental treatment for 12 weeks, 3 days per week and a single session on eachday. Speed, endurance, and explosive power were measured as the dependent variables for this study. 36 days ofexperimental treatment was conducted for all the groups and pre and post data was collected. The collected datawere analyzed using an analysis of covariance (ANCOVA and followed by a Scheffé’s post hoc test. The resultsrevealed significant differences between groups on all the selected dependent variables. This study demonstratedthat aquatic plyometric training can be one effective means for improving speed, endurance, and explosivepower in volley ball players

  20. Threshold-dependent variability of coronary artery calcification measurements - implications for contrast-enhanced multi-detector row-computed tomography

    International Nuclear Information System (INIS)

    Moselewski, Fabian; Ferencik, Maros; Achenbach, Stephan; Abbara, Suhny; Cury, Ricardo C.; Booth, Sarah L.; Jang, Ik-Kyung; Brady, Thomas J.; Hoffmann, Udo

    2006-01-01

    Introduction: The present study investigated the threshold-dependent variability of coronary artery calcification (CAC) measurements and the potential to quantify CAC in contrast-enhanced multi-detector row-computed tomography (MDCT). Methods: We compared the mean CT attenuation of CAC to luminal contrast enhancement of the coronary arteries in 30 patients (n = 30) undergoing standard coronary contrast-enhanced spiral MDCT. The modified Agatston score [AS], calcified plaque volume [CV], and mineral mass [MM]) at four different thresholds (130, 200, 300, and 400 HU) were measured in 50 patients who underwent non-contrast-enhanced MDCT. Results: Mean CT attenuation of CAC was similar to the attenuation of the contrast-enhanced coronary lumen (CAC 297.1 ± 68.7 HU versus 295 ± 65 HU (p < 0.0001), respectively). Above a threshold of 300 HU CAC measurements significantly varied to standard measurements obtained at a threshold of 130 HU (p < 0.0001). The threshold-dependent variation of MM measurements was significantly smaller than for AS and CV (130 HU versus 400 HU: 63, 75, and 81, respectively; p < 0.001). These differences resulted in a change of age and gender based percentile category for AS in 78% of subjects. Discussion: We demonstrated that CAC measurements are threshold dependent with MM measurements having significantly less variation than AS or CV. Due to the similarity of mean CT attenuation of CAC and the contrast-enhanced coronary lumen accurate quantification of CAC may be difficult in standard coronary contrast-enhanced spiral MDCT

  1. Threshold-dependent variability of coronary artery calcification measurements - implications for contrast-enhanced multi-detector row-computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Moselewski, Fabian [Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Ferencik, Maros [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Achenbach, Stephan [Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Department of Internal Medicine II (Cardiology), University of Erlangen (Germany); Abbara, Suhny [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Cury, Ricardo C. [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Booth, Sarah L. [Jean Mayer USDA Human Nutrition Research Center on Aging, 711 Washington St., Boston, MA 02114 (United States); Jang, Ik-Kyung [Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Brady, Thomas J. [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Hoffmann, Udo [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)]. E-mail: uhoffman@partners.org

    2006-03-15

    Introduction: The present study investigated the threshold-dependent variability of coronary artery calcification (CAC) measurements and the potential to quantify CAC in contrast-enhanced multi-detector row-computed tomography (MDCT). Methods: We compared the mean CT attenuation of CAC to luminal contrast enhancement of the coronary arteries in 30 patients (n = 30) undergoing standard coronary contrast-enhanced spiral MDCT. The modified Agatston score [AS], calcified plaque volume [CV], and mineral mass [MM] at four different thresholds (130, 200, 300, and 400 HU) were measured in 50 patients who underwent non-contrast-enhanced MDCT. Results: Mean CT attenuation of CAC was similar to the attenuation of the contrast-enhanced coronary lumen (CAC 297.1 {+-} 68.7 HU versus 295 {+-} 65 HU (p < 0.0001), respectively). Above a threshold of 300 HU CAC measurements significantly varied to standard measurements obtained at a threshold of 130 HU (p < 0.0001). The threshold-dependent variation of MM measurements was significantly smaller than for AS and CV (130 HU versus 400 HU: 63, 75, and 81, respectively; p < 0.001). These differences resulted in a change of age and gender based percentile category for AS in 78% of subjects. Discussion: We demonstrated that CAC measurements are threshold dependent with MM measurements having significantly less variation than AS or CV. Due to the similarity of mean CT attenuation of CAC and the contrast-enhanced coronary lumen accurate quantification of CAC may be difficult in standard coronary contrast-enhanced spiral MDCT.

  2. A data based random number generator for a multivariate distribution (using stochastic interpolation)

    Science.gov (United States)

    Thompson, J. R.; Taylor, M. S.

    1982-01-01

    Let X be a K-dimensional random variable serving as input for a system with output Y (not necessarily of dimension k). given X, an outcome Y or a distribution of outcomes G(Y/X) may be obtained either explicitly or implicity. The situation is considered in which there is a real world data set X sub j sub = 1 (n) and a means of simulating an outcome Y. A method for empirical random number generation based on the sample of observations of the random variable X without estimating the underlying density is discussed.

  3. A proof-of-concept randomized controlled study of gabapentin: effects on cannabis use, withdrawal and executive function deficits in cannabis-dependent adults.

    Science.gov (United States)

    Mason, Barbara J; Crean, Rebecca; Goodell, Vivian; Light, John M; Quello, Susan; Shadan, Farhad; Buffkins, Kimberly; Kyle, Mark; Adusumalli, Murali; Begovic, Adnan; Rao, Santosh

    2012-06-01

    There are no FDA-approved pharmacotherapies for cannabis dependence. Cannabis is the most widely used illicit drug in the world, and patients seeking treatment for primary cannabis dependence represent 25% of all substance use admissions. We conducted a phase IIa proof-of-concept pilot study to examine the safety and efficacy of a calcium channel/GABA modulating drug, gabapentin, for the treatment of cannabis dependence. A 12-week, randomized, double-blind, placebo-controlled clinical trial was conducted in 50 unpaid treatment-seeking male and female outpatients, aged 18-65 years, diagnosed with current cannabis dependence. Subjects received either gabapentin (1200 mg/day) or matched placebo. Manual-guided, abstinence-oriented individual counseling was provided weekly to all participants. Cannabis use was measured by weekly urine toxicology and by self-report using the Timeline Followback Interview. Cannabis withdrawal symptoms were assessed using the Marijuana Withdrawal Checklist. Executive function was measured using subtests from the Delis-Kaplan Executive Function System. Relative to placebo, gabapentin significantly reduced cannabis use as measured both by urine toxicology (p=0.001) and by the Timeline Followback Interview (p=0.004), and significantly decreased withdrawal symptoms as measured by the Marijuana Withdrawal Checklist (pcannabis dependence that merits further study, and provides an alternative conceptual framework for treatment of addiction aimed at restoring homeostasis in brain stress systems that are dysregulated in drug dependence and withdrawal.

  4. A Proof-of-Concept Randomized Controlled Study of Gabapentin: Effects on Cannabis Use, Withdrawal and Executive Function Deficits in Cannabis-Dependent Adults

    Science.gov (United States)

    Mason, Barbara J; Crean, Rebecca; Goodell, Vivian; Light, John M; Quello, Susan; Shadan, Farhad; Buffkins, Kimberly; Kyle, Mark; Adusumalli, Murali; Begovic, Adnan; Rao, Santosh

    2012-01-01

    There are no FDA-approved pharmacotherapies for cannabis dependence. Cannabis is the most widely used illicit drug in the world, and patients seeking treatment for primary cannabis dependence represent 25% of all substance use admissions. We conducted a phase IIa proof-of-concept pilot study to examine the safety and efficacy of a calcium channel/GABA modulating drug, gabapentin, for the treatment of cannabis dependence. A 12-week, randomized, double-blind, placebo-controlled clinical trial was conducted in 50 unpaid treatment-seeking male and female outpatients, aged 18–65 years, diagnosed with current cannabis dependence. Subjects received either gabapentin (1200 mg/day) or matched placebo. Manual-guided, abstinence-oriented individual counseling was provided weekly to all participants. Cannabis use was measured by weekly urine toxicology and by self-report using the Timeline Followback Interview. Cannabis withdrawal symptoms were assessed using the Marijuana Withdrawal Checklist. Executive function was measured using subtests from the Delis–Kaplan Executive Function System. Relative to placebo, gabapentin significantly reduced cannabis use as measured both by urine toxicology (p=0.001) and by the Timeline Followback Interview (p=0.004), and significantly decreased withdrawal symptoms as measured by the Marijuana Withdrawal Checklist (pbrain stress systems that are dysregulated in drug dependence and withdrawal. PMID:22373942

  5. Approximating prediction uncertainty for random forest regression models

    Science.gov (United States)

    John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

    2016-01-01

    Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

  6. MIRU-VNTR allelic variability depends on Mycobacterium bovis clonal group identity.

    Science.gov (United States)

    Hauer, Amandine; Michelet, Lorraine; De Cruz, Krystel; Cochard, Thierry; Branger, Maxime; Karoui, Claudine; Henault, Sylvie; Biet, Franck; Boschiroli, María Laura

    2016-11-01

    The description of the population of M. bovis strains circulating in France from 1978 to 2013 has highlighted the discriminating power of the MLVA among predominant spoligotype groups. In the present study we aimed to characterize clonal groups via MLVA and to better understand the strain's population structure. MLVA was performed with eight MIRU-VNTR loci, most of them defined by the Venomyc European consortium. The discriminatory index of each MLVA loci was calculated for SB0120, SB0134, SB0121 and the "F4-family", the main spoligotype groups in France. Differences in global DI per spoligotype, but also by locus within each spoligotype, were observed, which strongly suggest the clonal complex nature of these major groups. These MLVA results were compared to those of other European countries where strain collections had been characterized (Spain, Portugal, Italy, Northern Ireland and Belgium). Overall, QUB 3232 and ETR D are respectively the most and the least discriminative loci, regardless of the strains geographical origin. However, marked DI differences are observed in the rest of the MIRU-VNTR loci, again highlighting that strain genetic variability in a country depends on the dominant existing clonal complexes. A web application for M. bovis, including spoligotyping and MIRU-VNTR typing data, was developed to allow inter-laboratory comparison of field isolates. In conclusion, combination of typing methods is required for M. bovis optimum discrimination and differentiation of groups of strains. Thus, the loci employed for MLVA in a country should be those which are the most discriminative for the clonal complexes which characterize their M. bovis population. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Impact of Flavonols on Cardiometabolic Biomarkers: A Meta-Analysis of Randomized Controlled Human Trials to Explore the Role of Inter-Individual Variability

    Science.gov (United States)

    Menezes, Regina; Rodriguez-Mateos, Ana; Kaltsatou, Antonia; González-Sarrías, Antonio; Greyling, Arno; Giannaki, Christoforos; Andres-Lacueva, Cristina; Milenkovic, Dragan; Gibney, Eileen R.; Dumont, Julie; Schär, Manuel; Garcia-Aloy, Mar; Palma-Duran, Susana Alejandra; Ruskovska, Tatjana; Maksimova, Viktorija; Combet, Emilie; Pinto, Paula

    2017-01-01

    Several epidemiological studies have linked flavonols with decreased risk of cardiovascular disease (CVD). However, some heterogeneity in the individual physiological responses to the consumption of these compounds has been identified. This meta-analysis aimed to study the effect of flavonol supplementation on biomarkers of CVD risk such as, blood lipids, blood pressure and plasma glucose, as well as factors affecting their inter-individual variability. Data from 18 human randomized controlled trials were pooled and the effect was estimated using fixed or random effects meta-analysis model and reported as difference in means (DM). Variability in the response of blood lipids to supplementation with flavonols was assessed by stratifying various population subgroups: age, sex, country, and health status. Results showed significant reductions in total cholesterol (DM = −0.10 mmol/L; 95% CI: −0.20, −0.01), LDL cholesterol (DM = −0.14 mmol/L; 95% CI: −0.21, 0.07), and triacylglycerol (DM = −0.10 mmol/L; 95% CI: −0.18, 0.03), and a significant increase in HDL cholesterol (DM = 0.05 mmol/L; 95% CI: 0.02, 0.07). A significant reduction was also observed in fasting plasma glucose (DM = −0.18 mmol/L; 95% CI: −0.29, −0.08), and in blood pressure (SBP: DM = −4.84 mmHg; 95% CI: −5.64, −4.04; DBP: DM = −3.32 mmHg; 95% CI: −4.09, −2.55). Subgroup analysis showed a more pronounced effect of flavonol intake in participants from Asian countries and in participants with diagnosed disease or dyslipidemia, compared to healthy and normal baseline values. In conclusion, flavonol consumption improved biomarkers of CVD risk, however, country of origin and health status may influence the effect of flavonol intake on blood lipid levels. PMID:28208791

  8. Quantifying and mapping spatial variability in simulated forest plots

    Science.gov (United States)

    Gavin R. Corral; Harold E. Burkhart

    2016-01-01

    We used computer simulations to test the efficacy of multivariate statistical methods to detect, quantify, and map spatial variability of forest stands. Simulated stands were developed of regularly-spaced plantations of loblolly pine (Pinus taeda L.). We assumed no affects of competition or mortality, but random variability was added to individual tree characteristics...

  9. Internal and external variability in regional simulations of the Iberian Peninsula climate over the last millennium

    Directory of Open Access Journals (Sweden)

    J. J. Gómez-Navarro

    2012-01-01

    Full Text Available In this study we analyse the role of internal variability in regional climate simulations through a comparison of two regional paleoclimate simulations for the last millennium. They share the same external forcings and model configuration, differing only in the initial condition used to run the driving global model simulation. A comparison of these simulations allows us to study the role of internal variability in climate models at regional scales, and how it affects the long-term evolution of climate variables such as temperature and precipitation. The results indicate that, although temperature is homogeneously sensitive to the effect of external forcings, the evolution of precipitation is more strongly governed by random unpredictable internal dynamics. There are, however, some areas where the role of internal variability is lower than expected, allowing precipitation to respond to the external forcings. In this respect, we explore the underlying physical mechanisms responsible for it. This study identifies areas, depending on the season, in which a direct comparison between model simulations of precipitation and climate reconstructions would be meaningful, but also other areas where good agreement between them should not be expected even if both are perfect.

  10. Travel time variability and rational inattention

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Jiang, Gege

    2017-01-01

    This paper sets up a rational inattention model for the choice of departure time for a traveler facing random travel time. The traveler chooses how much information to acquire about the travel time out-come before choosing departure time. This reduces the cost of travel time variability compared...

  11. A unified approach for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties

    Science.gov (United States)

    Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

    2017-09-01

    Automotive brake systems are always subjected to various types of uncertainties and two types of random-fuzzy uncertainties may exist in the brakes. In this paper, a unified approach is proposed for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties. In the proposed approach, two uncertainty analysis models with mixed variables are introduced to model the random-fuzzy uncertainties. The first one is the random and fuzzy model, in which random variables and fuzzy variables exist simultaneously and independently. The second one is the fuzzy random model, in which uncertain parameters are all treated as random variables while their distribution parameters are expressed as fuzzy numbers. Firstly, the fuzziness is discretized by using α-cut technique and the two uncertainty analysis models are simplified into random-interval models. Afterwards, by temporarily neglecting interval uncertainties, the random-interval models are degraded into random models, in which the expectations, variances, reliability indexes and reliability probabilities of system stability functions are calculated. And then, by reconsidering the interval uncertainties, the bounds of the expectations, variances, reliability indexes and reliability probabilities are computed based on Taylor series expansion. Finally, by recomposing the analysis results at each α-cut level, the fuzzy reliability indexes and probabilities can be obtained, by which the brake squeal instability can be evaluated. The proposed approach gives a general framework to deal with both types of random-fuzzy uncertainties that may exist in the brakes and its effectiveness is demonstrated by numerical examples. It will be a valuable supplement to the systematic study of brake squeal considering uncertainty.

  12. Fracture fragility of HFIR vessel caused by random crack size or random toughness

    International Nuclear Information System (INIS)

    Chang, Shih-Jung; Proctor, L.D.

    1993-01-01

    This report discuses the probability of fracture (fracture fragility) versus a range of applied hoop stresses along the HFIR vessel which is obtained as an estimate of its fracture capacity. Both the crack size and the fracture toughness are assumed to be random variables that follow given distribution functions. Possible hoop stress is based on the numerical solution of the vessel response by applying a point pressure-pulse it the center of the fluid volume within the vessel. Both the fluid-structure interaction and radiation embrittlement are taken into consideration. Elastic fracture mechanics is used throughout the analysis. The probability of vessel fracture for a single crack caused by either a variable crack depth or a variable toughness is first derived. Then the probability of fracture with multiple number of cracks is obtained. The probability of fracture is further extended to include different levels of confidence and variability. It, therefore, enables one to estimate the high confidence and low probability capacity accident load

  13. Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP

    Directory of Open Access Journals (Sweden)

    Sornkitja Boonprong

    2018-05-01

    Full Text Available Burnt forest recovery is normally monitored with a time-series analysis of satellite data because of its proficiency for large observation areas. Traditional methods, such as linear correlation plotting, have been proven to be effective, as forest recovery naturally increases with time. However, these methods are complicated and time consuming when increasing the number of observed parameters. In this work, we present a random forest variable importance (RF-VIMP scheme called multilevel RF-VIMP to compare and assess the relationship between 36 spectral indices (parameters of burnt boreal forest recovery in the Great Xing’an Mountain, China. Six Landsat images were acquired in the same month 0, 1, 4, 14, 16, and 20 years after a fire, and 39,380 fixed-location samples were then extracted to calculate the effectiveness of the 36 parameters. Consequently, the proposed method was applied to find correlations between the forest recovery indices. The experiment showed that the proposed method is suitable for explaining the efficacy of those spectral indices in terms of discrimination and trend analysis, and for showing the satellite data and forest succession dynamics when applied in a time series. The results suggest that the tasseled cap transformation wetness, brightness, and the shortwave infrared bands (both 1 and 2 perform better than other indices for both classification and monitoring.

  14. Bio-Psycho-Spiritual Modeling in Drug Dependents and Compiling of Intervention Program for Promotion of Resiliency Based on Cognitive Narratology and Positive Psychology

    Directory of Open Access Journals (Sweden)

    Ezat ollah Kordmirza Nikoozadeh

    2009-08-01

    Full Text Available Introduction: Since the past few decades, the concentration of researches on drug abuse and drugs dependency have shift from risk factor to protective factors. In the past two decades, the concept of resiliency was increasingly considered by developmental psychology. The concentration shifted from risk to resiliency originates from disadvantage in emphasizing on identification of risk factors. Method: Target population was all volunteer addicts who referred to clinics in Tehran city. The group selected based on random cluster sampling. In total 319 persons (male composed of two groups, dependent to drug (150 persons and independent to drug (169 persons were participated in research and in general, 108 questionnaires of non-addicts and 126 of addicts were analyzed. In order to determine the fit model based on assumed variables in the research, by utilizing LISREL softwar99e, initially the relation between primary fundamental variables and final endogenous variables were reviewed. In continuation, the - relations between intermediary and endogenous variables were determined. Results: The results showed the fitting of predicted model of resiliency. Conclusion: In this research the program based on bio-psycho-spiritual model for instructional intervention in order to enhance of resiliency of addict people provided.

  15. Evaluating the Impact of Antibiotic Exposures as Time-Dependent Variables on the Acquisition of Carbapenem-Resistant Acinetobacter baumannii.

    Science.gov (United States)

    Munoz-Price, L Silvia; Rosa, Rossana; Castro, Jose G; Laowansiri, Panthipa; Latibeaudiere, Rachel; Namias, Nicholas; Tarima, Sergey

    2016-10-01

    To determine the time-dependent effect of antibiotics on the initial acquisition of carbapenem-resistant Acinetobacter baumannii. Retrospective cohort study. Forty-bed trauma ICU in Miami, FL. All consecutive patients admitted to the unit from November 1, 2010, to November 30, 2011. None. Patients underwent surveillance cultures at admission to the unit and weekly thereafter. The primary outcome was the acquisition of carbapenem-resistant A. baumannii on surveillance cultures. Daily antibiotic exposures during the time of observation were used to construct time-dependent variables, including cumulative exposures (in grams and daily observed doses [defined daily doses]). Among 360 patients, 45 (12.5%) became colonized with carbapenem-resistant A. baumannii. Adjusted Cox models showed that each additional point in the Acute Physiologic and Chronic Health Evaluation score increased the hazard by 4.8% (hazard ratio, 1.048; 95% CI, 1.010-1.087; p = 0.0124) and time-dependent exposure to carbapenems quadrupled the hazard (hazard ratio, 4.087; 95% CI, 1.873-8.920; p = 0.0004) of acquiring carbapenem-resistant A. baumannii. Additionally, adjusted Cox models determined that every additional carbapenem defined daily dose increased the hazard of acquiring carbapenem-resistant A. baumannii by 5.1% (hazard ratio, 1.051; 95% CI, 1.007-1.093; p = 0.0243). Carbapenem exposure quadrupled the hazards of acquiring A. baumannii even after controlling for severity of illness.

  16. Collocation methods for uncertainty quanti cation in PDE models with random data

    KAUST Repository

    Nobile, Fabio

    2014-01-06

    In this talk we consider Partial Differential Equations (PDEs) whose input data are modeled as random fields to account for their intrinsic variability or our lack of knowledge. After parametrizing the input random fields by finitely many independent random variables, we exploit the high regularity of the solution of the PDE as a function of the input random variables and consider sparse polynomial approximations in probability (Polynomial Chaos expansion) by collocation methods. We first address interpolatory approximations where the PDE is solved on a sparse grid of Gauss points in the probability space and the solutions thus obtained interpolated by multivariate polynomials. We present recent results on optimized sparse grids in which the selection of points is based on a knapsack approach and relies on sharp estimates of the decay of the coefficients of the polynomial chaos expansion of the solution. Secondly, we consider regression approaches where the PDE is evaluated on randomly chosen points in the probability space and a polynomial approximation constructed by the least square method. We present recent theoretical results on the stability and optimality of the approximation under suitable conditions between the number of sampling points and the dimension of the polynomial space. In particular, we show that for uniform random variables, the number of sampling point has to scale quadratically with the dimension of the polynomial space to maintain the stability and optimality of the approximation. Numerical results show that such condition is sharp in the monovariate case but seems to be over-constraining in higher dimensions. The regression technique seems therefore to be attractive in higher dimensions.

  17. Prediction of soil CO2 flux in sugarcane management systems using the Random Forest approach

    Directory of Open Access Journals (Sweden)

    Rose Luiza Moraes Tavares

    Full Text Available ABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80 for predicted and observed values.

  18. Application of random effects to the study of resource selection by animals.

    Science.gov (United States)

    Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

    2006-07-01

    1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions

  19. Comparing of the Reaction Time in Substance-Dependent and Non-Dependent Individuals

    Directory of Open Access Journals (Sweden)

    Mohammad Narimani

    2012-11-01

    Full Text Available Aim: The aim of this study was to compare the simple, selective, and discrimination reaction time in substance-dependent and non-dependent individuals. Method: In this causal-comparative study, the population included of 425 males (opium and crystal dependents who were referred to addiction rehabilitation centers in Tabriz. By random sampling, 16 opium dependents, 16 crystal dependents, and 16 non-dependent individuals with no history of dependency as the compare group were selected. All groups peered in age, and marital status. For gathering data, “Addicts Admit Questionnaire” and laboratory device known as the "Reaction Time Assay" have been used. Results: The results of this study showed that there are significant differences among all groups in simple reaction time, choice reaction time and reaction time to auditory stimuli, but no significant difference in discrimination reaction time and reaction time to visual stimulus observed. Conclusion: The reaction time of substance-dependent groups is slower than non-dependent groups.

  20. Bunches of random cross-correlated sequences

    International Nuclear Information System (INIS)

    Maystrenko, A A; Melnik, S S; Pritula, G M; Usatenko, O V

    2013-01-01

    The statistical properties of random cross-correlated sequences constructed by the convolution method (likewise referred to as the Rice or the inverse Fourier transformation) are examined. We clarify the meaning of the filtering function—the kernel of the convolution operator—and show that it is the value of the cross-correlation function which describes correlations between the initial white noise and constructed correlated sequences. The matrix generalization of this method for constructing a bunch of N cross-correlated sequences is presented. Algorithms for their generation are reduced to solving the problem of decomposition of the Fourier transform of the correlation matrix into a product of two mutually conjugate matrices. Different decompositions are considered. The limits of weak and strong correlations for the one-point probability and pair correlation functions of sequences generated by the method under consideration are studied. Special cases of heavy-tailed distributions of the generated sequences are analyzed. We show that, if the filtering function is rather smooth, the distribution function of generated variables has the Gaussian or Lévy form depending on the analytical properties of the distribution (or characteristic) functions of the initial white noise. Anisotropic properties of statistically homogeneous random sequences related to the asymmetry of a filtering function are revealed and studied. These asymmetry properties are expressed in terms of the third- or fourth-order correlation functions. Several examples of the construction of correlated chains with a predefined correlation matrix are given. (paper)

  1. More randomness from the same data

    International Nuclear Information System (INIS)

    Bancal, Jean-Daniel; Sheridan, Lana; Scarani, Valerio

    2014-01-01

    Correlations that cannot be reproduced with local variables certify the generation of private randomness. Usually, the violation of a Bell inequality is used to quantify the amount of randomness produced. Here, we show how private randomness generated during a Bell test can be directly quantified from the observed correlations, without the need to process these data into an inequality. The frequency with which the different measurement settings are used during the Bell test can also be taken into account. This improved analysis turns out to be very relevant for Bell tests performed with a finite collection efficiency. In particular, applying our technique to the data of a recent experiment (Christensen et al 2013 Phys. Rev. Lett. 111 130406), we show that about twice as much randomness as previously reported can be potentially extracted from this setup. (paper)

  2. A randomized double-blind, placebo-controlled trial of venlafaxine-extended release for co-occurring cannabis dependence and depressive disorders.

    Science.gov (United States)

    Levin, Frances R; Mariani, John; Brooks, Daniel J; Pavlicova, Martina; Nunes, Edward V; Agosti, Vito; Bisaga, Adam; Sullivan, Maria A; Carpenter, Kenneth M

    2013-06-01

    To evaluate whether venlafaxine-extended release (VEN-XR) is an effective treatment for cannabis dependence with concurrent depressive disorders. This was a randomized, 12-week, double-blind, placebo-controlled trial of out-patients (n = 103) with DSM-IV cannabis dependence and major depressive disorder or dysthymia. Participants received up to 375 mg VEN-XR on a fixed-flexible schedule or placebo. All patients received weekly individual cognitive-behavioral psychotherapy that primarily targeted marijuana use. The trial was conducted at two university research centers in the United States. One hundred and three cannabis-dependent adults participated in the trial. The primary outcome measures were (i) abstinence from marijuana defined as at least two consecutive urine-confirmed abstinent weeks and (ii) improvement in depressive symptoms based on the Hamilton Depression Rating Scale. The proportion of patients achieving a clinically significant mood improvement (50% decrease in Hamilton Depression score from baseline) was high and did not differ between groups receiving VEN-XR (63%) and placebo (69%) (χ1 (2)  = 0.48, P = 0.49). The proportion of patients achieving abstinence was low overall, but was significantly worse on VEN-XR (11.8%) compared to placebo (36.5%) (χ1 (2)  = 7.46, P marijuana use in the placebo group (F1,179  = 30.49, P depressed, cannabis-dependent patients, venlafaxine-extended release does not appear to be effective at reducing depression and may lead to an increase in cannabis use. © 2013 Society for the Study of Addiction.

  3. Mum, why do you keep on growing? Impacts of environmental variability on optimal growth and reproduction allocation strategies of annual plants.

    Science.gov (United States)

    De Lara, Michel

    2006-05-01

    In their 1990 paper Optimal reproductive efforts and the timing of reproduction of annual plants in randomly varying environments, Amir and Cohen considered stochastic environments consisting of i.i.d. sequences in an optimal allocation discrete-time model. We suppose here that the sequence of environmental factors is more generally described by a Markov chain. Moreover, we discuss the connection between the time interval of the discrete-time dynamic model and the ability of the plant to rebuild completely its vegetative body (from reserves). We formulate a stochastic optimization problem covering the so-called linear and logarithmic fitness (corresponding to variation within and between years), which yields optimal strategies. For "linear maximizers'', we analyse how optimal strategies depend upon the environmental variability type: constant, random stationary, random i.i.d., random monotonous. We provide general patterns in terms of targets and thresholds, including both determinate and indeterminate growth. We also provide a partial result on the comparison between ;"linear maximizers'' and "log maximizers''. Numerical simulations are provided, allowing to give a hint at the effect of different mathematical assumptions.

  4. Biological Sampling Variability Study

    Energy Technology Data Exchange (ETDEWEB)

    Amidan, Brett G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hutchison, Janine R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-11-08

    There are many sources of variability that exist in the sample collection and analysis process. This paper addresses many, but not all, sources of variability. The main focus of this paper was to better understand and estimate variability due to differences between samplers. Variability between days was also studied, as well as random variability within each sampler. Experiments were performed using multiple surface materials (ceramic and stainless steel), multiple contaminant concentrations (10 spores and 100 spores), and with and without the presence of interfering material. All testing was done with sponge sticks using 10-inch by 10-inch coupons. Bacillus atrophaeus was used as the BA surrogate. Spores were deposited using wet deposition. Grime was coated on the coupons which were planned to include the interfering material (Section 3.3). Samples were prepared and analyzed at PNNL using CDC protocol (Section 3.4) and then cultured and counted. Five samplers were trained so that samples were taken using the same protocol. Each sampler randomly sampled eight coupons each day, four coupons with 10 spores deposited and four coupons with 100 spores deposited. Each day consisted of one material being tested. The clean samples (no interfering materials) were run first, followed by the dirty samples (coated with interfering material). There was a significant difference in recovery efficiency between the coupons with 10 spores deposited (mean of 48.9%) and those with 100 spores deposited (mean of 59.8%). There was no general significant difference between the clean and dirty (containing interfering material) coupons or between the two surface materials; however, there was a significant interaction between concentration amount and presence of interfering material. The recovery efficiency was close to the same for coupons with 10 spores deposited, but for the coupons with 100 spores deposited, the recovery efficiency for the dirty samples was significantly larger (65

  5. Random elements on lattices: Review and statistical applications

    Science.gov (United States)

    Potocký, Rastislav; Villarroel, Claudia Navarro; Sepúlveda, Maritza; Luna, Guillermo; Stehlík, Milan

    2017-07-01

    We discuss important contributions to random elements on lattices. We relate to both algebraic and probabilistic properties. Several applications and concepts are discussed, e.g. positive dependence, Random walks and distributions on lattices, Super-lattices, learning. The application to Chilean Ecology is given.

  6. Effect of random edge failure on the average path length

    Energy Technology Data Exchange (ETDEWEB)

    Guo Dongchao; Liang Mangui; Li Dandan; Jiang Zhongyuan, E-mail: mgliang58@gmail.com, E-mail: 08112070@bjtu.edu.cn [Institute of Information Science, Beijing Jiaotong University, 100044, Beijing (China)

    2011-10-14

    We study the effect of random removal of edges on the average path length (APL) in a large class of uncorrelated random networks in which vertices are characterized by hidden variables controlling the attachment of edges between pairs of vertices. A formula for approximating the APL of networks suffering random edge removal is derived first. Then, the formula is confirmed by simulations for classical ER (Erdoes and Renyi) random graphs, BA (Barabasi and Albert) networks, networks with exponential degree distributions as well as random networks with asymptotic power-law degree distributions with exponent {alpha} > 2. (paper)

  7. Association between increased EEG signal complexity and cannabis dependence.

    Science.gov (United States)

    Laprevote, Vincent; Bon, Laura; Krieg, Julien; Schwitzer, Thomas; Bourion-Bedes, Stéphanie; Maillard, Louis; Schwan, Raymund

    2017-12-01

    Both acute and regular cannabis use affects the functioning of the brain. While several studies have demonstrated that regular cannabis use can impair the capacity to synchronize neural assemblies during specific tasks, less is known about spontaneous brain activity. This can be explored by measuring EEG complexity, which reflects the spontaneous variability of human brain activity. A recent study has shown that acute cannabis use can affect that complexity. Since the characteristics of cannabis use can affect the impact on brain functioning, this study sets out to measure EEG complexity in regular cannabis users with or without dependence, in comparison with healthy controls. We recruited 26 healthy controls, 25 cannabis users without cannabis dependence and 14 cannabis users with cannabis dependence, based on DSM IV TR criteria. The EEG signal was extracted from at least 250 epochs of the 500ms pre-stimulation phase during a visual evoked potential paradigm. Brain complexity was estimated using Lempel-Ziv Complexity (LZC), which was compared across groups by non-parametric Kruskall-Wallis ANOVA. The analysis revealed a significant difference between the groups, with higher LZC in participants with cannabis dependence than in non-dependent cannabis users. There was no specific localization of this effect across electrodes. We showed that cannabis dependence is associated to an increased spontaneous brain complexity in regular users. This result is in line with previous results in acute cannabis users. It may reflect increased randomness of neural activity in cannabis dependence. Future studies should explore whether this effect is permanent or diminishes with cannabis cessation. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

  8. Encoding dependence in Bayesian causal networks

    Science.gov (United States)

    Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...

  9. Randomized trials, generalizability, and meta-analysis: Graphical insights for binary outcomes

    Directory of Open Access Journals (Sweden)

    Kramer Barnett S

    2003-06-01

    Full Text Available Abstract Background Randomized trials stochastically answer the question. "What would be the effect of treatment on outcome if one turned back the clock and switched treatments in the given population?" Generalizations to other subjects are reliable only if the particular trial is performed on a random sample of the target population. By considering an unobserved binary variable, we graphically investigate how randomized trials can also stochastically answer the question, "What would be the effect of treatment on outcome in a population with a possibly different distribution of an unobserved binary baseline variable that does not interact with treatment in its effect on outcome?" Method For three different outcome measures, absolute difference (DIF, relative risk (RR, and odds ratio (OR, we constructed a modified BK-Plot under the assumption that treatment has the same effect on outcome if either all or no subjects had a given level of the unobserved binary variable. (A BK-Plot shows the effect of an unobserved binary covariate on a binary outcome in two treatment groups; it was originally developed to explain Simpsons's paradox. Results For DIF and RR, but not OR, the BK-Plot shows that the estimated treatment effect is invariant to the fraction of subjects with an unobserved binary variable at a given level. Conclusion The BK-Plot provides a simple method to understand generalizability in randomized trials. Meta-analyses of randomized trials with a binary outcome that are based on DIF or RR, but not OR, will avoid bias from an unobserved covariate that does not interact with treatment in its effect on outcome.

  10. Maximal Increments of Local Time of a Random Walk

    OpenAIRE

    Jain, Naresh C.; Pruitt, William E.

    1987-01-01

    Let $(S_j)$ be a lattice random walk, i.e., $S_j = X_1 + \\cdots + X_j$, where $X_1, X_2,\\ldots$ are independent random variables with values in $\\mathbb{Z}$ and common nondegenerate distribution $F$. Let $\\{t_n\\}$ be a nondecreasing sequence of positive integers, $t_n \\leq n$, and $L^\\ast_n = \\max_{0\\leq j\\leq n-t_n}(L_{j+t_n} - L_j)$, where $L_n = \\sum^n_{j=1}1_{\\{0\\}}(S_j)$, the number of times zero is visited by the random walk by time $n$. Assuming that the random walk is recurrent and sa...

  11. Experimental Evaluation of Novel Master-Slave Configurations for Position Control under Random Network Delay and Variable Load for Teleoperation

    Directory of Open Access Journals (Sweden)

    Ahmet Kuzu

    2014-01-01

    Full Text Available This paper proposes two novel master-slave configurations that provide improvements in both control and communication aspects of teleoperation systems to achieve an overall improved performance in position control. The proposed novel master-slave configurations integrate modular control and communication approaches, consisting of a delay regulator to address problems related to variable network delay common to such systems, and a model tracking control that runs on the slave side for the compensation of uncertainties and model mismatch on the slave side. One of the configurations uses a sliding mode observer and the other one uses a modified Smith predictor scheme on the master side to ensure position transparency between the master and slave, while reference tracking of the slave is ensured by a proportional-differentiator type controller in both configurations. Experiments conducted for the networked position control of a single-link arm under system uncertainties and randomly varying network delays demonstrate significant performance improvements with both configurations over the past literature.

  12. Motivational and psychological correlates of bodybuilding dependence.

    Science.gov (United States)

    Emini, Neim N; Bond, Malcolm J

    2014-09-01

    Exercise may become physically and psychologically maladaptive if taken to extremes. One example is the dependence reported by some individuals who engage in weight training. The current study explored potential psychological, motivational, emotional and behavioural concomitants of bodybuilding dependence, with a particular focus on motives for weight training. Using a path analysis paradigm, putative causal models sought to explain associations among key study variables. A convenience sample of 101 men aged between 18 and 67 years was assembled from gymnasia in Adelaide, South Australia. Active weight trainers voluntarily completed a questionnaire that included measures of bodybuilding dependence (social dependency, training dependency, and mastery), anger, hostility and aggression, stress and motivations for weight training. Three motives for weight training were identified: mood control, physique anxiety and personal challenge. Of these, personal challenge and mood control were the most directly salient to dependence. Social dependency was particularly relevant to personal challenge, whereas training dependency was associated with both personal challenge and mood control. Mastery demonstrated a direct link with physique anxiety, thus reflecting a unique component of exercise dependence. While it was not possible to determine causality with the available data, the joint roles of variables that influence, or are influenced by, bodybuilding dependence are identified. RESULTS highlight unique motivations for bodybuilding and suggest that dependence could be a result of, and way of coping with, stress manifesting as aggression. A potential framework for future research is provided through the demonstration of plausible causal linkages among these variables.

  13. Random walk in dynamically disordered chains: Poisson white noise disorder

    International Nuclear Information System (INIS)

    Hernandez-Garcia, E.; Pesquera, L.; Rodriguez, M.A.; San Miguel, M.

    1989-01-01

    Exact solutions are given for a variety of models of random walks in a chain with time-dependent disorder. Dynamic disorder is modeled by white Poisson noise. Models with site-independent (global) and site-dependent (local) disorder are considered. Results are described in terms of an affective random walk in a nondisordered medium. In the cases of global disorder the effective random walk contains multistep transitions, so that the continuous limit is not a diffusion process. In the cases of local disorder the effective process is equivalent to usual random walk in the absence of disorder but with slower diffusion. Difficulties associated with the continuous-limit representation of random walk in a disordered chain are discussed. In particular, the authors consider explicit cases in which taking the continuous limit and averaging over disorder sources do not commute

  14. Financial management of a large multisite randomized clinical trial.

    Science.gov (United States)

    Sheffet, Alice J; Flaxman, Linda; Tom, MeeLee; Hughes, Susan E; Longbottom, Mary E; Howard, Virginia J; Marler, John R; Brott, Thomas G

    2014-08-01

    The Carotid Revascularization Endarterectomy versus Stenting Trial (CREST) received five years' funding ($21 112 866) from the National Institutes of Health to compare carotid stenting to surgery for stroke prevention in 2500 randomized participants at 40 sites. Herein we evaluate the change in the CREST budget from a fixed to variable-cost model and recommend strategies for the financial management of large-scale clinical trials. Projections of the original grant's fixed-cost model were compared to the actual costs of the revised variable-cost model. The original grant's fixed-cost budget included salaries, fringe benefits, and other direct and indirect costs. For the variable-cost model, the costs were actual payments to the clinical sites and core centers based upon actual trial enrollment. We compared annual direct and indirect costs and per-patient cost for both the fixed and variable models. Differences between clinical site and core center expenditures were also calculated. Using a variable-cost budget for clinical sites, funding was extended by no-cost extension from five to eight years. Randomizing sites tripled from 34 to 109. Of the 2500 targeted sample size, 138 (5·5%) were randomized during the first five years and 1387 (55·5%) during the no-cost extension. The actual per-patient costs of the variable model were 9% ($13 845) of the projected per-patient costs ($152 992) of the fixed model. Performance-based budgets conserve funding, promote compliance, and allow for additional sites at modest additional cost. Costs of large-scale clinical trials can thus be reduced through effective management without compromising scientific integrity. © 2014 The Authors. International Journal of Stroke © 2014 World Stroke Organization.

  15. Variability in the management of lithium poisoning.

    Science.gov (United States)

    Roberts, Darren M; Gosselin, Sophie

    2014-01-01

    Three patterns of lithium poisoning are recognized: acute, acute-on-chronic, and chronic. Intravenous fluids with or without an extracorporeal treatment are the mainstay of treatment; their respective roles may differ depending on the mode of poisoning being treated. Recommendations for treatment selection are available but these are based on a small number of observational studies and their uptake by clinicians is not known. Clinician decision-making in the treatment of four cases of lithium poisoning was assessed at a recent clinical toxicology meeting using an audience response system. Variability in treatment decisions was evident in addition to discordance with published recommendations. Participants did not consistently indicate that hemodialysis was the first-line treatment, instead opting for a conservative approach, and continuous modalities were viewed favorably; this is in contrast to recommendations in some references. The development of multidisciplinary consensus guidelines may improve the management of patients with lithium poisoning but prospective randomized controlled trials are required to more clearly define the role of extracorporeal treatments. © 2014 Wiley Periodicals, Inc.

  16. Soil variability in mountain areas

    OpenAIRE

    Zanini, E.; Freppaz, M.; Stanchi, S.; Bonifacio, E.; Egli, M.

    2015-01-01

    The high spatial variability of soils is a relevant issue at local and global scales, and determines the complexity of soil ecosystem functions and services. This variability derives from strong dependencies of soil ecosystems on parent materials, climate, relief and biosphere, including human impact. Although present in all environments, the interactions of soils with these forming factors are particularly striking in mountain areas.

  17. Prediction of N2O emission from local information with Random Forest

    International Nuclear Information System (INIS)

    Philibert, Aurore; Loyce, Chantal; Makowski, David

    2013-01-01

    Nitrous oxide is a potent greenhouse gas, with a global warming potential 298 times greater than that of CO 2 . In agricultural soils, N 2 O emissions are influenced by a large number of environmental characteristics and crop management techniques that are not systematically reported in experiments. Random Forest (RF) is a machine learning method that can handle missing data and ranks input variables on the basis of their importance. We aimed to predict N 2 O emission on the basis of local information, to rank environmental and crop management variables according to their influence on N 2 O emission, and to compare the performances of RF with several regression models. RF outperformed the regression models for predictive purposes, and this approach led to the identification of three important input variables: N fertilization, type of crop, and experiment duration. This method could be used in the future for prediction of N 2 O emissions from local information. -- Highlights: ► Random Forest gave more accurate N 2 O predictions than regression. ► Missing data were well handled by Random Forest. ► The most important factors were nitrogen rate, type of crop and experiment duration. -- Random Forest, a machine learning method, outperformed the regression models for predicting N 2 O emissions and led to the identification of three important input variables

  18. Random coil chemical shift for intrinsically disordered proteins

    DEFF Research Database (Denmark)

    Kjærgaard, Magnus; Brander, Søren; Poulsen, Flemming Martin

    2011-01-01

    . Temperature has a non-negligible effect on the (13)C random coil chemical shifts, so temperature coefficients are reported for the random coil chemical shifts to allow extrapolation to other temperatures. The pH dependence of the histidine random coil chemical shifts is investigated in a titration series......, which allows the accurate random coil chemical shifts to be obtained at any pH. By correcting the random coil chemical shifts for the effects of temperature and pH, systematic biases of the secondary chemical shifts are minimized, which will improve the reliability of detection of transient secondary...

  19. Quantum interference magnetoconductance of polycrystalline germanium films in the variable-range hopping regime

    Science.gov (United States)

    Li, Zhaoguo; Peng, Liping; Zhang, Jicheng; Li, Jia; Zeng, Yong; Zhan, Zhiqiang; Wu, Weidong

    2018-06-01

    Direct evidence of quantum interference magnetotransport in polycrystalline germanium films in the variable-range hopping (VRH) regime is reported. The temperature dependence of the conductivity of germanium films fulfilled the Mott VRH mechanism with the form of ? in the low-temperature regime (?). For the magnetotransport behaviour of our germanium films in the VRH regime, a crossover, from negative magnetoconductance at the low-field to positive magnetoconductance at the high-field, is observed while the zero-field conductivity is higher than the critical value (?). In the regime of ?, the magnetoconductance is positive and quadratic in the field for some germanium films. These features are in agreement with the VRH magnetotransport theory based on the quantum interference effect among random paths in the hopping process.

  20. Molecular Excitation Energies from Time-Dependent Density Functional Theory Employing Random-Phase Approximation Hessians with Exact Exchange.

    Science.gov (United States)

    Heßelmann, Andreas

    2015-04-14

    Molecular excitation energies have been calculated with time-dependent density-functional theory (TDDFT) using random-phase approximation Hessians augmented with exact exchange contributions in various orders. It has been observed that this approach yields fairly accurate local valence excitations if combined with accurate asymptotically corrected exchange-correlation potentials used in the ground-state Kohn-Sham calculations. The inclusion of long-range particle-particle with hole-hole interactions in the kernel leads to errors of 0.14 eV only for the lowest excitations of a selection of three alkene, three carbonyl, and five azabenzene molecules, thus surpassing the accuracy of a number of common TDDFT and even some wave function correlation methods. In the case of long-range charge-transfer excitations, the method typically underestimates accurate reference excitation energies by 8% on average, which is better than with standard hybrid-GGA functionals but worse compared to range-separated functional approximations.

  1. Clinical Implications of Glucose Variability: Chronic Complications of Diabetes

    Directory of Open Access Journals (Sweden)

    Hye Seung Jung

    2015-06-01

    Full Text Available Glucose variability has been identified as a potential risk factor for diabetic complications; oxidative stress is widely regarded as the mechanism by which glycemic variability induces diabetic complications. However, there remains no generally accepted gold standard for assessing glucose variability. Representative indices for measuring intraday variability include calculation of the standard deviation along with the mean amplitude of glycemic excursions (MAGE. MAGE is used to measure major intraday excursions and is easily measured using continuous glucose monitoring systems. Despite a lack of randomized controlled trials, recent clinical data suggest that long-term glycemic variability, as determined by variability in hemoglobin A1c, may contribute to the development of microvascular complications. Intraday glycemic variability is also suggested to accelerate coronary artery disease in high-risk patients.

  2. Cartesian integration of Grassmann variables over invariant functions

    Energy Technology Data Exchange (ETDEWEB)

    Kieburg, Mario; Kohler, Heiner; Guhr, Thomas [Universitaet Duisburg-Essen, Duisburg (Germany)

    2009-07-01

    Supersymmetry plays an important role in field theory as well as in random matrix theory and mesoscopic physics. Anticommuting variables are the fundamental objects of supersymmetry. The integration over these variables is equivalent to the derivative. Recently[arxiv:0809.2674v1[math-ph] (2008)], we constructed a differential operator which only acts on the ordinary part of the superspace consisting of ordinary and anticommuting variables. This operator is equivalent to the integration over all anticommuting variables of an invariant function. We present this operator and its applications for functions which are rotation invariant under the supergroups U(k{sub 1}/k{sub 2}) and UOSp(k{sub 1}/k{sub 2}).

  3. Transition Achievement among Young Adults with Deafness: What Variables Relate to Success?

    Science.gov (United States)

    Bullis, Michael; And Others

    1995-01-01

    Examines the transition achievement of deaf persons 3 or 4 years out of high school (n=308). Ten independent variables were used to predict 2 dichotomous dependent variables: engagement with community (56%), and residential status (52% living independently). Results are presented for each dependent variable. (JPS)

  4. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Science.gov (United States)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

    This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  5. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Directory of Open Access Journals (Sweden)

    Medyńska-Gulij Beata

    2016-06-01

    Full Text Available This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  6. Financial Management of a Large Multi-site Randomized Clinical Trial

    Science.gov (United States)

    Sheffet, Alice J.; Flaxman, Linda; Tom, MeeLee; Hughes, Susan E.; Longbottom, Mary E.; Howard, Virginia J.; Marler, John R.; Brott, Thomas G.

    2014-01-01

    Background The Carotid Revascularization Endarterectomy versus Stenting Trial (CREST) received five years’ funding ($21,112,866) from the National Institutes of Health to compare carotid stenting to surgery for stroke prevention in 2,500 randomized participants at 40 sites. Aims Herein we evaluate the change in the CREST budget from a fixed to variable-cost model and recommend strategies for the financial management of large-scale clinical trials. Methods Projections of the original grant’s fixed-cost model were compared to the actual costs of the revised variable-cost model. The original grant’s fixed-cost budget included salaries, fringe benefits, and other direct and indirect costs. For the variable-cost model, the costs were actual payments to the clinical sites and core centers based upon actual trial enrollment. We compared annual direct and indirect costs and per-patient cost for both the fixed and variable models. Differences between clinical site and core center expenditures were also calculated. Results Using a variable-cost budget for clinical sites, funding was extended by no-cost extension from five to eight years. Randomizing sites tripled from 34 to 109. Of the 2,500 targeted sample size, 138 (5.5%) were randomized during the first five years and 1,387 (55.5%) during the no-cost extension. The actual per-patient costs of the variable model were 9% ($13,845) of the projected per-patient costs ($152,992) of the fixed model. Conclusions Performance-based budgets conserve funding, promote compliance, and allow for additional sites at modest additional cost. Costs of large-scale clinical trials can thus be reduced through effective management without compromising scientific integrity. PMID:24661748

  7. On the pertinence to Physics of random walks induced by random dynamical systems: a survey

    International Nuclear Information System (INIS)

    Petritis, Dimitri

    2016-01-01

    Let be an abstract space and a denumerable (finite or infinite) alphabet. Suppose that is a family of functions such that for all we have and a family of transformations . The pair (( S_a)_a , ( p_a)_a ) is termed an iterated function system with place dependent probabilities. Such systems can be thought as generalisations of random dynamical systems. As a matter of fact, suppose we start from a given ; we pick then randomly, with probability p_a (x) , the transformation S_a and evolve to S_a (x) . We are interested in the behaviour of the system when the iteration continues indefinitely. Random walks of the above type are omnipresent in both classical and quantum Physics. To give a small sample of occurrences we mention: random walks on the affine group, random walks on Penrose lattices, random walks on partially directed lattices, evolution of density matrices induced by repeated quantum measurements, quantum channels, quantum random walks, etc. In this article, we review some basic properties of such systems and provide with a pathfinder in the extensive bibliography (both on mathematical and physical sides) where the main results have been originally published. (paper)

  8. Numerical study of microphase separation in gels and random media

    International Nuclear Information System (INIS)

    Uchida, Nariya

    2004-01-01

    Microphase separation in gels and random media is numerically studied using a Ginzburg-Landau model. A random field destroys long-range orientational (lamellar) order and gives rise to a disordered bicontinuous morphology. The dependence of the correlation length on the field strength is distinct from that of random-field magnets

  9. A randomized trial of female-specific cognitive behavior therapy for alcohol dependent women.

    Science.gov (United States)

    Epstein, Elizabeth E; McCrady, Barbara S; Hallgren, Kevin A; Cook, Sharon; Jensen, Noelle K; Hildebrandt, Thomas

    2018-02-01

    This study compared Female-Specific Cognitive Behavioral Therapy (FS-CBT) to evidence-based, gender-neutral CBT (GN-CBT; Epstein & McCrady, 2009) for women with alcohol use disorder (AUD). Women (N = 99) with AUD, mean age 48, were randomly assigned to 12 outpatient manual-guided sessions of FS-CBT (n = 44) or GN-CBT (n = 55). Women were assessed at baseline and 3, 9 and 15 months after baseline for drinking and for specific issues common among women with AUD. A FS-CBT protocol was developed that was discriminable on treatment integrity ratings from GN-CBT. No treatment condition differences were found in treatment engagement, changes in drinking, alcohol-related coping, abstinence self-efficacy, motivation to change, or constructs directly targeted in FS-CBT (sociotropy, autonomy, depression, anxiety). Women in both conditions were highly engaged and satisfied with treatment, and reported significant reductions in drinking and changes in desired directions for all other variables except social support for abstinence. In the year following treatment, women in the FS-CBT but not in the CBT condition reported an increase in percentage of abstainers in their social networks (0.69% per month, SE = 0.21, p = .002). The value and appeal of female-specific programming in AUD treatment has been established in the wider literature (Epstein & Menges, 2013), and the current study provides support for the use of the Female-Specific Cognitive Behavioral Therapy (FS-CBT) manual as an option that may yield outcomes similar to standard gender-neutral CBT for women with AUD. Future research should examine whether FS-CBT enhances treatment utilization for women. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  10. Identification of phreatophytic groundwater dependent ecosystems using geospatial technologies

    Science.gov (United States)

    Perez Hoyos, Isabel Cristina

    The protection of groundwater dependent ecosystems (GDEs) is increasingly being recognized as an essential aspect for the sustainable management and allocation of water resources. Ecosystem services are crucial for human well-being and for a variety of flora and fauna. However, the conservation of GDEs is only possible if knowledge about their location and extent is available. Several studies have focused on the identification of GDEs at specific locations using ground-based measurements. However, recent progress in technologies such as remote sensing and their integration with geographic information systems (GIS) has provided alternative ways to map GDEs at much larger spatial extents. This study is concerned with the discovery of patterns in geospatial data sets using data mining techniques for mapping phreatophytic GDEs in the United States at 1 km spatial resolution. A methodology to identify the probability of an ecosystem to be groundwater dependent is developed. Probabilities are obtained by modeling the relationship between the known locations of GDEs and main factors influencing groundwater dependency, namely water table depth (WTD) and aridity index (AI). A methodology is proposed to predict WTD at 1 km spatial resolution using relevant geospatial data sets calibrated with WTD observations. An ensemble learning algorithm called random forest (RF) is used in order to model the distribution of groundwater in three study areas: Nevada, California, and Washington, as well as in the entire United States. RF regression performance is compared with a single regression tree (RT). The comparison is based on contrasting training error, true prediction error, and variable importance estimates of both methods. Additionally, remote sensing variables are omitted from the process of fitting the RF model to the data to evaluate the deterioration in the model performance when these variables are not used as an input. Research results suggest that although the prediction

  11. Variability in large-scale wind power generation: Variability in large-scale wind power generation

    Energy Technology Data Exchange (ETDEWEB)

    Kiviluoma, Juha [VTT Technical Research Centre of Finland, Espoo Finland; Holttinen, Hannele [VTT Technical Research Centre of Finland, Espoo Finland; Weir, David [Energy Department, Norwegian Water Resources and Energy Directorate, Oslo Norway; Scharff, Richard [KTH Royal Institute of Technology, Electric Power Systems, Stockholm Sweden; Söder, Lennart [Royal Institute of Technology, Electric Power Systems, Stockholm Sweden; Menemenlis, Nickie [Institut de recherche Hydro-Québec, Montreal Canada; Cutululis, Nicolaos A. [DTU, Wind Energy, Roskilde Denmark; Danti Lopez, Irene [Electricity Research Centre, University College Dublin, Dublin Ireland; Lannoye, Eamonn [Electric Power Research Institute, Palo Alto California USA; Estanqueiro, Ana [LNEG, Laboratorio Nacional de Energia e Geologia, UESEO, Lisbon Spain; Gomez-Lazaro, Emilio [Renewable Energy Research Institute and DIEEAC/EDII-AB, Castilla-La Mancha University, Albacete Spain; Zhang, Qin [State Grid Corporation of China, Beijing China; Bai, Jianhua [State Grid Energy Research Institute Beijing, Beijing China; Wan, Yih-Huei [National Renewable Energy Laboratory, Transmission and Grid Integration Group, Golden Colorado USA; Milligan, Michael [National Renewable Energy Laboratory, Transmission and Grid Integration Group, Golden Colorado USA

    2015-10-25

    The paper demonstrates the characteristics of wind power variability and net load variability in multiple power systems based on real data from multiple years. Demonstrated characteristics include probability distribution for different ramp durations, seasonal and diurnal variability and low net load events. The comparison shows regions with low variability (Sweden, Spain and Germany), medium variability (Portugal, Ireland, Finland and Denmark) and regions with higher variability (Quebec, Bonneville Power Administration and Electric Reliability Council of Texas in North America; Gansu, Jilin and Liaoning in China; and Norway and offshore wind power in Denmark). For regions with low variability, the maximum 1 h wind ramps are below 10% of nominal capacity, and for regions with high variability, they may be close to 30%. Wind power variability is mainly explained by the extent of geographical spread, but also higher capacity factor causes higher variability. It was also shown how wind power ramps are autocorrelated and dependent on the operating output level. When wind power was concentrated in smaller area, there were outliers with high changes in wind output, which were not present in large areas with well-dispersed wind power.

  12. Cost-effectiveness of extended buprenorphine-naloxone treatment for opioid-dependent youth: data from a randomized trial.

    Science.gov (United States)

    Polsky, Daniel; Glick, Henry A; Yang, Jianing; Subramaniam, Geetha A; Poole, Sabrina A; Woody, George E

    2010-09-01

    The objective is to estimate cost, net social cost and cost-effectiveness in a clinical trial of extended buprenorphine-naloxone (BUP) treatment versus brief detoxification treatment in opioid-dependent youth. Economic evaluation of a clinical trial conducted at six community out-patient treatment programs from July 2003 to December 2006, who were randomized to 12 weeks of BUP or a 14-day taper (DETOX). BUP patients were prescribed up to 24 mg per day for 9 weeks and then tapered to zero at the end of week 12. DETOX patients were prescribed up to 14 mg per day and then tapered to zero on day 14. All were offered twice-weekly drug counseling. 152 patients aged 15-21 years. Data were collected prospectively during the 12-week treatment and at follow-up interviews at months 6, 9 and 12. The 12-week out-patient study treatment cost was $1514 (P DETOX. One-year total direct medical cost was only $83 higher for BUP (P = 0.97). The cost-effectiveness ratio of BUP relative to DETOX was $1376 in terms of 1-year direct medical cost per quality-adjusted life year (QALY) and $25,049 in terms of out-patient treatment program cost per QALY. The acceptability curve suggests that the cost-effectiveness ratio of BUP relative to DETOX has an 86% chance of being accepted as cost-effective for a threshold of $100,000 per QALY. Extended BUP treatment relative to brief detoxification is cost effective in the US health-care system for the outpatient treatment of opioid-dependent youth.

  13. On a direct algorithm for the generation of log-normal pseudo-random numbers

    CERN Document Server

    Chamayou, J M F

    1976-01-01

    The random variable ( Pi /sub i=1//sup n/X/sub i//X/sub i+n/)/sup 1/ square root 2n/ is used to generate standard log normal variables Lambda (0, 1), where the X/sub i/ are independent uniform variables on (0, 1). (8 refs).

  14. Sources of variability in consonant perception of normal-hearing listeners

    DEFF Research Database (Denmark)

    Zaar, Johannes; Dau, Torsten

    2015-01-01

    between responses. The speech-induced variability across and within talkers and the across-listener variability were substantial and of similar magnitude. The noise-induced variability, obtained with time-shifted realizations of the same random process, was smaller but significantly larger than the amount......Responses obtained in consonant perception experiments typically show a large variability across stimuli of the same phonetic identity. The present study investigated the influence of different potential sources of this response variability. It was distinguished between source-induced variability......, referring to perceptual differences caused by acoustical differences in the speech tokens and/or the masking noise tokens, and receiver-related variability, referring to perceptual differences caused by within- and across-listener uncertainty. Consonant-vowel combinations consisting of 15 consonants...

  15. Random walk term weighting for information retrieval

    DEFF Research Database (Denmark)

    Blanco, R.; Lioma, Christina

    2007-01-01

    We present a way of estimating term weights for Information Retrieval (IR), using term co-occurrence as a measure of dependency between terms.We use the random walk graph-based ranking algorithm on a graph that encodes terms and co-occurrence dependencies in text, from which we derive term weights...

  16. Long-range spatial dependence in fractured rock. Empirical evidence and implications for tracer transport

    International Nuclear Information System (INIS)

    Painter, S.

    1999-02-01

    Nonclassical stochastic continuum models incorporating long-range spatial dependence are evaluated as models for fractured crystalline rock. Open fractures and fracture zones are not modeled explicitly in this approach. The fracture zones and intact rock are modeled as a single stochastic continuum. The large contrasts between the fracture zones and unfractured rock are accounted for by making use of random field models specifically designed for highly variable systems. Hydraulic conductivity data derived from packer tests in the vicinity of the Aespoe Hard Rock Laboratory form the basis for the evaluation. The Aespoe log K data were found to be consistent with a fractal scaling model based on bounded fractional Levy motion (bfLm), a model that has been used previously to model highly variable sedimentary formations. However, the data are not sufficient to choose between this model, a fractional Brownian motion model for the normal-score transform of log K, and a conventional geostatistical model. Stochastic simulations conditioned by the Aespoe data coupled with flow and tracer transport calculations demonstrate that the models with long-range dependence predict earlier arrival times for contaminants. This demonstrates the need to evaluate this class of models when assessing the performance of proposed waste repositories. The relationship between intermediate-scale and large-scale transport properties in media with long-range dependence is also addressed. A new Monte Carlo method for stochastic upscaling of intermediate-scale field data is proposed

  17. The Effect of the Psychiatric Nursing Approach Based on the Tidal Model on Coping and Self-esteem in People with Alcohol Dependency: A Randomized Trial.

    Science.gov (United States)

    Savaşan, Ayşegül; Çam, Olcay

    2017-06-01

    People with alcohol dependency have lower self-esteem than controls and when their alcohol use increases, their self-esteem decreases. Coping skills in alcohol related issues are predicted to reduce vulnerability to relapse. It is important to adapt care to individual needs so as to prevent a return to the cycle of alcohol use. The Tidal Model focuses on providing support and services to people who need to live a constructive life. The aim of the randomized study was to determine the effect of the psychiatric nursing approach based on the Tidal Model on coping and self-esteem in people with alcohol dependency. The study was semi-experimental in design with a control group, and was conducted on 36 individuals (18 experimental, 18 control). An experimental and a control group were formed by assigning persons to each group using the stratified randomization technique in the order in which they were admitted to hospital. The Coping Inventory (COPE) and the Coopersmith Self-Esteem Inventory (CSEI) were used as measurement instruments. The measurement instruments were applied before the application and three months after the application. In addition to routine treatment and follow-up, the psychiatric nursing approach based on the Tidal Model was applied to the experimental group in the One-to-One Sessions. The psychiatric nursing approach based on the Tidal Model is an approach which is effective in increasing the scores of people with alcohol dependency in positive reinterpretation and growth, active coping, restraint, emotional social support and planning and reducing their scores in behavioral disengagement. It was seen that self-esteem rose, but the difference from the control group did not reach significance. The psychiatric nursing approach based on the Tidal Model has an effect on people with alcohol dependency in maintaining their abstinence. The results of the study may provide practices on a theoretical basis for improving coping behaviors and self-esteem and

  18. Uniform Estimate of the Finite-Time Ruin Probability for All Times in a Generalized Compound Renewal Risk Model

    Directory of Open Access Journals (Sweden)

    Qingwu Gao

    2012-01-01

    Full Text Available We discuss the uniformly asymptotic estimate of the finite-time ruin probability for all times in a generalized compound renewal risk model, where the interarrival times of successive accidents and all the claim sizes caused by an accident are two sequences of random variables following a wide dependence structure. This wide dependence structure allows random variables to be either negatively dependent or positively dependent.

  19. Properties and simulation of α-permanental random fields

    DEFF Research Database (Denmark)

    Møller, Jesper; Rubak, Ege Holger

    An α-permanental random field is briefly speaking a model for a collection of random variables with positive associations, where α is a positive number and the probability generating function is given in terms of a covariance or more general function so that density and moment expressions are given...... by certain α-permanents. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of  α-permanental random fields and their potential applications. The purpose of this paper is first to summarize useful probabilistic results using the simplest possible setting......, and second to study stochastic constructions and simulation techniques, which should provide a useful basis for discussing the statistical aspects in future work. The paper also discusses some examples of  α-permanental random fields....

  20. Nonparametric indices of dependence between components for inhomogeneous multivariate random measures and marked sets

    OpenAIRE

    van Lieshout, Maria Nicolette Margaretha

    2018-01-01

    We propose new summary statistics to quantify the association between the components in coverage-reweighted moment stationary multivariate random sets and measures. They are defined in terms of the coverage-reweighted cumulant densities and extend classic functional statistics for stationary random closed sets. We study the relations between these statistics and evaluate them explicitly for a range of models. Unbiased estimators are given for all statistics and applied to simulated examples a...