Rights, Jason D; Sterba, Sonya K
2016-11-01
Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.
Structure of random discrete spacetime
NASA Technical Reports Server (NTRS)
Brightwell, Graham; Gregory, Ruth
1991-01-01
The usual picture of spacetime consists of a continuous manifold, together with a metric of Lorentzian signature which imposes a causal structure on the spacetime. A model, first suggested by Bombelli et al., is considered in which spacetime consists of a discrete set of points taken at random from a manifold, with only the causal structure on this set remaining. This structure constitutes a partially ordered set (or poset). Working from the poset alone, it is shown how to construct a metric on the space which closely approximates the metric on the original spacetime manifold, how to define the effective dimension of the spacetime, and how such quantities may depend on the scale of measurement. Possible desirable features of the model are discussed.
Structure of random discrete spacetime
NASA Technical Reports Server (NTRS)
Brightwell, Graham; Gregory, Ruth
1991-01-01
The usual picture of spacetime consists of a continuous manifold, together with a metric of Lorentzian signature which imposes a causal structure on the spacetime. A model, first suggested by Bombelli et al., is considered in which spacetime consists of a discrete set of points taken at random from a manifold, with only the causal structure on this set remaining. This structure constitutes a partially ordered set (or poset). Working from the poset alone, it is shown how to construct a metric on the space which closely approximates the metric on the original spacetime manifold, how to define the effective dimension of the spacetime, and how such quantities may depend on the scale of measurement. Possible desirable features of the model are discussed.
Handling Correlations between Covariates and Random Slopes in Multilevel Models
ERIC Educational Resources Information Center
Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders
2014-01-01
This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…
Handling Correlations between Covariates and Random Slopes in Multilevel Models
ERIC Educational Resources Information Center
Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders
2014-01-01
This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…
Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials
ERIC Educational Resources Information Center
Sanders, Elizabeth A.
2011-01-01
This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…
Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials
ERIC Educational Resources Information Center
Sanders, Elizabeth A.
2011-01-01
This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…
ERIC Educational Resources Information Center
Zhu, Xiaoshu
2013-01-01
The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…
Modified Discrete Grey Wolf Optimizer Algorithm for Multilevel Image Thresholding
Sun, Lijuan; Guo, Jian; Xu, Bin; Li, Shujing
2017-01-01
The computation of image segmentation has become more complicated with the increasing number of thresholds, and the option and application of the thresholds in image thresholding fields have become an NP problem at the same time. The paper puts forward the modified discrete grey wolf optimizer algorithm (MDGWO), which improves on the optimal solution updating mechanism of the search agent by the weights. Taking Kapur's entropy as the optimized function and based on the discreteness of threshold in image segmentation, the paper firstly discretizes the grey wolf optimizer (GWO) and then proposes a new attack strategy by using the weight coefficient to replace the search formula for optimal solution used in the original algorithm. The experimental results show that MDGWO can search out the optimal thresholds efficiently and precisely, which are very close to the result examined by exhaustive searches. In comparison with the electromagnetism optimization (EMO), the differential evolution (DE), the Artifical Bee Colony (ABC), and the classical GWO, it is concluded that MDGWO has advantages over the latter four in terms of image segmentation quality and objective function values and their stability. PMID:28127305
Modified Discrete Grey Wolf Optimizer Algorithm for Multilevel Image Thresholding.
Li, Linguo; Sun, Lijuan; Guo, Jian; Qi, Jin; Xu, Bin; Li, Shujing
2017-01-01
The computation of image segmentation has become more complicated with the increasing number of thresholds, and the option and application of the thresholds in image thresholding fields have become an NP problem at the same time. The paper puts forward the modified discrete grey wolf optimizer algorithm (MDGWO), which improves on the optimal solution updating mechanism of the search agent by the weights. Taking Kapur's entropy as the optimized function and based on the discreteness of threshold in image segmentation, the paper firstly discretizes the grey wolf optimizer (GWO) and then proposes a new attack strategy by using the weight coefficient to replace the search formula for optimal solution used in the original algorithm. The experimental results show that MDGWO can search out the optimal thresholds efficiently and precisely, which are very close to the result examined by exhaustive searches. In comparison with the electromagnetism optimization (EMO), the differential evolution (DE), the Artifical Bee Colony (ABC), and the classical GWO, it is concluded that MDGWO has advantages over the latter four in terms of image segmentation quality and objective function values and their stability.
Scalable networks for discrete quantum random walks
Fujiwara, S.; Osaki, H.; Buluta, I.M.; Hasegawa, S.
2005-09-15
Recently, quantum random walks (QRWs) have been thoroughly studied in order to develop new quantum algorithms. In this paper we propose scalable quantum networks for discrete QRWs on circles, lines, and also in higher dimensions. In our method the information about the position of the walker is stored in a quantum register and the network consists of only one-qubit rotation and (controlled){sup n}-NOT gates, therefore it is purely computational and independent of the physical implementation. As an example, we describe the experimental realization in an ion-trap system.
The structure of random discrete spacetime
NASA Technical Reports Server (NTRS)
Brightwell, Graham; Gregory, Ruth
1990-01-01
The usual picture of spacetime consists of a continuous manifold, together with a metric of Lorentzian signature which imposes a causal structure on the spacetime. A model, first suggested by Bombelli et al., is considered in which spacetime consists of a discrete set of points taken at random from a manifold, with only the causal structure on this set remaining. This structure constitutes a partially ordered set (or poset). Working from the poset alone, it is shown how to construct a metric on the space which closely approximates the metric on the original spacetime manifold, how to define the effective dimension of the spacetime, and how such quantities may depend on the scale of measurement. Possible desirable features of the model are discussed.
Imaging Through Random Discrete-Scatterer Dispersive Media
2015-08-27
AFRL-AFOSR-VA-TR-2015-0255 Imaging through random discrete-scatterer dispersive media Elizabeth Bleszynski MONOPOLE RESEARCH THOUSAND OAKS CA Final...DATES COVERED Final report 15 April 2012 – 14 April 2015 4. TITLE AND SUBTITLE Imaging Through Random Discrete-Scatterer Dispersive Media 5. FUNDING...and/or target detection through optically obscuring, dilute, discrete-scatterer media such as clouds, fog, dust and other aerosols. (A) Properties of
A multilevel local discrete convolution method for the numerical solution for Maxwell's Equations
NASA Astrophysics Data System (ADS)
Lo, Boris; Colella, Phillip
2016-10-01
We present a new discrete multilevel local discrete convolution method for solving Maxwell's equations in three dimensions. We obtain an explicit real-space representation for the propagator of an auxiliary system of differential equations with initial value constraints that is equivalent to Maxwell's equations. The propagator preserves finite speed of propagation and source locality. Because the propagator involves convolution against a singular distribution, we regularize via convolution with smoothing kernels (B-splines) prior to sampling. We have shown that the ultimate discrete convolutional propagator can be constructed to attain an arbitrarily high order of accuracy by using higher-order regularizing kernels and finite difference stencils. The discretized propagator is compactly supported and can be applied using Hockney's method (1970) and parallelized using domain decomposition, leading to a method that is computationally efficient. The algorithm is extended to work for locally refined fixed hierarchy of rectangular grids. This research is supported by the Office of Advanced Scientific Computing Research of the US Department of Energy under Contract Number DE-AC02-05CH11231.
ERIC Educational Resources Information Center
Zhou, Ji; Castellanos, Michelle
2013-01-01
Utilizing longitudinal data of 3477 students from 28 institutions, we examine the effects of structural diversity and quality of interracial relation on students' persistence towards graduation within six years. We utilize multilevel discrete-time survival analysis to account for the longitudinal persistence patterns as well as the nested…
The ergodic decomposition of stationary discrete random processes
NASA Technical Reports Server (NTRS)
Gray, R. M.; Davisson, L. D.
1974-01-01
The ergodic decomposition is discussed, and a version focusing on the structure of individual sample functions of stationary processes is proved for the special case of discrete-time random processes with discrete alphabets. The result is stronger in this case than the usual theorem, and the proof is both intuitive and simple. Estimation-theoretic and information-theoretic interpretations are developed and applied to prove existence theorems for universal source codes, both noiseless and with a fidelity criterion.
Discrete Modeling of the Worm Spread with Random Scanning
NASA Astrophysics Data System (ADS)
Uchida, Masato
In this paper, we derive a set of discrete time difference equations that models the spreading process of computer worms such as Code-Red and Slammer, which uses a common strategy called “random scanning” to spread through the Internet. We show that the derived set of discrete time difference equations has an exact relationship with the Kermack and McKendrick susceptible-infectious-removed (SIR) model, which is known as a standard continuous time model for worm spreading.
Examining school-based bullying interventions using multilevel discrete time hazard modeling.
Ayers, Stephanie L; Wagaman, M Alex; Geiger, Jennifer Mullins; Bermudez-Parsai, Monica; Hedberg, E C
2012-10-01
Although schools have been trying to address bullying by utilizing different approaches that stop or reduce the incidence of bullying, little remains known about what specific intervention strategies are most successful in reducing bullying in the school setting. Using the social-ecological framework, this paper examines school-based disciplinary interventions often used to deliver consequences to deter the reoccurrence of bullying and aggressive behaviors among school-aged children. Data for this study are drawn from the School-Wide Information System (SWIS) with the final analytic sample consisting of 1,221 students in grades K - 12 who received an office disciplinary referral for bullying during the first semester. Using Kaplan-Meier Failure Functions and Multi-level discrete time hazard models, determinants of the probability of a student receiving a second referral over time were examined. Of the seven interventions tested, only Parent-Teacher Conference (AOR = 0.65, p < .01) and Loss of Privileges (AOR = 0.71, p < .10) were significant in reducing the rate of the reoccurrence of bullying and aggressive behaviors. By using a social-ecological framework, schools can develop strategies that deter the reoccurrence of bullying by identifying key factors that enhance a sense of connection between the students' mesosystems as well as utilizing disciplinary strategies that take into consideration student's microsystem roles.
Examining School-Based Bullying Interventions Using Multilevel Discrete Time Hazard Modeling
Wagaman, M. Alex; Geiger, Jennifer Mullins; Bermudez-Parsai, Monica; Hedberg, E. C.
2014-01-01
Although schools have been trying to address bulling by utilizing different approaches that stop or reduce the incidence of bullying, little remains known about what specific intervention strategies are most successful in reducing bullying in the school setting. Using the social-ecological framework, this paper examines school-based disciplinary interventions often used to deliver consequences to deter the reoccurrence of bullying and aggressive behaviors among school-aged children. Data for this study are drawn from the School-Wide Information System (SWIS) with the final analytic sample consisting of 1,221 students in grades K – 12 who received an office disciplinary referral for bullying during the first semester. Using Kaplan-Meier Failure Functions and Multi-level discrete time hazard models, determinants of the probability of a student receiving a second referral over time were examined. Of the seven interventions tested, only Parent-Teacher Conference (AOR=0.65, p<.01) and Loss of Privileges (AOR=0.71, p<.10) were significant in reducing the rate of the reoccurrence of bullying and aggressive behaviors. By using a social-ecological framework, schools can develop strategies that deter the reoccurrence of bullying by identifying key factors that enhance a sense of connection between the students’ mesosystems as well as utilizing disciplinary strategies that take into consideration student’s microsystem roles. PMID:22878779
NASA Technical Reports Server (NTRS)
Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.
2016-01-01
A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell- Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of
NASA Astrophysics Data System (ADS)
Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.
2016-05-01
A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell-Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of
MULTILEVEL ACCELERATION OF STOCHASTIC COLLOCATION METHODS FOR PDE WITH RANDOM INPUT DATA
Webster, Clayton G; Jantsch, Peter A; Teckentrup, Aretha L; Gunzburger, Max D
2013-01-01
Stochastic Collocation (SC) methods for stochastic partial differential equa- tions (SPDEs) suffer from the curse of dimensionality, whereby increases in the stochastic dimension cause an explosion of computational effort. To combat these challenges, multilevel approximation methods seek to decrease computational complexity by balancing spatial and stochastic discretization errors. As a form of variance reduction, multilevel techniques have been successfully applied to Monte Carlo (MC) methods, but may be extended to accelerate other methods for SPDEs in which the stochastic and spatial degrees of freedom are de- coupled. This article presents general convergence and computational complexity analysis of a multilevel method for SPDEs, demonstrating its advantages with regard to standard, single level approximation. The numerical results will highlight conditions under which multilevel sparse grid SC is preferable to the more traditional MC and SC approaches.
Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain
NASA Technical Reports Server (NTRS)
Lang, R. H.
1984-01-01
Microwave remote sensing of agricultural crops and forested regions is studied. Long term goals of the research involve modeling vegetation so that radar signatures can be used to infer the parameters which characterize the vegetation and underlying ground. Vegetation is modeled by discrete scatterers viz, leaves, stems, branches and trunks. These are replaced by glossy dielectric discs and cylinders. Rough surfaces are represented by their mean and spectral characteristics. Average scattered power is then calculated by employing discrete random media methodology such as the distorted Born approximation or transport theory. Both coherent and incoherent multiple scattering techniques are explored. Once direct methods are developed, inversion techniques can be investigated.
Random matrices with discrete spectrum and finite Toda chains
Kavalov, A.R.; Mkrtchyan, R.L.; Zurabyan, L.A. )
1991-12-21
Restricting the eigenvalues of matrices in random matrix models produces different models (Hermitian, unitary, (anti)symmetric, Penner's, etc.). This paper considers the model in which the eigenvalues receive values from some discrete finite set of points, establish the connection of such a model with a finite Toda chain and study the details of this connection. The authors derive the string equation, which in the limit, when eigenvalues become dense on a real axis, tends to the usual string equation.
A discrete impulsive model for random heating and Brownian motion
NASA Astrophysics Data System (ADS)
Ramshaw, John D.
2010-01-01
The energy of a mechanical system subjected to a random force with zero mean increases irreversibly and diverges with time in the absence of friction or dissipation. This random heating effect is usually encountered in phenomenological theories formulated in terms of stochastic differential equations, the epitome of which is the Langevin equation of Brownian motion. We discuss a simple discrete impulsive model that captures the essence of random heating and Brownian motion. The model may be regarded as a discrete analog of the Langevin equation, although it is developed ab initio. Its analysis requires only simple algebraic manipulations and elementary averaging concepts, but no stochastic differential equations (or even calculus). The irreversibility in the model is shown to be a consequence of a natural causal stochastic condition that is closely analogous to Boltzmann's molecular chaos hypothesis in the kinetic theory of gases. The model provides a simple introduction to several ostensibly more advanced topics, including random heating, molecular chaos, irreversibility, Brownian motion, the Langevin equation, and fluctuation-dissipation theorems.
Asymptotic Effect of Misspecification in the Random Part of the Multilevel Model
ERIC Educational Resources Information Center
Berkhof, Johannes; Kampen, Jarl Kennard
2004-01-01
The authors examine the asymptotic effect of omitting a random coefficient in the multilevel model and derive expressions for the change in (a) the variance components estimator and (b) the estimated variance of the fixed effects estimator. They apply the method of moments, which yields a closed form expression for the omission effect. In…
Asymptotic Effect of Misspecification in the Random Part of the Multilevel Model
ERIC Educational Resources Information Center
Berkhof, Johannes; Kampen, Jarl Kennard
2004-01-01
The authors examine the asymptotic effect of omitting a random coefficient in the multilevel model and derive expressions for the change in (a) the variance components estimator and (b) the estimated variance of the fixed effects estimator. They apply the method of moments, which yields a closed form expression for the omission effect. In…
ERIC Educational Resources Information Center
Bauer, Daniel J.; Preacher, Kristopher J.; Gil, Karen M.
2006-01-01
The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects.…
A Structural Modeling Approach to a Multilevel Random Coefficients Model.
ERIC Educational Resources Information Center
Rovine, Michael J.; Molenaar, Peter C. M.
2000-01-01
Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)
Aremu, Olatunde; Lawoko, Stephen; Dalal, Koustuv
2011-01-01
Background High maternal mortality continues to be a major public health problem in most part of the developing world, including Nigeria. Understanding the utilization pattern of maternal healthcare services has been accepted as an important factor for reducing maternal deaths. This study investigates the effect of neighborhood and individual socioeconomic position on the utilization of different forms of place of delivery among women of reproductive age in Nigeria. Methods A population-based multilevel discrete choice analysis was performed using the most recent population-based 2008 Nigerian Demographic and Health Surveys data of women aged between 15 and 49 years. The analysis was restricted to 15,162 ever-married women from 888 communities across the 36 states of the federation including the Federal Capital Territory of Abuja. Results The choice of place to deliver varies across the socioeconomic strata. The results of the multilevel discrete choice models indicate that with every other factor controlled for, the household wealth status, women’s occupation, women’s and partner’s high level of education attainment, and possession of health insurance were associated with use of private and government health facilities for child birth relative to home delivery. The results also show that higher birth order and young maternal age were associated with use of home delivery. Living in a highly socioeconomic disadvantaged neighborhood is associated with home birth compared with the patronage of government health facilities. More specifically, the result revealed that choice of facility-based delivery is clustered around the neighborhoods. Conclusion Home delivery, which cuts across all socioeconomic strata, is a common practice among women in Nigeria. Initiatives that would encourage the appropriate use of healthcare facilities at little or no cost to the most disadvantaged should be accorded the utmost priority. PMID:21792338
Electromagnetic scattering by spheroidal volumes of discrete random medium
NASA Astrophysics Data System (ADS)
Mishchenko, Michael I.; Dlugach, Janna M.
2017-10-01
We use the superposition T-matrix method to compare the far-field scattering matrices generated by spheroidal and spherical volumes of discrete random medium having the same volume and populated by identical spherical particles. Our results fully confirm the robustness of the previously identified coherent and diffuse scattering regimes and associated optical phenomena exhibited by spherical particulate volumes and support their explanation in terms of the interference phenomenon coupled with the order-of-scattering expansion of the far-field Foldy equations. We also show that increasing nonsphericity of particulate volumes causes discernible (albeit less pronounced) optical effects in forward and backscattering directions and explain them in terms of the same interference/multiple-scattering phenomenon.
Fast Multilevel Solvers for a Class of Discrete Fourth Order Parabolic Problems
Zheng, Bin; Chen, Luoping; Hu, Xiaozhe; Chen, Long; Nochetto, Ricardo H.; Xu, Jinchao
2016-03-05
In this paper, we study fast iterative solvers for the solution of fourth order parabolic equations discretized by mixed finite element methods. We propose to use consistent mass matrix in the discretization and use lumped mass matrix to construct efficient preconditioners. We provide eigenvalue analysis for the preconditioned system and estimate the convergence rate of the preconditioned GMRes method. Furthermore, we show that these preconditioners only need to be solved inexactly by optimal multigrid algorithms. Our numerical examples indicate that the proposed preconditioners are very efficient and robust with respect to both discretization parameters and diffusion coefficients. We also investigate the performance of multigrid algorithms with either collective smoothers or distributive smoothers when solving the preconditioner systems.
Multilevel analysis of group-randomized trials with binary outcomes.
Kim, Hae-Young; Preisser, John S; Rozier, R Gary; Valiyaparambil, Jayasanker V
2006-08-01
Many dental studies have assessed the effectiveness of community- or group-based interventions such as community water fluoridation. These cluster trials, of which group-randomized trials (GRTs) are one type, have design and analysis considerations not found in studies with randomization of treatments to individuals (randomized controlled trials, RCTs). The purpose of this paper is to review analytic methods used for the analysis of binary outcomes from cluster trials and to illustrate these concepts and analytical methods using a school-based GRT. We examine characteristics of GRTs including intra-class correlation (ICC), their most distinctive feature, and review analytical methods for GRTs including group-level analysis, adjusted chi-square test and multivariable analysis (mixed effect models and generalized estimating equations) for correlated binary data. We consider two- and three-level modeling of data from a cross-sectional cluster design. We apply the concepts reviewed using a GRT designed to determine the effect of incentives on response rates in a school-based dental study. We compare the results of analyses using methods for correlated binary data with those from traditional methods that do not account for ICC. Application of traditional analytic methods to the dental GRT used as an example for this paper led to a substantial overstatement of the effectiveness of the intervention. Ignoring the ICC among members of the same group in the analysis of public health intervention studies can lead to erroneous conclusions where groups are the unit of assignment. Special consideration is needed in the analysis of data from these cluster trials. Randomization of treatments to groups also should receive more consideration in the design of cluster trials in dental public health.
Genome mapping by random anchoring: A discrete theoretical analysis
NASA Astrophysics Data System (ADS)
Zhang, M. Q.; Marr, T. G.
1993-11-01
As a part of the international human genome project, large-scale genomic maps of human and other model organisms are being generated. More recently, mapping using various anchoring (as opposed to the traditional "fingerprinting") strategies have been proposed based largely on mathematical models. In all of the theoretical work dealing with anchoring, an anchor has been idealized as a point on a continuous, infinite-length genome. In general, it is not desirable to make these assumptions, since in practice they may be violated under a variety of actual biological situations. Here we analyze a discrete model that can be used to predict the expected progress made when mapping by random anchoring. By virtue of keeping all three length scales (genome length, clone length, and probe length) finite, our results for the random anchoring strategy are derived in full generality, which contain previous results as special cases and hence can have broad application for planning mapping experiments or assessing the accuracy of the continuum models. Finally, we pose a challenging nonrandom anchoring model corresponding to a more efficient mapping scheme.
Smoking in young adolescents: an approach with multilevel discrete choice models
Pinilla, J; Gonzalez, B; Barber, P; Santana, Y
2002-01-01
Design: Cross sectional analysis performed by multilevel logistic regression with pupils at the first level and schools at the second level. The data came from a stratified sample of students surveyed on their own, their families' and their friends' smoking habits, their schools, and their awareness of cigarette prices and advertising. Setting: The study was performed in the Island of Gran Canaria, Spain. Participants: 1877 students from 30 secondary schools in spring of 2000 (model's effective sample sizes 1697 and 1738) . Main results: 14.2% of the young teenagers surveyed use tobacco, almost half of them (6.3% of the total surveyed) on a daily basis. According to the ordered logistic regression model, to have a smoker as the best friend increases significantly the probability of smoking (odds ratio: 6.96, 95% confidence intervals (CI) (4.93 to 9.84), and the same stands for one smoker living at home compared with a smoking free home (odds ratio: 2.03, 95% CI 1.22 to 3.36). Girls smoke more (odds ratio: 1.85, 95% CI 1.33 to 2.59). Experience with alcohol, and lack of interest in studies are also significant factors affecting smoking. Multilevel models of logistic regression showed that factors related to the school affect the smoking behaviour of young teenagers. More specifically, whether a school complies with antismoking rules or not is the main factor to predict smoking prevalence in schools. The remainder of the differences can be attributed to individual and family characteristics, tobacco consumption by parents or other close relatives, and peer group. Conclusions: A great deal of the individual differences in smoking are explained by factors at the school level, therefore the context is very relevant in this case. The most relevant predictors for smoking in young adolescents include some factors related to the schools they attend. One variable stood out in accounting for the school to school differences: how well they enforced the no smoking rule
Dasgupta, Paramita; Cramb, Susanna M; Aitken, Joanne F; Turrell, Gavin; Baade, Peter D
2014-10-04
Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20-84 years diagnosed during 1997-2007 from Queensland, Australia. Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings.
Discrete random media techniques for microwave modeling of vegetated terrain
NASA Technical Reports Server (NTRS)
Lang, Roger H.
1991-01-01
Microwave remote sensing models of vegetated terrain are investigated. The problem is to determine canopy characteristics such as biomass, canopy height, and the moisture of the underlying soil. The report describes a discrete scatter model which has been employed to model backscatter in the active (radar) case and to model brightness temperature in the passive (radiometric) case. The acquisition of ground truth data is discussed, as well as the comparison of theory and experiment. The overall conclusion of the work has been that the discrete scatter model in conjunction with efficient scatter algorithms and the distorted Born approximation is a most appropriate methodology to use for modeling purposes in the microwave region.
Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain
NASA Technical Reports Server (NTRS)
Lang, R. H.
1984-01-01
Microwave modeling of vegetated terrain was investigated. The purpose was to: (1) use discrete scatter theory to model vegetation (crops and forested regions) in microwave region; (2) develop models for scatterers and ground; (3) multiple scattering analysis relate model parameters to average scattered power; and (4) develop inversion techniques to remotely determine model parameters.
Multiple Scattering of Waves in Discrete Random Media.
1987-12-31
2.2 Material Properties for Piezoelectric Composites (SH Wave Incidence) Case I Case 2 P, (kg/m ) 6600 7000 3 1100 1000 c44 (N/nm) 8.5 x 109 8 .S x...patterns of R-1 and R.4 are presented as Figures 7 and 8 respectively. The matrix material was chosen to be PVC and the dielectric constant of PVC...PENNSYLVANIA STATE UNIVERSITY * RESEARCH CENTER FOR THE ENGINEERING OF ELECTRONIC & ACOUSTIC MATERIALS 00 Multiple Scattering of Waves 0 in Discrete
Self-consistent quasiparticle random-phase approximation for a multilevel pairing model
Hung, N. Quang; Dang, N. Dinh
2007-11-15
Particle-number projection within the Lipkin-Nogami (LN) method is applied to the self-consistent quasiparticle random-phase approximation (SCQRPA), which is tested in an exactly solvable multilevel pairing model. The SCQRPA equations are numerically solved to find the energies of the ground and excited states at various numbers {omega} of doubly degenerate equidistant levels. The use of the LN method allows one to avoid the collapse of the BCS (QRPA) to obtain the energies of the ground and excited states as smooth functions of the interaction parameter G. The comparison between results given by different approximations such as the SCRPA, QRPA, LNQRPA, SCQRPA, and LNSCQRPA is carried out. Although the use of the LN method significantly improves the agreement with the exact results in the intermediate coupling region, we found that in the strong coupling region the SCQRPA results are closest to the exact ones.
ERIC Educational Resources Information Center
Aydin, Burak; Leite, Walter L.; Algina, James
2016-01-01
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
ERIC Educational Resources Information Center
Aydin, Burak; Leite, Walter L.; Algina, James
2016-01-01
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
Multiple scattering of arbitrarily incident Bessel beams by random discrete particles.
Cui, Zhiwei; Han, Yiping; Ai, Xia
2013-11-01
In this paper, we introduce an efficient numerical method to characterize the multiple scattering by random discrete particles illuminated by Bessel beams with arbitrary incidence. Specifically, the vector expressions of Bessel beams that perfectly satisfy Maxwell's equations in combination with rotation Euler angles are used to represent the arbitrarily incident Bessel beams. A hybrid vector finite element-boundary integral-characteristic-basis function method is utilized to formulate the scattering problems involving multiple discrete particles with a random distribution. Due to the flexibility of the finite element method, the adopted method can conveniently deal with the problems of multiple scattering by randomly distributed homogeneous particles, inhomogeneous particles, and anisotropic particles. Some numerical results are included to illustrate the validity and capability of the proposed method and to show the scattering behaviors of random discrete particles when they are illuminated by Bessel beams.
Multiple Scattering of Electromagnetic Waves in Discrete Random Media.
1984-12-31
purposes, we have also investigated the electromagnetic wave propagation through randomly distributed and oriented scatterers by introducing the concept...computer to determine whether or not particle overlap has occurred. The implementation of the "physics" of the system and orientations of non-spherical...34Coherent electromagnetic wave propagation through randomly distributed and oriented pair-correlated dielectric scatterers," Radio Sci., 19, 1445-1449
Multilevel covariance regression with correlated random effects in the mean and variance structure.
Quintero, Adrian; Lesaffre, Emmanuel
2017-09-01
Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Passive imaging with cross correlations in a discrete random medium
NASA Astrophysics Data System (ADS)
Moscoso, M.; Papanicolaou, G.; Sun, R.-H.
2010-01-01
The purpose of this paper is to study the potential and limitations of cross-correlation techniques using numerical simulations, and in particular, we intend to show (i) an estimate of the Green's function in different configurations and (ii) results for passive imaging. This problem seems especially interesting in seismology, nondestructive testing, structure health monitoring, and wireless sensor networks. To compute cross correlations of the impulse signals collected by the receivers, we consider scattering by discrete scatterers to generate impluse responses with targets and without targets. We compute the difference of the cross correlations with targets and the cross correlations without targets to estimate the backpropagator (Green's function) in the Kirchhoff migration functional. The migration functional is essential to compute images of targets. We run numerical simulations for different configurations to explore the limitations of this cross correlation methodology from the results of passive imaging.
Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain
NASA Technical Reports Server (NTRS)
Lang, R. H. (Principal Investigator)
1985-01-01
Microwave remote sensing of vegetated terrain has been studied. Vegetation is modeled so that backscattered radar signals can be used to infer parameters which characterize the vegetation and underlying ground. The vegetation is modeled by discrete lossy dielectric scatterers with prescribed characteristics. The goal of the modeling effort is to remotely sense vegetation type (classification), growth stage, and plant/ground moisture. This information can then be used as input into agricultural, forestry and global circulation models. The microwave frequency spectrum, particularly L and C bands, are especially appropriate for this purpose since the wavelength is comparable to plant leaf and stem size. The resulting resonant interaction leads to backscattered data highly depend on plant shape and orientation. In addition, the transparent nature of the atmosphere in this frequency regime allows for algorithm development which requires no atmospheric correction.
Rantz, Marilyn J.; Nahm, Helen E.; Zwygart-Stauffacher, Mary; Hicks, Lanis; Mehr, David; Flesner, Marcia; Petroski, Gregory F.; Madsen, Richard W.; Scott-Cawiezell, Jill
2012-01-01
Purpose A comprehensive multilevel intervention was tested to build organizational capacity to create and sustain improvement in quality of care and subsequently improve resident outcomes in nursing homes in need of improvement. Intervention facilities (n=29) received a two-year multilevel intervention with monthly on-site consultation from expert nurses with graduate education in gerontological nursing. Attention control facilities (n=29) that also needed to improve resident outcomes received monthly information about aging and physical assessment of elders. Design and Methods Randomized clinical trial of nursing homes in need of improving resident outcomes of bladder and bowel incontinence, weight loss, pressure ulcers, and decline in activities of daily living (ADL). It was hypothesized that following the intervention, experimental facilities would have better resident outcomes, higher quality of care, higher staff retention, more organizational attributes of improved working conditions than control facilities, similar staffing and staff mix, and lower total and direct care costs. Results The intervention did improve quality of care (p=0.02); there were improvements in pressure ulcers (p=0.05), weight loss (p=0.05). Staff retention, organizational working conditions, staffing, and staff mix and most costs were not affected by the intervention. Leadership turnover was surprisingly excessive in both intervention and control groups. Implications Some facilities that are in need of improving quality of care and resident outcomes are able to build the organizational capacity to improve while not increasing staffing or costs of care. Improvement requires continuous supportive consultation and leadership willing to involve staff and work together to build the systematic improvements in care delivery needed. PMID:21816681
Estimation of Parameters from Discrete Random Nonstationary Time Series
NASA Astrophysics Data System (ADS)
Takayasu, H.; Nakamura, T.
For the analysis of nonstationary stochastic time series we introduce a formulation to estimate the underlying time-dependent parameters. This method is designed for random events with small numbers that are out of the applicability range of the normal distribution. The method is demonstrated for numerical data generated by a known system, and applied to time series of traffic accidents, batting average of a baseball player and sales volume of home electronics.
Generation of Random Particle Packings for Discrete Element Models
NASA Astrophysics Data System (ADS)
Abe, S.; Weatherley, D.; Ayton, T.
2012-04-01
An important step in the setup process of Discrete Element Model (DEM) simulations is the generation of a suitable particle packing. There are quite a number of properties such a granular material specimen should ideally have, such as high coordination number, isotropy, the ability to fill arbitrary bounding volumes and the absence of locked-in stresses. An algorithm which is able to produce specimens fulfilling these requirements is the insertion based sphere packing algorithm originally proposed by Place and Mora, 2001 [2] and extended in this work. The algorithm works in two stages. First a number of "seed" spheres are inserted into the bounding volume. In the second stage the gaps between the "seed" spheres are filled by inserting new spheres in a way so they have D+1 (i.e. 3 in 2D, 4 in 3D) touching contacts with either other spheres or the boundaries of the enclosing volume. Here we present an implementation of the algorithm and a systematic statistical analysis of the generated sphere packings. The analysis of the particle radius distribution shows that they follow a power-law with an exponent ≈ D (i.e. ≈3 for a 3D packing and ≈2 for 2D). Although the algorithm intrinsically guarantees coordination numbers of at least 4 in 3D and 3 in 2D, the coordination numbers realized in the generated packings can be significantly higher, reaching beyond 50 if the range of particle radii is sufficiently large. Even for relatively small ranges of particle sizes (e.g. Rmin = 0.5Rmax) the maximum coordination number may exceed 10. The degree of isotropy of the generated sphere packing is also analysed in both 2D and 3D, by measuring the distribution of orientations of vectors joining the centres of adjacent particles. If the range of particle sizes is small, the packing algorithm yields moderate anisotropy approaching that expected for a face-centred cubic packing of equal-sized particles. However, once Rmin < 0.3Rmax a very high degree of isotropy is demonstrated in
ERIC Educational Resources Information Center
Safarkhani, Maryam; Moerbeek, Mirjam
2013-01-01
In a randomized controlled trial, a decision needs to be made about the total number of subjects for adequate statistical power. One way to increase the power of a trial is by including a predictive covariate in the model. In this article, the effects of various covariate adjustment strategies on increasing the power is studied for discrete-time…
ERIC Educational Resources Information Center
Safarkhani, Maryam; Moerbeek, Mirjam
2013-01-01
In a randomized controlled trial, a decision needs to be made about the total number of subjects for adequate statistical power. One way to increase the power of a trial is by including a predictive covariate in the model. In this article, the effects of various covariate adjustment strategies on increasing the power is studied for discrete-time…
NASA Astrophysics Data System (ADS)
Dlugach, J. M.; Mishchenko, M. I.
2017-07-01
In this paper, we discuss some aspects of numerical modeling of electromagnetic scattering by discrete random medium by using numerically exact solutions of the macroscopic Maxwell equations. Typical examples of such media are clouds of interstellar dust, clouds of interplanetary dust in the Solar system, dusty atmospheres of comets, particulate planetary rings, clouds in planetary atmospheres, aerosol particles with numerous inclusions and so on. Our study is based on the results of extensive computations of different characteristics of electromagnetic scattering obtained by using the superposition T-matrix method which represents a direct computer solver of the macroscopic Maxwell equations for an arbitrary multisphere configuration. As a result, in particular, we clarify the range of applicability of the low-density theories of radiative transfer and coherent backscattering as well as of widely used effective-medium approximations.
NASA Technical Reports Server (NTRS)
Dlugach, Janna M.; Mishchenko, Michael I.
2017-01-01
In this paper, we discuss some aspects of numerical modeling of electromagnetic scattering by discrete random medium by using numerically exact solutions of the macroscopic Maxwell equations. Typical examples of such media are clouds of interstellar dust, clouds of interplanetary dust in the Solar system, dusty atmospheres of comets, particulate planetary rings, clouds in planetary atmospheres, aerosol particles with numerous inclusions and so on. Our study is based on the results of extensive computations of different characteristics of electromagnetic scattering obtained by using the superposition T-matrix method which represents a direct computer solver of the macroscopic Maxwell equations for an arbitrary multisphere configuration. As a result, in particular, we clarify the range of applicability of the low-density theories of radiative transfer and coherent backscattering as well as of widely used effective-medium approximations.
NASA Astrophysics Data System (ADS)
Müller, Florian; Jenny, Patrick; Daniel, Meyer
2014-05-01
To a large extent, the flow and transport behaviour within a subsurface reservoir is governed by its permeability. Typically, permeability measurements of a subsurface reservoir are affordable at few spatial locations only. Due to this lack of information, permeability fields are preferably described by stochastic models rather than deterministically. A stochastic method is needed to asses the transition of the input uncertainty in permeability through the system of partial differential equations describing flow and transport to the output quantity of interest. Monte Carlo (MC) is an established method for quantifying uncertainty arising in subsurface flow and transport problems. Although robust and easy to implement, MC suffers from slow statistical convergence. To reduce the computational cost of MC, the multilevel Monte Carlo (MLMC) method was introduced. Instead of sampling a random output quantity of interest on the finest affordable grid as in case of MC, MLMC operates on a hierarchy of grids. If parts of the sampling process are successfully delegated to coarser grids where sampling is inexpensive, MLMC can dramatically outperform MC. MLMC has proven to accelerate MC for several applications including integration problems, stochastic ordinary differential equations in finance as well as stochastic elliptic and hyperbolic partial differential equations. In this study, MLMC is combined with a reservoir simulator to assess uncertain two phase (water/oil) flow and transport within a random permeability field. The performance of MLMC is compared to MC for a two-dimensional reservoir with a multi-point Gaussian logarithmic permeability field. It is found that MLMC yields significant speed-ups with respect to MC while providing results of essentially equal accuracy. This finding holds true not only for one specific Gaussian logarithmic permeability model but for a range of correlation lengths and variances.
Aga, Fekadu Gochole; Woo, Jiyong; Song, Jeonghwan; Park, Jaehyuk; Lim, Seokjae; Sung, Changhyuck; Hwang, Hyunsang
2017-03-17
In this paper, we investigate the quantized conduction behavior of conductive bridge random access memory (CBRAM) with varied materials and ramping rates. We report stable and reproducible quantized conductance states with integer multiples of fundamental conductance obtained by optimizing the voltage ramping rate and the Ti-diffusion barrier (DB) at the Cu/HfO2 interface. Owing to controlled diffusion of Cu ions by the Ti-DB and the optimized ramping rate, through which it was possible to control the time delay of Cu ion reduction, more than seven levels of discrete conductance states were clearly observed. Analytical modeling was performed to determine the rate-limiting step in filament growth based on an electrochemical redox reaction. Our understanding of the fundamental mechanisms of quantized conductance behaviors provide a promising future for the multi-bit CBRAM device.
NASA Astrophysics Data System (ADS)
Gochole Aga, Fekadu; Woo, Jiyong; Song, Jeonghwan; Park, Jaehyuk; Lim, Seokjae; Sung, Changhyuck; Hwang, Hyunsang
2017-03-01
In this paper, we investigate the quantized conduction behavior of conductive bridge random access memory (CBRAM) with varied materials and ramping rates. We report stable and reproducible quantized conductance states with integer multiples of fundamental conductance obtained by optimizing the voltage ramping rate and the Ti-diffusion barrier (DB) at the Cu/HfO2 interface. Owing to controlled diffusion of Cu ions by the Ti-DB and the optimized ramping rate, through which it was possible to control the time delay of Cu ion reduction, more than seven levels of discrete conductance states were clearly observed. Analytical modeling was performed to determine the rate-limiting step in filament growth based on an electrochemical redox reaction. Our understanding of the fundamental mechanisms of quantized conductance behaviors provide a promising future for the multi-bit CBRAM device.
Comparing Algorithms for Graph Isomorphism Using Discrete- and Continuous-Time Quantum Random Walks
Rudinger, Kenneth; Gamble, John King; Bach, Eric; ...
2013-07-01
Berry and Wang [Phys. Rev. A 83, 042317 (2011)] show numerically that a discrete-time quan- tum random walk of two noninteracting particles is able to distinguish some non-isomorphic strongly regular graphs from the same family. Here we analytically demonstrate how it is possible for these walks to distinguish such graphs, while continuous-time quantum walks of two noninteracting parti- cles cannot. We show analytically and numerically that even single-particle discrete-time quantum random walks can distinguish some strongly regular graphs, though not as many as two-particle noninteracting discrete-time walks. Additionally, we demonstrate how, given the same quantum random walk, subtle di erencesmore » in the graph certi cate construction algorithm can nontrivially im- pact the walk's distinguishing power. We also show that no continuous-time walk of a xed number of particles can distinguish all strongly regular graphs when used in conjunction with any of the graph certi cates we consider. We extend this constraint to discrete-time walks of xed numbers of noninteracting particles for one kind of graph certi cate; it remains an open question as to whether or not this constraint applies to the other graph certi cates we consider.« less
Comparing Algorithms for Graph Isomorphism Using Discrete- and Continuous-Time Quantum Random Walks
Rudinger, Kenneth; Gamble, John King; Bach, Eric; Friesen, Mark; Joynt, Robert; Coppersmith, S. N.
2013-07-01
Berry and Wang [Phys. Rev. A 83, 042317 (2011)] show numerically that a discrete-time quan- tum random walk of two noninteracting particles is able to distinguish some non-isomorphic strongly regular graphs from the same family. Here we analytically demonstrate how it is possible for these walks to distinguish such graphs, while continuous-time quantum walks of two noninteracting parti- cles cannot. We show analytically and numerically that even single-particle discrete-time quantum random walks can distinguish some strongly regular graphs, though not as many as two-particle noninteracting discrete-time walks. Additionally, we demonstrate how, given the same quantum random walk, subtle di erences in the graph certi cate construction algorithm can nontrivially im- pact the walk's distinguishing power. We also show that no continuous-time walk of a xed number of particles can distinguish all strongly regular graphs when used in conjunction with any of the graph certi cates we consider. We extend this constraint to discrete-time walks of xed numbers of noninteracting particles for one kind of graph certi cate; it remains an open question as to whether or not this constraint applies to the other graph certi cates we consider.
Monceau, Pascal
2012-12-01
The effects of disorder on the critical behavior of the q-state Potts model in noninteger dimensions are studied by comparison of deterministic and random fractals sharing the same dimensions in the framework of a discrete scale invariance. We carried out intensive Monte Carlo simulations. In the case of a fractal dimension slightly smaller than two d(f) ~/= 1.974636, we give evidence that the disorder structured by discrete scale invariance does not change the first order transition associated with the deterministic case when q = 7. Furthermore the study of the high value q = 14 shows that the transition is a second order one both for deterministic and random scale invariance, but that their behavior belongs to different university classes.
Localization estimates for a random discrete wave equation at high frequency
Faris, W.G.
1987-02-01
It is shown that at high frequencies matrix elements of the Green's function of a random discrete wave equation decay exponentially at long distances. This is the input to the proof of dense point spectrum with localized eigenfunctions in this frequency range. The proof uses techniques of Froehlich and Spencer. A sequence of renormalization transformations shows that large regions where wave propagation is easily maintained become increasingly sparse as resonance is approached.
NASA Astrophysics Data System (ADS)
Matthews, J. O.; Hopcraft, K. I.; Jakeman, E.
2003-11-01
Some properties of classical population processes that comprise births, deaths and multiple immigrations are investigated. The rates at which the immigrants arrive can be tailored to produce a population whose steady state fluctuations are described by a pre-selected distribution. Attention is focused on the class of distributions with a discrete stable law, which have power-law tails and whose moments and autocorrelation function do not exist. The separate problem of monitoring and characterizing the fluctuations is studied, analysing the statistics of individuals that leave the population. The fluctuations in the size of the population are transferred to the times between emigrants that form an intermittent time series of events. The emigrants are counted with a detector of finite dynamic range and response time. This is modelled through clipping the time series or saturating it at an arbitrary but finite level, whereupon its moments and correlation properties become finite. Distributions for the time to the first counted event and for the time between events exhibit power-law regimes that are characteristic of the fluctuations in population size. The processes provide analytical models with which properties of complex discrete random phenomena can be explored, and in addition provide generic means by which random time series encompassing a wide range of intermittent and other discrete random behaviour may be generated.
Random or Fixed Testlet Effects: A Comparison of Two Multilevel Testlet Models
ERIC Educational Resources Information Center
Chen, Tzu-An
2010-01-01
This simulation study compared the performance of two multilevel measurement testlet (MMMT) models: Beretvas and Walker's (2008) two-level MMMT model and Jiao, Wang, and Kamata's (2005) three-level model. Several conditions were manipulated (including testlet length, sample size, and the pattern of the testlet effects) to assess the impact on the…
Cho, Sun-Joo; Gilbert, Jennifer K; Goodwin, Amanda P
2013-10-01
This paper presents an explanatory multidimensional multilevel random item response model and its application to reading data with multilevel item structure. The model includes multilevel random item parameters that allow consideration of variability in item parameters at both item and item group levels. Item-level random item parameters were included to model unexplained variance remaining when item related covariates were used to explain variation in item difficulties. Item group-level random item parameters were included to model dependency in item responses among items having the same item stem. Using the model, this study examined the dimensionality of a person's word knowledge, termed lexical representation, and how aspects of morphological knowledge contributed to lexical representations for different persons, items, and item groups.
NASA Astrophysics Data System (ADS)
Ding, Derui; Shen, Yuxuan; Song, Yan; Wang, Yongxiong
2016-07-01
This paper is concerned with the state estimation problem for a class of discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks. The stochastic nonlinearity described by statistical means which covers several classes of well-studied nonlinearities as special cases is taken into discussion. The randomly occurring deception attacks are modelled by a set of random variables obeying Bernoulli distributions with given probabilities. The purpose of the addressed state estimation problem is to design an estimator with hope to minimize the upper bound for estimation error covariance at each sampling instant. Such an upper bound is minimized by properly designing the estimator gain. The proposed estimation scheme in the form of two Riccati-like difference equations is of a recursive form. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed scheme.
Lee, Jong-Hyeon; Stow, Craig A; Landrum, Peter F
2009-11-01
We exposed Hyalella azteca to p,p'-dichlorodiphenyldichloroethylene for intervals of 1 to 4 d and followed mortality out to 10 d. Mortality was determined as the cessation of heartbeat; dead organism body residue was determined daily. To model mortality probability, body residues of the living organisms were estimated using published kinetic data with concentration-dependent rate constants. The estimated residues compared favorably with measured residues in the dead organisms (predicted body residue = 1.302 ± 0.142 measured body residue + 10.351 ± 15.766, r² = 0.64, n = 50). The response data were collected at discrete intervals; thus, it was not possible to determine the exact time of death for organisms. Consequently, we analyzed the mortality data using discrete interval analysis, in a Bayesian hierarchical framework, with body residue as the dose metric. The predicted body residues to produce mortality were similar across the duration of exposure when postexposure mortality was considered. The concentration for 50% mortality was 0.47 μmol/g (148.6 tg/g, range 0.32-0.66 μmol/g), and predictions of response indicted 95% (range 73-99.9%) mortality at 0.79 μmol/g (250 μg/g) and 4% (range 1.2-9.6%) mortality at 0.16 μmol/g (50 μg/g). The lethal residue for 50% mortality based on interval analysis for short-term exposures with postexposure mortality resulted in values similar to long-term continuous exposures for exposure durations of more than 600 h.
Feng, Zhixin; Jones, Kelvyn; Wang, Wenfei Winnie
2015-04-01
This study undertakes a survival analysis of elderly persons in China using Chinese Longitudinal Healthy Longevity Survey 2002-2008. Employing discrete-time multilevel models, we explored the effect of social support on the survival of elderly people in China. This study focuses on objective (living arrangements and received support) and subjective activities (perceived support) of social support, finding that the effect of different activities of social support on the survival of elderly people varies according to the availability of different support resources. Specifically, living with a spouse, financial independence, perceiving care support from any resource is associated with higher survival rates for elderly people. Separate analysis focusing on urban elderly and rural elderly revealed broadly similar results. There is a larger difference between those perceiving care support from family or social service and not perceiving care support in urban areas comparing to those in rural areas. Those who cannot pay medical expenses are the least likely to survive. The higher level of economic development in province has no significant effect on the survival of elderly people for the whole sample model and the elderly people in urban areas; however, there is a negative influence on the survival of the rural elderly people.
Feng, Zhixin; Jones, Kelvyn; Wang, Wenfei Winnie
2015-01-01
This study undertakes a survival analysis of elderly persons in China using Chinese Longitudinal Healthy Longevity Survey 2002–2008. Employing discrete-time multilevel models, we explored the effect of social support on the survival of elderly people in China. This study focuses on objective (living arrangements and received support) and subjective activities (perceived support) of social support, finding that the effect of different activities of social support on the survival of elderly people varies according to the availability of different support resources. Specifically, living with a spouse, financial independence, perceiving care support from any resource is associated with higher survival rates for elderly people. Separate analysis focusing on urban elderly and rural elderly revealed broadly similar results. There is a larger difference between those perceiving care support from family or social service and not perceiving care support in urban areas comparing to those in rural areas. Those who cannot pay medical expenses are the least likely to survive. The higher level of economic development in province has no significant effect on the survival of elderly people for the whole sample model and the elderly people in urban areas; however, there is a negative influence on the survival of the rural elderly people. PMID:25703671
NASA Astrophysics Data System (ADS)
Goudarzi, Alireza; Riahi, Mohammad Ali
2012-12-01
One of the most crucial challenges in seismic data processing is the reduction of the noise in the data or improving the signal-to-noise ratio. In this study, the 1D undecimated discrete wavelet transform (UDWT) has been acquired to attenuate random noise and ground roll. Wavelet domain ground roll analysis (WDGA) is applied to find the ground roll energy in the wavelet domain. The WDGA will be a substitute method for thresholding in seismic data processing. To compare the effectiveness of the WDGA method, we apply the 1D double density discrete wavelet transform (DDDWT) using soft thresholding in the random noise reduction and ground roll attenuation processes. Seismic signals intersect with ground roll in the time and frequency domains. Random noise and ground roll have many undesirable effects on pre-stack seismic data, and result in an inaccurate velocity analysis for NMO correction. In this paper, the UDWT by using the WDGA technique and DDDWT (using the soft thresholding technique) and the regular Fourier based method as f-k transform will be used and compared for seismic denoising.
Coherent Backscattering by Polydisperse Discrete Random Media: Exact T-Matrix Results
NASA Technical Reports Server (NTRS)
Mishchenko, Michael I.; Dlugach, Janna M.; Mackowski, Daniel W.
2011-01-01
The numerically exact superposition T-matrix method is used to compute, for the first time to our knowledge, electromagnetic scattering by finite spherical volumes composed of polydisperse mixtures of spherical particles with different size parameters or different refractive indices. The backscattering patterns calculated in the far-field zone of the polydisperse multiparticle volumes reveal unequivocally the classical manifestations of the effect of weak localization of electromagnetic waves in discrete random media, thereby corroborating the universal interference nature of coherent backscattering. The polarization opposition effect is shown to be the least robust manifestation of weak localization fading away with increasing particle size parameter.
Coherent Backscattering by Polydisperse Discrete Random Media: Exact T-Matrix Results
NASA Technical Reports Server (NTRS)
Mishchenko, Michael I.; Dlugach, Janna M.; Mackowski, Daniel W.
2011-01-01
The numerically exact superposition T-matrix method is used to compute, for the first time to our knowledge, electromagnetic scattering by finite spherical volumes composed of polydisperse mixtures of spherical particles with different size parameters or different refractive indices. The backscattering patterns calculated in the far-field zone of the polydisperse multiparticle volumes reveal unequivocally the classical manifestations of the effect of weak localization of electromagnetic waves in discrete random media, thereby corroborating the universal interference nature of coherent backscattering. The polarization opposition effect is shown to be the least robust manifestation of weak localization fading away with increasing particle size parameter.
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Nakamori, S.
2008-11-06
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.
Dynamical Localization for Discrete and Continuous Random Schrödinger Operators
NASA Astrophysics Data System (ADS)
Germinet, F.; De Bièvre, S.
We show for a large class of random Schrödinger operators Ho on and on that dynamical localization holds, i.e. that, with probability one, for a suitable energy interval I and for q a positive real,
Sui, Liansheng; Duan, Kuaikuai; Liang, Junli; Hei, Xinhong
2014-05-05
A double-image encryption is proposed based on the discrete fractional random transform and logistic maps. First, an enlarged image is composited from two original images and scrambled in the confusion process which consists of a number of rounds. In each round, the pixel positions of the enlarged image are relocated by using cat maps which are generated based on two logistic maps. Then the scrambled enlarged image is decomposed into two components. Second, one of two components is directly separated into two phase masks and the other component is used to derive the ciphertext image with stationary white noise distribution by using the cascaded discrete fractional random transforms generated based on the logistic map. The cryptosystem is asymmetric and has high resistance against to the potential attacks such as chosen plaintext attack, in which the initial values of logistic maps and the fractional orders are considered as the encryption keys while two decryption keys are produced in the encryption process and directly related to the original images. Simulation results and security analysis verify the feasibility and effectiveness of the proposed encryption scheme.
Double-image encryption using discrete fractional random transform and logistic maps
NASA Astrophysics Data System (ADS)
Sui, Liansheng; Lu, Haiwei; Wang, Zhanmin; Sun, Qindong
2014-05-01
A double-image encryption is proposed based on the discrete fractional random transform and logistic maps. Firstly, an enlarged image is composited from two original plaintexts, in which the pixel positions are relocated and the intensity values are changed by a chaotic confusion-diffusion process, and then two scrambled plaintexts are recovered from the enlarged image. Secondly, the two scrambled plaintexts are encoded into the phase and amplitude part of a complex function which is encrypted into a ciphertext with stationary white noise distribution by using the discrete fractional random transform generated based on logistic map. Not only the initial values of the logistic maps used in the cryptosystem but also the phase distribution produced in the encryption process can be used as private keys, which makes the proposed scheme has the characteristic of asymmetric encryption technique and high resistance against to the conventional attacks such as chosen plaintext attack, ciphertext-only attack. Simulation results and security analysis verify the feasibility and effectiveness of the proposed method.
Lemon, Stephenie C.; Wang, Monica L.; Wedick, Nicole M.; Estabrook, Barbara; Druker, Susan; Schneider, Kristin L.; Li, Wenjun; Pbert, Lori
2014-01-01
Objective To describe the effectiveness, reach and implementation of a weight gain prevention intervention among public school employees. Method A multi-level intervention was tested in a cluster randomized trial among 782 employees in 12 central Massachusetts public high schools from 2009 to 2012. The intervention targeted the nutrition and physical activity environment and policies, the social environment and individual knowledge, attitudes and skills. The intervention was compared to a materials only condition. The primary outcome measures were change in weight and body mass index (BMI) at 24-month follow-up. Implementation of physical environment, policy and social environment strategies at the school and interpersonal levels, and intervention participation at the individual level were assessed. Results At 24-month follow-up, there was a net change (difference of the difference) of −3.03 pounds (p=.04) and of −.48 BMI units (p=.05) between intervention and comparison conditions. The majority of intervention strategies were successfully implemented by all intervention schools, although establishing formal policies was challenging. Employee participation in programs targeting the physical and social environment was maintained over time. Conclusion This study supports that a multi-level intervention integrated within the organizational culture can be successfully implemented and prevent weight gain in public high school employees. PMID:24345602
Discrete-time systems with random switches: From systems stability to networks synchronization
NASA Astrophysics Data System (ADS)
Guo, Yao; Lin, Wei; Ho, Daniel W. C.
2016-03-01
In this article, we develop some approaches, which enable us to more accurately and analytically identify the essential patterns that guarantee the almost sure stability of discrete-time systems with random switches. We allow for the case that the elements in the switching connection matrix even obey some unbounded and continuous-valued distributions. In addition to the almost sure stability, we further investigate the almost sure synchronization in complex dynamical networks consisting of randomly connected nodes. Numerical examples illustrate that a chaotic dynamics in the synchronization manifold is preserved when statistical parameters enter some almost sure synchronization region established by the developed approach. Moreover, some delicate configurations are considered on probability space for ensuring synchronization in networks whose nodes are described by nonlinear maps. Both theoretical and numerical results on synchronization are presented by setting only a few random connections in each switch duration. More interestingly, we analytically find it possible to achieve almost sure synchronization in the randomly switching complex networks even with very large population sizes, which cannot be easily realized in non-switching but deterministically connected networks.
Discrete-time systems with random switches: From systems stability to networks synchronization
Guo, Yao; Lin, Wei; Ho, Daniel W. C.
2016-03-15
In this article, we develop some approaches, which enable us to more accurately and analytically identify the essential patterns that guarantee the almost sure stability of discrete-time systems with random switches. We allow for the case that the elements in the switching connection matrix even obey some unbounded and continuous-valued distributions. In addition to the almost sure stability, we further investigate the almost sure synchronization in complex dynamical networks consisting of randomly connected nodes. Numerical examples illustrate that a chaotic dynamics in the synchronization manifold is preserved when statistical parameters enter some almost sure synchronization region established by the developed approach. Moreover, some delicate configurations are considered on probability space for ensuring synchronization in networks whose nodes are described by nonlinear maps. Both theoretical and numerical results on synchronization are presented by setting only a few random connections in each switch duration. More interestingly, we analytically find it possible to achieve almost sure synchronization in the randomly switching complex networks even with very large population sizes, which cannot be easily realized in non-switching but deterministically connected networks.
Baird, Rachel; Maxwell, Scott E
2016-06-01
Time-varying predictors in multilevel models are a useful tool for longitudinal research, whether they are the research variable of interest or they are controlling for variance to allow greater power for other variables. However, standard recommendations to fix the effect of time-varying predictors may make an assumption that is unlikely to hold in reality and may influence results. A simulation study illustrates that treating the time-varying predictor as fixed may allow analyses to converge, but the analyses have poor coverage of the true fixed effect when the time-varying predictor has a random effect in reality. A second simulation study shows that treating the time-varying predictor as random may have poor convergence, except when allowing negative variance estimates. Although negative variance estimates are uninterpretable, results of the simulation show that estimates of the fixed effect of the time-varying predictor are as accurate for these cases as for cases with positive variance estimates, and that treating the time-varying predictor as random and allowing negative variance estimates performs well whether the time-varying predictor is fixed or random in reality. Because of the difficulty of interpreting negative variance estimates, 2 procedures are suggested for selection between fixed-effect and random-effect models: comparing between fixed-effect and constrained random-effect models with a likelihood ratio test or fitting a fixed-effect model when an unconstrained random-effect model produces negative variance estimates. The performance of these 2 procedures is compared. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Müller, Florian Jenny, Patrick Meyer, Daniel W.
2013-10-01
Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley–Leverett transport in random heterogeneous porous media. The performance of MLMC is compared to MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.
Multilevel ensemble Kalman filtering
Hoel, Hakon; Law, Kody J. H.; Tempone, Raul
2016-06-14
This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Multilevel ensemble Kalman filtering
Hoel, Hakon; Law, Kody J. H.; Tempone, Raul
2016-06-14
This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Olsen, Maren K; DeLong, Elizabeth R; Oddone, Eugene Z; Bosworth, Hayden B
2008-12-20
Frequently, studies are conducted in a real clinic setting. When the outcome of interest is collected longitudinally over a specified period of time, this design can lead to unequally spaced intervals and varying numbers of assessments. In our study, these features were embedded in a randomized, factorial design in which interventions to improve blood pressure control were delivered to both patients and providers. We examine the effect of the intervention and compare methods of estimation of both fixed effects and variance components in the multilevel generalized linear mixed model. Methods of comparison include penalized quasi-likelihood (PQL), adaptive quadrature, and Bayesian Monte Carlo methods. We also investigate the implications of reducing the data and analysis to baseline and final measurements. In the full analysis, the PQL fixed-effects estimates were closest to zero and confidence intervals were generally narrower than those of the other methods. The adaptive quadrature and Bayesian fixed-effects estimates were similar, but the Bayesian credible intervals were consistently wider. Variance component estimation was markedly different across methods, particularly for the patient-level random effects. In the baseline and final measurement analysis, we found that estimates and corresponding confidence intervals for the adaptive quadrature and Bayesian methods were very similar. However, the time effect was diminished and other factors also failed to reach statistical significance, most likely due to decreased power. When analyzing data from this type of design, we recommend using either adaptive quadrature or Bayesian methods to fit a multilevel generalized linear mixed model including all available measurements.
Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network
NASA Technical Reports Server (NTRS)
Kuhn, D. Richard; Kacker, Raghu; Lei, Yu
2010-01-01
This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.
Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems
NASA Astrophysics Data System (ADS)
Mahdi Alavi, S. M.; Saif, Mehrdad
2013-12-01
This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.
Order tracking for discrete-random separation in variable speed conditions
NASA Astrophysics Data System (ADS)
Borghesani, P.; Pennacchi, P.; Randall, R. B.; Ricci, R.
2012-07-01
The transmission path from the excitation to the measured vibration on the surface of a mechanical system introduces a distortion both in amplitude and in phase. Moreover, in variable speed conditions, the amplification/attenuation and the phase shift, due to the transfer function of the mechanical system, varies in time. This phenomenon reduces the effectiveness of the traditionally tachometer based order tracking, compromising the results of a discrete-random separation performed by a synchronous averaging. In this paper, for the first time, the extent of the distortion is identified both in the time domain and in the order spectrum of the signal, highlighting the consequences for the diagnostics of rotating machinery. A particular focus is given to gears, providing some indications on how to take advantage of the quantification of the disturbance to better tune the techniques developed for the compensation of the distortion. The full theoretical analysis is presented and the results are applied to an experimental case.
Calcium waves in a model with a random spatially discrete distribution of Ca2+ release sites.
Bugrim, A E; Zhabotinsky, A M; Epstein, I R
1997-01-01
We study the propagation of intracellular calcium waves in a model that features Ca2+ release from discrete sites in the endoplasmic reticulum membrane and random spatial distribution of these sites. The results of our simulations qualitatively reproduce the experimentally observed behavior of the waves. When the level of the channel activator inositol trisphosphate is low, the wave undergoes fragmentation and eventually vanishes at a finite distance from the region of initiation, a phenomenon we refer to as an abortive wave. With increasing activator concentration, the mean distance of propagation increases. Above a critical level of activator, the wave becomes stable. We show that the heterogeneous distribution of Ca2+ channels is the cause of this phenomenon. Images FIGURE 2 FIGURE 9 PMID:9414204
Gottfredson, Nisha C; Sterba, Sonya K; Jackson, Kristina M
2017-01-01
Random coefficient-dependent (RCD) missingness is a non-ignorable mechanism through which missing data can arise in longitudinal designs. RCD, for which we cannot test, is a problematic form of missingness that occurs if subject-specific random effects correlate with propensity for missingness or dropout. Particularly when covariate missingness is a problem, investigators typically handle missing longitudinal data by using single-level multiple imputation procedures implemented with long-format data, which ignores within-person dependency entirely, or implemented with wide-format (i.e., multivariate) data, which ignores some aspects of within-person dependency. When either of these standard approaches to handling missing longitudinal data is used, RCD missingness leads to parameter bias and incorrect inference. We explain why multilevel multiple imputation (MMI) should alleviate bias induced by a RCD missing data mechanism under conditions that contribute to stronger determinacy of random coefficients. We evaluate our hypothesis with a simulation study. Three design factors are considered: intraclass correlation (ICC; ranging from .25 to .75), number of waves (ranging from 4 to 8), and percent of missing data (ranging from 20 to 50%). We find that MMI greatly outperforms the single-level wide-format (multivariate) method for imputation under a RCD mechanism. For the MMI analyses, bias was most alleviated when the ICC is high, there were more waves of data, and when there was less missing data. Practical recommendations for handling longitudinal missing data are suggested.
ERIC Educational Resources Information Center
Laurenceau, Jean-Philippe; Stanley, Scott M.; Olmos-Gallo, Antonio; Baucom, Brian; Markham, Howard J.
2004-01-01
This study is a cluster randomized controlled trial of the Prevention and Relationship Enhancement Program (PREP; H. J. Markman, S. M. Stanley, & S. L. Blumberg, 2001). Fifty-seven religious organizations (ROs), consisting of 217 newlywed couples, were randomly assigned to 1 of 3 intervention conditions: PREP delivered by university clinicians…
NASA Astrophysics Data System (ADS)
Lang, Jun; Hao, Zhengchao
2014-01-01
In this paper, we first propose the discrete multi-parameter fractional random transform (DMPFRNT), which can make the spectrum distributed randomly and uniformly. Then we introduce this new spectrum transform into the image fusion field and present a new approach for the remote sensing image fusion, which utilizes both adaptive pulse coupled neural network (PCNN) and the discrete multi-parameter fractional random transform in order to meet the requirements of both high spatial resolution and low spectral distortion. In the proposed scheme, the multi-spectral (MS) and panchromatic (Pan) images are converted into the discrete multi-parameter fractional random transform domains, respectively. In DMPFRNT spectrum domain, high amplitude spectrum (HAS) and low amplitude spectrum (LAS) components carry different informations of original images. We take full advantage of the synchronization pulse issuance characteristics of PCNN to extract the HAS and LAS components properly, and give us the PCNN ignition mapping images which can be used to determine the fusion parameters. In the fusion process, local standard deviation of the amplitude spectrum is chosen as the link strength of pulse coupled neural network. Numerical simulations are performed to demonstrate that the proposed method is more reliable and superior than several existing methods based on Hue Saturation Intensity representation, Principal Component Analysis, the discrete fractional random transform etc.
Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams
NASA Technical Reports Server (NTRS)
Mackowski, Daniel W.; Mishchenko, Michael I.
2011-01-01
The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.
Direct simulation of multiple scattering by discrete random media illuminated by Gaussian beams
Mackowski, Daniel W.; Mishchenko, Michael I.
2011-01-15
The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.
Discrete random distribution of source dopants in nanowire tunnel transistors (TFETs)
NASA Astrophysics Data System (ADS)
Sylvia, Somaia; Abul Khayer, M.; Alam, Khairul; Park, Hong-Hyun; Klimeck, Gerhard; Lake, Roger
2013-03-01
InAs and InSb nanowire (NW) tunnel field effect transistors (TFETs) require highly degenerate source doping to support the high electric fields in the tunnel region. For a target on-current of 1 μA , the doping requirement may be as high as 1 . 5 ×1020cm-3 in a NW with diameter as low as 4 nm. The small size of these devices demand that the dopants near tunneling region be treated discretely. Therefore, the effects resulting from the random distribution of dopant atoms in the source of a TFET are studied for 30 test devices. Comparing with the transfer characteristics of the same device simulated with a continuum doping model, our results show (1) a spread of I - V toward the positive gate voltage axis, (2) the same average threshold voltage, (3) an average 62% reduction in the on current, and (4) a slight degradation of the subthreshold slope. Random fluctuations in both the number and placement of dopants will be discussed. Also, as the channel length is scaled down, direct tunneling through the channel starts limiting the device performance. Therefore, a comparison of materials is also performed, showing their ability to block direct tunneling for sub-10 nm channel FETs and TFETs. This work was supported in part by the Center on Functional Engineered Nano Architectonics and the Materials, Structures and Devices Focus Center, under the Focus Center Research Program, and by the National Science Foundation under Grant OCI-0749140
Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams
NASA Technical Reports Server (NTRS)
Mackowski, Daniel W.; Mishchenko, Michael I.
2011-01-01
The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.
Revisiting random walks in fractal media: on the occurrence of time discrete scale invariance.
Bab, M A; Fabricius, G; Albano, Ezequiel V
2008-01-28
This paper addresses the kinetic behavior of random walks in fractal media. We perform extensive numerical simulations of both single and annihilating random walkers on several Sierpinski carpets, in order to study the time behavior of three observables: the average number of distinct sites visited by a single walker, the mean-square displacement from the origin, and the density of annihilating random walkers. We found that the time behavior of those observables is given by a power law modulated by soft logarithmic-periodic oscillations. We conjecture that logarithmic-periodic oscillations are a manifestation of a time domain discrete scale iNvariance (DSI) that occurs as a consequence of the spatial DSI of the substrate. Our conjecture implies that the logarithmic periods of oscillations in space and time domains are linked by a dynamic exponent z, through z=log(tau)/log(b(1)), where tau and b(1) are the fundamental scaling ratios of the DSI symmetry in the time and space domains, respectively. We use this relationship in order to compute z for different observables and fractals. Furthermore, we check the values obtained with independent measurements provided by the power-law behavior of the mean-square displacement with time [R(2)(t) proportional variant t(2/z)]. The very good agreement obtained between both computations of the z exponent gives strong support to the idea of an intimate interplay between spatial and time symmetry properties that we expect will have a quite general scope. We expect that the application of the outlined concepts in the field of dynamic processes in fractal media will stimulate further research.
Goldstein, Harvey; Leckie, George; Charlton, Christopher; Tilling, Kate; Browne, William J
2017-01-01
Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subjects and methods A Bayesian model is developed that includes random effects for the mean growth function, an individual age-alignment random effect and random effects for the within-individual variance function. This model is applied to data on boys' heights from the Edinburgh longitudinal growth study and to repeated weight measurements of a sample of pregnant women in the Avon Longitudinal Study of Parents and Children cohort. Results The mean age at which the growth curves for individual boys are aligned is 11.4 years, corresponding to the mean 'take off' age for pubertal growth. The within-individual variance (standard deviation) is found to decrease from 0.24 cm(2) (0.50 cm) at 9 years for the 'average' boy to 0.07 cm(2) (0.25 cm) at 16 years. Change in weight during pregnancy can be characterised by regression splines with random effects that include a large woman-specific random effect for the within-individual variation, which is also correlated with overall weight and weight gain. Conclusions The proposed model provides a useful extension to existing approaches, allowing considerable flexibility in describing within- and between-individual differences in growth patterns.
Calibration of Discrete Random Walk (DRW) Model via G.I Taylor's Dispersion Theory
NASA Astrophysics Data System (ADS)
Javaherchi, Teymour; Aliseda, Alberto
2012-11-01
Prediction of particle dispersion in turbulent flows is still an important challenge with many applications to environmental, as well as industrial, fluid mechanics. Several models of dispersion have been developed to predict particle trajectories and their relative velocities, in combination with a RANS-based simulation of the background flow. The interaction of the particles with the velocity fluctuations at different turbulent scales represents a significant difficulty in generalizing the models to the wide range of flows where they are used. We focus our attention on the Discrete Random Walk (DRW) model applied to flow in a channel, particularly to the selection of eddies lifetimes as realizations of a Poisson distribution with a mean value proportional to κ / ɛ . We present a general method to determine the constant of this proportionality by matching the DRW model dispersion predictions for fluid element and particle dispersion to G.I Taylor's classical dispersion theory. This model parameter is critical to the magnitude of predicted dispersion. A case study of its influence on sedimentation of suspended particles in a tidal channel with an array of Marine Hydrokinetic (MHK) turbines highlights the dependency of results on this time scale parameter. Support from US DOE through the Northwest National Marine Renewable Energy Center, a UW-OSU partnership.
Bao, Haibo; Cao, Jinde
2011-01-01
This paper is concerned with the state estimation problem for a class of discrete-time stochastic neural networks (DSNNs) with random delays. The effect of both variation range and distribution probability of the time delay are taken into account in the proposed approach. The stochastic disturbances are described in terms of a Brownian motion and the time-varying delay is characterized by introducing a Bernoulli stochastic variable. By employing a Lyapunov-Krasovskii functional, sufficient delay-distribution-dependent conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the existence of the state estimator which can be checked readily by the Matlab toolbox. The main feature of the results obtained in this paper is that they are dependent on not only the bound but also the distribution probability of the time delay, and we obtain a larger allowance variation range of the delay, hence our results are less conservative than the traditional delay-independent ones. One example is given to illustrate the effectiveness of the proposed result. Copyright © 2010 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Liu, Yurong; Alsaadi, Fuad E.; Yin, Xiaozhou; Wang, Yamin
2015-02-01
In this paper, we are concerned with the robust H∞ filtering problem for a class of nonlinear discrete time-delay stochastic systems. The system under consideration involves parameter uncertainties, stochastic disturbances, time-varying delays and sector nonlinearities. Both missing measurements and randomly occurring nonlinearities are described via the binary switching sequences satisfying a conditional probability distribution, and the nonlinearities are assumed to be sector bounded. The problem addressed is the design of a full-order filter such that, for all admissible uncertainties, nonlinearities and time-delays, the dynamics of the filtering error is constrained to be robustly exponentially stable in the mean square, and a prescribed ? disturbance rejection attenuation level is also guaranteed. By using the Lyapunov stability theory and some new techniques, sufficient conditions are first established to ensure the existence of the desired filtering parameters. Then, the explicit expression of the desired filter gains is described in terms of the solution to a linear matrix inequality. Finally, a numerical example is exploited to show the usefulness of the results derived.
Sobel, Michael; Madigan, David; Wang, Wei
2016-07-07
We construct a framework for meta-analysis and other multi-level data structures that codifies the sources of heterogeneity between studies or settings in treatment effects and examines their implications for analyses. The key idea is to consider, for each of the treatments under investigation, the subject's potential outcome in each study or setting were he to receive that treatment. We consider four sources of heterogeneity: (1) response inconsistency, whereby a subject's response to a given treatment would vary across different studies or settings, (2) the grouping of nonequivalent treatments, where two or more treatments are grouped and treated as a single treatment under the incorrect assumption that a subject's responses to the different treatments would be identical, (3) nonignorable treatment assignment, and (4) response-related variability in the composition of subjects in different studies or settings. We then examine how these sources affect heterogeneity/homogeneity of conditional and unconditional treatment effects. To illustrate the utility of our approach, we re-analyze individual participant data from 29 randomized placebo-controlled studies on the cardiovascular risk of Vioxx, a Cox-2 selective nonsteroidal anti-inflammatory drug approved by the FDA in 1999 for the management of pain and withdrawn from the market in 2004.
Thomas, D.L.; Johnson, D.; Griffith, B.
2006-01-01
Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a
Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal
2016-01-01
Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive
Ephraim, Patti L.; Hill-Briggs, Felicia; Roter, Debra; Bone, Lee; Wolff, Jennifer; Lewis-Boyer, LaPricia; Levine, David; Aboumatar, Hanan; Cooper, Lisa A; Fitzpatrick, Stephanie; Gudzune, Kimberly; Albert, Michael; Monroe, Dwyan; Simmons, Michelle; Hickman, Debra; Purnell, Leon; Fisher, Annette; Matens, Richard; Noronha, Gary; Fagan, Peter; Ramamurthi, Hema; Ameling, Jessica; Charlston, Jeanne; Sam, Tanyka; Carson, Kathryn A.; Wang, Nae-Yuh; Crews, Deidra; Greer, Raquel; Sneed, Valerie; Flynn, Sarah J.; DePasquale, Nicole; Boulware, L. Ebony
2014-01-01
Background Given their high rates of uncontrolled blood pressure, urban African Americans comprise a particularly vulnerable subgroup of persons with hypertension. Substantial evidence has demonstrated the important role of family and community support in improving patients’ management of a variety of chronic illnesses. However, studies of multilevel interventions designed specifically to improve urban African American patients’ blood pressure self-management by simultaneously leveraging patient, family, and community strengths are lacking. Methods/Design We report the protocol of the Achieving Blood Pressure Control Together (ACT) study, a randomized controlled trial designed to study the effectiveness of interventions that engage patient, family, and community-level resources to facilitate urban African American hypertensive patients’ improved hypertension self-management and subsequent hypertension control. African American patients with uncontrolled hypertension receiving health care in an urban primary care clinic will be randomly assigned to receive 1) an educational intervention led by a community health worker alone, 2) the community health worker intervention plus a patient and family communication activation intervention, or 3) the community health worker intervention plus a problem-solving intervention. All participants enrolled in the study will receive and be trained to use a digital home blood pressure machine. The primary outcome of the randomized controlled trial will be patients’ blood pressure control at 12 months. Discussion Results from the ACT study will provide needed evidence on the effectiveness of comprehensive multi-level interventions to improve urban African American patients’ hypertension control. PMID:24956323
Vanderbei, Robert J.; P Latin-Small-Letter-Dotless-I nar, Mustafa C.; Bozkaya, Efe B.
2013-02-15
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
NASA Astrophysics Data System (ADS)
Gyanathan, Ashvini; Yeo, Yee-Chia
2012-11-01
This work demonstrates a novel two-bit multi-level device structure comprising three phase change material (PCM) layers, separated by SiN thermal barrier layers. This triple PCM stack consisted of (from bottom to top), Ge2Sb2Te5 (GST), an ultrathin SiN barrier, nitrogen-doped GST, another ultrathin SiN barrier, and Ag0.5In0.5Sb3Te6. The PCM layers can selectively amorphize to form 4 different resistance levels ("00," "01," "10," and "11") using respective voltage pulses. Electrical characterization was extensively performed on these devices. Thermal analysis was also done to understand the physics behind the phase changing characteristics of the two-bit memory devices. The melting and crystallization temperatures of the PCMs play important roles in the power consumption of the multi-level devices. The electrical resistivities and thermal conductivities of the PCMs and the SiN thermal barrier are also crucial factors contributing to the phase changing behaviour of the PCMs in the two-bit multi-level PCRAM device.
ERIC Educational Resources Information Center
Connections: A Journal of Adult Literacy, 1997
1997-01-01
This issue contains 12 articles written by teachers who have investigated various aspects of the multilevel question in their own classrooms. "The Multilevel Question" (Lenore Balliro) provides an introduction. "Deconstructing the Great Wall of Print" (Richard Goldberg) investigates reading strategies that allow students with a wide range of…
Direct and inverse problems in radiation of sound from discrete random sources on two coaxial rings
NASA Technical Reports Server (NTRS)
Maestrello, L.
1979-01-01
An analytical model consisting of two ring sources of sound is developed to study the direct radiation in terms of correlation, coherence, and phase and also to aid in solving the inverse-radiation problem of determining the noise source in terms of farfield measurements. The rings consist of discrete sources which are either monopoles or quadrupoles with Gaussian autocorrelations. Only adjacent sources, both within and between the rings, are correlated. Results show that from the farfield information one can determine when the sources are compact or noncompact with respect to the acoustic wavelength and distinguish between the types of sources. In addition, from the inverse-radiation approach one can recover the center of mass, the location and separation distance of the ring, and the respective diameters.
Direct and inverse problems in radiation of sound from discrete random sources on two coaxial rings
NASA Technical Reports Server (NTRS)
Maestrello, L.
1979-01-01
An analytical model consisting of two ring sources of sound is developed to study the direct radiation in terms of correlation, coherence, and phase and also to aid in solving the inverse-radiation problem of determining the noise source in terms of farfield measurements. The rings consist of discrete sources which are either monopoles or quadrupoles with Gaussian autocorrelations. Only adjacent sources, both within and between the rings, are correlated. Results show that from the farfield information one can determine when the sources are compact or noncompact with respect to the acoustic wavelength and distinguish between the types of sources. In addition, from the inverse-radiation approach one can recover the center of mass, the location and separation distance of the ring, and the respective diameters.
Lee, Myoung-Jae; Ahn, Seung-Eon; Lee, Chang Bum; Kim, Chang-Jung; Jeon, Sanghun; Chung, U-In; Yoo, In-Kyeong; Park, Gyeong-Su; Han, Seungwu; Hwang, In Rok; Park, Bae-Ho
2011-11-01
Present charge-based silicon memories are unlikely to reach terabit densities because of scaling limits. As the feature size of memory shrinks to just tens of nanometers, there is insufficient volume available to store charge. Also, process temperatures higher than 800 °C make silicon incompatible with three-dimensional (3D) stacking structures. Here we present a device unit consisting of all NiO storage and switch elements for multilevel terabit nonvolatile random access memory using resistance switching. It is demonstrated that NiO films are scalable to around 30 nm and compatible with multilevel cell technology. The device unit can be a building block for 3D stacking structure because of its simple structure and constituent, high performance, and process temperature lower than 300 °C. Memory resistance switching of NiO storage element is accompanied by an increase in density of grain boundary while threshold resistance switching of NiO switch element is controlled by current flowing through NiO film.
NASA Astrophysics Data System (ADS)
Serinaldi, F.
2010-12-01
Discrete multiplicative random cascade (MRC) models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity) at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC) model based on beta distribution and a discrete canonical beta-logstable (BLS), the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM) model, which is used as a physically based benchmark model. Monte Carlo simulations point out that the dependence of MC and BLS
Practical Marginalized Multilevel Models
Griswold, Michael E.; Swihart, Bruce J.; Caffo, Brian S.; Zeger, Scott L.
2013-01-01
Clustered data analysis is characterized by the need to describe both systematic variation in a mean model and cluster-dependent random variation in an association model. Marginalized multilevel models embrace the robustness and interpretations of a marginal mean model, while retaining the likelihood inference capabilities and flexible dependence structures of a conditional association model. Although there has been increasing recognition of the attractiveness of marginalized multilevel models, there has been a gap in their practical application arising from a lack of readily available estimation procedures. We extend the marginalized multilevel model to allow for nonlinear functions in both the mean and association aspects. We then formulate marginal models through conditional specifications to facilitate estimation with mixed model computational solutions already in place. We illustrate the MMM and approximate MMM approaches on a cerebrovascular deficiency crossover trial using SAS and an epidemiological study on race and visual impairment using R. Datasets, SAS and R code are included as supplemental materials. PMID:24357884
Hou, Nan; Dong, Hongli; Wang, Zidong; Ren, Weijian; Alsaadi, Fuad E
2017-05-01
In this paper, the H∞ state estimation problem is investigated for a class of uncertain discrete-time neural networks subject to infinitely distributed delays and fading channels. Randomly occurring uncertainties (ROUs) are introduced to reflect the random nature of the network condition fluctuations, and the channel fading phenomenon is considered to account for the possibly unreliable network medium on which the measurement signal is transmitted. A set of Bernoulli-distributed white sequences are employed to govern the ROUs and the L-th Rice fading model is utilized where channel coefficients are mutually independent random variables with certain probability density function on [0,1]. We aim to design a state estimator such that the dynamics of the estimation error is asymptotically stable while satisfying the prescribed H∞ performance constraint. By adopting the Lyapunov-Krasovskii functional and the stochastic analysis theory, sufficient conditions are established to ensure the existence of the desired state estimators and the explicit expression of such estimators is acquired. A simulation example is provided to verify the usefulness of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Zhu, P. Y.
1991-01-01
The effective-medium approximation is applied to investigate scattering from a half-space of randomly and densely distributed discrete scatterers. Starting from vector wave equations, an approximation, called effective-medium Born approximation, a particular way, treating Green's functions, and special coordinates, of which the origin is set at the field point, are used to calculate the bistatic- and back-scatterings. An analytic solution of backscattering with closed form is obtained and it shows a depolarization effect. The theoretical results are in good agreement with the experimental measurements in the cases of snow, multi- and first-year sea-ice. The root product ratio of polarization to depolarization in backscattering is equal to 8; this result constitutes a law about polarized scattering phenomena in the nature.
NASA Technical Reports Server (NTRS)
Zhu, P. Y.
1991-01-01
The effective-medium approximation is applied to investigate scattering from a half-space of randomly and densely distributed discrete scatterers. Starting from vector wave equations, an approximation, called effective-medium Born approximation, a particular way, treating Green's functions, and special coordinates, of which the origin is set at the field point, are used to calculate the bistatic- and back-scatterings. An analytic solution of backscattering with closed form is obtained and it shows a depolarization effect. The theoretical results are in good agreement with the experimental measurements in the cases of snow, multi- and first-year sea-ice. The root product ratio of polarization to depolarization in backscattering is equal to 8; this result constitutes a law about polarized scattering phenomena in the nature.
NASA Technical Reports Server (NTRS)
Jin, Y. Q.; Kong, J. A.
1985-01-01
In the strong fluctuation theory for a bounded layer of random discrete scatterers, the second moments of the fields in the second-order distorted Born approximation are obtained for copolarized and cross-polarized fields. The backscattering cross sections per unit area are calculated by including the mutual coherence of the fields due to the coincidental ray paths, and that due to the opposite ray paths, corresponding to the ladder and cross terms in the Feynman diagramatic representation. It is proved that the contributions from ladder and cross terms for the copolarized backscattering cross sections are the same, while the contributions for the cross-polarized backscattering cross sections are of the same order. The bistatic scattering coefficients in the second-order approximation for both the ladder and cross terms are also obtained. The contributions from the cross terms explain the enhancement in the backscattering direction.
Structure and Randomness of Continuous-Time, Discrete-Event Processes
NASA Astrophysics Data System (ADS)
Marzen, Sarah E.; Crutchfield, James P.
2017-08-01
Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calculate, for the first time, the entropy rate and statistical complexity of stochastic processes generated by finite unifilar hidden semi-Markov models—memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel mathematical objects (ɛ -machines of hidden semi-Markov processes) and new information-theoretic methods to stochastic processes.
Random Graphs Associated to Some Discrete and Continuous Time Preferential Attachment Models
NASA Astrophysics Data System (ADS)
Pachon, Angelica; Polito, Federico; Sacerdote, Laura
2016-03-01
We give a common description of Simon, Barabási-Albert, II-PA and Price growth models, by introducing suitable random graph processes with preferential attachment mechanisms. Through the II-PA model, we prove the conditions for which the asymptotic degree distribution of the Barabási-Albert model coincides with the asymptotic in-degree distribution of the Simon model. Furthermore, we show that when the number of vertices in the Simon model (with parameter α ) goes to infinity, a portion of them behave as a Yule model with parameters (λ ,β ) = (1-α ,1), and through this relation we explain why asymptotic properties of a random vertex in Simon model, coincide with the asymptotic properties of a random genus in Yule model. As a by-product of our analysis, we prove the explicit expression of the in-degree distribution for the II-PA model, given without proof in Newman (Contemp Phys 46:323-351, 2005). References to traditional and recent applications of the these models are also discussed.
NASA Astrophysics Data System (ADS)
Ding, Derui; Wang, Zidong; Hu, Jun; Shu, Huisheng
2013-04-01
In this paper, the dissipative control problem is investigated for a class of discrete time-varying systems with simultaneous presence of state saturations, randomly occurring nonlinearities as well as multiple missing measurements. In order to render more practical significance of the system model, some Bernoulli distributed white sequences with known conditional probabilities are adopted to describe the phenomena of the randomly occurring nonlinearities and the multiple missing measurements. The purpose of the addressed problem is to design a time-varying output-feedback controller such that the dissipativity performance index is guaranteed over a given finite-horizon. By introducing a free matrix with its infinity norm less than or equal to 1, the system state is bounded by a convex hull so that some sufficient conditions can be obtained in the form of recursive nonlinear matrix inequalities. A novel controller design algorithm is then developed to deal with the recursive nonlinear matrix inequalities. Furthermore, the obtained results are extended to the case when the state saturation is partial. Two numerical simulation examples are provided to demonstrate the effectiveness and applicability of the proposed controller design approach.
Mandt, C.E.; Leung Tsang )
1992-12-01
The authors study backscattering enhancement from a sparse random distribution of large scatterers wtih a size distribution. Second-order multiple-scattering theory based on the Bethe-Salpeter equation is used to compute the scattered field. The second-order cyclical term is used to account for the enhancement. The effects of polarization are included by using the Mie theory to account for scattering by individual particles, and the result is then averaged over the size distribution. Comparisons are made with experimental data for the case of a slab medium of sparsely distributed dielectric spheres with average ka of 298 and moderate optical thickness. Agreement between theory and experiment is good for both the copolarized and the cross-polarized returns. The Mueller matrix is also derived, an the degree of polarization is computed for the same case. Results show that including the cyclical term reduces the degree of polarization of the computed backscattered return. 19 refs., 5 figs., 2 tabs.
Reliable H∞ control of discrete-time systems against random intermittent faults
NASA Astrophysics Data System (ADS)
Tao, Yuan; Shen, Dong; Fang, Mengqi; Wang, Youqing
2016-07-01
A passive fault-tolerant control strategy is proposed for systems subject to a novel kind of intermittent fault, which is described by a Bernoulli distributed random variable. Three cases of fault location are considered, namely, sensor fault, actuator fault, and both sensor and actuator faults. The dynamic feedback controllers are designed not only to stabilise the fault-free system, but also to guarantee an acceptable performance of the faulty system. The robust H∞ performance index is used to evaluate the effectiveness of the proposed control scheme. In terms of linear matrix inequality, the sufficient conditions of the existence of controllers are given. An illustrative example indicates the effectiveness of the proposed fault-tolerant control method.
NASA Astrophysics Data System (ADS)
Maillot, J.; Davy, P.; Le Goc, R.; Darcel, C.; de Dreuzy, J. R.
2016-11-01
A major use of DFN models for industrial applications is to evaluate permeability and flow structure in hardrock aquifers from geological observations of fracture networks. The relationship between the statistical fracture density distributions and permeability has been extensively studied, but there has been little interest in the spatial structure of DFN models, which is generally assumed to be spatially random (i.e., Poisson). In this paper, we compare the predictions of Poisson DFNs to new DFN models where fractures result from a growth process defined by simplified kinematic rules for nucleation, growth, and fracture arrest. This so-called "kinematic fracture model" is characterized by a large proportion of T intersections, and a smaller number of intersections per fracture. Several kinematic models were tested and compared with Poisson DFN models with the same density, length, and orientation distributions. Connectivity, permeability, and flow distribution were calculated for 3-D networks with a self-similar power law fracture length distribution. For the same statistical properties in orientation and density, the permeability is systematically and significantly smaller by a factor of 1.5-10 for kinematic than for Poisson models. In both cases, the permeability is well described by a linear relationship with the areal density p32, but the threshold of kinematic models is 50% larger than of Poisson models. Flow channeling is also enhanced in kinematic DFN models. This analysis demonstrates the importance of choosing an appropriate DFN organization for predicting flow properties from fracture network parameters.
Nicklas, Jacinda M; Skurnik, Geraldine; Zera, Chloe A; Reforma, Liberty G; Levkoff, Sue E; Seely, Ellen W
2016-02-01
The postpartum period is a window of opportunity for diabetes prevention in women with recent gestational diabetes (GDM), but recruitment for clinical trials during this period of life is a major challenge. We adapted a social-ecologic model to develop a multi-level recruitment strategy at the macro (high or institutional level), meso (mid or provider level), and micro (individual) levels. Our goal was to recruit 100 women with recent GDM into the Balance after Baby randomized controlled trial over a 17-month period. Participants were asked to attend three in-person study visits at 6 weeks, 6, and 12 months postpartum. They were randomized into a control arm or a web-based intervention arm at the end of the baseline visit at six weeks postpartum. At the end of the recruitment period, we compared population characteristics of our enrolled subjects to the entire population of women with GDM delivering at Brigham and Women's Hospital (BWH). We successfully recruited 107 of 156 (69 %) women assessed for eligibility, with the majority (92) recruited during pregnancy at a mean 30 (SD ± 5) weeks of gestation, and 15 recruited postpartum, at a mean 2 (SD ± 3) weeks postpartum. 78 subjects attended the initial baseline visit, and 75 subjects were randomized into the trial at a mean 7 (SD ± 2) weeks postpartum. The recruited subjects were similar in age and race/ethnicity to the total population of 538 GDM deliveries at BWH over the 17-month recruitment period. Our multilevel approach allowed us to successfully meet our recruitment goal and recruit a representative sample of women with recent GDM. We believe that our most successful strategies included using a dedicated in-person recruiter, integrating recruitment into clinical flow, allowing for flexibility in recruitment, minimizing barriers to participation, and using an opt-out strategy with providers. Although the majority of women were recruited while pregnant, women recruited in the early postpartum period were
Skurnik, Geraldine; Zera, Chloe A.; Reforma, Liberty G.; Levkoff, Sue E.; Seely, Ellen W.
2016-01-01
Objective The postpartum period is a window of opportunity for diabetes prevention in women with recent gestational diabetes (GDM), but recruitment for clinical trials during this period of life is a major challenge. Methods We adapted a social-ecologic model to develop a multi-level recruitment strategy at the macro (high or institutional level), meso (mid or provider level), and micro (individual) levels. Our goal was to recruit 100 women with recent GDM into the Balance after Baby randomized controlled trial over a 17-month period. Participants were asked to attend three in-person study visits at 6 weeks, 6 months, and 12 months postpartum. They were randomized into a control arm or a web-based intervention arm at the end of the baseline visit at six weeks postpartum. At the end of the recruitment period, we compared population characteristics of our enrolled subjects to the entire population of women with GDM delivering at Brigham and Women's Hospital (BWH). Results We successfully recruited 107 of 156 (69%) women assessed for eligibility, with the majority (92) recruited during pregnancy at a mean 30 (SD± 5) weeks of gestation, and 15 recruited postpartum, at a mean 2 (SD±3) weeks postpartum. 78 subjects attended the initial baseline visit, and 75 subjects were randomized into the trial at a mean 7 (SD±2) weeks postpartum. The recruited subjects were similar in age and race/ethnicity to the total population of 538 GDM deliveries at BWH over the 17-month recruitment period. Conclusions Our multilevel approach allowed us to successfully meet our recruitment goal and recruit a representative sample of women with recent GDM. We believe that our most successful strategies included using a dedicated in-person recruiter, integrating recruitment into clinical flow, allowing for flexibility in recruitment, minimizing barriers to participation, and using an opt-out strategy with providers. Although the majority of women were recruited while pregnant, women recruited
Lancsar, Emily; Savage, Elizabeth
2004-09-01
Discrete choice experiments (DCEs) are being used increasingly in health economics to elicit preferences for products and programs. The results of such experiments have been used to calculate measures of welfare or more specifically, respondents' 'willingness to pay' (WTP) for products and programs and their 'marginal willingness to pay' (MWTP) for the attributes that make up such products and programs. In this note we show that the methods currently used to derive measures of welfare from DCEs in the health economics literature are not consistent with random utility theory (RUT), or with microeconomic welfare theory more generally. The inconsistency with welfare theory is an important limitation on the use of such WTP estimates in cost-benefit analyses. We describe an alternative method of deriving measures of welfare (compensating variation) from DCEs that is consistent with RUT and is derived using welfare theory. We demonstrate its use in an empirical application to derive the WTP for asthma medication and compare it to the results elicited from the method currently used in the health economics literature.
Liu, Jung-Tzu; Tsou, Hsiao-Hui; Gordon Lan, K K; Chen, Chi-Tian; Lai, Yi-Hsuan; Chang, Wan-Jung; Tzeng, Chyng-Shyan; Hsiao, Chin-Fu
2016-06-30
In recent years, developing pharmaceutical products via multiregional clinical trials (MRCTs) has become standard. Traditionally, an MRCT would assume that a treatment effect is uniform across regions. However, heterogeneity among regions may have impact upon the evaluation of a medicine's effect. In this study, we consider a random effects model using discrete distribution (DREM) to account for heterogeneous treatment effects across regions for the design and evaluation of MRCTs. We derive an power function for a treatment that is beneficial under DREM and illustrate determination of the overall sample size in an MRCT. We use the concept of consistency based on Method 2 of the Japanese Ministry of Health, Labour, and Welfare's guidance to evaluate the probability for treatment benefit and consistency under DREM. We further derive an optimal sample size allocation over regions to maximize the power for consistency. Moreover, we provide three algorithms for deriving sample size at the desired level of power for benefit and consistency. In practice, regional treatment effects are unknown. Thus, we provide some guidelines on the design of MRCTs with consistency when the regional treatment effect are assumed to fall into a specified interval. Numerical examples are given to illustrate applications of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Misra, Sudip; Oommen, B John; Yanamandra, Sreekeerthy; Obaidat, Mohammad S
2010-02-01
In this paper, we present a learning-automata-like The reason why the mechanism is not a pure LA, but rather why it yet mimics one, will be clarified in the body of this paper. (LAL) mechanism for congestion avoidance in wired networks. Our algorithm, named as LAL Random Early Detection (LALRED), is founded on the principles of the operations of existing RED congestion-avoidance mechanisms, augmented with a LAL philosophy. The primary objective of LALRED is to optimize the value of the average size of the queue used for congestion avoidance and to consequently reduce the total loss of packets at the queue. We attempt to achieve this by stationing a LAL algorithm at the gateways and by discretizing the probabilities of the corresponding actions of the congestion-avoidance algorithm. At every time instant, the LAL scheme, in turn, chooses the action that possesses the maximal ratio between the number of times the chosen action is rewarded and the number of times that it has been chosen. In LALRED, we simultaneously increase the likelihood of the scheme converging to the action, which minimizes the number of packet drops at the gateway. Our approach helps to improve the performance of congestion avoidance by adaptively minimizing the queue-loss rate and the average queue size. Simulation results obtained using NS2 establish the improved performance of LALRED over the traditional RED methods which were chosen as the benchmarks for performance comparison purposes.
Carlson, Mary; Brennan, Robert T; Earls, Felton
2012-09-01
The potential capacity of children to confront the HIV/AIDS pandemic is rarely considered. Interventions to address the impact of the pandemic on children and adolescents commonly target only their vulnerabilities. We evaluated the Young Citizens Program, an adolescent-centered health promotion curriculum designed to increase self- and collective efficacy through public education and community mobilization across a municipality in the Kilimanjaro Region of Tanzania. The theoretical framework for the program integrates aspects of human capability, communicative action, social ecology and social cognition. The design consists of a cluster randomized-controlled trial (CRCT). Fifteen pairs of matched geopolitically defined neighborhoods of roughly 2000-4000 residents were randomly allocated to treatment and control arms. Within each neighborhood cluster, 24 randomly selected adolescents, ages 9-14, deliberated on topics of social ecology, citizenship, community health and HIV/AIDS competence. Building on their acquired understanding and confidence, they dramatized the scientific basis and social context of HIV infection, testing and treatment in their communities over a 28-week period. The curriculum comprised 5 modules: Group Formation, Understanding our Community, Health and our Community, Making Assessments and Taking Action in our Community and Inter-Acting in our Community. Adolescent participants and adult residents representative of their neighborhoods were surveyed before and after the intervention; data were analyzed using multilevel modeling. In treatment neighborhoods, adolescents increased their deliberative and communicative efficacy and adults showed higher collective efficacy for children. Following the CRCT assessments, the control group received the same curriculum. In the Kilimanjaro Region, the Young Citizens Program is becoming recognized as a structural, health promotion approach through which adolescent self-efficacy and child collective efficacy
A multilevel stochastic collocation method for SPDEs
Gunzburger, Max; Jantsch, Peter; Teckentrup, Aretha; Webster, Clayton
2015-03-10
We present a multilevel stochastic collocation method that, as do multilevel Monte Carlo methods, uses a hierarchy of spatial approximations to reduce the overall computational complexity when solving partial differential equations with random inputs. For approximation in parameter space, a hierarchy of multi-dimensional interpolants of increasing fidelity are used. Rigorous convergence and computational cost estimates for the new multilevel stochastic collocation method are derived and used to demonstrate its advantages compared to standard single-level stochastic collocation approximations as well as multilevel Monte Carlo methods.
Carty, N J; Ravichandran, D; Carter, C; Mudan, S; Royle, G T; Taylor, I
1994-09-01
In a minority of patients with a discrete breast lump the initial cytological assessment is either unsatisfactory or at variance with the results of other methods of diagnosis. A randomized comparison of repeat cytology and needle-core biopsy provided clinically useful information in 14 of 31 patients receiving repeat cytology and in 26 of 29 randomized to core biopsy. Nineteen patients had carcinoma: ten who received repeat cytology, which indicated malignancy in only three (diagnostic of malignancy in one, suspicious in two), while all nine patients who underwent core biopsy had a correct diagnosis (only suspicious of malignancy in one). The sensitivity for the definitive diagnosis of carcinoma on repeat cytology and core biopsy was 10 and 89 per cent respectively. Patients with a discrete breast lump and unclear cytology results require needle-core biopsy. This has more diagnostic value than repeat cytology.
Reboussin, Beth A.; Preisser, John S.; Song, Eun-Young; Wolfson, Mark
2012-01-01
Summary Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called ‘clustering’. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure. PMID:24347839
Raeder, Sabine; Kraft, Pål; Bjørkli, Cato Alexander
2013-01-01
Background Stress is commonly experienced by many people and it is a contributing factor to many mental and physical health conditions, However, few efforts have been made to develop and test the effects of interventions for stress. Objective The aim of this study was to examine the effects of a Web-based stress-reduction intervention on stress, investigate mindfulness and procrastination as potential mediators of any treatment effects, and test whether the intervention is equally effective for females as males, all ages, and all levels of education. Methods We employed a randomized controlled trial in this study. Participants were recruited online via Facebook and randomly assigned to either the stress intervention or a control condition. The Web-based stress intervention was fully automated and consisted of 13 sessions over 1 month. The controls were informed that they would get access to the intervention after the final data collection. Data were collected at baseline and at 1, 2, and 6 months after intervention onset by means of online questionnaires. Outcomes were stress, mindfulness, and procrastination, which were all measured at every measurement occasion. Results A total of 259 participants were included and were allocated to either the stress intervention (n=126) or the control condition (n=133). Participants in the intervention and control group were comparable at baseline; however, results revealed that participants in the stress intervention followed a statistically different (ie, cubic) developmental trajectory in stress levels over time compared to the controls. A growth curve analysis showed that participants in the stress intervention (unstandardized beta coefficient [B]=–3.45, P=.008) recovered more quickly compared to the control group (B=–0.81, P=.34) from baseline to 1 month. Although participants in the stress intervention did show increases in stress levels during the study period (B=2.23, P=.008), long-term stress levels did decrease
Drozd, Filip; Raeder, Sabine; Kraft, Pål; Bjørkli, Cato Alexander
2013-04-22
Stress is commonly experienced by many people and it is a contributing factor to many mental and physical health conditions, However, few efforts have been made to develop and test the effects of interventions for stress. The aim of this study was to examine the effects of a Web-based stress-reduction intervention on stress, investigate mindfulness and procrastination as potential mediators of any treatment effects, and test whether the intervention is equally effective for females as males, all ages, and all levels of education. We employed a randomized controlled trial in this study. Participants were recruited online via Facebook and randomly assigned to either the stress intervention or a control condition. The Web-based stress intervention was fully automated and consisted of 13 sessions over 1 month. The controls were informed that they would get access to the intervention after the final data collection. Data were collected at baseline and at 1, 2, and 6 months after intervention onset by means of online questionnaires. Outcomes were stress, mindfulness, and procrastination, which were all measured at every measurement occasion. A total of 259 participants were included and were allocated to either the stress intervention (n=126) or the control condition (n=133). Participants in the intervention and control group were comparable at baseline; however, results revealed that participants in the stress intervention followed a statistically different (ie, cubic) developmental trajectory in stress levels over time compared to the controls. A growth curve analysis showed that participants in the stress intervention (unstandardized beta coefficient [B]=-3.45, P=.008) recovered more quickly compared to the control group (B=-0.81, P=.34) from baseline to 1 month. Although participants in the stress intervention did show increases in stress levels during the study period (B=2.23, P=.008), long-term stress levels did decrease again toward study end at 6 months (B=-0
Canino, Glorisa; Shrout, Patrick E; Vila, Doryliz; Ramírez, Rafael; Rand, Cynthia
2016-01-01
Poor self-management by families is an important factor in explaining high rates of asthma morbidity in Puerto Rico, and for this reason we previously tested a family intervention called CALMA that was found effective in improving most asthma outcomes, but not effective in increasing the use of controller medications. CALMA-plus was developed to address this issue by adding to CALMA, components of provider training and screening for asthma in clinics. Study participants were selected from claims Medicaid data in San Juan, Puerto Rico. After screening, 404 children in eight clinics were selected after forming pairs of clinics and randomizing the clinics) to CALMA-only or CALMA-plus. For all three primary outcomes at 12 months, the mean differences between treatment arms were small but in the predicted direction. However, after adjusting for clinic variation, the study failed to demonstrate that the CALMA-plus intervention was more efficacious than the CALMA-only intervention for increasing controller medication use, or decreasing asthma symptoms. Both groups had lower rates of asthma symptoms and service utilization, consistent with previous results of the CALMA-only intervention. Compliance of providers with the intervention and training, small number of clinics available and the multiple barriers experienced by providers for medicating may have been related to the lack of difference observed between the groups. Future interventions should respond to the limitations of the present study design and provide more resources to providers that will increase provider participation in training and implementation of the intervention.
Parallel multilevel preconditioners
Bramble, J.H.; Pasciak, J.E.; Xu, Jinchao.
1989-01-01
In this paper, we shall report on some techniques for the development of preconditioners for the discrete systems which arise in the approximation of solutions to elliptic boundary value problems. Here we shall only state the resulting theorems. It has been demonstrated that preconditioned iteration techniques often lead to the most computationally effective algorithms for the solution of the large algebraic systems corresponding to boundary value problems in two and three dimensional Euclidean space. The use of preconditioned iteration will become even more important on computers with parallel architecture. This paper discusses an approach for developing completely parallel multilevel preconditioners. In order to illustrate the resulting algorithms, we shall describe the simplest application of the technique to a model elliptic problem.
Fang, Carolyn Y; Ma, Grace X; Handorf, Elizabeth A; Feng, Ziding; Tan, Yin; Rhee, Joanne; Miller, Suzanne M; Kim, Charles; Koh, Han Seung
2017-05-15
Korean American women have among the lowest rates of cervical cancer screening in the United States. The authors evaluated a multicomponent intervention combining community education with navigation services to reduce access barriers and increase screening rates in this underserved population. It was hypothesized that cervical cancer screening rates would be higher among women who received the intervention program compared with those in the control program. Korean American women (N = 705) were recruited from 22 churches. In this matched-pair, group-randomized design, 347 women received the intervention, which consisted of a culturally relevant cancer education program combined with provision of navigation services. The control group (N = 358) received general health education, including information about cervical cancer risk and screening and where to obtain low-cost or no-cost screening. Screening behavior was assessed 12 months after the program. Screening behavior data were obtained from 588 women 12 months after the program. In both site-level and participant-level analyses, the intervention program contributed to significantly higher screening rates compared with the control program (odds ratio [OR], 25.9; 95% confidence interval [CI], 10.1-66.1; P < .001). In sensitivity analysis, the treatment effect remained highly significant (OR, 16.7; 95% CI, 8.1-34.4; P < .001). A multicomponent intervention combining community cancer education with navigation services yielded significant increases in cervical cancer screening rates among underscreened Korean American women. Community-accessible programs that incorporate cancer education with the delivery of key navigation services can be highly effective in increasing cervical cancer screening rates in this underserved population. Cancer 2017;123:1018-26. © 2016 American Cancer Society. © 2016 American Cancer Society.
Multilevel Modeling with Correlated Effects
ERIC Educational Resources Information Center
Kim, Jee-Seon; Frees, Edward W.
2007-01-01
When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…
Multilevel Modeling with Correlated Effects
ERIC Educational Resources Information Center
Kim, Jee-Seon; Frees, Edward W.
2007-01-01
When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…
NASA Technical Reports Server (NTRS)
Ippolito, L. J., Jr.
1977-01-01
The multiple scattering effects on wave propagation through a volume of discrete scatterers were investigated. The mean field and intensity for a distribution of scatterers was developed using a discrete random media formulation, and second order series expansions for the mean field and total intensity derived for one-dimensional and three-dimensional configurations. The volume distribution results were shown to proceed directly from the one-dimensional results. The multiple scattering intensity expansion was compared to the classical single scattering intensity and the classical result was found to represent only the first three terms in the total intensity expansion. The Foldy approximation to the mean field was applied to develop the coherent intensity, and was found to exactly represent all coherent terms of the total intensity.
Challenges of evaluating multilevel interventions.
Nastasi, Bonnie K; Hitchcock, John
2009-06-01
This article uses the Comprehensive Mixed-Methods Participatory Evaluation (CMMPE; Nastasi and Hitchcock Transforming school mental health services: Population-based approaches to promoting the competency and wellness of children, Thousand Oaks, CA: Corwin Press with National Association of School Psychologists 2008; Nastasi et al. School-based mental health services: creating comprehensive and culturally specific programs. Washington, DC: American Psychological Association 2004) model as a framework for addressing the multiplicity of evaluation decisions and complex nature of questions related to program success in multilevel interventions. CMMPE defines program success in terms of acceptability, integrity, social or cultural validity, outcomes (impact), sustainability and institutionalization, thus broadening the traditional notions of program outcomes. The authors use CMMPE and an example of a community-based multilevel sexual risk prevention program with multiple outcomes to discuss challenges of evaluating multilevel interventions. The sexual risk program exemplifies what Schensul and Trickett (this issue) characterize as multilevel intervention-multilevel evaluation (M-M), with both intervention and evaluation at community, health practitioner, and patient levels. The illustration provides the context for considering several challenges related to M-M designs: feasibility of randomized controlled trials within community-based multilevel intervention; acceptability and social or cultural validity of evaluation procedures; implementer, recipient, and contextual variations in program success; interactions among levels of the intervention; unanticipated changes or conditions; multiple indicators of program success; engaging multiple stakeholders in a participatory process; and evaluating sustainability and institutionalization. The complexity of multilevel intervention and evaluation designs challenges traditional notions of evaluation research and experimental
Müller, Eike H; Scheichl, Rob; Shardlow, Tony
2015-04-08
This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy.
Müller, Eike H.; Scheichl, Rob; Shardlow, Tony
2015-01-01
This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy. PMID:27547075
Consequences of Unmodeled Nonlinear Effects in Multilevel Models
ERIC Educational Resources Information Center
Bauer, Daniel J.; Cai, Li
2009-01-01
Applications of multilevel models have increased markedly during the past decade. In incorporating lower-level predictors into multilevel models, a key interest is often whether or not a given predictor requires a random slope, that is, whether the effect of the predictor varies over upper-level units. If the variance of a random slope…
Consequences of Unmodeled Nonlinear Effects in Multilevel Models
ERIC Educational Resources Information Center
Bauer, Daniel J.; Cai, Li
2009-01-01
Applications of multilevel models have increased markedly during the past decade. In incorporating lower-level predictors into multilevel models, a key interest is often whether or not a given predictor requires a random slope, that is, whether the effect of the predictor varies over upper-level units. If the variance of a random slope…
Hong, Y Alicia; Forjuoh, Samuel N; Ory, Marcia G; Reis, Michael D; Sang, Huiyan
2017-09-12
Most older adults do not adhere to the US Centers for Disease Control physical activity guidelines; their physical inactivity contributes to overweight and multiple chronic conditions. An urgent need exists for effective physical activity-promotion programs for the large number of older adults in the United States. This study presents the development of the intervention and trial protocol of iCanFit 2.0, a multi-level, mobile-enabled, physical activity-promotion program developed for overweight older adults in primary care settings. The iCanFit 2.0 program was developed based on our prior mHealth intervention programs, qualitative interviews with older patients in a primary care clinic, and iterative discussions with key stakeholders. We will test the efficacy of iCanFit 2.0 through a cluster randomized controlled trial in six pairs of primary care clinics. The proposed protocol received a high score in a National Institutes of Health review, but was not funded due to limited funding sources. We are seeking other funding sources to conduct the project. The iCanFit 2.0 program is one of the first multi-level, mobile-enabled, physical activity-promotion programs for older adults in a primary care setting. The development process has actively involved older patients and other key stakeholders. The patients, primary care providers, health coaches, and family and friends were engaged in the program using a low-cost, off-the-shelf mobile tool. Such low-cost, multi-level programs can potentially address the high prevalence of physical inactivity in older adults.
Fan, Xiaozheng; Wang, Yan; Hu, Manfeng
2016-01-01
In this paper, the fuzzy [Formula: see text] output-feedback control problem is investigated for a class of discrete-time T-S fuzzy systems with channel fadings, sector nonlinearities, randomly occurring interval delays (ROIDs) and randomly occurring nonlinearities (RONs). A series of variables of the randomly occurring phenomena obeying the Bernoulli distribution is used to govern ROIDs and RONs. Meanwhile, the measurement outputs are subject to the sector nonlinearities (i.e. the sensor saturations) and we assume the system output is [Formula: see text], [Formula: see text]. The Lth-order Rice model is utilized to describe the phenomenon of channel fadings by setting different values of the channel coefficients. The aim of this work is to deal with the problem of designing a full-order dynamic fuzzy [Formula: see text] output-feedback controller such that the fuzzy closed-loop system is exponentially mean-square stable and the [Formula: see text] performance constraint is satisfied, by means of a combination of Lyapunov stability theory and stochastic analysis along with LMI methods. The proposed fuzzy controller parameters are derived by solving a convex optimization problem via the semidefinite programming technique. Finally, a numerical simulation is given to illustrate the feasibility and effectiveness of the proposed design technique.
NASA Technical Reports Server (NTRS)
Tsang, Leung; Ding, Kung-Hau
1991-01-01
Complete polarimetric signatures of a layer of random, nonspherical discrete scatterers overlying a homogeneous half space are studied with the first- and second-order solutions of the vector radiative transfer theory. Some of the salient features of the numerical results are as follows: (1) the inclusion of the nondiagonal extinction matrix in the vector radiative transfer theory accounts for an appreciable phase difference between vv and hh polarizations, particularly for aligned scatterers; (2) the ensemble-averaged scattered Stokes vector is generally partially polarized, with the degree of polarization less than unity; (3) there generally exists a pedestal in the copolarization return when plotted as a function of ellipticity and orientation angles, which may be due to heterogeneity of scattering objects and/or multiple scattering effects; and (4) multiple scattering effects generally enhance the pedestal in copolarization return, decrease the degree of polarization, affect phase difference, and also enhance the depolarization return.
NASA Astrophysics Data System (ADS)
Wei, Kang Liang; Liu, Xiao Yan; Du, Gang
2013-04-01
Using full three-dimensional (3D) technology computer-aided design (TCAD) simulations, we present a comprehensive statistical study on the random discrete dopant (RDD) induced variability in state-of-the-art intrinsic channel trigate MOSFETs. This paper is focused on the RDD variability sources that are introduced by dopant diffusion from highly doped source/drain (S/D) regions into the undoped channel region, which is referred to as junction nonabruptness (JNA). By considering a realistic lateral doping profile in the channel and evaluating the impact of JNA on the variability of performance parameters such as threshold voltage (Vth), subthreshold slope (SS), drain-induced barrier lowering (DIBL), on current (Ion), and off current (Ioff), we show that the effect of JNA can lead to substantial device variations. The nonnegligible influence of JNA puts limitations on device scaling, which is also investigated in this paper.
Robinson, Thomas N; Matheson, Donna; Desai, Manisha; Wilson, Darrell M; Weintraub, Dana L; Haskell, William L; McClain, Arianna; McClure, Samuel; Banda, Jorge A; Sanders, Lee M; Haydel, K Farish; Killen, Joel D
2013-11-01
To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families. © 2013 Elsevier Inc. All rights reserved.
Robinson, Thomas N.; Matheson, Donna; Desai, Manisha; Wilson, Darrell M.; Weintraub, Dana L.; Haskell, William L.; McClain, Arianna; McClure, Samuel; Banda, Jorge; Sanders, Lee M.; Haydel, K. Farish; Killen, Joel D.
2013-01-01
Objective To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Design Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Participants Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Interventions Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Main Outcome Measure Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. Conclusions The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families
An adaptive multi-level simulation algorithm for stochastic biological systems.
Lester, C; Yates, C A; Giles, M B; Baker, R E
2015-01-14
Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, "Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics," SIAM Multiscale Model. Simul. 10(1), 146-179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the
ERIC Educational Resources Information Center
Park, Jungkyu; Yu, Hsiu-Ting
2016-01-01
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
ERIC Educational Resources Information Center
Park, Jungkyu; Yu, Hsiu-Ting
2016-01-01
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Multilevel and Diverse Classrooms
ERIC Educational Resources Information Center
Baurain, Bradley, Ed.; Ha, Phan Le, Ed.
2010-01-01
The benefits and advantages of classroom practices incorporating unity-in-diversity and diversity-in-unity are what "Multilevel and Diverse Classrooms" is all about. Multilevel classrooms--also known as mixed-ability or heterogeneous classrooms--are a fact of life in ESOL programs around the world. These classrooms are often not only…
Multilevel and Diverse Classrooms
ERIC Educational Resources Information Center
Baurain, Bradley, Ed.; Ha, Phan Le, Ed.
2010-01-01
The benefits and advantages of classroom practices incorporating unity-in-diversity and diversity-in-unity are what "Multilevel and Diverse Classrooms" is all about. Multilevel classrooms--also known as mixed-ability or heterogeneous classrooms--are a fact of life in ESOL programs around the world. These classrooms are often not only…
Multilevel Mixture Factor Models
ERIC Educational Resources Information Center
Varriale, Roberta; Vermunt, Jeroen K.
2012-01-01
Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure. These Multilevel Factor Models (MFMs)…
Multilevel joint competing risk models
NASA Astrophysics Data System (ADS)
Karunarathna, G. H. S.; Sooriyarachchi, M. R.
2017-09-01
Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).
NASA Astrophysics Data System (ADS)
Barnard, J. M.; Augarde, C. E.
2012-12-01
The simulation of reactions in flow through unsaturated porous media is a more complicated process when using particle tracking based models than in continuum based models. In the fomer particles are reacted on an individual particle-to-particle basis using either deterministic or probabilistic methods. This means that particle tracking methods, especially when simulations of reactions are included, are computationally intensive as the reaction simulations require tens of thousands of nearest neighbour searches per time step. Despite this, particle tracking methods merit further study due to their ability to eliminate numerical dispersion, to simulate anomalous transport and incomplete mixing of reactive solutes. A new model has been developed using discrete time random walk particle tracking methods to simulate reactive mass transport in porous media which includes a variation of colocation probability function based methods of reaction simulation from those presented by Benson & Meerschaert (2008). Model development has also included code acceleration via graphics processing units (GPUs). The nature of particle tracking methods means that they are well suited to parallelization using GPUs. The architecture of GPUs is single instruction - multiple data (SIMD). This means that only one operation can be performed at any one time but can be performed on multiple data simultaneously. This allows for significant speed gains where long loops of independent operations are performed. Computationally expensive code elements, such the nearest neighbour searches required by the reaction simulation, are therefore prime targets for GPU acceleration.
Multilevel filtering elliptic preconditioners
NASA Technical Reports Server (NTRS)
Kuo, C. C. Jay; Chan, Tony F.; Tong, Charles
1989-01-01
A class of preconditioners is presented for elliptic problems built on ideas borrowed from the digital filtering theory and implemented on a multilevel grid structure. They are designed to be both rapidly convergent and highly parallelizable. The digital filtering viewpoint allows the use of filter design techniques for constructing elliptic preconditioners and also provides an alternative framework for understanding several other recently proposed multilevel preconditioners. Numerical results are presented to assess the convergence behavior of the new methods and to compare them with other preconditioners of multilevel type, including the usual multigrid method as preconditioner, the hierarchical basis method and a recent method proposed by Bramble-Pasciak-Xu.
Kim, Eun Sook; Cao, Chunhua
2015-01-01
Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.
An adaptive multi-level simulation algorithm for stochastic biological systems
Lester, C. Giles, M. B.; Baker, R. E.; Yates, C. A.
2015-01-14
Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, “Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics,” SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the
Multilevel modeling in psychosomatic medicine research.
Myers, Nicholas D; Brincks, Ahnalee M; Ames, Allison J; Prado, Guillermo J; Penedo, Frank J; Benedict, Catherine
2012-01-01
The primary purpose of this study is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The article begins with a general introduction to multilevel modeling. Multilevel regression modeling at two levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated data sets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive-behavioral stress management intervention in prostate cancer.
Multilevel Modeling in Psychosomatic Medicine Research
Myers, Nicholas D.; Brincks, Ahnalee M.; Ames, Allison J.; Prado, Guillermo J.; Penedo, Frank J.; Benedict, Catherine
2012-01-01
The primary purpose of this manuscript is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The manuscript begins with a general introduction to multilevel modeling. Multilevel regression modeling at two-levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated datasets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including: communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive behavioral stress management intervention in prostate cancer. PMID:23107843
Multilevel corporate environmental responsibility.
Karassin, Orr; Bar-Haim, Aviad
2016-12-01
The multilevel empirical study of the antecedents of corporate social responsibility (CSR) has been identified as "the first knowledge gap" in CSR research. Based on an extensive literature review, the present study outlines a conceptual multilevel model of CSR, then designs and empirically validates an operational multilevel model of the principal driving factors affecting corporate environmental responsibility (CER), as a measure of CSR. Both conceptual and operational models incorporate three levels of analysis: institutional, organizational, and individual. The multilevel nature of the design allows for the assessment of the relative importance of the levels and of their components in the achievement of CER. Unweighted least squares (ULS) regression analysis reveals that the institutional-level variables have medium relationships with CER, some variables having a negative effect. The organizational level is revealed as having strong and positive significant relationships with CER, with organizational culture and managers' attitudes and behaviors as significant driving forces. The study demonstrates the importance of multilevel analysis in improving the understanding of CSR drivers, relative to single level models, even if the significance of specific drivers and levels may vary by context.
A multilevel nonvolatile magnetoelectric memory
NASA Astrophysics Data System (ADS)
Shen, Jianxin; Cong, Junzhuang; Shang, Dashan; Chai, Yisheng; Shen, Shipeng; Zhai, Kun; Sun, Young
2016-09-01
The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric memories have been proposed and explored in the past decade. Here we propose a new principle to realize a multilevel nonvolatile memory based on the multiple states of the magnetoelectric coefficient (α) of multiferroics. Because the states of α depends on the relative orientation between magnetization and polarization, one can reach different levels of α by controlling the ratio of up and down ferroelectric domains with external electric fields. Our experiments in a device made of the PMN-PT/Terfenol-D multiferroic heterostructure confirm that the states of α can be well controlled between positive and negative by applying selective electric fields. Consequently, two-level, four-level, and eight-level nonvolatile memory devices are demonstrated at room temperature. This kind of multilevel magnetoelectric memory retains all the advantages of ferroelectric random access memory but overcomes the drawback of destructive reading of polarization. In contrast, the reading of α is nondestructive and highly efficient in a parallel way, with an independent reading coil shared by all the memory cells.
A multilevel nonvolatile magnetoelectric memory
Shen, Jianxin; Cong, Junzhuang; Shang, Dashan; Chai, Yisheng; Shen, Shipeng; Zhai, Kun; Sun, Young
2016-01-01
The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric memories have been proposed and explored in the past decade. Here we propose a new principle to realize a multilevel nonvolatile memory based on the multiple states of the magnetoelectric coefficient (α) of multiferroics. Because the states of α depends on the relative orientation between magnetization and polarization, one can reach different levels of α by controlling the ratio of up and down ferroelectric domains with external electric fields. Our experiments in a device made of the PMN-PT/Terfenol-D multiferroic heterostructure confirm that the states of α can be well controlled between positive and negative by applying selective electric fields. Consequently, two-level, four-level, and eight-level nonvolatile memory devices are demonstrated at room temperature. This kind of multilevel magnetoelectric memory retains all the advantages of ferroelectric random access memory but overcomes the drawback of destructive reading of polarization. In contrast, the reading of α is nondestructive and highly efficient in a parallel way, with an independent reading coil shared by all the memory cells. PMID:27681812
Seynaeve, Bert; Rosseel, Eveline; Nicolai, Bart; Vandewalle, Stefan . E-mail: Stefan.Vandewalle@cs.kuleuven.be
2007-05-20
Partial differential equations with random coefficients appear for example in reliability problems and uncertainty propagation models. Various approaches exist for computing the stochastic characteristics of the solution of such a differential equation. In this paper, we consider the spectral expansion approach. This method transforms the continuous model into a large discrete algebraic system. We study the convergence properties of iterative methods for solving this discretized system. We consider one-level and multi-level methods. The classical Fourier mode analysis technique is extended towards the stochastic case. This is done by taking the eigenstructure into account of a certain matrix that depends on the random structure of the problem. We show how the convergence properties depend on the particulars of the algorithm, on the discretization parameters and on the stochastic characteristics of the model. Numerical results are added to illustrate some of our theoretical findings.
Oosterhoff, M; Joore, M; Ferreira, I
2016-11-01
Primary prevention of childhood obesity and related hypertension is warrant given that both risk factors are intertwined and track into adulthood. This systematic review and meta-analysis assess the impact of school-based lifestyle interventions on children's body mass index (BMI) and blood pressure. We searched databases and prior reviews. Eligibility criteria were the following: randomized controlled trial design, evaluation of a school-based intervention, targeting children aged 4-12 years, reporting on BMI and/or related cardiovascular risk factors, reporting data on at least one follow-up moment. The effects on BMI, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were evaluated by means of univariate and multivariate three-level random effects models. A total of 85 RCTs (91 papers) were included in the meta-analyses. In univariate models, the pooled effects were -0.072 (95%CI: -0.106; -0.038) for BMI, -0.183 (95%CI: -0.288; -0.078) for SBP and -0.071 (95%CI: -0.185; 0.044) for DBP. In multivariate analyses, the pooled effects of interventions were -0.054 (95%CI: -0.131; 0.022) for BMI, -0.182 (95%CI: -0.266; -0.098) for SBP and -0.144 (95%CI: -0.230; -0.057) for DBP. Parental involvement accentuated the beneficial effects of interventions. School-based lifestyle prevention interventions result in beneficial changes in children's BMI and blood pressure, and the effects on the latter may be stronger than and accrue independently from those in the former.
Multilevel cervical arthroplasty: current evidence. A systematic review.
Joaquim, Andrei F; Riew, K Daniel
2017-02-01
OBJECTIVE Cervical disc arthroplasty (CDA) has been demonstrated to be an effective treatment modality for single-level cervical radiculopathy or myelopathy. Its advantages over an anterior cervical discectomy and fusion (ACDF) include motion preservation and decreased reoperations at the index and adjacent segments up to 7 years postoperatively. Considering the fact that many patients have multilevel cervical disc degeneration (CDD), the authors performed a systematic review of the clinical studies evaluating patients who underwent multilevel CDA (2 or more levels). METHODS A systematic review in the MEDLINE database was performed. Clinical studies including patients who had multilevel CDA were selected and included. Case reports and literature reviews were excluded. Articles were then grouped according to their main study objective: 1) studies comparing multilevel CDA versus ACDF; 2) studies comparing single-level CDA versus multilevel CDA; and 3) multilevel CDA after a previous cervical spine surgery. RESULTS Fourteen articles met all inclusion criteria. The general conclusions were that multilevel CDA was at least as safe and effective as ACDF, with preservation of cervical motion when compared with ACDF and potentially with fewer reoperations expected in most of the studies. Multilevel CDAs are clinically effective as single-level surgeries, with good clinical and radiological outcomes. Some studies reported a higher incidence of heterotopic ossification in multilevel CDA when compared with single-level procedures, but without clinical relevance during the follow-up period. A CDA may be indicated even after a previous cervical surgery in selected cases. CONCLUSIONS The current literature supports the use of multilevel CDA. Caution is necessary regarding the more restrictive indications for CDA when compared with ACDF. Further prospective, controlled, multicenter, and randomized studies not sponsored by the device manufactures are desirable to prove the
Multilevel resistive information storage and retrieval
Lohn, Andrew; Mickel, Patrick R.
2016-08-09
The present invention relates to resistive random-access memory (RRAM or ReRAM) systems, as well as methods of employing multiple state variables to form degenerate states in such memory systems. The methods herein allow for precise write and read steps to form multiple state variables, and these steps can be performed electrically. Such an approach allows for multilevel, high density memory systems with enhanced information storage capacity and simplified information retrieval.
Courteix, Daniel; Valente-dos-Santos, João; Ferry, Béatrice; Lac, Gérard; Lesourd, Bruno; Chapier, Robert; Naughton, Geraldine; Marceau, Geoffroy; João Coelho-e-Silva, Manuel; Vinet, Agnès; Walther, Guillaume; Obert, Philippe; Dutheil, Frédéric
2015-01-01
Background Weight loss is a public health concern in obesity-related diseases such as metabolic syndrome (MetS). However, restrictive diets might induce bone loss. The nature of exercise and whether exercise with weight loss programs can protect against potential bone mass deficits remains unclear. Moreover, compliance is essential in intervention programs. Thus, we aimed to investigate the effects that modality and exercise compliance have on bone mineral content (BMC) and density (BMD). Methods We investigated 90 individuals with MetS who were recruited for the 1-year RESOLVE trial. Community-dwelling seniors with MetS were randomly assigned into three different modalities of exercise (intensive resistance, intensive endurance, moderate mixed) combined with a restrictive diet. They were compared to 44 healthy controls who did not undergo the intervention. Results This intensive lifestyle intervention (15–20 hours of training/week + restrictive diet) resulted in weight loss, body composition changes and health improvements. Baseline BMC and BMD for total body, lumbar spine and femoral neck did not differ between MetS groups and between MetS and controls. Despite changes over time, BMC or BMD did not differ between the three modalities of exercise and when compared with the controls. However, independent of exercise modality, compliant participants increased their BMC and BMD compared with their less compliant peers. Decreases in total body lean mass and negative energy balance significantly and independently contributed to decreases in lumbar spine BMC. Conclusion After the one year intervention, differences relating to exercise modalities were not evident. However, compliance with an intensive exercise program resulted in a significantly higher bone mass during energy restriction than non-compliance. Exercise is therefore beneficial to bone in the context of a weight loss program. Trial Registration ClinicalTrials.gov NCT00917917 PMID:26376093
Courteix, Daniel; Valente-dos-Santos, João; Ferry, Béatrice; Lac, Gérard; Lesourd, Bruno; Chapier, Robert; Naughton, Geraldine; Marceau, Geoffroy; João Coelho-e-Silva, Manuel; Vinet, Agnès; Walther, Guillaume; Obert, Philippe; Dutheil, Frédéric
2015-01-01
Weight loss is a public health concern in obesity-related diseases such as metabolic syndrome (MetS). However, restrictive diets might induce bone loss. The nature of exercise and whether exercise with weight loss programs can protect against potential bone mass deficits remains unclear. Moreover, compliance is essential in intervention programs. Thus, we aimed to investigate the effects that modality and exercise compliance have on bone mineral content (BMC) and density (BMD). We investigated 90 individuals with MetS who were recruited for the 1-year RESOLVE trial. Community-dwelling seniors with MetS were randomly assigned into three different modalities of exercise (intensive resistance, intensive endurance, moderate mixed) combined with a restrictive diet. They were compared to 44 healthy controls who did not undergo the intervention. This intensive lifestyle intervention (15-20 hours of training/week + restrictive diet) resulted in weight loss, body composition changes and health improvements. Baseline BMC and BMD for total body, lumbar spine and femoral neck did not differ between MetS groups and between MetS and controls. Despite changes over time, BMC or BMD did not differ between the three modalities of exercise and when compared with the controls. However, independent of exercise modality, compliant participants increased their BMC and BMD compared with their less compliant peers. Decreases in total body lean mass and negative energy balance significantly and independently contributed to decreases in lumbar spine BMC. After the one year intervention, differences relating to exercise modalities were not evident. However, compliance with an intensive exercise program resulted in a significantly higher bone mass during energy restriction than non-compliance. Exercise is therefore beneficial to bone in the context of a weight loss program. ClinicalTrials.gov NCT00917917.
Parallel multilevel adaptive methods
NASA Technical Reports Server (NTRS)
Dowell, B.; Govett, M.; Mccormick, S.; Quinlan, D.
1989-01-01
The progress of a project for the design and analysis of a multilevel adaptive algorithm (AFAC/HM/) targeted for the Navier Stokes Computer is discussed. The results of initial timing tests of AFAC, coupled with multigrid and an efficient load balancer, on a 16-node Intel iPSC/2 hypercube are included. The results of timing tests are presented.
Prediction in Multilevel Models
ERIC Educational Resources Information Center
Afshartous, David; de Leeuw, Jan
2005-01-01
Multilevel modeling is an increasingly popular technique for analyzing hierarchical data. This article addresses the problem of predicting a future observable y[subscript *j] in the jth group of a hierarchical data set. Three prediction rules are considered and several analytical results on the relative performance of these prediction rules are…
Multilevel phase-and amplitude-encoded modified-filter synthetic-discriminant-function filters
NASA Astrophysics Data System (ADS)
Wang, Ruikang; Chatwin, Chris R.
1995-07-01
The performance of the modified-filter synthetic-discriminant-function (MfSDF) filter with multilevel phase and amplitude (MLAP) constraints is investigated with various in-plane rotated images from an in-class Bradley armored personnel carrier vehicle and an out-of-class Abram MI tank; this is of interest because of the commercial availability of liquid-crystal televisions, which are able to encode the gray-level amplitude and/or the discrete multilevel phase information. The evaluation is performed to explain better the image-distortion range that can be covered effectively by MLAP/MfSDF filters. The results show that the MLAP/MfSDF filter offers much-improved correlator system performance with a greater allowable image-distortion range while maintaining 100% discrimination between in-class and out-of-class images; furthermore, it shows an improved ability to accommodate the input image noise when compared with the MfSDF filter with a binary phase-only constraint. Thus the MLAP/MfSDF can be implemented effectively by a hybrid optical/digital correlator system to track a vehicle or a tank dynamically as it moves along a random trajectory across the input field.
Variability of multilevel switching in scaled hybrid RS/CMOS nanoelectronic circuits: theory
NASA Astrophysics Data System (ADS)
Heittmann, Arne; Noll, Tobias G.
2013-07-01
A theory is presented which describes the variability of multilevel switching in scaled hybrid resistive-switching/CMOS nanoelectronic circuits. Variability is quantified in terms of conductance variation using the first two moments derived from the probability density function (PDF) of the RS conductance. For RS, which are based on the electrochemical metallization effect (ECM), this variability is - to some extent - caused by discrete events such as electrochemical reactions, which occur on atomic scale and are at random. The theory shows that the conductance variation depends on the joint interaction between the programming circuit and the resistive switch (RS), and explicitly quantifies the impact of RS device parameters and parameters of the programming circuit on the conductance variance. Using a current mirror as an exemplary programming circuit an upper limit of 2-4 bits (dependent on the filament surface area) is estimated as the storage capacity exploiting the multilevel capabilities of an ECM cell. The theoretical results were verified by Monte Carlo circuit simulations on a standard circuit simulation environment using an ECM device model which models the filament growth by a Poisson process. Contribution to the Topical Issue “International Semiconductor Conference Dresden-Grenoble - ISCDG 2012”, Edited by Gérard Ghibaudo, Francis Balestra and Simon Deleonibus.
Multilevel Interventions: Measurement and Measures
Charns, Martin P.; Alligood, Elaine C.; Benzer, Justin K.; Burgess, James F.; Mcintosh, Nathalie M.; Burness, Allison; Partin, Melissa R.; Clauser, Steven B.
2012-01-01
Background Multilevel intervention research holds the promise of more accurately representing real-life situations and, thus, with proper research design and measurement approaches, facilitating effective and efficient resolution of health-care system challenges. However, taking a multilevel approach to cancer care interventions creates both measurement challenges and opportunities. Methods One-thousand seventy two cancer care articles from 2005 to 2010 were reviewed to examine the state of measurement in the multilevel intervention cancer care literature. Ultimately, 234 multilevel articles, 40 involving cancer care interventions, were identified. Additionally, literature from health services, social psychology, and organizational behavior was reviewed to identify measures that might be useful in multilevel intervention research. Results The vast majority of measures used in multilevel cancer intervention studies were individual level measures. Group-, organization-, and community-level measures were rarely used. Discussion of the independence, validity, and reliability of measures was scant. Discussion Measurement issues may be especially complex when conducting multilevel intervention research. Measurement considerations that are associated with multilevel intervention research include those related to independence, reliability, validity, sample size, and power. Furthermore, multilevel intervention research requires identification of key constructs and measures by level and consideration of interactions within and across levels. Thus, multilevel intervention research benefits from thoughtful theory-driven planning and design, an interdisciplinary approach, and mixed methods measurement and analysis. PMID:22623598
Multi-level adaptive computations in fluid dynamics
NASA Technical Reports Server (NTRS)
Brandt, A.
1979-01-01
The multi-level adaptive technique (MLAT) is a general strategy of solving continuous problems by cycling between coarser and finer levels of discretization. It provides very fast solvers together with adaptive, nearly optimal discretization schemes to general boundary-value problems in general domains. Here the state of the art is surveyed, emphasizing steady-state fluid dynamics applications, from slow viscous flows to transonic ones. Various new techniques are briefly discussed, including distributive relaxation schemes, the treatment of evolution problems, the combined use of upstream and central differencing, local truncation extrapolations, and other 'super-solver' techniques.
Advanced multilevel metallization technology
NASA Astrophysics Data System (ADS)
Ohba, Takayuki
1995-10-01
In order for ULSI manufacturing to minimize the COO (cost of ownership) aspect in the wiring process and realize fabricating over 256M bits DRAM, several wiring technologies have been proposed. The evidential criteria in choosing the most probable one are physical or material limitations (e.g. step-coverage and resistivity) and requirements from manufacturing (e.g. process complexity, reliability, throughput, and total cost). Therefore, a combination of metallurgy using chemical vapor deposition (CVD) with simplified multilevel interconnects has a high potential in overcoming those difficulties. In this paper, an integrated multilevel metallization (IMM) by considering the above criteria is discussed. Alternatives of improved W-CVD, TiN-CVD using diborane (B 2H 6) and methylhydrazine (MH) reduction, selective W-CVD, and Cu wiring are described from our recent studies.
The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models
ERIC Educational Resources Information Center
Schoeneberger, Jason A.
2016-01-01
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models
ERIC Educational Resources Information Center
Schoeneberger, Jason A.
2016-01-01
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
NASA Astrophysics Data System (ADS)
Wuensche, Andrew
DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.
Recent developments in multilevel optimization
NASA Technical Reports Server (NTRS)
Vanderplaats, Garret N.; Kim, D.-S.
1989-01-01
Recent developments in multilevel optimization are briefly reviewed. The general nature of the multilevel design task, the use of approximations to develop and solve the analysis design task, the structure of the formal multidiscipline optimization problem, a simple cantilevered beam which demonstrates the concepts of multilevel design and the basic mathematical details of the optimization task and the system level are among the topics discussed.
Methods for testing theory and evaluating impact in randomized field trials
Brown, C. Hendricks; Wang, Wei; Kellam, Sheppard G.; Muthén, Bengt O.; Petras, Hanno; Toyinbo, Peter; Poduska, Jeanne; Ialongo, Nicholas; Wyman, Peter A.; Chamberlain, Patricia; Sloboda, Zili; MacKinnon, David P.; Windham, Amy
2008-01-01
Randomized field trials provide unique opportunities to examine the effectiveness of an intervention in real world settings and to test and extend both theory of etiology and theory of intervention. These trials are designed not only to test for overall intervention impact but also to examine how impact varies as a function of individual level characteristics, context, and across time. Examination of such variation in impact requires analytical methods that take into account the trial’s multiple nested structure and the evolving changes in outcomes over time. The models that we describe here merge multilevel modeling with growth modeling, allowing for variation in impact to be represented through discrete mixtures—growth mixture models—and nonparametric smooth functions—generalized additive mixed models. These methods are part of an emerging class of multilevel growth mixture models, and we illustrate these with models that examine overall impact and variation in impact. In this paper, we define intent-to-treat analyses in group-randomized multilevel field trials and discuss appropriate ways to identify, examine, and test for variation in impact without inflating the Type I error rate. We describe how to make causal inferences more robust to misspecification of covariates in such analyses and how to summarize and present these interactive intervention effects clearly. Practical strategies for reducing model complexity, checking model fit, and handling missing data are discussed using six randomized field trials to show how these methods may be used across trials randomized at different levels. PMID:18215473
Fast multilevel radiative transfer
NASA Astrophysics Data System (ADS)
Paletou, Frédéric; Léger, Ludovick
2007-01-01
The vast majority of recent advances in the field of numerical radiative transfer relies on approximate operator methods better known in astrophysics as Accelerated Lambda-Iteration (ALI). A superior class of iterative schemes, in term of rates of convergence, such as Gauss-Seidel and Successive Overrelaxation methods were therefore quite naturally introduced in the field of radiative transfer by Trujillo Bueno & Fabiani Bendicho (1995); it was thoroughly described for the non-LTE two-level atom case. We describe hereafter in details how such methods can be generalized when dealing with non-LTE unpolarised radiation transfer with multilevel atomic models, in monodimensional geometry.
A Primer on Multilevel Modeling
ERIC Educational Resources Information Center
Hayes, Andrew F.
2006-01-01
Multilevel modeling (MLM) is growing in use throughout the social sciences. Although daunting from a mathematical perspective, MLM is relatively easy to employ once some basic concepts are understood. In this article, I present a primer on MLM, describing some of these principles and applying them to the analysis of a multilevel data set on…
Omitted Variables in Multilevel Models
ERIC Educational Resources Information Center
Kim, Jee-Seon; Frees, Edward W.
2006-01-01
Statistical methodology for handling omitted variables is presented in a multilevel modeling framework. In many nonexperimental studies, the analyst may not have access to all requisite variables, and this omission may lead to biased estimates of model parameters. By exploiting the hierarchical nature of multilevel data, a battery of statistical…
Multilevel Modeling of Social Segregation
ERIC Educational Resources Information Center
Leckie, George; Pillinger, Rebecca; Jones, Kelvyn; Goldstein, Harvey
2012-01-01
The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…
Multi-level adaptive finite element methods. 1: Variation problems
NASA Technical Reports Server (NTRS)
Brandt, A.
1979-01-01
A general numerical strategy for solving partial differential equations and other functional problems by cycling between coarser and finer levels of discretization is described. Optimal discretization schemes are provided together with very fast general solvers. It is described in terms of finite element discretizations of general nonlinear minimization problems. The basic processes (relaxation sweeps, fine-grid-to-coarse-grid transfers of residuals, coarse-to-fine interpolations of corrections) are directly and naturally determined by the objective functional and the sequence of approximation spaces. The natural processes, however, are not always optimal. Concrete examples are given and some new techniques are reviewed. Including the local truncation extrapolation and a multilevel procedure for inexpensively solving chains of many boundary value problems, such as those arising in the solution of time-dependent problems.
Multilevel structural equation models for assessing moderation within and across levels of analysis.
Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J
2016-06-01
Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Muir, William M; Bijma, P; Schinckel, A
2013-01-01
An experiment was conducted comparing multilevel selection in Japanese quail for 43 days weight and survival with birds housed in either kin (K) or random (R) groups. Multilevel selection significantly reduced mortality (6.6% K vs. 8.5% R) and increased weight (1.30 g/MG K vs. 0.13 g/MG R) resulting in response an order of magnitude greater with Kin than Random. Thus, multilevel selection was effective in reducing detrimental social interactions, which contributed to improved weight gain. The observed rates of response did not differ significantly from expected, demonstrating that current theory is adequate to explain multilevel selection response. Based on estimated genetic parameters, group selection would always be superior to any other combination of multilevel selection. Further, near optimal results could be attained using multilevel selection if 20% of the weight was on the group component regardless of group composition. Thus, in nature the conditions for multilevel selection to be effective in bringing about social change maybe common. In terms of a sustainability of breeding programs, multilevel selection is easy to implement and is expected to give near optimal responses with reduced rates of inbreeding as compared to group selection, the only requirement is that animals be housed in kin groups. PMID:23730755
Muir, William M; Bijma, P; Schinckel, A
2013-06-01
An experiment was conducted comparing multilevel selection in Japanese quail for 43 days weight and survival with birds housed in either kin (K) or random (R) groups. Multilevel selection significantly reduced mortality (6.6% K vs. 8.5% R) and increased weight (1.30 g/MG K vs. 0.13 g/MG R) resulting in response an order of magnitude greater with Kin than Random. Thus, multilevel selection was effective in reducing detrimental social interactions, which contributed to improved weight gain. The observed rates of response did not differ significantly from expected, demonstrating that current theory is adequate to explain multilevel selection response. Based on estimated genetic parameters, group selection would always be superior to any other combination of multilevel selection. Further, near optimal results could be attained using multilevel selection if 20% of the weight was on the group component regardless of group composition. Thus, in nature the conditions for multilevel selection to be effective in bringing about social change maybe common. In terms of a sustainability of breeding programs, multilevel selection is easy to implement and is expected to give near optimal responses with reduced rates of inbreeding as compared to group selection, the only requirement is that animals be housed in kin groups. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
Prosocial behavior: multilevel perspectives.
Penner, Louis A; Dovidio, John F; Piliavin, Jane A; Schroeder, David A
2005-01-01
Current research on prosocial behavior covers a broad and diverse range of phenomena. We argue that this large research literature can be best organized and understood from a multilevel perspective. We identify three levels of analysis of prosocial behavior: (a) the "meso" level--the study of helper-recipient dyads in the context of a specific situation; (b) the micro level--the study of the origins of prosocial tendencies and the sources of variation in these tendencies; and (c) the macro level--the study of prosocial actions that occur within the context of groups and large organizations. We present research at each level and discuss similarities and differences across levels. Finally, we consider ways in which theory and research at these three levels of analysis might be combined in future intra- and interdisciplinary research on prosocial behavior.
Su, Gui-Jia
2003-06-10
A multilevel DC link inverter and method for improving torque response and current regulation in permanent magnet motors and switched reluctance motors having a low inductance includes a plurality of voltage controlled cells connected in series for applying a resulting dc voltage comprised of one or more incremental dc voltages. The cells are provided with switches for increasing the resulting applied dc voltage as speed and back EMF increase, while limiting the voltage that is applied to the commutation switches to perform PWM or dc voltage stepping functions, so as to limit current ripple in the stator windings below an acceptable level, typically 5%. Several embodiments are disclosed including inverters using IGBT's, inverters using thyristors. All of the inverters are operable in both motoring and regenerating modes.
Totally parallel multilevel algorithms
NASA Technical Reports Server (NTRS)
Frederickson, Paul O.
1988-01-01
Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.
Discretization errors in particle tracking
NASA Astrophysics Data System (ADS)
Carmon, G.; Mamman, N.; Feingold, M.
2007-03-01
High precision video tracking of microscopic particles is limited by systematic and random errors. Systematic errors are partly due to the discretization process both in position and in intensity. We study the behavior of such errors in a simple tracking algorithm designed for the case of symmetric particles. This symmetry algorithm uses interpolation to estimate the value of the intensity at arbitrary points in the image plane. We show that the discretization error is composed of two parts: (1) the error due to the discretization of the intensity, bD and (2) that due to interpolation, bI. While bD behaves asymptotically like N-1 where N is the number of intensity gray levels, bI is small when using cubic spline interpolation.
Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models
Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.
2014-01-01
Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071
Multilevel Algorithms for Nonlinear Optimization
1994-06-01
NASA Contractor Report 194940 ICASE Report No. 94-53 AD-A284 318 * ICASE MULTILEVEL ALGORITHMSDDTIC FOR NONLINEAR OPTIMIZATION ELECTESEP 1 4 1994 F...Association SOperated b MULTILEVEL ALGORITHMS FOR NONLINEAR OPTIMIZATION Natalia Alexandrov Accesion For ICASE C Mail Stop 132C NTIS CRA&ID C TAB 1Q...ABSTRACT Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that
Modelling partially cross-classified multilevel data.
Luo, Wen; Cappaert, Kevin J; Ning, Ling
2015-05-01
This article proposes an approach to modelling partially cross-classified multilevel data where some of the level-1 observations are nested in one random factor and some are cross-classified by two random factors. Comparisons between a proposed approach to two other commonly used approaches which treat the partially cross-classified data as either fully nested or fully cross-classified are completed with a simulation study. Results show that the proposed approach demonstrates desirable performance in terms of parameter estimates and statistical inferences. Both the fully nested model and the fully cross-classified model suffer from biased estimates of some variance components and statistical inferences of some fixed effects. Results also indicate that the proposed model is robust against cluster size imbalance. © 2015 The British Psychological Society.
[How to fit and interpret multilevel models using SPSS].
Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael
2007-05-01
Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.
Wang, S; Huang, G H; Zhou, Y
2016-05-01
In this study, a multi-level factorial-vertex fuzzy-stochastic programming (MFFP) approach is developed for optimization of water resources systems under probabilistic and possibilistic uncertainties. MFFP is capable of tackling fuzzy parameters at various combinations of α-cut levels, reflecting distinct attitudes of decision makers towards fuzzy parameters in the fuzzy discretization process based on the α-cut concept. The potential interactions among fuzzy parameters can be explored through a multi-level factorial analysis. A water resources management problem with fuzzy and random features is used to demonstrate the applicability of the proposed methodology. The results indicate that useful solutions can be obtained for the optimal allocation of water resources under fuzziness and randomness. They can help decision makers to identify desired water allocation schemes with maximized total net benefits. A variety of decision alternatives can also be generated under different scenarios of water management policies. The findings from the factorial experiment reveal the interactions among design factors (fuzzy parameters) and their curvature effects on the total net benefit, which are helpful in uncovering the valuable information hidden beneath the parameter interactions affecting system performance. A comparison between MFFP and the vertex method is also conducted to demonstrate the merits of the proposed methodology.
Multilevel turbulence simulations
Tziperman, E.
1994-12-31
The authors propose a novel method for the simulation of turbulent flows, that is motivated by and based on the Multigrid (MG) formalism. The method, called Multilevel Turbulence Simulations (MTS), is potentially more efficient and more accurate than LES. In many physical problems one is interested in the effects of the small scales on the larger ones, or in a typical realization of the flow, and not in the detailed time history of each small scale feature. MTS takes advantage of the fact that the detailed simulation of small scales is not needed at all times, in order to make the calculation significantly more efficient, while accurately accounting for the effects of the small scales on the larger scale of interest. In MTS, models of several resolutions are used to represent the turbulent flow. The model equations in each coarse level incorporate a closure term roughly corresponding to the tau correction in the MG formalism that accounts for the effects of the unresolvable scales on that grid. The finer resolution grids are used only a small portion of the simulation time in order to evaluate the closure terms for the coarser grids, while the coarse resolution grids are then used to accurately and efficiently calculate the evolution of the larger scales. The methods efficiency relative to direct simulations is of the order of the ratio of required integration time to the smallest eddies turnover time, potentially resulting in orders of magnitude improvement for a large class of turbulence problems.
Observation of discrete diffraction patterns in an optically induced lattice.
Sheng, Jiteng; Wang, Jing; Miri, Mohammad-Ali; Christodoulides, Demetrios N; Xiao, Min
2015-07-27
We have experimentally observed the discrete diffraction of light in a coherently prepared multi-level atomic medium. This is achieved by launching a probe beam into an optical lattice induced from the interference of two coupling beams. The diffraction pattern can be controlled through the atomic parameters such as two-photon detuning and temperature, as well as orientations of the coupling and probe beams. Clear diffraction patterns occur only near the two-photon resonance.
Three-dimensional discrete ordinates reactor assembly calculations on GPUs
Evans, Thomas M; Joubert, Wayne; Hamilton, Steven P; Johnson, Seth R; Turner, John A; Davidson, Gregory G; Pandya, Tara M
2015-01-01
In this paper we describe and demonstrate a discrete ordinates sweep algorithm on GPUs. This sweep algorithm is nested within a multilevel comunication-based decomposition based on energy. We demonstrated the effectiveness of this algorithm on detailed three-dimensional critical experiments and PWR lattice problems. For these problems we show improvement factors of 4 6 over conventional communication-based, CPU-only sweeps. These sweep kernel speedups resulted in a factor of 2 total time-to-solution improvement.
Multilevel solvers of first-order system least-squares for Stokes equations
Lai, Chen-Yao G.
1996-12-31
Recently, The use of first-order system least squares principle for the approximate solution of Stokes problems has been extensively studied by Cai, Manteuffel, and McCormick. In this paper, we study multilevel solvers of first-order system least-squares method for the generalized Stokes equations based on the velocity-vorticity-pressure formulation in three dimensions. The least-squares functionals is defined to be the sum of the L{sup 2}-norms of the residuals, which is weighted appropriately by the Reynolds number. We develop convergence analysis for additive and multiplicative multilevel methods applied to the resulting discrete equations.
Multilevel phase gratings for array illuminators.
Arrizón, V; Ojeda-Castañeda, J
1994-09-01
We describe a variety of multilevel phase structures that can be used to generate Lohmann's array illuminators. We report several experimental verifications of the synthesis of such multilevel phase structures by using simple binary curves in a conventional optical processor.
Principles of Discrete Time Mechanics
NASA Astrophysics Data System (ADS)
Jaroszkiewicz, George
2014-04-01
1. Introduction; 2. The physics of discreteness; 3. The road to calculus; 4. Temporal discretization; 5. Discrete time dynamics architecture; 6. Some models; 7. Classical cellular automata; 8. The action sum; 9. Worked examples; 10. Lee's approach to discrete time mechanics; 11. Elliptic billiards; 12. The construction of system functions; 13. The classical discrete time oscillator; 14. Type 2 temporal discretization; 15. Intermission; 16. Discrete time quantum mechanics; 17. The quantized discrete time oscillator; 18. Path integrals; 19. Quantum encoding; 20. Discrete time classical field equations; 21. The discrete time Schrodinger equation; 22. The discrete time Klein-Gordon equation; 23. The discrete time Dirac equation; 24. Discrete time Maxwell's equations; 25. The discrete time Skyrme model; 26. Discrete time quantum field theory; 27. Interacting discrete time scalar fields; 28. Space, time and gravitation; 29. Causality and observation; 30. Concluding remarks; Appendix A. Coherent states; Appendix B. The time-dependent oscillator; Appendix C. Quaternions; Appendix D. Quantum registers; References; Index.
Enders, Craig K; Mistler, Stephen A; Keller, Brian T
2016-06-01
Although missing data methods have advanced in recent years, methodologists have devoted less attention to multilevel data structures where observations at level-1 are nested within higher-order organizational units at level-2 (e.g., individuals within neighborhoods; repeated measures nested within individuals; students nested within classrooms). Joint modeling and chained equations imputation are the principal imputation frameworks for single-level data, and both have multilevel counterparts. These approaches differ algorithmically and in their functionality; both are appropriate for simple random intercept analyses with normally distributed data, but they differ beyond that. The purpose of this paper is to describe multilevel imputation strategies and evaluate their performance in a variety of common analysis models. Using multiple imputation theory and computer simulations, we derive 4 major conclusions: (a) joint modeling and chained equations imputation are appropriate for random intercept analyses; (b) the joint model is superior for analyses that posit different within- and between-cluster associations (e.g., a multilevel regression model that includes a level-1 predictor and its cluster means, a multilevel structural equation model with different path values at level-1 and level-2); (c) chained equations imputation provides a dramatic improvement over joint modeling in random slope analyses; and (d) a latent variable formulation for categorical variables is quite effective. We use a real data analysis to demonstrate multilevel imputation, and we suggest a number of avenues for future research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Tree Ensembles on the Induced Discrete Space.
Yildiz, Olcay Taner
2016-05-01
Decision trees are widely used predictive models in machine learning. Recently, K -tree is proposed, where the original discrete feature space is expanded by generating all orderings of values of k discrete attributes and these orderings are used as the new attributes in decision tree induction. Although K -tree performs significantly better than the proper one, their exponential time complexity can prohibit their use. In this brief, we propose K -forest, an extension of random forest, where a subset of features is selected randomly from the induced discrete space. Simulation results on 17 data sets show that the novel ensemble classifier has significantly lower error rate compared with the random forest based on the original feature space.
Multi-level methods and approximating distribution functions
NASA Astrophysics Data System (ADS)
Wilson, D.; Baker, R. E.
2016-07-01
Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie's direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie's direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146-179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.
Multi-level methods and approximating distribution functions
Wilson, D. Baker, R. E.
2016-07-15
Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.
A General Multilevel SEM Framework for Assessing Multilevel Mediation
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Zyphur, Michael J.; Zhang, Zhen
2010-01-01
Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between- and within-level components of indirect effects. Moreover,…
A General Multilevel SEM Framework for Assessing Multilevel Mediation
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Zyphur, Michael J.; Zhang, Zhen
2010-01-01
Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between- and within-level components of indirect effects. Moreover,…
Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis.
Dean, Danielle O; Bauer, Daniel J; Prinstein, Mitchell J
2017-01-01
A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common-as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed.
ERIC Educational Resources Information Center
Sebro, Negusse Yohannes; Goshu, Ayele Taye
2017-01-01
This study aims to explore Bayesian multilevel modeling to investigate variations of average academic achievement of grade eight school students. A sample of 636 students is randomly selected from 26 private and government schools by a two-stage stratified sampling design. Bayesian method is used to estimate the fixed and random effects. Input and…
A New Approach for Estimating a Nonlinear Growth Component in Multilevel Modeling
ERIC Educational Resources Information Center
Tolvanen, Asko; Kiuru, Noona; Leskinen, Esko; Hakkarainen, Kai; Inkinen, Mikko; Lonka, Kirsti; Salmela-Aro, Katariina
2011-01-01
This study presents a new approach to estimation of a nonlinear growth curve component with fixed and random effects in multilevel modeling. This approach can be used to estimate change in longitudinal data, such as day-of-the-week fluctuation. The motivation of the new approach is to avoid spurious estimates in a random coefficient regression…
A New Approach for Estimating a Nonlinear Growth Component in Multilevel Modeling
ERIC Educational Resources Information Center
Tolvanen, Asko; Kiuru, Noona; Leskinen, Esko; Hakkarainen, Kai; Inkinen, Mikko; Lonka, Kirsti; Salmela-Aro, Katariina
2011-01-01
This study presents a new approach to estimation of a nonlinear growth curve component with fixed and random effects in multilevel modeling. This approach can be used to estimate change in longitudinal data, such as day-of-the-week fluctuation. The motivation of the new approach is to avoid spurious estimates in a random coefficient regression…
Discreteness inducing coexistence
NASA Astrophysics Data System (ADS)
dos Santos, Renato Vieira
2013-12-01
Consider two species that diffuse through space. Consider further that they differ only in initial densities and, possibly, in diffusion constants. Otherwise they are identical. What happens if they compete with each other in the same environment? What is the influence of the discrete nature of the interactions on the final destination? And what are the influence of diffusion and additive fluctuations corresponding to random migration and immigration of individuals? This paper aims to answer these questions for a particular competition model that incorporates intra and interspecific competition between the species. Based on mean field theory, the model has a stationary state dependent on the initial density conditions. We investigate how this initial density dependence is affected by the presence of demographic multiplicative noise and additive noise in space and time. There are three main conclusions: (1) Additive noise favors denser populations at the expense of the less dense, ratifying the competitive exclusion principle. (2) Demographic noise, on the other hand, favors less dense populations at the expense of the denser ones, inducing equal densities at the quasi-stationary state, violating the aforementioned principle. (3) The slower species always suffers the more deleterious effects of statistical fluctuations in a homogeneous medium.
Finite Markov Chains and Random Discrete Structures
1994-07-26
arrays with fixed margins 4. Persi Diaconis and Susan Holmes, Three Examples of Monte- Carlo Markov Chains: at the Interface between Statistical Computing...solutions for a math- ematical model of thermomechanical phase transitions in shape memory materials with Landau- Ginzburg free energy 1168 Angelo Favini
Feedback nonlinear discrete-time systems
NASA Astrophysics Data System (ADS)
Yu, Miao; Wang, Jiasen; Qi, Donglian
2014-11-01
In this paper, we design an adaptive iterative learning control method for a class of high-order nonlinear output feedback discrete-time systems with random initial conditions and iteration-varying desired trajectories. An n-step ahead predictor approach is employed to estimate future outputs. The discrete Nussbaum gain method is incorporated into the control design to deal with unknown control directions. The proposed control algorithm ensures that the tracking error converges to zero asymptotically along the iterative learning axis except for the beginning outputs affected by random initial conditions. A numerical simulation is carried out to demonstrate the efficacy of the presented control laws.
Multilevel Assessments of Science Standards
ERIC Educational Resources Information Center
Quellmalz, Edys S.; Timms, Michael J.; Silberglitt, Matt D.
2011-01-01
The Multilevel Assessment of Science Standards (MASS) project is creating a new generation of technology-enhanced formative assessments that bring the best formative assessment practices into classrooms to transform what, how, when, and where science learning is assessed. The project is investigating the feasibility, utility, technical quality,…
Multilevel algorithms for nonlinear optimization
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Dennis, J. E., Jr.
1994-01-01
Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that naturally occur in blocks. We propose a class of multilevel optimization methods motivated by the structure and number of constraints and by the expense of the derivative computations for MDO. The algorithms are an extension to the nonlinear programming problem of the successful class of local Brown-Brent algorithms for nonlinear equations. Our extensions allow the user to partition constraints into arbitrary blocks to fit the application, and they separately process each block and the objective function, restricted to certain subspaces. The methods use trust regions as a globalization strategy, and they have been shown to be globally convergent under reasonable assumptions. The multilevel algorithms can be applied to all classes of MDO formulations. Multilevel algorithms for solving nonlinear systems of equations are a special case of the multilevel optimization methods. In this case, they can be viewed as a trust-region globalization of the Brown-Brent class.
Generalized Multilevel Structural Equation Modeling
ERIC Educational Resources Information Center
Rabe-Hesketh, Sophia; Skrondal, Anders; Pickles, Andrew
2004-01-01
A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…
On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo
NASA Astrophysics Data System (ADS)
Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl
2016-09-01
A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; ...
2014-05-29
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε–2) or (ε–2(lnε)2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε–3) for direct simulation Monte Carlo or binary collision methods.more » We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10–5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.« less
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
2014-05-29
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε^{–2}) or (ε^{–2}(lnε)^{2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε^{–3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10^{–5}. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M.S.; Ricketson, L.F.; Dimits, A.M.; Caflisch, R.E.; Cohen, B.I.
2014-10-01
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε, the computational cost of the method is O(ε{sup −2}) or O(ε{sup −2}(lnε){sup 2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε{sup −3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10{sup −5}. We discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.
Modeling Repeatable Events Using Discrete-Time Data: Predicting Marital Dissolution
ERIC Educational Resources Information Center
Teachman, Jay
2011-01-01
I join two methodologies by illustrating the application of multilevel modeling principles to hazard-rate models with an emphasis on procedures for discrete-time data that contain repeatable events. I demonstrate this application using data taken from the 1995 National Survey of Family Growth (NSFG) to ascertain the relationship between multiple…
Modeling Repeatable Events Using Discrete-Time Data: Predicting Marital Dissolution
ERIC Educational Resources Information Center
Teachman, Jay
2011-01-01
I join two methodologies by illustrating the application of multilevel modeling principles to hazard-rate models with an emphasis on procedures for discrete-time data that contain repeatable events. I demonstrate this application using data taken from the 1995 National Survey of Family Growth (NSFG) to ascertain the relationship between multiple…
A latent-variable marginal method for multi-level incomplete binary data
Chen, Baojiang; Zhou, Xiao-Hua
2013-01-01
Incomplete multi-level data arise commonly in many clinical trials and observational studies. Because of multi-level variations in this type of data, appropriate data analysis should take these variations into account. A random effects model can allow for the multi-level variations by assuming random effects at each level, but the computation is intensive because high-dimensional integrations are often involved in fitting models. Marginal methods such as the inverse probability weighted generalized estimating equations can involve simple estimation computation, but it is hard to specify the working correlation matrix for multi-level data. In this paper, we introduce a latent variable method to deal with incomplete multi-level data when the missing mechanism is missing at random, which fills the gap between the random effects model and marginal models. Latent variable models are built for both the response and missing data processes to incorporate the variations that arise at each level. Simulation studies demonstrate that this method performs well in various situations. We apply the proposed method to an Alzheimer’s disease study. PMID:22733392
A latent-variable marginal method for multi-level incomplete binary data.
Chen, Baojiang; Zhou, Xiao-Hua
2012-11-20
Incomplete multi-level data arise commonly in many clinical trials and observational studies. Because of multi-level variations in this type of data, appropriate data analysis should take these variations into account. A random effects model can allow for the multi-level variations by assuming random effects at each level, but the computation is intensive because high-dimensional integrations are often involved in fitting models. Marginal methods such as the inverse probability weighted generalized estimating equations can involve simple estimation computation, but it is hard to specify the working correlation matrix for multi-level data. In this paper, we introduce a latent variable method to deal with incomplete multi-level data when the missing mechanism is missing at random, which fills the gap between the random effects model and marginal models. Latent variable models are built for both the response and missing data processes to incorporate the variations that arise at each level. Simulation studies demonstrate that this method performs well in various situations. We apply the proposed method to an Alzheimer's disease study.
Comparing Spatial and Multilevel Regression Models for Binary Outcomes in Neighborhood Studies
Xu, Hongwei
2013-01-01
The standard multilevel regressions that are widely used in neighborhood research typically ignore potential between-neighborhood correlations due to underlying spatial processes, and hence produce inappropriate inferences about neighborhood effects. In contrast, spatial models make estimations and predictions across areas by explicitly modeling the spatial correlations among observations in different locations. A better understanding of the strengths and limitations of spatial models as compared to the standard multilevel model is needed to improve the research on neighborhood and spatial effects. This research systematically compares model estimations and predictions for binary outcomes between (distance- and lattice-based) spatial and the standard multilevel models in the presence of both within- and between-neighborhood correlations, through simulations. Results from simulation analysis reveal that the standard multilevel and spatial models produce similar estimates of fixed effects, but different estimates of random effects variances. Both the standard multilevel and pure spatial models tend to overestimate the corresponding random effects variances, compared to hybrid models when both non-spatial within neighborhood and spatial between-neighborhood effects exist. Spatial models also outperform the standard multilevel model by a narrow margin in case of fully out-of-sample predictions. Distance-based spatial models provide extra spatial information and have stronger predictive power than lattice-based models under certain circumstances. These merits of spatial modeling are exhibited in an empirical analysis of the child mortality data from 1880 Newark, New Jersey. PMID:25284905
NASA Astrophysics Data System (ADS)
Alford, Mark G.; March-Russell, John
In this review we discuss the formulation and distinguishing characteristics of discrete gauge theories, and describe several important applications of the concept. For the abelian (ℤN) discrete gauge theories, we consider the construction of the discrete charge operator F(Σ*) and the associated gauge-invariant order parameter that distinguishes different Higgs phases of a spontaneously broken U(1) gauge theory. We sketch some of the important thermodynamic consequences of the resultant discrete quantum hair on black holes. We further show that, as a consequence of unbroken discrete gauge symmetries, Grand Unified cosmic strings generically exhibit a Callan-Rubakov effect. For non-abelian discrete gauge theories we discuss in some detail the charge measurement process, and in the context of a lattice formulation we construct the non-abelian generalization of F(Σ*). This enables us to build the order parameter that distinguishes the different Higgs phases of a non-abelian discrete lattice gauge theory with matter. We also describe some of the fascinating phenomena associated with non-abelian gauge vortices. For example, we argue that a loop of Alice string, or any non-abelian string, is super-conducting by virtue of charged zero modes whose charge cannot be localized anywhere on or around the string (“Cheshire charge”). Finally, we discuss the relationship between discrete gauge theories and the existence of excitations possessing exotic spin and statistics (and more generally excitations whose interactions are purely “topological”).
Morris, J; Johnson, S
2007-12-03
The Distinct Element Method (also frequently referred to as the Discrete Element Method) (DEM) is a Lagrangian numerical technique where the computational domain consists of discrete solid elements which interact via compliant contacts. This can be contrasted with Finite Element Methods where the computational domain is assumed to represent a continuum (although many modern implementations of the FEM can accommodate some Distinct Element capabilities). Often the terms Discrete Element Method and Distinct Element Method are used interchangeably in the literature, although Cundall and Hart (1992) suggested that Discrete Element Methods should be a more inclusive term covering Distinct Element Methods, Displacement Discontinuity Analysis and Modal Methods. In this work, DEM specifically refers to the Distinct Element Method, where the discrete elements interact via compliant contacts, in contrast with Displacement Discontinuity Analysis where the contacts are rigid and all compliance is taken up by the adjacent intact material.
Synchronous Discrete Harmonic Oscillator
Antippa, Adel F.; Dubois, Daniel M.
2008-10-17
We introduce the synchronous discrete harmonic oscillator, and present an analytical, numerical and graphical study of its characteristics. The oscillator is synchronous when the time T for one revolution covering an angle of 2{pi} in phase space, is an integral multiple N of the discrete time step {delta}t. It is fully synchronous when N is even. It is pseudo-synchronous when T/{delta}t is rational. In the energy conserving hyperincursive representation, the phase space trajectories are perfectly stable at all time scales, and in both synchronous and pseudo-synchronous modes they cycle through a finite number of phase space points. Consequently, both the synchronous and the pseudo-synchronous hyperincursive modes of time-discretization provide a physically realistic and mathematically coherent, procedure for dynamic, background independent, discretization of spacetime. The procedure is applicable to any stable periodic dynamical system, and provokes an intrinsic correlation between space and time, whereby space-discretization is a direct consequence of background-independent time-discretization. Hence, synchronous discretization moves the formalism of classical mechanics towards that of special relativity. The frequency of the hyperincursive discrete harmonic oscillator is ''blue shifted'' relative to its continuum counterpart. The frequency shift has the precise value needed to make the speed of the system point in phase space independent of the discretizing time interval {delta}t. That is the speed of the system point is the same on the polygonal (in the discrete case) and the circular (in the continuum case) phase space trajectories.
Multi-Level Adaptive Techniques (MLAT) for singular-perturbation problems
NASA Technical Reports Server (NTRS)
Brandt, A.
1978-01-01
The multilevel (multigrid) adaptive technique, a general strategy of solving continuous problems by cycling between coarser and finer levels of discretization is described. It provides very fast general solvers, together with adaptive, nearly optimal discretization schemes. In the process, boundary layers are automatically either resolved or skipped, depending on a control function which expresses the computational goal. The global error decreases exponentially as a function of the overall computational work, in a uniform rate independent of the magnitude of the singular-perturbation terms. The key is high-order uniformly stable difference equations, and uniformly smoothing relaxation schemes.
Electrolytic plating apparatus for discrete microsized particles
Mayer, Anton
1976-11-30
Method and apparatus are disclosed for electrolytically producing very uniform coatings of a desired material on discrete microsized particles. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with a powered cathode for a time sufficient for such to occur.
Electroless plating apparatus for discrete microsized particles
Mayer, Anton
1978-01-01
Method and apparatus are disclosed for producing very uniform coatings of a desired material on discrete microsized particles by electroless techniques. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with each other for a time sufficient for such to occur.
Discrete dislocations in graphene
NASA Astrophysics Data System (ADS)
Ariza, M. P.; Ortiz, M.
2010-05-01
In this work, we present an application of the theory of discrete dislocations of Ariza and Ortiz (2005) to the analysis of dislocations in graphene. Specifically, we discuss the specialization of the theory to graphene and its further specialization to the force-constant model of Aizawa et al. (1990). The ability of the discrete-dislocation theory to predict dislocation core structures and energies is critically assessed for periodic arrangements of dislocation dipoles and quadrupoles. We show that, with the aid of the discrete Fourier transform, those problems are amenable to exact solution within the discrete-dislocation theory, which confers the theory a distinct advantage over conventional atomistic models. The discrete dislocations exhibit 5-7 ring core structures that are consistent with observation and result in dislocation energies that fall within the range of prediction of other models. The asymptotic behavior of dilute distributions of dislocations is characterized analytically in terms of a discrete prelogarithmic energy tensor. Explicit expressions for this discrete prelogarithmic energy tensor are provided up to quadratures.
Dendritic growth model of multilevel marketing
NASA Astrophysics Data System (ADS)
Pang, James Christopher S.; Monterola, Christopher P.
2017-02-01
Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.
Wieselquist, William A.; Anistratov, Dmitriy Y.; Morel, Jim E.
2014-09-15
We present a quasidiffusion (QD) method for solving neutral particle transport problems in Cartesian XY geometry on unstructured quadrilateral meshes, including local refinement capability. Neutral particle transport problems are central to many applications including nuclear reactor design, radiation safety, astrophysics, medical imaging, radiotherapy, nuclear fuel transport/storage, shielding design, and oil well-logging. The primary development is a new discretization of the low-order QD (LOQD) equations based on cell-local finite differences. The accuracy of the LOQD equations depends on proper calculation of special non-linear QD (Eddington) factors from a transport solution. In order to completely define the new QD method, a proper discretization of the transport problem is also presented. The transport equation is discretized by a conservative method of short characteristics with a novel linear approximation of the scattering source term and monotonic, parabolic representation of the angular flux on incoming faces. Analytic and numerical tests are used to test the accuracy and spatial convergence of the non-linear method. All tests exhibit O(h{sup 2}) convergence of the scalar flux on orthogonal, random, and multi-level meshes.
ERIC Educational Resources Information Center
Peters, James V.
2004-01-01
Using the methods of finite difference equations the discrete analogue of the parabolic and catenary cable are analysed. The fibonacci numbers and the golden ratio arise in the treatment of the catenary.
ERIC Educational Resources Information Center
Peters, James V.
2004-01-01
Using the methods of finite difference equations the discrete analogue of the parabolic and catenary cable are analysed. The fibonacci numbers and the golden ratio arise in the treatment of the catenary.
ERIC Educational Resources Information Center
Crisler, Nancy; Froelich, Gary
1990-01-01
Discussed are summary recommendations concerning the integration of some aspects of discrete mathematics into existing secondary mathematics courses. Outlines of course activities are grouped into the three levels of prealgebra, algebra, and geometry. Some sample problems are included. (JJK)
A continuation multilevel Monte Carlo algorithm
Collier, Nathan; Haji-Ali, Abdul-Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raúl
2014-09-05
Here, we propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. Moreover, the actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Our numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients.
Go, Vivian F.; Frangakis, Constantine; Minh, Nguyen Le; Latkin, Carl; Ha, Tran Viet; Mo, Tran Thi; Sripaipan, Teerada; Davis, Wendy W.; Zelaya, Carla; Vu, Pham The; Celentano, David D.; Quan, Vu Minh
2015-01-01
Introduction Injecting drug use is a primary driver of HIV epidemics in many countries. People who inject drugs (PWID) and are HIV infected are often doubly stigmatized and many encounter difficulties reducing risk behaviors. Prevention interventions for HIV-infected PWID that provide enhanced support at the individual, family, and community level to facilitate risk-reduction are needed. Methods 455 HIV-infected PWID and 355 of their HIV negative injecting network members living in 32 sub-districts in Thai Nguyen Province were enrolled. We conducted a two-stage randomization: First, sub-districts were randomized to either a community video screening and house-to-house visits or standard of care educational pamphlets. Second, within each sub-district, participants were randomized to receive either enhanced individual level post-test counseling and group support sessions or standard of care HIV testing and counseling. This resulted in four arms: 1) standard of care; 2) community level intervention; 3) individual level intervention; and 4) community plus individual intervention. Follow-up was conducted at 6, 12, 18, and 24 months. Primary outcomes were self-reported HIV injecting and sexual risk behaviors. Secondary outcomes included HIV incidence among HIV negative network members. Results Fewer participants reported sharing injecting equipment and unprotected sex from baseline to 24 months in all arms (77% to 4% and 24% to 5% respectively). There were no significant differences at the 24-month visit among the 4 arms (Wald = 3.40 (3 df); p = 0.33; Wald = 6.73 (3 df); p = 0.08). There were a total of 4 HIV seroconversions over 24 months with no significant difference between intervention and control arms. Discussion Understanding the mechanisms through which all arms, particularly the control arm, demonstrated both low risk behaviors and low HIV incidence has important implications for policy and prevention programming. Trial Registration ClinicalTrials.gov NCT
Go, Vivian F; Frangakis, Constantine; Minh, Nguyen Le; Latkin, Carl; Ha, Tran Viet; Mo, Tran Thi; Sripaipan, Teerada; Davis, Wendy W; Zelaya, Carla; Vu, Pham The; Celentano, David D; Quan, Vu Minh
2015-01-01
Injecting drug use is a primary driver of HIV epidemics in many countries. People who inject drugs (PWID) and are HIV infected are often doubly stigmatized and many encounter difficulties reducing risk behaviors. Prevention interventions for HIV-infected PWID that provide enhanced support at the individual, family, and community level to facilitate risk-reduction are needed. 455 HIV-infected PWID and 355 of their HIV negative injecting network members living in 32 sub-districts in Thai Nguyen Province were enrolled. We conducted a two-stage randomization: First, sub-districts were randomized to either a community video screening and house-to-house visits or standard of care educational pamphlets. Second, within each sub-district, participants were randomized to receive either enhanced individual level post-test counseling and group support sessions or standard of care HIV testing and counseling. This resulted in four arms: 1) standard of care; 2) community level intervention; 3) individual level intervention; and 4) community plus individual intervention. Follow-up was conducted at 6, 12, 18, and 24 months. Primary outcomes were self-reported HIV injecting and sexual risk behaviors. Secondary outcomes included HIV incidence among HIV negative network members. Fewer participants reported sharing injecting equipment and unprotected sex from baseline to 24 months in all arms (77% to 4% and 24% to 5% respectively). There were no significant differences at the 24-month visit among the 4 arms (Wald = 3.40 (3 df); p = 0.33; Wald = 6.73 (3 df); p = 0.08). There were a total of 4 HIV seroconversions over 24 months with no significant difference between intervention and control arms. Understanding the mechanisms through which all arms, particularly the control arm, demonstrated both low risk behaviors and low HIV incidence has important implications for policy and prevention programming. ClinicalTrials.gov NCT01689545.
Gans, Kim M; Gorham, Gemma; Risica, Patricia M; Dulin-Keita, Akilah; Dionne, Laura; Gao, Tina; Peters, Sarah; Principato, Ludovica
2016-06-28
Adequate fruit and vegetable (F&V) intake is important for disease prevention. Yet, most Americans, especially low-income and racial/ethnic minorities, do not eat adequate amounts. These disparities are partly attributable to food environments in low-income neighborhoods where residents often have limited access to affordable, healthful food and easy access to inexpensive, unhealthful foods. Increasing access to affordable healthful food in underserved neighborhoods through mobile markets is a promising, year-round strategy for improving dietary behaviors and reducing F&V intake disparities. However, to date, there have been no randomized controlled trials studying their effectiveness. The objective of the 'Live Well, Viva Bien' (LWVB) cluster randomized controlled trial is to evaluate the efficacy of a multicomponent mobile market intervention at increasing F&V intake among residents of subsidized housing complexes. One housing complex served as a pilot site for the intervention group and the remaining 14 demographically-matched sites were randomized into either the intervention or control group. The intervention group received bimonthly, discount, mobile, fresh F&V markets in conjunction with a nutrition education intervention (two F&V campaigns, newsletters, DVDs and cooking demonstrations) for 12 months. The control group received physical activity and stress reduction interventions. Outcome measures include F&V intake (measured by two validated F&V screeners at baseline, six-month and twelve-months) along with potential psychosocial mediating variables. Extensive quantitative and qualitative process evaluation was also conducted throughout the study. Modifying neighborhood food environments in ways that increase access to affordable, healthful food is a promising strategy for improving dietary behaviors among low-income, racial and ethnic minority groups at increased risk for obesity and other food-related chronic diseases. Discount, mobile F&V markets
Structural optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.; James, B.; Dovi, A.
1983-01-01
A method is described for decomposing an optimization problem into a set of subproblems and a coordination problem which preserves coupling between the subproblems. The method is introduced as a special case of multilevel, multidisciplinary system optimization and its algorithm is fully described for two level optimization for structures assembled of finite elements of arbitrary type. Numerical results are given for an example of a framework to show that the decomposition method converges and yields results comparable to those obtained without decomposition. It is pointed out that optimization by decomposition should reduce the design time by allowing groups of engineers, using different computers to work concurrently on the same large problem.
Propensity score weighting for a continuous exposure with multilevel data.
Schuler, Megan S; Chu, Wanghuan; Coffman, Donna
2016-12-01
Propensity score methods (e.g., matching, weighting, subclassification) provide a statistical approach for balancing dissimilar exposure groups on baseline covariates. These methods were developed in the context of data with no hierarchical structure or clustering. Yet in many applications the data have a clustered structure that is of substantive importance, such as when individuals are nested within healthcare providers or within schools. Recent work has extended propensity score methods to a multilevel setting, primarily focusing on binary exposures. In this paper, we focus on propensity score weighting for a continuous, rather than binary, exposure in a multilevel setting. Using simulations, we compare several specifications of the propensity score: a random effects model, a fixed effects model, and a single-level model. Additionally, our simulations compare the performance of marginal versus cluster-mean stabilized propensity score weights. In our results, regression specifications that accounted for the multilevel structure reduced bias, particularly when cluster-level confounders were omitted. Furthermore, cluster mean weights outperformed marginal weights.
A Multilevel Assessment of Differential Item Functioning.
ERIC Educational Resources Information Center
Shen, Linjun
A multilevel approach was proposed for the assessment of differential item functioning and compared with the traditional logistic regression approach. Data from the Comprehensive Osteopathic Medical Licensing Examination for 2,300 freshman osteopathic medical students were analyzed. The multilevel approach used three-level hierarchical generalized…
Scalable Adaptive Multilevel Solvers for Multiphysics Problems
Xu, Jinchao
2014-11-26
In this project, we carried out many studies on adaptive and parallel multilevel methods for numerical modeling for various applications, including Magnetohydrodynamics (MHD) and complex fluids. We have made significant efforts and advances in adaptive multilevel methods of the multiphysics problems: multigrid methods, adaptive finite element methods, and applications.
Griebel, M.
1994-12-31
In recent years, it has turned out that many modern iterative algorithms (multigrid schemes, multilevel preconditioners, domain decomposition methods etc.) for solving problems resulting from the discretization of PDEs can be interpreted as additive (Jacobi-like) or multiplicative (Gauss-Seidel-like) subspace correction methods. The key to their analysis is the study of certain metric properties of the underlying splitting of the discretization space V into a sum of subspaces V{sub j}, j = 1{hor_ellipsis}, J resp. of the variational problem on V into auxiliary problems on these subspaces. Here, the author proposes a modified approach to the abstract convergence theory of these additive and multiplicative Schwarz iterative methods, that makes the relation to traditional iteration methods more explicit. To this end he introduces the enlarged Hilbert space V = V{sub 0} x {hor_ellipsis} x V{sub j} which is nothing else but the usual construction of the Cartesian product of the Hilbert spaces V{sub j} and use it now in the discretization process. This results in an enlarged, semidefinite linear system to be solved instead of the usual definite system. Then, modern multilevel methods as well as domain decomposition methods simplify to just traditional (block-) iteration methods. Now, the convergence analysis can be carried out directly for these traditional iterations on the enlarged system, making convergence proofs of multilevel and domain decomposition methods more clear, or, at least, more classical. The terms that enter the convergence proofs are exactly the ones of the classical iterative methods. It remains to estimate them properly. The convergence proof itself follow basically line by line the old proofs of the respective traditional iterative methods. Additionally, new multilevel/domain decomposition methods are constructed straightforwardly by now applying just other old and well known traditional iterative methods to the enlarged system.
Multilevel Sequential Monte Carlo Samplers for Normalizing Constants
Moral, Pierre Del; Jasra, Ajay; Law, Kody J. H.; ...
2017-08-24
This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of themore » solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.« less
Multigrid and multilevel domain decomposition for unstructured grids
Chan, T.; Smith, B.
1994-12-31
Multigrid has proven itself to be a very versatile method for the iterative solution of linear and nonlinear systems of equations arising from the discretization of PDES. In some applications, however, no natural multilevel structure of grids is available, and these must be generated as part of the solution procedure. In this presentation the authors will consider the problem of generating a multigrid algorithm when only a fine, unstructured grid is given. Their techniques generate a sequence of coarser grids by first forming an approximate maximal independent set of the vertices and then applying a Cavendish type algorithm to form the coarser triangulation. Numerical tests indicate that convergence using this approach can be as fast as standard multigrid on a structured mesh, at least in two dimensions.
Multilevel Sequential Monte Carlo Samplers for Normalizing Constants
Moral, Pierre Del; Jasra, Ajay; Law, Kody J. H.; ...
2017-08-24
Our article considers the Sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Furthermore, two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic Partial Differential Equations (PDEs). Finally, the examples involve the inversion of observationsmore » of the solution of (i) a one-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a two-dimensional Poisson equation to infer the external forcing.« less
Multi-level Algorithm for the Anderson Impurity Model
NASA Astrophysics Data System (ADS)
Chandrasekharan, S.; Yoo, J.; Baranger, H. U.
2004-03-01
We develop a new quantum Monte Carlo algorithm to solve the Anderson impurity model. Instead of integrating out the Fermions, we work in the Fermion occupation number basis and thus have direct access to the Fermionic physics. The sign problem that arises in this formulation can be solved by a multi-level technique developed by Luscher and Weisz in the context of lattice QCD [JHEP, 0109 (2001) 010]. We use the directed-loop algorithm to update the degrees of freedom. Further, this algorithm allows us to work directly in the Euclidean time continuum limit for arbitrary values of the interaction strength thus avoiding time discretization errors. We present results for the impurity susceptibility and the properties of the screening cloud obtained using the algorithm.
Depression: discrete or continuous?
Bowins, Brad
2015-01-01
Elucidating the true structure of depression is necessary if we are to advance our understanding and treatment options. Central to the issue of structure is whether depression represents discrete types or occurs on a continuum. Nature almost universally operates on the basis of continuums, whereas human perception favors discrete categories. This reality might be formalized into a 'continuum principle': natural phenomena tend to occur on a continuum, and any instance of hypothesized discreteness requires unassailable proof. Research evidence for discrete types falls far short of this standard, with most evidence supporting a continuum. However, quantitative variation can yield qualitative differences as an emergent property, fostering the appearance of discreteness. Depression as a continuum is best characterized by duration and severity dimensions, with the latter understood in terms of depressive inhibition. In the absence of some degree of cognitive, emotional, social, and physical inhibition, depression should not be diagnosed. Combining the dimensions of duration and severity provides an optimal way to characterize the quantitative and related qualitative aspects of depression and to describe the overall degree of dysfunction. The presence of other symptom types occurs when anxiety, hypomanic/manic, psychotic, and personality continuums interface with the depression continuum.
Within-Cluster and Across-Cluster Matching with Observational Multilevel Data
ERIC Educational Resources Information Center
Kim, Jee-Seon; Steiner, Peter M.; Hall, Courtney; Thoemmes, Felix
2013-01-01
When randomized experiments cannot be conducted in practice, propensity score (PS) techniques for matching treated and control units are frequently used for estimating causal treatment effects from observational data. Despite the popularity of PS techniques, they are not yet well studied for matching multilevel data where selection into treatment…
Kadengye, Damazo T; Cools, Wilfried; Ceulemans, Eva; Van den Noortgate, Wim
2012-06-01
Missing data, such as item responses in multilevel data, are ubiquitous in educational research settings. Researchers in the item response theory (IRT) context have shown that ignoring such missing data can create problems in the estimation of the IRT model parameters. Consequently, several imputation methods for dealing with missing item data have been proposed and shown to be effective when applied with traditional IRT models. Additionally, a nonimputation direct likelihood analysis has been shown to be an effective tool for handling missing observations in clustered data settings. This study investigates the performance of six simple imputation methods, which have been found to be useful in other IRT contexts, versus a direct likelihood analysis, in multilevel data from educational settings. Multilevel item response data were simulated on the basis of two empirical data sets, and some of the item scores were deleted, such that they were missing either completely at random or simply at random. An explanatory IRT model was used for modeling the complete, incomplete, and imputed data sets. We showed that direct likelihood analysis of the incomplete data sets produced unbiased parameter estimates that were comparable to those from a complete data analysis. Multiple-imputation approaches of the two-way mean and corrected item mean substitution methods displayed varying degrees of effectiveness in imputing data that in turn could produce unbiased parameter estimates. The simple random imputation, adjusted random imputation, item means substitution, and regression imputation methods seemed to be less effective in imputing missing item scores in multilevel data settings.
Discrete Newtonian cosmology: perturbations
NASA Astrophysics Data System (ADS)
Ellis, George F. R.; Gibbons, Gary W.
2015-03-01
In a previous paper (Gibbons and Ellis 2014 Discrete Newtonian cosmology Class. Quantum Grav. 31 025003), we showed how a finite system of discrete particles interacting with each other via Newtonian gravitational attraction would lead to precisely the same dynamical equations for homothetic motion as in the case of the pressure-free Friedmann-Lemaître-Robertson-Walker cosmological models of general relativity theory, provided the distribution of particles obeys the central configuration equation. In this paper we show that one can obtain perturbed such Newtonian solutions that give the same linearized structure growth equations as in the general relativity case. We also obtain the Dmitriev-Zel’dovich equations for subsystems in this discrete gravitational model, and show how it leads to the conclusion that voids have an apparent negative mass.
NASA Astrophysics Data System (ADS)
Klette, Reinhard; Jiang, Ruyi; Morales, Sandino; Vaudrey, Tobi
Applying computer technology, such as computer vision in driver assistance, implies that processes and data are modeled as being discretized rather than being continuous. The area of stereo vision provides various examples how concepts known in discrete mathematics (e.g., pixel adjacency graphs, belief propagation, dynamic programming, max-flow/min-cut, or digital straight lines) are applied when aiming for efficient and accurate pixel correspondence solutions. The paper reviews such developments for a reader in discrete mathematics who is interested in applied research (in particular, in vision-based driver assistance). As a second subject, the paper also discusses lane detection and tracking, which is a particular task in driver assistance; recently the Euclidean distance transform proved to be a very appropriate tool for obtaining a fairly robust solution.
Discrete breathers in crystals
NASA Astrophysics Data System (ADS)
Dmitriev, S. V.; Korznikova, E. A.; Baimova, Yu A.; Velarde, M. G.
2016-05-01
It is well known that periodic discrete defect-containing systems, in addition to traveling waves, support vibrational defect-localized modes. It turned out that if a periodic discrete system is nonlinear, it can support spatially localized vibrational modes as exact solutions even in the absence of defects. Since the nodes of the system are all on equal footing, it is only through the special choice of initial conditions that a group of nodes can be found on which such a mode, called a discrete breather (DB), will be excited. The DB frequency must be outside the frequency range of the small-amplitude traveling waves. Not resonating with and expending no energy on the excitation of traveling waves, a DB can theoretically conserve its vibrational energy forever provided no thermal vibrations or other perturbations are present. Crystals are nonlinear discrete systems, and the discovery in them of DBs was only a matter of time. It is well known that periodic discrete defect-containing systems support both traveling waves and vibrational defect-localized modes. It turns out that if a periodic discrete system is nonlinear, it can support spatially localized vibrational modes as exact solutions even in the absence of defects. Because the nodes of the system are all on equal footing, only a special choice of the initial conditions allows selecting a group of nodes on which such a mode, called a discrete breather (DB), can be excited. The DB frequency must be outside the frequency range of small-amplitude traveling waves. Not resonating with and expending no energy on the excitation of traveling waves, a DB can theoretically preserve its vibrational energy forever if no thermal vibrations or other perturbations are present. Crystals are nonlinear discrete systems, and the discovery of DBs in them was only a matter of time. Experimental studies of DBs encounter major technical difficulties, leaving atomistic computer simulations as the primary investigation tool. Despite
Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey
2015-01-01
The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey. PMID:25598587
Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey
2015-01-01
The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey.
Makris, Konstantinos G; Suntsov, Sergiy; Christodoulides, Demetrios N; Stegeman, George I; Hache, Alain
2005-09-15
It is theoretically shown that discrete nonlinear surface waves are possible in waveguide lattices. These self-trapped states are located at the edge of the array and can exist only above a certain power threshold. The excitation characteristics and stability properties of these surface waves are systematically investigated.
On multilevel block modulation codes
NASA Technical Reports Server (NTRS)
Kasami, Tadao; Takata, Toyoo; Fujiwara, Toru; Lin, Shu
1991-01-01
The multilevel (ML) technique for combining block coding and modulation is investigated. A general formulation is presented for ML modulation codes in terms of component codes with appropriate distance measures. A specific method for constructing ML block modulation codes (MLBMCs) with interdependency among component codes is proposed. Given an MLBMC C with no interdependency among the binary component codes, the proposed method gives an MLBC C-prime that has the same rate as C, a minimum squared Euclidean distance not less than that of C, a trellis diagram with the same number of states as that of C, and a smaller number of nearest-neighbor codewords than that of C. Finally, a technique is presented for analyzing the error performance of MLBMCs for an additive white Gaussian noise channel based on soft-decision maximum-likelihood decoding.
On multilevel block modulation codes
NASA Technical Reports Server (NTRS)
Kasami, Tadao; Takata, Toyoo; Fujiwara, Toru; Lin, Shu
1991-01-01
The multilevel (ML) technique for combining block coding and modulation is investigated. A general formulation is presented for ML modulation codes in terms of component codes with appropriate distance measures. A specific method for constructing ML block modulation codes (MLBMCs) with interdependency among component codes is proposed. Given an MLBMC C with no interdependency among the binary component codes, the proposed method gives an MLBC C-prime that has the same rate as C, a minimum squared Euclidean distance not less than that of C, a trellis diagram with the same number of states as that of C, and a smaller number of nearest-neighbor codewords than that of C. Finally, a technique is presented for analyzing the error performance of MLBMCs for an additive white Gaussian noise channel based on soft-decision maximum-likelihood decoding.
Multilevel modelling: Beyond the basic applications.
Wright, Daniel B; London, Kamala
2009-05-01
Over the last 30 years statistical algorithms have been developed to analyse datasets that have a hierarchical/multilevel structure. Particularly within developmental and educational psychology these techniques have become common where the sample has an obvious hierarchical structure, like pupils nested within a classroom. We describe two areas beyond the basic applications of multilevel modelling that are important to psychology: modelling the covariance structure in longitudinal designs and using generalized linear multilevel modelling as an alternative to methods from signal detection theory (SDT). Detailed code for all analyses is described using packages for the freeware R.
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
1985-08-23
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, David B.
1987-01-01
In the fabrication of multilevel integrated circuits, each metal layer is anarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, David B.
1989-01-01
In the fabrication of multilevel integrated circuits, each metal layer is anarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
1985-06-24
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping lase pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
1989-03-21
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration. 6 figs.
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
1989-03-21
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration. 6 figs.
Multilevel converters for power system applications
Lai, J.S.; Stovall, J.P.; Peng, F.Z. |
1995-09-01
Multilevel converters are emerging as a new breed of power converter options for power system applications. These converters are most suitable for high voltage high power applications because they connect devices in series without the need for component matching. One of the major limitations of the multilevel converters is the voltage unbalance between different levels. To avoid voltage unbalance between different levels, several techniques have been proposed for different applications. Excluding magnetic-coupled converters, this paper introduces three multilevel voltage source converters: (1) diode-clamp, (2) flying-capacitors, and (3) cascaded inverters with separate dc sources. The operation principle, features, constraints, and potential applications of these converters will be discussed.
Multilevel modeling for inference of genetic regulatory networks
NASA Astrophysics Data System (ADS)
Ng, Shu-Kay; Wang, Kui; McLachlan, Geoffrey J.
2005-12-01
Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.
Resilience under conditions of extreme stress: a multilevel perspective.
Cicchetti, Dante
2010-10-01
Resilience has been conceptualized as a dynamic developmental process encompassing the attainment of positive adaptation within the context of significant threat, severe adversity, or trauma. Until the past decade, the empirical study of resilience predominantly focused on behavioral and psychosocial correlates of, and contributors to, the phenomenon and did not examine neurobiological or genetic correlates of and contributors to resilience. Technological advances in molecular genetics and neuroimaging, and in measuring other biological aspects of behavior, have made it more feasible to begin to conduct research on pathways to resilient functioning from a multilevel perspective. Child maltreatment constitutes a profound immersion in severe stress that challenges and frequently impairs development across diverse domains of biological and psychological functioning. Research on the determinants of resilience in maltreated children is presented as an illustration of empirical work that is moving from single-level to multilevel investigations of competent functioning in the face of adversity and trauma. These include studies of personality, neural, neuroendocrine, and molecular genetic contributors to resilient adaptation. Analogous to neural plasticity that takes place in response to brain injury, it is conjectured that it may be possible to conceptualize resilience as the ability of individuals to recover functioning after exposure to extreme stress. Multilevel randomized control prevention and intervention trials have substantial potential for facilitating the promotion of resilient functioning in diverse high-risk populations that have experienced significant adversity. Determining the multiple levels at which change is engendered through randomized control trials will provide insight into the mechanisms of change, the extent to which neural plasticity may be promoted, and the interrelations between biological and psychological processes in the development of
Resilience under conditions of extreme stress: a multilevel perspective
CICCHETTI, DANTE
2010-01-01
Resilience has been conceptualized as a dynamic developmental process encompassing the attainment of positive adaptation within the context of significant threat, severe adversity, or trauma. Until the past decade, the empirical study of resilience predominantly focused on behavioral and psychosocial correlates of, and contributors to, the phenomenon and did not examine neurobiological or genetic correlates of and contributors to resilience. Technological advances in molecular genetics and neuroimaging, and in measuring other biological aspects of behavior, have made it more feasible to begin to conduct research on pathways to resilient functioning from a multilevel perspective. Child maltreatment constitutes a profound immersion in severe stress that challenges and frequently impairs development across diverse domains of biological and psychological functioning. Research on the determinants of resilience in maltreated children is presented as an illustration of empirical work that is moving from single-level to multilevel investigations of competent functioning in the face of adversity and trauma. These include studies of personality, neural, neuroendocrine, and molecular genetic contributors to resilient adaptation. Analogous to neural plasticity that takes place in response to brain injury, it is conjectured that it may be possible to conceptualize resilience as the ability of individuals to recover functioning after exposure to extreme stress. Multilevel randomized control prevention and intervention trials have substantial potential for facilitating the promotion of resilient functioning in diverse high-risk populations that have experienced significant adversity. Determining the multiple levels at which change is engendered through randomized control trials will provide insight into the mechanisms of change, the extent to which neural plasticity may be promoted, and the interrelations between biological and psychological processes in the development of
Application of single-level and multi-level Rasch models using the lme4 package.
Lamprianou, Iasonas
2013-01-01
The aim of the article is to illustrate how researchers may use the lme4 package to run multilevel Rasch models. The lme4 package is a popular open-source software and is frequently used by researchers around the world to fit generalized mixed-effects models with crossed or partially crossed random effects. The article starts with a short discussion of the reasons why a researcher might, sometimes, be motivated to use a multi-level Rasch model and presents a practical example using empirical data. The main features of the lme4 package are presented, and finally, the paper presents information about other open-source software that could alternatively be used to fit multi-level Rasch models.
Practical implementation of an accurate method for multilevel design sensitivity analysis
NASA Technical Reports Server (NTRS)
Nguyen, Duc T.
1987-01-01
Solution techniques for handling large scale engineering optimization problems are reviewed. Potentials for practical applications as well as their limited capabilities are discussed. A new solution algorithm for design sensitivity is proposed. The algorithm is based upon the multilevel substructuring concept to be coupled with the adjoint method of sensitivity analysis. There are no approximations involved in the present algorithm except the usual approximations introduced due to the discretization of the finite element model. Results from the six- and thirty-bar planar truss problems show that the proposed multilevel scheme for sensitivity analysis is more effective (in terms of computer incore memory and the total CPU time) than a conventional (one level) scheme even on small problems. The new algorithm is expected to perform better for larger problems and its applications on the new generation of computer hardwares with 'parallel processing' capability is very promising.
Discrete Variational Optimal Control
NASA Astrophysics Data System (ADS)
Jiménez, Fernando; Kobilarov, Marin; Martín de Diego, David
2013-06-01
This paper develops numerical methods for optimal control of mechanical systems in the Lagrangian setting. It extends the theory of discrete mechanics to enable the solutions of optimal control problems through the discretization of variational principles. The key point is to solve the optimal control problem as a variational integrator of a specially constructed higher dimensional system. The developed framework applies to systems on tangent bundles, Lie groups, and underactuated and nonholonomic systems with symmetries, and can approximate either smooth or discontinuous control inputs. The resulting methods inherit the preservation properties of variational integrators and result in numerically robust and easily implementable algorithms. Several theoretical examples and a practical one, the control of an underwater vehicle, illustrate the application of the proposed approach.
Discrete minimal flavor violation
Zwicky, Roman; Fischbacher, Thomas
2009-10-01
We investigate the consequences of replacing the global flavor symmetry of minimal flavor violation (MFV) SU(3){sub Q}xSU(3){sub U}xSU(3){sub D}x{center_dot}{center_dot}{center_dot} by a discrete D{sub Q}xD{sub U}xD{sub D}x{center_dot}{center_dot}{center_dot} symmetry. Goldstone bosons resulting from the breaking of the flavor symmetry generically lead to bounds on new flavor structure many orders of magnitude above the TeV scale. The absence of Goldstone bosons for discrete symmetries constitute the primary motivation of our work. Less symmetry implies further invariants and renders the mass-flavor basis transformation observable in principle and calls for a hierarchy in the Yukawa matrix expansion. We show, through the dimension of the representations, that the (discrete) symmetry in principle does allow for additional {delta}F=2 operators. If though the {delta}F=2 transitions are generated by two subsequent {delta}F=1 processes, as, for example, in the standard model, then the four crystal-like groups {sigma}(168){approx_equal}PSL(2,F{sub 7}), {sigma}(72{phi}), {sigma}(216{phi}) and especially {sigma}(360{phi}) do provide enough protection for a TeV-scale discrete MFV scenario. Models where this is not the case have to be investigated case by case. Interestingly {sigma}(216{phi}) has a (nonfaithful) representation corresponding to an A{sub 4} symmetry. Moreover we argue that the, apparently often omitted, (D) groups are subgroups of an appropriate {delta}(6g{sup 2}). We would like to stress that we do not provide an actual model that realizes the MFV scenario nor any other theory of flavor.
The Discrete Wavelet Transform
1991-06-01
Split- Band Coding," Proc. ICASSP, May 1977, pp 191-195. 12. Vetterli, M. "A Theory of Multirate Filter Banks ," IEEE Trans. ASSP, 35, March 1987, pp 356...both special cases of a single filter bank structure, the discrete wavelet transform, the behavior of which is governed by one’s choice of filters . In...B-1 ,.iii FIGURES 1.1 A wavelet filter bank structure ..................................... 2 2.1 Diagram illustrating the dialation and
Steerable Discrete Fourier Transform
NASA Astrophysics Data System (ADS)
Fracastoro, Giulia; Magli, Enrico
2017-03-01
Directional transforms have recently raised a lot of interest thanks to their numerous applications in signal compression and analysis. In this letter, we introduce a generalization of the discrete Fourier transform, called steerable DFT (SDFT). Since the DFT is used in numerous fields, it may be of interest in a wide range of applications. Moreover, we also show that the SDFT is highly related to other well-known transforms, such as the Fourier sine and cosine transforms and the Hilbert transforms.
Cervical Laminoplasty for Multilevel Cervical Myelopathy
Sayana, Murali Krishna; Jamil, Hassan; Poynton, Ashley
2011-01-01
Cervical spondylotic myelopathy can result from degenerative cervical spondylosis, herniated disk material, osteophytes, redundant ligamentum flavum, or ossification of the posterior longitudinal ligament. Surgical intervention for multi-level myelopathy aims to decompress the spinal cord and maintain stability of the cervical spine. Laminoplasty was major surgical advancement as laminectomy resulted in kyphosis and unsatisfactory outcomes. Hirabayashi popularised the expansive open door laminoplasty which was later modified several surgeons. Laminoplasty has changed the way surgeons approach multilevel cervical spondylotic myelopathy. PMID:21991408
The discrete regime of flame propagation
NASA Astrophysics Data System (ADS)
Tang, Francois-David; Goroshin, Samuel; Higgins, Andrew
The propagation of laminar dust flames in iron dust clouds was studied in a low-gravity envi-ronment on-board a parabolic flight aircraft. The elimination of buoyancy-induced convection and particle settling permitted measurements of fundamental combustion parameters such as the burning velocity and the flame quenching distance over a wide range of particle sizes and in different gaseous mixtures. The discrete regime of flame propagation was observed by substitut-ing nitrogen present in air with xenon, an inert gas with a significantly lower heat conductivity. Flame propagation in the discrete regime is controlled by the heat transfer between neighbor-ing particles, rather than by the particle burning rate used by traditional continuum models of heterogeneous flames. The propagation mechanism of discrete flames depends on the spa-tial distribution of particles, and thus such flames are strongly influenced by local fluctuations in the fuel concentration. Constant pressure laminar dust flames were observed inside 70 cm long, 5 cm diameter Pyrex tubes. Equally-spaced plate assemblies forming rectangular chan-nels were placed inside each tube to determine the quenching distance defined as the minimum channel width through which a flame can successfully propagate. High-speed video cameras were used to measure the flame speed and a fiber optic spectrometer was used to measure the flame temperature. Experimental results were compared with predictions obtained from a numerical model of a three-dimensional flame developed to capture both the discrete nature and the random distribution of particles in the flame. Though good qualitative agreement was obtained between model predictions and experimental observations, residual g-jitters and the short reduced-gravity periods prevented further investigations of propagation limits in the dis-crete regime. The full exploration of the discrete flame phenomenon would require high-quality, long duration reduced gravity environment
Bittig, Arne; Uhrmacher, Adelinde
2016-08-03
Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.
Exploring Discretization Error in Simulation-Based Aerodynamic Databases
NASA Technical Reports Server (NTRS)
Aftosmis, Michael J.; Nemec, Marian
2010-01-01
This work examines the level of discretization error in simulation-based aerodynamic databases and introduces strategies for error control. Simulations are performed using a parallel, multi-level Euler solver on embedded-boundary Cartesian meshes. Discretization errors in user-selected outputs are estimated using the method of adjoint-weighted residuals and we use adaptive mesh refinement to reduce these errors to specified tolerances. Using this framework, we examine the behavior of discretization error throughout a token database computed for a NACA 0012 airfoil consisting of 120 cases. We compare the cost and accuracy of two approaches for aerodynamic database generation. In the first approach, mesh adaptation is used to compute all cases in the database to a prescribed level of accuracy. The second approach conducts all simulations using the same computational mesh without adaptation. We quantitatively assess the error landscape and computational costs in both databases. This investigation highlights sensitivities of the database under a variety of conditions. The presence of transonic shocks or the stiffness in the governing equations near the incompressible limit are shown to dramatically increase discretization error requiring additional mesh resolution to control. Results show that such pathologies lead to error levels that vary by over factor of 40 when using a fixed mesh throughout the database. Alternatively, controlling this sensitivity through mesh adaptation leads to mesh sizes which span two orders of magnitude. We propose strategies to minimize simulation cost in sensitive regions and discuss the role of error-estimation in database quality.
A paradigm for discrete physics
Noyes, H.P.; McGoveran, D.; Etter, T.; Manthey, M.J.; Gefwert, C.
1987-01-01
An example is outlined for constructing a discrete physics using as a starting point the insight from quantum physics that events are discrete, indivisible and non-local. Initial postulates are finiteness, discreteness, finite computability, absolute nonuniqueness (i.e., homogeneity in the absence of specific cause) and additivity.
Bond, Stephen D.
2014-01-01
The availability of efficient algorithms for long-range pairwise interactions is central to the success of numerous applications, ranging in scale from atomic-level modeling of materials to astrophysics. This report focuses on the implementation and analysis of the multilevel summation method for approximating long-range pairwise interactions. The computational cost of the multilevel summation method is proportional to the number of particles, N, which is an improvement over FFTbased methods whos cost is asymptotically proportional to N logN. In addition to approximating electrostatic forces, the multilevel summation method can be use to efficiently approximate convolutions with long-range kernels. As an application, we apply the multilevel summation method to a discretized integral equation formulation of the regularized generalized Poisson equation. Numerical results are presented using an implementation of the multilevel summation method in the LAMMPS software package. Preliminary results show that the computational cost of the method scales as expected, but there is still a need for further optimization.
NASA Astrophysics Data System (ADS)
Cusini, Matteo; van Kruijsdijk, Cor; Hajibeygi, Hadi
2016-06-01
This paper presents the development of an algebraic dynamic multilevel method (ADM) for fully implicit simulations of multiphase flow in homogeneous and heterogeneous porous media. Built on the fine-scale fully implicit (FIM) discrete system, ADM constructs a multilevel FIM system describing the coupled process on a dynamically defined grid of hierarchical nested topology. The multilevel adaptive resolution is determined at each time step on the basis of an error criterion. Once the grid resolution is established, ADM employs sequences of restriction and prolongation operators in order to map the FIM system across the considered resolutions. Several choices can be considered for prolongation (interpolation) operators, e.g., constant, bilinear and multiscale basis functions, all of which form partition of unity. The adaptive multilevel restriction operators, on the other hand, are constructed using a finite-volume scheme. This ensures mass conservation of the ADM solutions, and as such, the stability and accuracy of the simulations with multiphase transport. For several homogeneous and heterogeneous test cases, it is shown that ADM applies only a small fraction of the full FIM fine-scale grid cells in order to provide accurate solutions. The sensitivity of the solutions with respect to the employed fraction of grid cells (determined automatically based on the threshold value of the error criterion) is investigated for all test cases. ADM is a significant step forward in the application of dynamic local grid refinement methods, in the sense that it is algebraic, allows for systematic mapping across different scales, and applicable to heterogeneous test cases without any upscaling of fine-scale high resolution quantities. It also develops a novel multilevel multiscale method for FIM multiphase flow simulations in natural subsurface formations.
Discrete Gust Model for Launch Vehicle Assessments
NASA Technical Reports Server (NTRS)
Leahy, Frank B.
2008-01-01
Analysis of spacecraft vehicle responses to atmospheric wind gusts during flight is important in the establishment of vehicle design structural requirements and operational capability. Typically, wind gust models can be either a spectral type determined by a random process having a wide range of wavelengths, or a discrete type having a single gust of predetermined magnitude and shape. Classical discrete models used by NASA during the Apollo and Space Shuttle Programs included a 9 m/sec quasi-square-wave gust with variable wavelength from 60 to 300 m. A later study derived discrete gust from a military specification (MIL-SPEC) document that used a "1-cosine" shape. The MIL-SPEC document contains a curve of non-dimensional gust magnitude as a function of non-dimensional gust half-wavelength based on the Dryden spectral model, but fails to list the equation necessary to reproduce the curve. Therefore, previous studies could only estimate a value of gust magnitude from the curve, or attempt to fit a function to it. This paper presents the development of the MIL-SPEC curve, and provides the necessary information to calculate discrete gust magnitudes as a function of both gust half-wavelength and the desired probability level of exceeding a specified gust magnitude.
Alternative Methods for Assessing Mediation in Multilevel Data: The Advantages of Multilevel SEM
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Zhang, Zhen; Zyphur, Michael J.
2011-01-01
Multilevel modeling (MLM) is a popular way of assessing mediation effects with clustered data. Two important limitations of this approach have been identified in prior research and a theoretical rationale has been provided for why multilevel structural equation modeling (MSEM) should be preferred. However, to date, no empirical evidence of MSEM's…
Gu, Fei; Preacher, Kristopher J; Wu, Wei; Yung, Yiu-Fai
2014-01-01
Although the state space approach for estimating multilevel regression models has been well established for decades in the time series literature, it does not receive much attention from educational and psychological researchers. In this article, we (a) introduce the state space approach for estimating multilevel regression models and (b) extend the state space approach for estimating multilevel factor models. A brief outline of the state space formulation is provided and then state space forms for univariate and multivariate multilevel regression models, and a multilevel confirmatory factor model, are illustrated. The utility of the state space approach is demonstrated with either a simulated or real example for each multilevel model. It is concluded that the results from the state space approach are essentially identical to those from specialized multilevel regression modeling and structural equation modeling software. More importantly, the state space approach offers researchers a computationally more efficient alternative to fit multilevel regression models with a large number of Level 1 units within each Level 2 unit or a large number of observations on each subject in a longitudinal study.
Multilevel Complex Networks and Systems
NASA Astrophysics Data System (ADS)
Caldarelli, Guido
2014-03-01
Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h_{L}. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levels ${\\infty}$ >h_{0}>h_{1 }...>h_{L}. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; ...
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h0>h1 ...>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less
Applications of cascade multilevel inverters.
Peng, Fang-zen; Qian, Zhao-ming
2003-01-01
Cascade multilevel inverters have been developed for electric utility applications. A cascade M-level inverter consists of (M-1)/2 H-bridges in which each bridge's dc voltage is supported by its own dc capacitor. The new inverter can: (1) generate almost sinusoidal waveform voltage while only switching one time per fundamental cycle; (2) dispense with multi-pulse inverters' transformers used in conventional utility interfaces and static var compensators; (3) enables direct parallel or series transformer-less connection to medium- and high-voltage power systems. In short, the cascade inverter is much more efficient and suitable for utility applications than traditional multi-pulse and pulse width modulation (PWM) inverters. The authors have experimentally demonstrated the superiority of the new inverter for power supply, (hybrid) electric vehicle (EV) motor drive, reactive power (var) and harmonic compensation. This paper summarizes the features, feasibility, and control schemes of the cascade inverter for utility applications including utility interface of renewable energy, voltage regulation, var compensation, and harmonic filtering in power systems. Analytical, simulated, and experimental results demonstrated the superiority of the new inverters.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h_{L}. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levels ${\\infty}$ >h_{0}>h_{1 }...>h_{L}. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.
Brauer, Fred; Feng, Zhilan; Castillo-Chavez, Carlos
2010-01-01
The mathematical theory of single outbreak epidemic models really began with the work of Kermack and Mackendrick about decades ago. This gave a simple answer to the long-standing question of why epidemics woould appear suddenly and then disappear just as suddenly without having infected an entire population. Therefore it seemed natural to expect that theoreticians would immediately proceed to expand this mathematical framework both because the need to handle recurrent single infectious disease outbreaks has always been a priority for public health officials and because theoreticians often try to push the limits of exiting theories. However, the expansion of the theory via the inclusion of refined epidemiological classifications or through the incorporation of categories that are essential for the evaluation of intervention strategies, in the context of ongoing epidemic outbreaks, did not materialize. It was the global threat posed by SARS in that caused theoreticians to expand the Kermack-McKendrick single-outbreak framework. Most recently, efforts to connect theoretical work to data have exploded as attempts to deal with the threat of emergent and re-emergent diseases including the most recent H1N1 influenza pandemic, have marched to the forefront of our global priorities. Since data are collected and/or reported over discrete units of time, developing single outbreak models that fit collected data naturally is relevant. In this note, we introduce a discrete-epidemic framework and highlight, through our analyses, the similarities between single-outbreak comparable classical continuous-time epidemic models and the discrete-time models introduced in this note. The emphasis is on comparisons driven by expressions for the final epidemic size.
NASA Astrophysics Data System (ADS)
Agaoglou, M.; Charalampidis, E. G.; Ioannidou, T. A.; Kevrekidis, P. G.
2017-09-01
A discrete analogue of the extended Bogomolny-Prasad-Sommerfeld (BPS) Skyrme model that admits time-dependent solutions is presented. Using the spacing h of adjacent lattice nodes as a parameter, we identify the spatial profile of the solution and the continuation of the relevant branch of solutions over the lattice spacing for different values of the potential (free) parameter α . In particular, we explore the dynamics and stability of the obtained solutions, finding that, while they generally seem to be prone to instabilities, for suitable values of the lattice spacing and for sufficiently large values of α , they may be long-lived in direct numerical simulations.
Momentum conservation in Multi-Level Multi-Domain (MLMD) simulations
NASA Astrophysics Data System (ADS)
Innocenti, M. E.; Beck, A.; Markidis, S.; Lapenta, G.
2016-05-01
Momentum conservation and self-forces reduction are challenges for all Particle-In-Cell (PIC) codes using spatial discretization schemes which do not fulfill the requirement of translational invariance of the grid Green's function. We comment here on the topic applied to the recently developed Multi-Level Multi-Domain (MLMD) method. The MLMD is a semi-implicit method for PIC plasma simulations. The multi-scale nature of plasma processes is addressed by using grids with different spatial resolutions in different parts of the domain.
Liu, Xuzhou; Wang, Hehui; Zhou, Zhilai; Jin, Anmin
2014-02-01
The optimal surgical strategy for anterior or posterior approaches remains controversial for multilevel cervical compressive myelopathy caused by multisegment cervical spondylotic myelopathy (MCSM) or ossification of the posterior longitudinal ligament (OPLL). A systematic review and meta-analysis was conducted evaluating the clinical results of anterior decompression and fusion (ADF) compared with posterior laminoplasty for patients with multilevel cervical compressive myelopathy. PubMed, Embase, and the Cochrane Library were searched for randomized controlled trials and nonrandomized cohort studies conducted from 1990 to May 2013 comparing ADF with posterior laminoplasty for the treatment of multilevel cervical compressive myelopathy due to MCSM or OPLL. The following outcome measures were extracted: Japanese Orthopedic Association (JOA) score, recovery rate, complication rate, reoperation rate, blood loss, and operative time. Subgroup analysis was conducted according to the mean number of surgical segments. Eleven studies were included in the review, all of which were prospective or retrospective cohort studies with relatively low quality indicated by GRADE Working Group assessment. A definitive conclusion could not be reached regarding which surgical approach is more effective for the treatment of multilevel cervical compressive myelopathy. Although ADF was associated with better postoperative neural function than posterior laminoplasty in the treatment of multilevel cervical compressive myelopathy due to MCSM or OPLL, there was no apparent difference in the neural function recovery rate between the 2 approaches. Higher rates of surgery-related complication and reoperation should be taken into consideration when ADF is used for patients with multilevel cervical compressive myelopathy. The surgical trauma associated with corpectomy was significantly higher than that associated with posterior laminoplasty.
Optimal estimation for discrete time jump processes
NASA Technical Reports Server (NTRS)
Vaca, M. V.; Tretter, S. A.
1977-01-01
Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.
Optimal estimation for discrete time jump processes
NASA Technical Reports Server (NTRS)
Vaca, M. V.; Tretter, S. A.
1978-01-01
Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.
A Bayesian Multilevel Model for Microcystin Prediction in ...
The frequency of cyanobacteria blooms in North American lakes is increasing. A major concernwith rising cyanobacteria blooms is microcystin, a common cyanobacterial hepatotoxin. Toexplore the conditions that promote high microcystin concentrations, we analyzed the US EPANational Lake Assessment (NLA) dataset collected in the summer of 2007. The NLA datasetis reported for nine eco-regions. We used the results of random forest modeling as a means ofvariable selection from which we developed a Bayesian multilevel model of microcystin concentrations.Model parameters under a multilevel modeling framework are eco-region specific, butthey are also assumed to be exchangeable across eco-regions for broad continental scaling. Theexchangeability assumption ensures that both the common patterns and eco-region specific featureswill be reflected in the model. Furthermore, the method incorporates appropriate estimatesof uncertainty. Our preliminary results show associations between microcystin and turbidity, totalnutrients, and N:P ratios. The NLA 2012 will be used for Bayesian updating. The results willhelp develop management strategies to alleviate microcystin impacts and improve lake quality. This work provides a probabilistic framework for predicting microcystin presences in lakes. It would allow for insights to be made about how changes in nutrient concentrations could potentially change toxin levels.
A Bayesian Multilevel Model for Microcystin Prediction in ...
The frequency of cyanobacteria blooms in North American lakes is increasing. A major concern with rising cyanobacteria blooms is microcystin, a common cyanobacterial hepatotoxin. To explore the conditions that promote high microcystin concentrations, we analyzed the US EPA National Lake Assessment (NLA) dataset collected in the summer of 2007. The NLA dataset is reported for nine eco-regions. We used the results of random forest modeling as a means ofvariable selection from which we developed a Bayesian multilevel model of microcystin concentrations. Model parameters under a multilevel modeling framework are eco-region specific, butthey are also assumed to be exchangeable across eco-regions for broad continental scaling. The exchangeability assumption ensures that both the common patterns and eco-region specific features will be reflected in the model. Furthermore, the method incorporates appropriate estimates of uncertainty. Our preliminary results show associations between microcystin and turbidity, total nutrients, and N:P ratios. Upon release of a comparable 2012 NLA dataset, we will apply Bayesian updating. The results will help develop management strategies to alleviate microcystin impacts and improve lake quality. This work provides a probabilistic framework for predicting microcystin presences in lakes. It would allow for insights to be made about how changes in nutrient concentrations could potentially change toxin levels.
Multilevel Intervention Research: Lessons Learned and Pathways Forward
Taplin, Stephen H.; Foster, Mary K.; Fagan, Pebbles; Kaluzny, Arnold D.
2012-01-01
This summary reflects on this monograph regarding multilevel intervention (MLI) research to 1) assess its added value; 2) discuss what has been learned to date about its challenges in cancer care delivery; and 3) identify specific ways to improve its scientific soundness, feasibility, policy relevance, and research agenda. The 12 submitted chapters, and discussion of them at the March 2011 multilevel meeting, were reviewed and discussed among the authors to elicit key findings and results addressing the questions raised at the outset of this effort. MLI research is underrepresented as an explicit focus in the cancer literature but may improve implementation of studies of cancer care delivery if they assess contextual, organizational, and environmental factors important to understanding behavioral and/or system-level interventions. The field lacks a single unifying theory, although several psychological or biological theories are useful, and an ecological model helps conceptualize and communicate interventions. MLI research designs are often complex, involving nonlinear and nonhierarchical relationships that may not be optimally studied in randomized designs. Simulation modeling and pilot studies may be necessary to evaluate MLI interventions. Measurement and evaluation of team and organizational interventions are especially needed in cancer care, as are attention to the context of health-care reform, eHealth technology, and genomics-based medicine. Future progress in MLI research requires greater attention to developing and supporting relevant metrics of level effects and interactions and evaluating MLI interventions. MLI research holds an unrealized promise for understanding how to improve cancer care delivery. PMID:22623606
Propensity score weighting with multilevel data.
Li, Fan; Zaslavsky, Alan M; Landrum, Mary Beth
2013-08-30
Propensity score methods are being increasingly used as a less parametric alternative to traditional regression to balance observed differences across groups in both descriptive and causal comparisons. Data collected in many disciplines often have analytically relevant multilevel or clustered structure. The propensity score, however, was developed and has been used primarily with unstructured data. We present and compare several propensity-score-weighted estimators for clustered data, including marginal, cluster-weighted, and doubly robust estimators. Using both analytical derivations and Monte Carlo simulations, we illustrate bias arising when the usual assumptions of propensity score analysis do not hold for multilevel data. We show that exploiting the multilevel structure, either parametrically or nonparametrically, in at least one stage of the propensity score analysis can greatly reduce these biases. We applied these methods to a study of racial disparities in breast cancer screening among beneficiaries of Medicare health plans.
Multilevel modelling and public health policy.
Leyland, Alastair H; Groenewegen, Peter P
2003-01-01
Multilevel modelling is a statistical technique that extends ordinary regression analysis to the situation where the data are hierarchical. Such data form an increasingly common evidence base for public health policy, and as such it is important that policy makers should be aware of this methodology. This paper therefore lays out the a basic description of multilevel modelling, discusses the problems of alternative approaches, and details the relevance for public health policy before describing which levels are relevant and illustrating the different kinds of hypotheses that can be tested using multilevel modelling. A series of examples is used throughout the paper. These relate to regional variations in the incidence of heart disease, the allocation of health resources, the relationship between neighbourhood disorder and mental health, the demand-control model in occupational health, and a school intervention to prevent cardiovascular disease.
Multilevel sequential Monte Carlo: Mean square error bounds under verifiable conditions
Del Moral, Pierre; Jasra, Ajay; Law, Kody J. H.
2017-01-09
We consider the multilevel sequential Monte Carlo (MLSMC) method of Beskos et al. (Stoch. Proc. Appl. [to appear]). This technique is designed to approximate expectations w.r.t. probability laws associated to a discretization. For instance, in the context of inverse problems, where one discretizes the solution of a partial differential equation. The MLSMC approach is especially useful when independent, coupled sampling is not possible. Beskos et al. show that for MLSMC the computational effort to achieve a given error, can be less than independent sampling. In this article we significantly weaken the assumptions of Beskos et al., extending the proofs tomore » non-compact state-spaces. The assumptions are based upon multiplicative drift conditions as in Kontoyiannis and Meyn (Electron. J. Probab. 10 [2005]: 61–123). The assumptions are verified for an example.« less
Integrable discrete PT symmetric model.
Ablowitz, Mark J; Musslimani, Ziad H
2014-09-01
An exactly solvable discrete PT invariant nonlinear Schrödinger-like model is introduced. It is an integrable Hamiltonian system that exhibits a nontrivial nonlinear PT symmetry. A discrete one-soliton solution is constructed using a left-right Riemann-Hilbert formulation. It is shown that this pure soliton exhibits unique features such as power oscillations and singularity formation. The proposed model can be viewed as a discretization of a recently obtained integrable nonlocal nonlinear Schrödinger equation.
Discrete spectrum of inflationary fluctuations
Hogan, Craig J.
2004-10-15
It is conjectured that inflation, taking account of quantum gravity, leads to a discrete spectrum of cosmological perturbations, instead of the continuous Gaussian spectrum predicted by standard field theory in an unquantized background. Heuristic models of discrete spectra are discussed, based on an inflaton mode with self-gravity, a lattice of amplitude states, an entangled ensemble of modes, and the holographic or covariant entropy bound. Estimates are given for the discreteness observable in cosmic background anisotropy, galaxy clustering, and gravitational wave backgrounds.
A multilevel preconditioner for domain decomposition boundary systems
Bramble, J.H.; Pasciak, J.E.; Xu, Jinchao.
1991-12-11
In this note, we consider multilevel preconditioning of the reduced boundary systems which arise in non-overlapping domain decomposition methods. It will be shown that the resulting preconditioned systems have condition numbers which be bounded in the case of multilevel spaces on the whole domain and grow at most proportional to the number of levels in the case of multilevel boundary spaces without multilevel extensions into the interior.
Nonintegrable Schrodinger discrete breathers.
Gómez-Gardeñes, J; Floría, L M; Peyrard, M; Bishop, A R
2004-12-01
In an extensive numerical investigation of nonintegrable translational motion of discrete breathers in nonlinear Schrödinger lattices, we have used a regularized Newton algorithm to continue these solutions from the limit of the integrable Ablowitz-Ladik lattice. These solutions are shown to be a superposition of a localized moving core and an excited extended state (background) to which the localized moving pulse is spatially asymptotic. The background is a linear combination of small amplitude nonlinear resonant plane waves and it plays an essential role in the energy balance governing the translational motion of the localized core. Perturbative collective variable theory predictions are critically analyzed in the light of the numerical results.
Discrete bisoliton fiber laser
Liu, X. M.; Han, X. X.; Yao, X. K.
2016-01-01
Dissipative solitons, which result from the intricate balance between dispersion and nonlinearity as well as gain and loss, are of the fundamental scientific interest and numerous important applications. Here, we report a fiber laser that generates bisoliton – two consecutive dissipative solitons that preserve a fixed separation between them. Deviations from this separation result in its restoration. It is also found that these bisolitons have multiple discrete equilibrium distances with the quantized separations, as is confirmed by the theoretical analysis and the experimental observations. The main feature of our laser is the anomalous dispersion that is increased by an order of magnitude in comparison to previous studies. Then the spectral filtering effect plays a significant role in pulse-shaping. The proposed laser has the potential applications in optical communications and high-resolution optics for coding and transmission of information in higher-level modulation formats. PMID:27767075
NASA Astrophysics Data System (ADS)
Noyes, H. Pierre; Starson, Scott
1991-03-01
Discrete physics, because it replaces time evolution generated by the energy operator with a global bit-string generator (program universe) and replaces fields with the relativistic Wheeler-Feynman action at a distance, allows the consistent formulation of the concept of signed gravitational charge for massive particles. The resulting prediction made by this version of the theory is that free anti-particles near the surface of the earth will fall up with the same acceleration that the corresponding particles fall down. So far as we can see, no current experimental information is in conflict with this prediction of our theory. The experiment crusis will be one of the anti-proton or anti-hydrogen experiments at CERN. Our prediction should be much easier to test than the small effects which those experiments are currently designed to detect or bound.
Discrete bisoliton fiber laser
NASA Astrophysics Data System (ADS)
Liu, X. M.; Han, X. X.; Yao, X. K.
2016-10-01
Dissipative solitons, which result from the intricate balance between dispersion and nonlinearity as well as gain and loss, are of the fundamental scientific interest and numerous important applications. Here, we report a fiber laser that generates bisoliton – two consecutive dissipative solitons that preserve a fixed separation between them. Deviations from this separation result in its restoration. It is also found that these bisolitons have multiple discrete equilibrium distances with the quantized separations, as is confirmed by the theoretical analysis and the experimental observations. The main feature of our laser is the anomalous dispersion that is increased by an order of magnitude in comparison to previous studies. Then the spectral filtering effect plays a significant role in pulse-shaping. The proposed laser has the potential applications in optical communications and high-resolution optics for coding and transmission of information in higher-level modulation formats.
Steerable Discrete Cosine Transform
NASA Astrophysics Data System (ADS)
Fracastoro, Giulia; Fosson, Sophie M.; Magli, Enrico
2017-01-01
In image compression, classical block-based separable transforms tend to be inefficient when image blocks contain arbitrarily shaped discontinuities. For this reason, transforms incorporating directional information are an appealing alternative. In this paper, we propose a new approach to this problem, namely a discrete cosine transform (DCT) that can be steered in any chosen direction. Such transform, called steerable DCT (SDCT), allows to rotate in a flexible way pairs of basis vectors, and enables precise matching of directionality in each image block, achieving improved coding efficiency. The optimal rotation angles for SDCT can be represented as solution of a suitable rate-distortion (RD) problem. We propose iterative methods to search such solution, and we develop a fully fledged image encoder to practically compare our techniques with other competing transforms. Analytical and numerical results prove that SDCT outperforms both DCT and state-of-the-art directional transforms.
Steerable Discrete Cosine Transform.
Fracastoro, Giulia; Fosson, Sophie M; Magli, Enrico
2017-01-01
In image compression, classical block-based separable transforms tend to be inefficient when image blocks contain arbitrarily shaped discontinuities. For this reason, transforms incorporating directional information are an appealing alternative. In this paper, we propose a new approach to this problem, namely, a discrete cosine transform (DCT) that can be steered in any chosen direction. Such transform, called steerable DCT (SDCT), allows to rotate in a flexible way pairs of basis vectors, and enables precise matching of directionality in each image block, achieving improved coding efficiency. The optimal rotation angles for SDCT can be represented as solution of a suitable rate-distortion (RD) problem. We propose iterative methods to search such solution, and we develop a fully fledged image encoder to practically compare our techniques with other competing transforms. Analytical and numerical results prove that SDCT outperforms both DCT and state-of-the-art directional transforms.
Noyes, H.P. ); Starson, S. )
1991-03-01
Discrete physics, because it replaces time evolution generated by the energy operator with a global bit-string generator (program universe) and replaces fields'' with the relativistic Wheeler-Feynman action at a distance,'' allows the consistent formulation of the concept of signed gravitational charge for massive particles. The resulting prediction made by this version of the theory is that free anti-particles near the surface of the earth will fall'' up with the same acceleration that the corresponding particles fall down. So far as we can see, no current experimental information is in conflict with this prediction of our theory. The experiment crusis will be one of the anti-proton or anti-hydrogen experiments at CERN. Our prediction should be much easier to test than the small effects which those experiments are currently designed to detect or bound. 23 refs.
Discrete Pearson distributions
Bowman, K.O.; Shenton, L.R.; Kastenbaum, M.A.
1991-11-01
These distributions are generated by a first order recursive scheme which equates the ratio of successive probabilities to the ratio of two corresponding quadratics. The use of a linearized form of this model will produce equations in the unknowns matched by an appropriate set of moments (assumed to exist). Given the moments we may find valid solutions. These are two cases; (1) distributions defined on the non-negative integers (finite or infinite) and (2) distributions defined on negative integers as well. For (1), given the first four moments, it is possible to set this up as equations of finite or infinite degree in the probability of a zero occurrence, the sth component being a product of s ratios of linear forms in this probability in general. For (2) the equation for the zero probability is purely linear but may involve slowly converging series; here a particular case is the discrete normal. Regions of validity are being studied. 11 refs.
Discrete Reliability Projection
2014-12-01
Defense, Handbook MIL - HDBK -189C, 2011 Hall, J. B., Methodology for Evaluating Reliability Growth Programs of Discrete Systems, Ph.D. thesis, University...pk,i ] · [ 1− (1− θ̆k) · ( N k · T )]k−m , (2.13) 5 2 Hall’s Model where m is the number of observed failure modes and d∗i estimates di (either based...Mode Failures FEF Ni d ∗ i 1 1 0.95 2 1 0.70 3 1 0.90 4 1 0.90 5 4 0.95 6 2 0.70 7 1 0.80 Using equations 2.1 and 2.2 we can calculate the failure
Immigration and Prosecutorial Discretion.
Apollonio, Dorie; Lochner, Todd; Heddens, Myriah
Immigration has become an increasingly salient national issue in the US, and the Department of Justice recently increased federal efforts to prosecute immigration offenses. This shift, however, relies on the cooperation of US attorneys and their assistants. Traditionally federal prosecutors have enjoyed enormous discretion and have been responsive to local concerns. To consider how the centralized goal of immigration enforcement may have influenced federal prosecutors in regional offices, we review their prosecution of immigration offenses in California using over a decade's worth of data. Our findings suggest that although centralizing forces influence immigration prosecutions, individual US attorneys' offices retain distinct characteristics. Local factors influence federal prosecutors' behavior in different ways depending on the office. Contrary to expectations, unemployment rates did not affect prosecutors' willingness to pursue immigration offenses, nor did local popular opinion about illegal immigration.
Discrete Minimal Surface Algebras
NASA Astrophysics Data System (ADS)
Arnlind, Joakim; Hoppe, Jens
2010-05-01
We consider discrete minimal surface algebras (DMSA) as generalized noncommutative analogues of minimal surfaces in higher dimensional spheres. These algebras appear naturally in membrane theory, where sequences of their representations are used as a regularization. After showing that the defining relations of the algebra are consistent, and that one can compute a basis of the enveloping algebra, we give several explicit examples of DMSAs in terms of subsets of sln (any semi-simple Lie algebra providing a trivial example by itself). A special class of DMSAs are Yang-Mills algebras. The representation graph is introduced to study representations of DMSAs of dimension d ≤ 4, and properties of representations are related to properties of graphs. The representation graph of a tensor product is (generically) the Cartesian product of the corresponding graphs. We provide explicit examples of irreducible representations and, for coinciding eigenvalues, classify all the unitary representations of the corresponding algebras.
Immigration and Prosecutorial Discretion
Apollonio, Dorie; Lochner, Todd; Heddens, Myriah
2015-01-01
Immigration has become an increasingly salient national issue in the US, and the Department of Justice recently increased federal efforts to prosecute immigration offenses. This shift, however, relies on the cooperation of US attorneys and their assistants. Traditionally federal prosecutors have enjoyed enormous discretion and have been responsive to local concerns. To consider how the centralized goal of immigration enforcement may have influenced federal prosecutors in regional offices, we review their prosecution of immigration offenses in California using over a decade's worth of data. Our findings suggest that although centralizing forces influence immigration prosecutions, individual US attorneys' offices retain distinct characteristics. Local factors influence federal prosecutors' behavior in different ways depending on the office. Contrary to expectations, unemployment rates did not affect prosecutors' willingness to pursue immigration offenses, nor did local popular opinion about illegal immigration. PMID:26146530
Thermodynamics of discrete quantum processes
NASA Astrophysics Data System (ADS)
Anders, Janet; Giovannetti, Vittorio
2013-03-01
We define thermodynamic configurations and identify two primitives of discrete quantum processes between configurations for which heat and work can be defined in a natural way. This allows us to uncover a general second law for any discrete trajectory that consists of a sequence of these primitives, linking both equilibrium and non-equilibrium configurations. Moreover, in the limit of a discrete trajectory that passes through an infinite number of configurations, i.e. in the reversible limit, we recover the saturation of the second law. Finally, we show that for a discrete Carnot cycle operating between four configurations one recovers Carnot's thermal efficiency.
Discrete Pathophysiology is Uncommon in Patients with Nonspecific Arm Pain
Kortlever, Joost T.P.; Janssen, Stein J.; Molleman, Jeroen; Hageman, Michiel G.J.S.; Ring, David
2016-01-01
Background: Nonspecific symptoms are common in all areas of medicine. Patients and caregivers can be frustrated when an illness cannot be reduced to a discrete pathophysiological process that corresponds with the symptoms. We therefore asked the following questions: 1) Which demographic factors and psychological comorbidities are associated with change from an initial diagnosis of nonspecific arm pain to eventual identification of discrete pathophysiology that corresponds with symptoms? 2) What is the percentage of patients eventually diagnosed with discrete pathophysiology, what are those pathologies, and do they account for the symptoms? Methods: We evaluated 634 patients with an isolated diagnosis of nonspecific upper extremity pain to see if discrete pathophysiology was diagnosed on subsequent visits to the same hand surgeon, a different hand surgeon, or any physician within our health system for the same pain. Results: There were too few patients with discrete pathophysiology at follow-up to address the primary study question. Definite discrete pathophysiology that corresponded with the symptoms was identified in subsequent evaluations by the index surgeon in one patient (0.16% of all patients) and cured with surgery (nodular fasciitis). Subsequent doctors identified possible discrete pathophysiology in one patient and speculative pathophysiology in four patients and the index surgeon identified possible discrete pathophysiology in four patients, but the five discrete diagnoses accounted for only a fraction of the symptoms. Conclusion: Nonspecific diagnoses are not harmful. Prospective randomized research is merited to determine if nonspecific, descriptive diagnoses are better for patients than specific diagnoses that imply pathophysiology in the absence of discrete verifiable pathophysiology. PMID:27517064
Dynamical Localization for Discrete Anderson Dirac Operators
NASA Astrophysics Data System (ADS)
Prado, Roberto A.; de Oliveira, César R.; Carvalho, Silas L.
2017-04-01
We establish dynamical localization for random Dirac operators on the d-dimensional lattice, with d\\in { 1, 2, 3} , in the three usual regimes: large disorder, band edge and 1D. These operators are discrete versions of the continuous Dirac operators and consist in the sum of a discrete free Dirac operator with a random potential. The potential is a diagonal matrix formed by different scalar potentials, which are sequences of independent and identically distributed random variables according to an absolutely continuous probability measure with bounded density and of compact support. We prove the exponential decay of fractional moments of the Green function for such models in each of the above regimes, i.e., (j) throughout the spectrum at larger disorder, (jj) for energies near the band edges at arbitrary disorder and (jjj) in dimension one, for all energies in the spectrum and arbitrary disorder. Dynamical localization in theses regimes follows from the fractional moments method. The result in the one-dimensional regime contrast with one that was previously obtained for 1D Dirac model with Bernoulli potential.
Hypernetworks: Multidimensional relationships in multilevel systems
NASA Astrophysics Data System (ADS)
Johnson, J. H.
2016-09-01
Networks provide a powerful way of modelling the dynamics of complex systems. Going beyond binary relations, embracing n-ary relations in network science can generalise many structures. This starts with hypergraphs and their Galois structures. Simplicial complexes generalise hypergraphs by adding orientation. Their multidimensional q-connectivity structure generalises connectivity in networks. Hypersimplices generalise simplices by making the relational structure explicit in the notation. This gives a new way of representing multilevel systems and their dynamics, leading to a new fragment-recombine operator to model the complex dynamics of interacting multilevel systems.
Overcoming erasure errors with multilevel systems
NASA Astrophysics Data System (ADS)
Muralidharan, Sreraman; Zou, Chang-Ling; Li, Linshu; Wen, Jianming; Jiang, Liang
2017-01-01
We investigate the usage of highly efficient error correcting codes of multilevel systems to protect encoded quantum information from erasure errors and implementation to repetitively correct these errors. Our scheme makes use of quantum polynomial codes to encode quantum information and generalizes teleportation based error correction for multilevel systems to correct photon losses and operation errors in a fault-tolerant manner. We discuss the application of quantum polynomial codes to one-way quantum repeaters. For various types of operation errors, we identify different parameter regions where quantum polynomial codes can achieve a superior performance compared to qubit based quantum parity codes.
Multilevel transport solution of LWR reactor cores
Jose Ignacio Marquez Damian; Cassiano R.E. de Oliveira; HyeonKae Park
2008-09-01
This work presents a multilevel approach for the solution of the transport equation in typical LWR assemblies and core configurations. It is based on the second-order, even-parity formulation of the transport equation, which is solved within the framework provided by the finite element-spherical harmonics code EVENT. The performance of the new solver has been compared with that of the standard conjugate gradient solver for diffusion and transport problems on structured and unstruc-tured grids. Numerical results demonstrate the potential of the multilevel scheme for realistic reactor calculations.
The effects of weather on daily mood: a multilevel approach.
Denissen, Jaap J A; Butalid, Ligaya; Penke, Lars; van Aken, Marcel A G
2008-10-01
The present study examines the effects of six weather parameters (temperature, wind power, sunlight, precipitation, air pressure, and photoperiod) on mood (positive affect, negative affect, and tiredness). Data were gathered from an online diary study (N = 1,233), linked to weather station data, and analyzed by means of multilevel analysis. Multivariate and univariate analyses enabled distinction between unique and shared effects. The results revealed main effects of temperature, wind power, and sunlight on negative affect. Sunlight had a main effect on tiredness and mediated the effects of precipitation and air pressure on tiredness. In terms of explained variance, however, the average effect of weather on mood was only small, though significant random variation was found across individuals, especially regarding the effect of photoperiod. However, these individual differences in weather sensitivity could not be explained by the Five Factor Model personality traits, gender, or age.
Testing mediation effects in cross-classified multilevel data.
Luo, Wen
2017-04-01
In this article, we propose an approach to test mediation effects in cross-classified multilevel data in which the initial cause is associated with one crossed factor, the mediator is associated with the other crossed factor, and the outcome is associated with Level-1 units (i.e., the 2((A))➔2((B))➔1 design). Multiple-membership models and cross-classified random effects models are used to estimate the indirect effects. The method is illustrated using real data from the Early Childhood Longitudinal Study-Kindergarten Cohort (1998). The results from the simulation study show that the proposed method can produce a consistent estimate of the indirect effect and reliable statistical inferences, given an adequate sample size.
Biases in multilevel analyses caused by cluster-specific fixed-effects imputation.
Speidel, Matthias; Drechsler, Jörg; Sakshaug, Joseph W
2017-08-24
When datasets are affected by nonresponse, imputation of the missing values is a viable solution. However, most imputation routines implemented in commonly used statistical software packages do not accommodate multilevel models that are popular in education research and other settings involving clustering of units. A common strategy to take the hierarchical structure of the data into account is to include cluster-specific fixed effects in the imputation model. Still, this ad hoc approach has never been compared analytically to the congenial multilevel imputation in a random slopes setting. In this paper, we evaluate the impact of the cluster-specific fixed-effects imputation model on multilevel inference. We show analytically that the cluster-specific fixed-effects imputation strategy will generally bias inferences obtained from random coefficient models. The bias of random-effects variances and global fixed-effects confidence intervals depends on the cluster size, the relation of within- and between-cluster variance, and the missing data mechanism. We illustrate the negative implications of cluster-specific fixed-effects imputation using simulation studies and an application based on data from the National Educational Panel Study (NEPS) in Germany.
Incorporating Mobility in Growth Modeling for Multilevel and Longitudinal Item Response Data.
Choi, In-Hee; Wilson, Mark
2016-01-01
Multilevel data often cannot be represented by the strict form of hierarchy typically assumed in multilevel modeling. A common example is the case in which subjects change their group membership in longitudinal studies (e.g., students transfer schools; employees transition between different departments). In this study, cross-classified and multiple membership models for multilevel and longitudinal item response data (CCMM-MLIRD) are developed to incorporate such mobility, focusing on students' school change in large-scale longitudinal studies. Furthermore, we investigate the effect of incorrectly modeling school membership in the analysis of multilevel and longitudinal item response data. Two types of school mobility are described, and corresponding models are specified. Results of the simulation studies suggested that appropriate modeling of the two types of school mobility using the CCMM-MLIRD yielded good recovery of the parameters and improvement over models that did not incorporate mobility properly. In addition, the consequences of incorrectly modeling the school effects on the variance estimates of the random effects and the standard errors of the fixed effects depended upon mobility patterns and model specifications. Two sets of large-scale longitudinal data are analyzed to illustrate applications of the CCMM-MLIRD for each type of school mobility.
Li, Baoyue; Bruyneel, Luk; Lesaffre, Emmanuel
2014-05-20
A traditional Gaussian hierarchical model assumes a nested multilevel structure for the mean and a constant variance at each level. We propose a Bayesian multivariate multilevel factor model that assumes a multilevel structure for both the mean and the covariance matrix. That is, in addition to a multilevel structure for the mean we also assume that the covariance matrix depends on covariates and random effects. This allows to explore whether the covariance structure depends on the values of the higher levels and as such models heterogeneity in the variances and correlation structure of the multivariate outcome across the higher level values. The approach is applied to the three-dimensional vector of burnout measurements collected on nurses in a large European study to answer the research question whether the covariance matrix of the outcomes depends on recorded system-level features in the organization of nursing care, but also on not-recorded factors that vary with countries, hospitals, and nursing units. Simulations illustrate the performance of our modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.
Discrete Mathematics and Its Applications
ERIC Educational Resources Information Center
Oxley, Alan
2010-01-01
The article gives ideas that lecturers of undergraduate Discrete Mathematics courses can use in order to make the subject more interesting for students and encourage them to undertake further studies in the subject. It is possible to teach Discrete Mathematics with little or no reference to computing. However, students are more likely to be…
Discrete Mathematics and Its Applications
ERIC Educational Resources Information Center
Oxley, Alan
2010-01-01
The article gives ideas that lecturers of undergraduate Discrete Mathematics courses can use in order to make the subject more interesting for students and encourage them to undertake further studies in the subject. It is possible to teach Discrete Mathematics with little or no reference to computing. However, students are more likely to be…
NASA Astrophysics Data System (ADS)
Lin, Paul T.; Shadid, John N.; Sala, Marzio; Tuminaro, Raymond S.; Hennigan, Gary L.; Hoekstra, Robert J.
2009-09-01
In this study results are presented for the large-scale parallel performance of an algebraic multilevel preconditioner for solution of the drift-diffusion model for semiconductor devices. The preconditioner is the key numerical procedure determining the robustness, efficiency and scalability of the fully-coupled Newton-Krylov based, nonlinear solution method that is employed for this system of equations. The coupled system is comprised of a source term dominated Poisson equation for the electric potential, and two convection-diffusion-reaction type equations for the electron and hole concentration. The governing PDEs are discretized in space by a stabilized finite element method. Solution of the discrete system is obtained through a fully-implicit time integrator, a fully-coupled Newton-based nonlinear solver, and a restarted GMRES Krylov linear system solver. The algebraic multilevel preconditioner is based on an aggressive coarsening graph partitioning of the nonzero block structure of the Jacobian matrix. Representative performance results are presented for various choices of multigrid V-cycles and W-cycles and parameter variations for smoothers based on incomplete factorizations. Parallel scalability results are presented for solution of up to 108 unknowns on 4096 processors of a Cray XT3/4 and an IBM POWER eServer system.
1992-01-01
interesting a research issue. An algorithm for this case, using a multiversion technique, will be the subject of future work. In addition, there is a...34 Multiversion Concurrency Control for Multilevel Secure Database Systems" in Proceedings of the IEEE Symposium on Security and Privacy, pp. 369-383...Oakland, CA May 1990. 7. William T. Maimone and Ira B. Greenberg, "Single-Level Multiversion Schedulers for Multilevel Secure Database Systems" in
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Efficiently Exploring Multilevel Data with Recursive Partitioning
ERIC Educational Resources Information Center
Martin, Daniel P.; von Oertzen, Timo; Rimm-Kaufman, Sara E.
2015-01-01
There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…
Single-Level and Multilevel Mediation Analysis
ERIC Educational Resources Information Center
Tofighi, Davood; Thoemmes, Felix
2014-01-01
Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…
Differential Item Functioning from a Multilevel Perspective.
ERIC Educational Resources Information Center
van den Bergh, Huub; And Others
The term differential item functioning (DIF) refers to whether or not the same psychological constructs are measured across different groups. If an item does not measure the same skills or subskills in different populations, it is said to function differentially or to display item bias. A multilevel approach to DIF is proposed. In such a model,…
Using Multilevel Modeling in Counseling Research
ERIC Educational Resources Information Center
Lynch, Martin F.
2012-01-01
This conceptual and practical overview of multilevel modeling (MLM) for researchers in counseling and development provides guidelines on setting up SPSS to perform MLM and an example of how to present the findings. It also provides a discussion on how counseling and developmental researchers can use MLM to address their own research questions.…
New multilevel codes over GF(q)
NASA Technical Reports Server (NTRS)
Wu, Jiantian; Costello, Daniel J., Jr.
1992-01-01
Set partitioning to multi-dimensional signal spaces over GF(q), particularly GF sup q-1(q) and GF sup q (q), and show how to construct both multi-level block codes and multi-level trellis codes over GF(q). Two classes of multi-level (n, k, d) block codes over GF(q) with block length n, number of information symbols k, and minimum distance d sub min greater than or = d, are presented. These two classes of codes use Reed-Solomon codes as component codes. They can be easily decoded as block length q-1 Reed-Solomon codes or block length q or q + 1 extended Reed-Solomon codes using multi-stage decoding. Many of these codes have larger distances than comparable q-ary block codes, as component codes. Low rate q-ary convolutional codes, work error correcting convolutional codes, and binary-to-q-ary convolutional codes can also be used to construct multi-level trellis codes over GF(q) or binary-to-q-ary trellis codes, some of which have better performance than the above block codes. All of the new codes have simple decoding algorithms based on hard decision multi-stage decoding.
A Practical Guide to Multilevel Modeling
ERIC Educational Resources Information Center
Peugh, James L.
2010-01-01
Collecting data from students within classrooms or schools, and collecting data from students on multiple occasions over time, are two common sampling methods used in educational research that often require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps…
The Economic Cost of Homosexuality: Multilevel Analyses
ERIC Educational Resources Information Center
Baumle, Amanda K.; Poston, Dudley, Jr.
2011-01-01
This article builds on earlier studies that have examined "the economic cost of homosexuality," by using data from the 2000 U.S. Census and by employing multilevel analyses. Our findings indicate that partnered gay men experience a 12.5 percent earnings penalty compared to married heterosexual men, and a statistically insignificant earnings…
The Economic Cost of Homosexuality: Multilevel Analyses
ERIC Educational Resources Information Center
Baumle, Amanda K.; Poston, Dudley, Jr.
2011-01-01
This article builds on earlier studies that have examined "the economic cost of homosexuality," by using data from the 2000 U.S. Census and by employing multilevel analyses. Our findings indicate that partnered gay men experience a 12.5 percent earnings penalty compared to married heterosexual men, and a statistically insignificant earnings…
Single-Level and Multilevel Mediation Analysis
ERIC Educational Resources Information Center
Tofighi, Davood; Thoemmes, Felix
2014-01-01
Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1988-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Multilevel soil-vapor extraction test for heterogeneous soil
Widdowson, M.A.; Haney, O.R.; Reeves, H.W.; Aelion, C.M.; Ray, R.P.
1997-02-01
The design, performance, and analysis of a field method for quantifying contaminant mass-extraction rates and air-phase permeability at discrete vertical locations of the vadose zones are presented. The test configuration consists of a multiscreen extraction well and multilevel observation probes located in soil layers adjacent to the extraction well. For each level tested an inflatable packer system is used to pneumatically isolate a single screen in the extraction well, and a vacuum is applied to induce air flow through the screen. Test data include contaminant concentration and flow characteristics at the extraction well, and transient or steady-state pressure drawdown data at observation probes located at variable radii from the extraction well. The test method is applicable to the design of soil-vapor extraction (SVE) and bioventing remediation systems in a variety of geologic settings, particularly stratified soils. Application of the test method at a gasoline-polluted site located in the Piedmont physiographic region is described. Contaminant mass-extraction rates, expressed in terms of volatile hydrocarbons, varied from 0.16 to 14 kg/d.
National INFOSEC technical baseline: multi-level secure systems
Anderson, J P
1998-09-28
The purpose of this report is to provide a baseline description of the state of multilevel processor/processing to the INFOSEC Research Council and at their discretion to the R&D community at large. From the information in the report, it is hoped that the members of the IRC will be aware of gaps in MLS research. A primary purpose is to bring IRC and the research community members up to date on what is happening in the MLS arena. The review will attempt to cover what MLS products are still available, and to identify companies who still offer MLS products. We have also attempted to identify requirements for MLS by interviewing senior officers of the Intelligence community as well as those elements of DoD and DOE who are or may be interested in procuring MLS products for various applications. The balance of the report consists of the following sections; a background review of the highlights of the developments of MLS, a quick summary of where we are today in terms of products, installations, and companies who are still in the business of supplying MLS systems [or who are developing MLS system], the requirements as expressed by senior members of the Intelligence community and DoD and DOE, issues and unmet R&D challenges surrounding MLS, and finally a set of recommended research topics.
NASA Technical Reports Server (NTRS)
1986-01-01
This false-color Voyager picture of Uranus shows a discrete cloud seen as a bright streak near the planet's limb. The picture is a highly processed composite of three images obtained Jan. 14, 1986, when the spacecraft was 12.9 million kilometers (8.0 million miles) from the planet. The cloud visible here is the most prominent feature seen in a series of Voyager images designed to track atmospheric motions. (The occasional donut-shaped features, including one at the bottom, are shadows cast by dust in the camera optics; the processing necessary to bring out the faint features on the planet also brings out these camera blemishes.) Three separate images were shuttered through violet, blue and orange filters. Each color image showed the cloud to a different degree; because they were not exposed at exactly the same time, the images were processed to provide a correction for a good spatial match. In a true-color image, the cloud would be barely discernible; the false color helps bring out additional details. The different colors imply variations in vertical structure, but as yet is not possible to be specific about such differences. One possibility is that the Uranian atmosphere contains smog-like constituents, in which case some color differences may represent differences in how these molecules are distributed. The Voyager project is managed for NASA by the Jet Propulsion Laboratory.
Xu, Hongwei; Logan, John R.; Short, Susan E.
2014-01-01
Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. In ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this paper, we propose an integrated multilevel-spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel-spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially-defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results did not vary by specific definitions of egocentric neighborhoods, they were sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial-multilevel approach enhances our ability to disentangle the effect of space from that of place, and point to the need for more careful spatial thinking in population research on neighborhoods and health. PMID:24763980
Rumor Processes on and Discrete Renewal Processes
NASA Astrophysics Data System (ADS)
Gallo, Sandro; Garcia, Nancy L.; Junior, Valdivino Vargas; Rodríguez, Pablo M.
2014-05-01
We study two rumor processes on , the dynamics of which are related to an SI epidemic model with long range transmission. Both models start with one spreader at site and ignorants at all the other sites of , but differ by the transmission mechanism. In one model, the spreaders transmit the information within a random distance on their right, and in the other the ignorants take the information from a spreader within a random distance on their left. We obtain the probability of survival, information on the distribution of the range of the rumor and limit theorems for the proportion of spreaders. The key step of our proofs is to show that, in each model, the position of the spreaders on can be related to a suitably chosen discrete renewal process.
Space-time adaptive solution of inverse problems with the discrete adjoint method
NASA Astrophysics Data System (ADS)
Alexe, Mihai; Sandu, Adrian
2014-08-01
This paper develops a framework for the construction and analysis of discrete adjoint sensitivities in the context of time dependent, adaptive grid, adaptive step models. Discrete adjoints are attractive in practice since they can be generated with low effort using automatic differentiation. However, this approach brings several important challenges. The space-time adjoint of the forward numerical scheme may be inconsistent with the continuous adjoint equations. A reduction in accuracy of the discrete adjoint sensitivities may appear due to the inter-grid transfer operators. Moreover, the optimization algorithm may need to accommodate state and gradient vectors whose dimensions change between iterations. This work shows that several of these potential issues can be avoided through a multi-level optimization strategy using discontinuous Galerkin (DG) hp-adaptive discretizations paired with Runge-Kutta (RK) time integration. We extend the concept of dual (adjoint) consistency to space-time RK-DG discretizations, which are then shown to be well suited for the adaptive solution of time-dependent inverse problems. Furthermore, we prove that DG mesh transfer operators on general meshes are also dual consistent. This allows the simultaneous derivation of the discrete adjoint for both the numerical solver and the mesh transfer logic with an automatic code generation mechanism such as algorithmic differentiation (AD), potentially speeding up development of large-scale simulation codes. The theoretical analysis is supported by numerical results reported for a two-dimensional non-stationary inverse problem.
Analysis of stochastic effects in Kaldor-type business cycle discrete model
NASA Astrophysics Data System (ADS)
Bashkirtseva, Irina; Ryashko, Lev; Sysolyatina, Anna
2016-07-01
We study nonlinear stochastic phenomena in the discrete Kaldor model of business cycles. A numerical parametric analysis of stochastically forced attractors (equilibria, closed invariant curves, discrete cycles) of this model is performed using the stochastic sensitivity functions technique. A spatial arrangement of random states in stochastic attractors is modeled by confidence domains. The phenomenon of noise-induced transitions ;chaos-order; is discussed.
Single event multilevel botulinum toxin type A treatment and surgery: similarities and differences.
Molenaers, G; Desloovere, K; De Cat, J; Jonkers, I; De Borre, L; Pauwels, P; Nijs, J; Fabry, G; De Cock, P
2001-11-01
The present study attempts to provide objective evidence of two treatment options for children with cerebral palsy (CP): multilevel botulinum toxin type A (BTX-A) injections and multilevel surgery. The purpose of the study was to clarify the differences and the similarities, and common treatment principles of both treatment strategies. Objective three dimensional gait analysis data were studied retrospectively in two patient groups pre- and post-treatment (randomly selected from a group of children that were treated between 1998 and 1999). In the first group, 29 children with CP were managed with BTX-A injections according to an integrated multilevel approach (Molenaers et al., 1999a). A second group of 23 children with CP were managed by a more traditional single event multilevel surgery, also according to an integrated approach. Our aim was to evaluate the differences as well as the similarities between both patient groups, using a set of 56 parameters selected from three-dimensional gait analysis. The unifying concept between management with BTX-A injections and orthopaedic surgery was the adoption of a multilevel approach at one session. The groups demonstrated considerable differences with respect to age, pretreatment condition and amount and level of improvement after treatment. The children who received BTX-A were typically younger, and showed primary gait problems in the distal joints, whereas the children who underwent surgery demonstrated a higher frequency of gait deviations in the transverse plane and had more complications. Although the benefit of both treatments was confirmed by the present study, a difference in the amount and level of improvement was also demonstrated. In conclusion, these treatment modalities should be regarded as complementary rather than mutually exclusive treatments, with both calling for an integrated approach.
Multilevel method for modeling large-scale networks.
Safro, I. M.
2012-02-24
Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from
Students' Misconceptions about Random Variables
ERIC Educational Resources Information Center
Kachapova, Farida; Kachapov, Ilias
2012-01-01
This article describes some misconceptions about random variables and related counter-examples, and makes suggestions about teaching initial topics on random variables in general form instead of doing it separately for discrete and continuous cases. The focus is on post-calculus probability courses. (Contains 2 figures.)
Wagner, Philippe; Merlo, Juan
2016-01-01
Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster‐specific random effects which allow one to partition the total individual variance into between‐cluster variation and between‐individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time‐to‐event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., ‘frailty’) Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:27885709
Austin, Peter C; Wagner, Philippe; Merlo, Juan
2017-03-15
Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Schuurman, N K; Grasman, R P P P; Hamaker, E L
2016-01-01
Multilevel autoregressive models are especially suited for modeling between-person differences in within-person processes. Fitting these models with Bayesian techniques requires the specification of prior distributions for all parameters. Often it is desirable to specify prior distributions that have negligible effects on the resulting parameter estimates. However, the conjugate prior distribution for covariance matrices-the Inverse-Wishart distribution-tends to be informative when variances are close to zero. This is problematic for multilevel autoregressive models, because autoregressive parameters are usually small for each individual, so that the variance of these parameters will be small. We performed a simulation study to compare the performance of three Inverse-Wishart prior specifications suggested in the literature, when one or more variances for the random effects in the multilevel autoregressive model are small. Our results show that the prior specification that uses plug-in ML estimates of the variances performs best. We advise to always include a sensitivity analysis for the prior specification for covariance matrices of random parameters, especially in autoregressive models, and to include a data-based prior specification in this analysis. We illustrate such an analysis by means of an empirical application on repeated measures data on worrying and positive affect.
Microscopic derivation of discrete hydrodynamics.
Español, Pep; Anero, Jesús G; Zúñiga, Ignacio
2009-12-28
By using the standard theory of coarse graining based on Zwanzig's projection operator, we derive the dynamic equations for discrete hydrodynamic variables. These hydrodynamic variables are defined in terms of the Delaunay triangulation. The resulting microscopically derived equations can be understood, a posteriori, as a discretization on an arbitrary irregular grid of the Navier-Stokes equations. The microscopic derivation provides a set of discrete equations that exactly conserves mass, momentum, and energy and the dissipative part of the dynamics produces strict entropy increase. In addition, the microscopic derivation provides a practical implementation of thermal fluctuations in a way that the fluctuation-dissipation theorem is satisfied exactly. This paper points toward a close connection between coarse-graining procedures from microscopic dynamics and discretization schemes for partial differential equations.
Chaos in Periodic Discrete Systems
NASA Astrophysics Data System (ADS)
Shi, Yuming; Zhang, Lijuan; Yu, Panpan; Huang, Qiuling
This paper focuses on chaos in periodic discrete systems, whose state space may vary with time. Some close relationships between some chaotic dynamical behaviors of a periodic discrete system and its autonomous induced system are given. Based on these relationships, several criteria of chaos are established and some sufficient conditions for no chaos are given for periodic discrete systems. Further, it is shown that a finite-dimensional linear periodic discrete system is not chaotic in the sense of Li-Yorke or Wiggins. In particular, an interesting problem of whether nonchaotic rules may generate a chaotic system is studied, with some examples provided, one of which surprisingly shows that a composition of globally asymptotically stable maps can be chaotic. In addition, some properties of sign pattern matrices of non-negative square matrices are given for convenience of the study.
Discrete solitons in graphene metamaterials
NASA Astrophysics Data System (ADS)
Bludov, Yu. V.; Smirnova, D. A.; Kivshar, Yu. S.; Peres, N. M. R.; Vasilevskiy, M. I.
2015-01-01
We study nonlinear properties of multilayer metamaterials created by graphene sheets separated by dielectric layers. We demonstrate that such structures can support localized nonlinear modes described by the discrete nonlinear Schrödinger equation and that its solutions are associated with stable discrete plasmon solitons. We also analyze the nonlinear surface modes in truncated graphene metamaterials being a nonlinear analog of surface Tamm states.
Concurrency and discrete event control
NASA Technical Reports Server (NTRS)
Heymann, Michael
1990-01-01
Much of discrete event control theory has been developed within the framework of automata and formal languages. An alternative approach inspired by the theories of process-algebra as developed in the computer science literature is presented. The framework, which rests on a new formalism of concurrency, can adequately handle nondeterminism and can be used for analysis of a wide range of discrete event phenomena.
2015-01-01
A step toward the development of optimally effective, efficient, and feasible implementation strategies that increase evidence-based treatment integration in mental health services involves identification of the multilevel mechanisms through which these strategies influence implementation outcomes. This article (a) provides an orientation to, and rationale for, consideration of multilevel mediating mechanisms in implementation trials, and (b) systematically reviews randomized controlled trials that examined mediators of implementation strategies in mental health. Nine trials were located. Mediation-related methodological deficiencies were prevalent and no trials supported a hypothesized mediator. The most common reason was failure to engage the mediation target. Discussion focuses on directions to accelerate implementation strategy development in mental health. PMID:26474761
Voltage balanced multilevel voltage source converter system
Peng, F.Z.; Lai, J.S.
1997-07-01
Disclosed is a voltage balanced multilevel converter for high power AC applications such as adjustable speed motor drives and back-to-back DC intertie of adjacent power systems. This converter provides a multilevel rectifier, a multilevel inverter, and a DC link between the rectifier and the inverter allowing voltage balancing between each of the voltage levels within the multilevel converter. The rectifier is equipped with at least one phase leg and a source input node for each of the phases. The rectifier is further equipped with a plurality of rectifier DC output nodes. The inverter is equipped with at least one phase leg and a load output node for each of the phases. The inverter is further equipped with a plurality of inverter DC input nodes. The DC link is equipped with a plurality of rectifier charging means and a plurality of inverter discharging means. The plurality of rectifier charging means are connected in series with one of the rectifier charging means disposed between and connected in an operable relationship with each adjacent pair of rectifier DC output nodes. The plurality of inverter discharging means are connected in series with one of the inverter discharging means disposed between and connected in an operable relationship with each adjacent pair of inverter DC input nodes. Each of said rectifier DC output nodes are individually electrically connected to the respective inverter DC input nodes. By this means, each of the rectifier DC output nodes and each of the inverter DC input nodes are voltage balanced by the respective charging and discharging of the rectifier charging means and the inverter discharging means. 15 figs.
Voltage balanced multilevel voltage source converter system
Peng, Fang Zheng; Lai, Jih-Sheng
1997-01-01
A voltage balanced multilevel converter for high power AC applications such as adjustable speed motor drives and back-to-back DC intertie of adjacent power systems. This converter provides a multilevel rectifier, a multilevel inverter, and a DC link between the rectifier and the inverter allowing voltage balancing between each of the voltage levels within the multilevel converter. The rectifier is equipped with at least one phase leg and a source input node for each of the phases. The rectifier is further equipped with a plurality of rectifier DC output nodes. The inverter is equipped with at least one phase leg and a load output node for each of the phases. The inverter is further equipped with a plurality of inverter DC input nodes. The DC link is equipped with a plurality of rectifier charging means and a plurality of inverter discharging means. The plurality of rectifier charging means are connected in series with one of the rectifier charging means disposed between and connected in an operable relationship with each adjacent pair of rectifier DC output nodes. The plurality of inverter discharging means are connected in series with one of the inverter discharging means disposed between and connected in an operable relationship with each adjacent pair of inverter DC input nodes. Each of said rectifier DC output nodes are individually electrically connected to the respective inverter DC input nodes. By this means, each of the rectifier DC output nodes and each of the inverter DC input nodes are voltage balanced by the respective charging and discharging of the rectifier charging means and the inverter discharging means.
Automatic Multilevel Parallelization Using OpenMP
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Yan, Jerry; Ayguade, Eduard; Gonzalez, Marc; Martorell, Xavier; Biegel, Bryan (Technical Monitor)
2002-01-01
In this paper we describe the extension of the CAPO parallelization support tool to support multilevel parallelism based on OpenMP directives. CAPO generates OpenMP directives with extensions supported by the NanosCompiler to allow for directive nesting and definition of thread groups. We report first results for several benchmark codes and one full application that have been parallelized using our system.
Automatic Multilevel Parallelization Using OpenMP
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Yan, Jerry; Ayguade, Eduard; Gonzalez, Marc; Martorell, Xavier; Biegel, Bryan (Technical Monitor)
2002-01-01
In this paper we describe the extension of the CAPO (CAPtools (Computer Aided Parallelization Toolkit) OpenMP) parallelization support tool to support multilevel parallelism based on OpenMP directives. CAPO generates OpenMP directives with extensions supported by the NanosCompiler to allow for directive nesting and definition of thread groups. We report some results for several benchmark codes and one full application that have been parallelized using our system.
Knowledge discovery of multilevel protein motifs
Conklin, D.; Glasgow, J.; Fortier, S.
1994-12-31
A new category of protein motif is introduced. This type of motif captures, in addition to global structure, the nested structure of its component parts. A dataset of four proteins is represented using this scheme. A structured machine discovery procedure is used to discover recurrent amino acid motifs and this knowledge is utilized for the expression of subsequent protein motif discoveries. Examples of discovered multilevel motifs are presented.
Addressing Asthma Health Disparities: A Multilevel Challenge
Canino, Glorisa; McQuaid, Elizabeth L.; Rand, Cynthia S.
2009-01-01
Substantial research has documented pervasive disparities in the prevalence, severity, and morbidity of asthma among minority populations compared to non-Latino whites. The underlying causes of these disparities are not well understood, and as a result, the leverage points to address them remain unclear. A multilevel framework for integrating research in asthma health disparities is proposed in order to advance both future research and clinical practice. The components of the proposed model include health care policies and regulations, operation of the health care system, provider/clinician-level factors, social/environmental factors, and individual/family attitudes and behaviors. The body of research suggests that asthma disparities have multiple, complex and inter-related sources. Disparities occur when individual, environmental, health system, and provider factors interact with one another over time. Given that the causes of asthma disparities are complex and multilevel, clinical strategies to address these disparities must therefore be comparably multilevel and target many aspects of asthma care. Clinical Implications: Several strategies that could be applied in clinical settings to reduce asthma disparities are described including the need for routine assessment of the patient’s beliefs, financial barriers to disease management, and health literacy, and the provision of cultural competence training and communication skills to health care provider groups. PMID:19447484
Multilevel sparse functional principal component analysis.
Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S
2014-01-29
We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.
Multi-level recording of photochromic indolylfulgide
NASA Astrophysics Data System (ADS)
Sun, Xuan; Park, Seongtae; Shin, Dong Soo; Dong, Wenliang; Zhao, Baoxiang; Jang, Kiwan
2007-12-01
The photon-mode multi-level optical storage properties using a photochromic indolylfulgide compound named 2-(1-benzyl-3-methyl-2-indolylmethylene)-3-isoproplidene succinic anhaydride have been investigated. It has been found that this compound possesses an absorption maximum at 400 nm and undergoes a photocyclization upon irradiation with UV light at 365 nm, leading to the formation of a pinkish product with absorption maximum at 505 nm. By irradiation with visible light at 514.5 nm, the original absorption spectrum was recovered completely. The transmittance of this photochromic material was found to change nonlinearly along with the exposure energy, indicating the potential of this compound as multi-level optical storage material. Eight-level optical storage of amplitude modulation is experimentally realized using the indolylfulgide dispersed PMMA film for the first time. By employing the laser beam at 514.5 nm with power of 3 mW for recording and readout, multi-level signals with high signal-to-noise ratio (SNR) have been detected.
Computational analyses of multilevel discourse comprehension.
Graesser, Arthur C; McNamara, Danielle S
2011-04-01
The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework.
Teachers' support and depression among Japanese adolescents: a multilevel analysis.
Mizuta, Akiko; Suzuki, Kohta; Yamagata, Zentaro; Ojima, Toshiyuki
2017-02-01
Depression is a major cause of suicide among adolescents. Therefore, childhood and adolescent depression is an important public health concern. This study explored factors as class and individual levels that may influence depression among adolescents in Japan. A questionnaire survey among junior high school students (N = 2968) from two cities in Japan was conducted. Depression was assessed using the Depression Self-Rating Scale for Children; teachers' support was assessed using the Scale of Expectancy for Social Support. The class average score of teachers' support was calculated to indicate what we termed the "homeroom teachers' support." Multilevel analysis was applied to clarify the relation between homeroom teachers' support and depression. Finally, 2466 students completed the questionnaire without missing variables (valid response rate, 83.1%). There was no random effect of the teachers' support at the class level on depression, although there was a significant association between teachers' support and depression for 9th graders (β = -0.12, p = 0.009). Moreover, there were significant associations between economic status, having a best friend, and experiencing unforgettable stress at the individual level and depression in all grades. There was no significant random effect of homeroom teachers' support in class level although there might be marginal negative association between teacher's support and depression. It is suggested that homeroom teachers need to promote population approaches to mental health.
Distributed Relaxation for Conservative Discretizations
NASA Technical Reports Server (NTRS)
Diskin, Boris; Thomas, James L.
2001-01-01
A multigrid method is defined as having textbook multigrid efficiency (TME) if the solutions to the governing system of equations are attained in a computational work that is a small (less than 10) multiple of the operation count in one target-grid residual evaluation. The way to achieve this efficiency is the distributed relaxation approach. TME solvers employing distributed relaxation have already been demonstrated for nonconservative formulations of high-Reynolds-number viscous incompressible and subsonic compressible flow regimes. The purpose of this paper is to provide foundations for applications of distributed relaxation to conservative discretizations. A direct correspondence between the primitive variable interpolations for calculating fluxes in conservative finite-volume discretizations and stencils of the discretized derivatives in the nonconservative formulation has been established. Based on this correspondence, one can arrive at a conservative discretization which is very efficiently solved with a nonconservative relaxation scheme and this is demonstrated for conservative discretization of the quasi one-dimensional Euler equations. Formulations for both staggered and collocated grid arrangements are considered and extensions of the general procedure to multiple dimensions are discussed.
Minisuperspace models of discrete systems
NASA Astrophysics Data System (ADS)
Baytaş, Bekir; Bojowald, Martin
2017-04-01
A discrete quantum spin system is presented in which several modern methods of canonical quantum gravity can be tested with promising results. In particular, features of interacting dynamics are analyzed with an emphasis on homogeneous configurations and the dynamical building-up and stability of long-range correlations. Different types of homogeneous minisuperspace models are introduced for the system, including one based on condensate states, and shown to capture different aspects of the discrete system. They are evaluated with effective methods and by means of continuum limits, showing good agreement with operator calculations whenever the latter are available. As a possibly quite general result, it is concluded that an analysis of the building-up of long-range correlations in discrete systems requires nonperturbative solutions of the dynamical equations. Some questions related to stability can be analyzed perturbatively but suggest that matter couplings may be relevant for this question in the context of quantum cosmology.
Integrable structure in discrete shell membrane theory
Schief, W. K.
2014-01-01
We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory. PMID:24808755
Zonostrophic instability driven by discrete particle noise
St-Onge, D. A.; Krommes, J. A.
2017-04-01
The consequences of discrete particle noise for a system possessing a possibly unstable collective mode are discussed. It is argued that a zonostrophic instability (of homogeneous turbulence to the formation of zonal flows) occurs just below the threshold for linear instability. The scenario provides a new interpretation of the random forcing that is ubiquitously invoked in stochastic models such as the second-order cumulant expansion or stochastic structural instability theory; neither intrinsic turbulence nor coupling to extrinsic turbulence is required. A representative calculation of the zonostrophic neutral curve is made for a simple two-field model of toroidal ion-temperature-gradient-driven modes. To themore » extent that the damping of zonal flows is controlled by the ion-ion collision rate, the point of zonostrophic instability is independent of that rate. Published by AIP Publishing.« less
Stable discrete surface light bullets.
Mihalache, Dumitru; Mazilu, Dumitru; Lederer, Falk; Kivshar, Yuri S
2007-01-22
We analyze spatiotemporal light localization near the edge of a semi-infinite array of weakly coupled nonlinear optical waveguides and demonstrate the existence of a novel class of continuous-discrete spatiotemporal solitons, the so-called discrete surface light bullets. We show that their properties are strongly affected by the presence of the surface. To this end the crossover between surface and quasi-bulk bullets is studied by analyzing the families of solitons propagating at different distances from the edge of the waveguide array.
Discrete cloud structure on Neptune
NASA Technical Reports Server (NTRS)
Hammel, H. B.
1989-01-01
Recent CCD imaging data for the discrete cloud structure of Neptune shows that while cloud features at CH4-band wavelengths are manifest in the southern hemisphere, they have not been encountered in the northern hemisphere since 1986. A literature search has shown the reflected CH4-band light from the planet to have come from a single discrete feature at least twice in the last 10 years. Disk-integrated photometry derived from the imaging has demonstrated that a bright cloud feature was responsible for the observed 8900 A diurnal variation in 1986 and 1987.
MAFFEY, L.; CARDINAL, M.V.; ORDÓÑEZ-KRASNOWSKI, P.C.; LANATI, L.A.; LAURICELLA, M.A.; SCHIJMAN, A.G.; GÜRTLER, R.E.
2013-01-01
SUMMARY We assessed the distribution of Trypanosoma cruzi Discrete Typing Units (DTUs) in domestic and peridomestic Triatoma infestans and Triatoma sordida specimens collected in a well-defined rural area in Pampa del Indio, northeastern Argentina. Microscopically-positive bugs were randomly selected with a multi-level sampling design, and DTUs were identified using direct PCR strategies. TcVI predominated in 61% of 69 T. infestans and in 56% of 9 T. sordida. TcV was the secondary DTU in T. infestans (16%) and was found in one T. sordida specimen (11%). Three T. sordida (33%) were found infected with TcI, a DTU also identified in local Didelphis albiventris opossums. Mixed DTU infections occurred rarely (5%) and were detected both directly from the bugs’ rectal ampoule and parasite cultures. The identified DTUs and bug collection sites of T. infestans were significantly associated. Bugs infected with TcV were almost exclusively captured in domiciles whereas those with TcVI were found similarly in domiciles and peridomiciles. All mixed infections occurred in domiciles. TcV-infected bugs fed more often on humans than on dogs, whereas TcVI-infected bugs showed the reverse pattern. T. sordida is a probable sylvatic vector of TcI linked to D. albiventris, and could represent a secondary vector of TcVI and TcV in the domestic/peridomestic cycle. PMID:23036510
Multilevel conductance switching in polymer films
NASA Astrophysics Data System (ADS)
Lauters, M.; McCarthy, B.; Sarid, D.; Jabbour, G. E.
2006-07-01
Multilevel conductance switching in poly[2-methoxy-5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV) films is demonstrated. A thin-film structure, ITO-coated glass/MEH-PPV/Al, has shown the ability to store a continuum of conductance states. These states are nonvolatile and can be switched reproducibly by applying appropriate programing biases above a certain threshold voltage. The electrical conductivity of the highest and lowest states can differ by five orders of magnitude. Furthermore, these devices exhibit good cyclic switching characteristics and retention times of several weeks.
Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung
NASA Astrophysics Data System (ADS)
Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani
2017-03-01
Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.
Matching Strategies for Observational Data with Multilevel Structure
ERIC Educational Resources Information Center
Steiner, Peter M.
2011-01-01
Given the different possibilities of matching in the context of multilevel data and the lack of research on corresponding matching strategies, the author investigates two main research questions. The first research question investigates the advantages and disadvantages of different matching strategies that can be pursued with multilevel data…
Extensions of Mantel-Haenszel for Multilevel DIF Detection
ERIC Educational Resources Information Center
French, Brian F.; Finch, W. Holmes
2013-01-01
Multilevel data structures are ubiquitous in the assessment of differential item functioning (DIF), particularly in large-scale testing programs. There are a handful of DIF procures for researchers to select from that appropriately account for multilevel data structures. However, little, if any, work has been completed to extend a popular DIF…
Multilevel Higher-Order Item Response Theory Models
ERIC Educational Resources Information Center
Huang, Hung-Yu; Wang, Wen-Chung
2014-01-01
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Multilevel Modeling and School Psychology: A Review and Practical Example
ERIC Educational Resources Information Center
Graves, Scott L., Jr.; Frohwerk, April
2009-01-01
The purpose of this article is to provide an overview of the state of multilevel modeling in the field of school psychology. The authors provide a systematic assessment of published research of multilevel modeling studies in 5 journals devoted to the research and practice of school psychology. In addition, a practical example from the nationally…
Alternatives to Multilevel Modeling for the Analysis of Clustered Data
ERIC Educational Resources Information Center
Huang, Francis L.
2016-01-01
Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…
A Multilevel Analysis of Parental Discipline and Child Antisocial Behavior
ERIC Educational Resources Information Center
Stoolmiller, Mike; Snyder, Jim
2004-01-01
We demonstrate graphical and analytical methods for multilevel (2- and 3-level) models using the analysis of observed microsocial interaction between parent-child dyads as an example. We also present multilevel path diagrams and argue that while not as compact as equations, path diagrams may communicate results better to a wider audience. The…
Minimally invasive treatment of multilevel spinal epidural abscess.
Safavi-Abbasi, Sam; Maurer, Adrian J; Rabb, Craig H
2013-01-01
The use of minimally invasive tubular retractor microsurgery for treatment of multilevel spinal epidural abscess is described. This technique was used in 3 cases, and excellent results were achieved. The authors conclude that multilevel spinal epidural abscesses can be safely and effectively managed using microsurgery via a minimally invasive tubular retractor system.
Alternatives to Multilevel Modeling for the Analysis of Clustered Data
ERIC Educational Resources Information Center
Huang, Francis L.
2016-01-01
Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…
Multilevel Higher-Order Item Response Theory Models
ERIC Educational Resources Information Center
Huang, Hung-Yu; Wang, Wen-Chung
2014-01-01
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Optimal control of a boiling water reactor in load-following via multilevel methods
Lin, C.; Grossman, L.M.
1986-04-01
A multilevel method is applied to the load-following control of a boiling water reactor using a nodal reactor model with practical operational constraints and thermal limits. Due to the very large size of the problem, a decomposition is made using hierarchical control techniques. The optimization of the resulting subproblems is performed using the feasible direction method. An objective functional, of quadratic form, is defined to reflect the control objective, namely to achieve the desired thermal power (tracking) with minimum effort, returning to the initial xenon and iodine concentration as closely as possible. Nodal source equation and discretized Xe-I dynamic equations are formulated as equality constraints, while the linear heat generation rate and the rate of power increase are formulated as inequality constraints. Core flow and control rod position are the control variables. A simplified model of the core is used, with 4 x 4 fuel assemblies that have one control rod at the center.
Multilevel-3D Bit Patterned Magnetic Media with 8 Signal Levels Per Nanocolumn
Amos, Nissim; Butler, John; Lee, Beomseop; Shachar, Meir H.; Hu, Bing; Tian, Yuan; Hong, Jeongmin; Garcia, Davil; Ikkawi, Rabee M.; Haddon, Robert C.; Litvinov, Dmitri; Khizroev, Sakhrat
2012-01-01
This letter presents an experimental study that shows that a 3rd physical dimension may be used to further increase information packing density in magnetic storage devices. We demonstrate the feasibility of at least quadrupling the magnetic states of magnetic-based data storage devices by recording and reading information from nanopillars with three magnetically-decoupled layers. Magneto-optical Kerr effect microscopy and magnetic force microscopy analysis show that both continuous (thin film) and patterned triple-stack magnetic media can generate eight magnetically-stable states. This is in comparison to only two states in conventional magnetic recording. Our work further reveals that ferromagnetic interaction between magnetic layers can be reduced by combining Co/Pt and Co/Pd multilayers media. Finally, we are showing for the first time an MFM image of multilevel-3D bit patterned media with 8 discrete signal levels. PMID:22808105
Coherent population transfer in multilevel systems with magnetic sublevels. II. Algebraic analysis
NASA Astrophysics Data System (ADS)
Martin, J.; Shore, B. W.; Bergmann, K.
1995-07-01
We extend previous theoretical work on coherent population transfer by stimulated Raman adiabatic passage for states involving nonzero angular momentum. The pump and Stokes fields are either copropagating or counterpropagating with the corresponding linearly polarized electric-field vectors lying in a common plane with the magnetic-field direction. Zeeman splitting lifts the magnetic sublevel degeneracy. We present an algebraic analysis of dressed-state properties to explain the behavior noted in numerical studies. In particular, we discuss conditions which are likely to lead to a failure of complete population transfer. The applied strategy, based on simple methods of linear algebra, will also be successful for other types of discrete multilevel systems, provided the rotating-wave and adiabatic approximation are valid.
Implementation of Hybrid V-Cycle Multilevel Methods for Mixed Finite Element Systems with Penalty
NASA Technical Reports Server (NTRS)
Lai, Chen-Yao G.
1996-01-01
The goal of this paper is the implementation of hybrid V-cycle hierarchical multilevel methods for the indefinite discrete systems which arise when a mixed finite element approximation is used to solve elliptic boundary value problems. By introducing a penalty parameter, the perturbed indefinite system can be reduced to a symmetric positive definite system containing the small penalty parameter for the velocity unknown alone. We stabilize the hierarchical spatial decomposition approach proposed by Cai, Goldstein, and Pasciak for the reduced system. We demonstrate that the relative condition number of the preconditioner is bounded uniformly with respect to the penalty parameter, the number of levels and possible jumps of the coefficients as long as they occur only across the edges of the coarsest elements.
Implementation of Hybrid V-Cycle Multilevel Methods for Mixed Finite Element Systems with Penalty
NASA Technical Reports Server (NTRS)
Lai, Chen-Yao G.
1996-01-01
The goal of this paper is the implementation of hybrid V-cycle hierarchical multilevel methods for the indefinite discrete systems which arise when a mixed finite element approximation is used to solve elliptic boundary value problems. By introducing a penalty parameter, the perturbed indefinite system can be reduced to a symmetric positive definite system containing the small penalty parameter for the velocity unknown alone. We stabilize the hierarchical spatial decomposition approach proposed by Cai, Goldstein, and Pasciak for the reduced system. We demonstrate that the relative condition number of the preconditioner is bounded uniformly with respect to the penalty parameter, the number of levels and possible jumps of the coefficients as long as they occur only across the edges of the coarsest elements.
Multilevel-3D bit patterned magnetic media with 8 signal levels per nanocolumn.
Amos, Nissim; Butler, John; Lee, Beomseop; Shachar, Meir H; Hu, Bing; Tian, Yuan; Hong, Jeongmin; Garcia, Davil; Ikkawi, Rabee M; Haddon, Robert C; Litvinov, Dmitri; Khizroev, Sakhrat
2012-01-01
This letter presents an experimental study that shows that a 3(rd) physical dimension may be used to further increase information packing density in magnetic storage devices. We demonstrate the feasibility of at least quadrupling the magnetic states of magnetic-based data storage devices by recording and reading information from nanopillars with three magnetically-decoupled layers. Magneto-optical Kerr effect microscopy and magnetic force microscopy analysis show that both continuous (thin film) and patterned triple-stack magnetic media can generate eight magnetically-stable states. This is in comparison to only two states in conventional magnetic recording. Our work further reveals that ferromagnetic interaction between magnetic layers can be reduced by combining Co/Pt and Co/Pd multilayers media. Finally, we are showing for the first time an MFM image of multilevel-3D bit patterned media with 8 discrete signal levels.
Reduced discretization error in HZETRN
Slaba, Tony C.; Blattnig, Steve R.; Tweed, John
2013-02-01
The deterministic particle transport code HZETRN is an efficient analysis tool for studying the effects of space radiation on humans, electronics, and shielding materials. In a previous work, numerical methods in the code were reviewed, and new methods were developed that further improved efficiency and reduced overall discretization error. It was also shown that the remaining discretization error could be attributed to low energy light ions (A < 4) with residual ranges smaller than the physical step-size taken by the code. Accurately resolving the spectrum of low energy light particles is important in assessing risk associated with astronaut radiation exposure. In this work, modifications to the light particle transport formalism are presented that accurately resolve the spectrum of low energy light ion target fragments. The modified formalism is shown to significantly reduce overall discretization error and allows a physical approximation to be removed. For typical step-sizes and energy grids used in HZETRN, discretization errors for the revised light particle transport algorithms are shown to be less than 4% for aluminum and water shielding thicknesses as large as 100 g/cm{sup 2} exposed to both solar particle event and galactic cosmic ray environments.
Police Discretion: A Selected Bibliography.
ERIC Educational Resources Information Center
Brenner, Robert N.; Kravitz, Marjorie
This bibliography was compiled with two goals. The first goal is to provide police administrators and officers with an overview of the issues involved in developing guidelines for police discretion and a discussion of the options available. The second goal is to demonstrate the need for continuing dialogue and interaction between lawmakers, law…
Reduced discretization error in HZETRN
NASA Astrophysics Data System (ADS)
Slaba, Tony C.; Blattnig, Steve R.; Tweed, John
2013-02-01
The deterministic particle transport code HZETRN is an efficient analysis tool for studying the effects of space radiation on humans, electronics, and shielding materials. In a previous work, numerical methods in the code were reviewed, and new methods were developed that further improved efficiency and reduced overall discretization error. It was also shown that the remaining discretization error could be attributed to low energy light ions (A < 4) with residual ranges smaller than the physical step-size taken by the code. Accurately resolving the spectrum of low energy light particles is important in assessing risk associated with astronaut radiation exposure. In this work, modifications to the light particle transport formalism are presented that accurately resolve the spectrum of low energy light ion target fragments. The modified formalism is shown to significantly reduce overall discretization error and allows a physical approximation to be removed. For typical step-sizes and energy grids used in HZETRN, discretization errors for the revised light particle transport algorithms are shown to be less than 4% for aluminum and water shielding thicknesses as large as 100 g/cm2 exposed to both solar particle event and galactic cosmic ray environments.
Professional Discretion and Teacher Satisfaction.
ERIC Educational Resources Information Center
Sweeney, Jim
1981-01-01
Reports a survey of 1,295 teachers in large Iowa high schools on their needs (following Maslow's categories) in relation to age, sex, and student ability level taught, plus their overall job satisfaction and its relationship to their professional discretion, participation in decision making, and reciprocal trust. (Author/SJL)
Discrete tomography in neutron radiography
NASA Astrophysics Data System (ADS)
Kuba, Attila; Rodek, Lajos; Kiss, Zoltán; Ruskó, László; Nagy, Antal; Balaskó, Márton
2005-04-01
Discrete tomography (DT) is an imaging technique for reconstructing discrete images from their projections using the knowledge that the object to be reconstructed contains only a few homogeneous materials characterized by known discrete absorption values. One of the main reasons for applying DT is that we will hopefully require relatively few projections. Using discreteness and some a priori information (such as an approximate shape of the object) we can apply two DT methods in neutron imaging by reducing the problem to an optimization task. The first method is a special one because it is only suitable if the object is composed of cylinders and sphere shapes. The second method is a general one in the sense that it can be used for reconstructing objects of any shape. Software was developed and physical experiments performed in order to investigate the effects of several reconstruction parameters: the number of projections, noise levels, and complexity of the object to be reconstructed. We give a summary of the experimental results and make a comparison of the results obtained using a classical reconstruction technique (FBP). The programs we developed are available in our DT reconstruction program package DIRECT.
Ambient changes in tracer concentrations from a multilevel monitoring system in Basalt
Bartholomay, Roy C.; Twining, Brian V.; Rose, Peter E.
2014-01-01
Starting in 2008, a 4-year tracer study was conducted to evaluate ambient changes in groundwater concentrations of a 1,3,6-naphthalene trisulfonate tracer that was added to drill water. Samples were collected under open borehole conditions and after installing a multilevel groundwater monitoring system completed with 11 discrete monitoring zones within dense and fractured basalt and sediment layers in the eastern Snake River aquifer. The study was done in cooperation with the U.S. Department of Energy to test whether ambient fracture flow conditions were sufficient to remove the effects of injected drill water prior to sample collection. Results from thief samples indicated that the tracer was present in minor concentrations 28 days after coring, but was not present 6 months after coring or 7 days after reaming the borehole. Results from sampling the multilevel monitoring system indicated that small concentrations of the tracer remained in 5 of 10 zones during some period after installation. All concentrations were several orders of magnitude lower than the initial concentrations in the drill water. The ports that had remnant concentrations of the tracer were either located near sediment layers or were located in dense basalt, which suggests limited groundwater flow near these ports. The ports completed in well-fractured and vesicular basalt had no detectable concentrations.
The XXZ Heisenberg model on random surfaces
NASA Astrophysics Data System (ADS)
Ambjørn, J.; Sedrakyan, A.
2013-09-01
We consider integrable models, or in general any model defined by an R-matrix, on random surfaces, which are discretized using random Manhattan lattices. The set of random Manhattan lattices is defined as the set dual to the lattice random surfaces embedded on a regular d-dimensional lattice. They can also be associated with the random graphs of multiparticle scattering nodes. As an example we formulate a random matrix model where the partition function reproduces the annealed average of the XXZ Heisenberg model over all random Manhattan lattices. A technique is presented which reduces the random matrix integration in partition function to an integration over their eigenvalues.
Gilthorpe, M S; Zamzuri, A T; Griffiths, G S; Maddick, I H; Eaton, K A; Johnson, N W
2003-03-01
Previously, burst and linear theories for periodontal disease progression were proposed based on different but limited statistical methods of analysis. Multilevel modeling provides a new approach, yielding a more comprehensive model. Random coefficient models were used to analyze longitudinal periodontal data consisting of repeated measures (level 1), sites (level 2), teeth (level 3), and subjects (level 4). Large negative and highly significant correlations between random linear and quadratic time coefficients indicated that subjects and teeth with greater-than-average linear change experienced decelerated variation. Conversely, subjects and teeth with less-than-average linear change experienced accelerated variation. Change therefore exhibited a dynamic regression to the mean at the tooth and subject levels. Since no equilibrium was attained throughout the study, changes were cyclical. When considered as a multilevel system, the "linear" and "burst" theories of periodontal disease progression are a manifestation of the same phenomenon: Some sites improve while others progress, in a cyclical manner.
Prakash, A. E-mail: amit.knp02@gmail.com Song, J.; Hwang, H. E-mail: amit.knp02@gmail.com; Deleruyelle, D.; Bocquet, M.
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.
Discrete dipole approximation simulation of bead enhanced diffraction grating biosensor
NASA Astrophysics Data System (ADS)
Arif, Khalid Mahmood
2016-08-01
We present the discrete dipole approximation simulation of light scattering from bead enhanced diffraction biosensor and report the effect of bead material, number of beads forming the grating and spatial randomness on the diffraction intensities of 1st and 0th orders. The dipole models of gratings are formed by volume slicing and image processing while the spatial locations of the beads on the substrate surface are randomly computed using discrete probability distribution. The effect of beads reduction on far-field scattering of 632.8 nm incident field, from fully occupied gratings to very coarse gratings, is studied for various bead materials. Our findings give insight into many difficult or experimentally impossible aspects of this genre of biosensors and establish that bead enhanced grating may be used for rapid and precise detection of small amounts of biomolecules. The results of simulations also show excellent qualitative similarities with experimental observations.
Multilevel converters -- A new breed of power converters
Lai, J.S.; Peng, F.Z. |
1995-09-01
Multilevel voltage source converters are emerging as a new breed of power converter options for high-power applications. The multilevel voltage source converters typically synthesize the staircase voltage wave from several levels of dc capacitor voltages. One of the major limitations of the multilevel converters is the voltage unbalance between different levels. The techniques to balance the voltage between different levels normally involve voltage clamping or capacitor charge control. There are several ways of implementing voltage balance in multilevel converters. Without considering the traditional magnetic coupled converters, this paper presents three recently developed multilevel voltage source converters: (1) diode-clamp, (2) flying-capacitors, and (3) cascaded-inverters with separate dc sources. The operating principle, features, constraints, and potential applications of these converters will be discussed.
Multilevel Charge Storage in a Multiple Alloy Nanodot Memory
NASA Astrophysics Data System (ADS)
Lee, Gae-Hun; Lee, Jung-Min; Heub Song, Yun; Bea, Ji Chel; Tanaka, Tetsu; Koyanagi, Mitsumasa
2011-09-01
A multilevel charge storage in a multiple FePt alloy nanodot memory is investigated for the first time. It is demonstrated that the memory structure with multiple FePt nanodot layers effectively realizes a multilevel state by the adjustment of gate voltage. Metal oxide semiconductor (MOS) capacitors with four FePt nanodot layers as a floating gate are fabricated to evaluate the multilevel cell characteristic and reliability. Here, the effect of memory window for a nanodot diameter is also investigated, and it is found that a smaller dot size gives a larger window. From the results showing good endurance and retention characteristics for the multilevel states, it is expected that a multiple FePt nanodot memory using Fowler-Nordheim (FN) tunneling can be a candidate structure for the future multilevel NAND flash memory.
Discrete implementations of scale transform
NASA Astrophysics Data System (ADS)
Djurdjanovic, Dragan; Williams, William J.; Koh, Christopher K.
1999-11-01
Scale as a physical quantity is a recently developed concept. The scale transform can be viewed as a special case of the more general Mellin transform and its mathematical properties are very applicable in the analysis and interpretation of the signals subject to scale changes. A number of single-dimensional applications of scale concept have been made in speech analysis, processing of biological signals, machine vibration analysis and other areas. Recently, the scale transform was also applied in multi-dimensional signal processing and used for image filtering and denoising. Discrete implementation of the scale transform can be carried out using logarithmic sampling and the well-known fast Fourier transform. Nevertheless, in the case of the uniformly sampled signals, this implementation involves resampling. An algorithm not involving resampling of the uniformly sampled signals has been derived too. In this paper, a modification of the later algorithm for discrete implementation of the direct scale transform is presented. In addition, similar concept was used to improve a recently introduced discrete implementation of the inverse scale transform. Estimation of the absolute discretization errors showed that the modified algorithms have a desirable property of yielding a smaller region of possible error magnitudes. Experimental results are obtained using artificial signals as well as signals evoked from the temporomandibular joint. In addition, discrete implementations for the separable two-dimensional direct and inverse scale transforms are derived. Experiments with image restoration and scaling through two-dimensional scale domain using the novel implementation of the separable two-dimensional scale transform pair are presented.
Stevens, D.E.; Bretherton, S.
1996-12-01
This paper presents a new forward-in-time advection method for nearly incompressible flow, MU, and its application to an adaptive multilevel flow solver for atmospheric flows. MU is a modification of Leonard et al.`s UTOPIA scheme. MU, like UTOPIA, is based on third-order accurate semi-Lagrangian multidimensional upwinding for constant velocity flows. for varying velocity fields, MU is a second-order conservative method. MU has greater stability and accuracy than UTOPIA and naturally decomposes into a monotone low-order method and a higher-order accurate correction for use with flux limiting. Its stability and accuracy make it a computationally efficient alternative to current finite-difference advection methods. We present a fully second-order accurate flow solver for the anelastic equations, a prototypical low Mach number flow. The flow solver is based on MU which is used for both momentum and scalar transport equations. This flow solver can also be implemented with any forward-in-time advection scheme. The multilevel flow solver conserves discrete global integrals of advected quantities and includes adaptive mesh refinements. Its second-order accuracy is verified using a nonlinear energy conservation integral for the anelastic equations. For a typical geophysical problem in which the flow is most rapidly varying in a small part of the domain, the multilevel flow solver achieves global accuracy comparable to uniform-resolution simulation for 10% of the computational cost. 36 refs., 10 figs.
ERIC Educational Resources Information Center
Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn
2016-01-01
To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…
ERIC Educational Resources Information Center
Huang, Hsiao-Ling; Chen, Fu-Li; Hsu, Chih-Cheng; Yen, Yea-Yin; Chen, Ted; Huang, Cheng-Ming; Shi, Hon-Yi; Hu, Chih-Yang; Lee, Chien-Hung
2010-01-01
The aim was to comprehensively examine school-based tobacco policy status, implementation and students' perceived smoking at school in regard to gender-specific differences in smoking behavior. We conducted a multilevel-based study to assess two-level effects for smoking among 2350 grades three to six students in 26 randomly selected elementary…
ERIC Educational Resources Information Center
Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn
2016-01-01
To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…
ERIC Educational Resources Information Center
Huang, Hsiao-Ling; Chen, Fu-Li; Hsu, Chih-Cheng; Yen, Yea-Yin; Chen, Ted; Huang, Cheng-Ming; Shi, Hon-Yi; Hu, Chih-Yang; Lee, Chien-Hung
2010-01-01
The aim was to comprehensively examine school-based tobacco policy status, implementation and students' perceived smoking at school in regard to gender-specific differences in smoking behavior. We conducted a multilevel-based study to assess two-level effects for smoking among 2350 grades three to six students in 26 randomly selected elementary…
Multilevel converters for large electric drives
Tolbert, L.M.; Peng, F.Z.
1997-11-01
Traditional two-level high frequency pulse width modulation (PWM) inverters for motor drives have several problems associated with their high frequency switching which produces common-mode voltage and high voltage change (dV/dt) rates to the motor windings. Multilevel inverters solve these problems because their devices can switch at a much lower frequency. Two different multilevel topologies are identified for use as a converter for electric drives, a cascade inverter with separate dc sources and a back-to-back diode clamped converter. The cascade inverter is a natural fit for large automotive all electric drives because of the high VA ratings possible and because it uses several levels of dc voltage sources which would be available from batteries or fuel cells. The back to back diode damped converter is ideal where a source of ac voltage is available such as a hybrid electric vehicle. Simulation and experimental results show the superiority of these two converters over PWM based drives.
Advanced micromechanisms in a multilevel polysilicon technology
NASA Astrophysics Data System (ADS)
Rodgers, M. Steven; Sniegowski, Jeffry J.; Miller, Samuel L.; Craig Barron, Carole; McWhorter, Paul J.
1997-09-01
Quad-level polysilicon surface micromachining technology, comprising three mechanical levels plus an electrical interconnect layer, is giving rise to a new generation of micro-electromechanical devices and assemblies. Enhanced components can now be produced through greater flexibility in fabrication and design. New levels of design complexity that include multi-level gears, single-attempt locks, and optical elements have recently been realized. Extensive utilization of the fourth layer of polysilicon differentiates these latter generation devices from their predecessors. This level of poly enables the fabrication of pin joints, linkage arms, hinges on moveable plates, and multi-level gear assemblies. The mechanical design aspects of these latest micromachines will be discussed with particular emphasis on a number of design modifications that improve the power, reliability, and smoothness of operation of the microengine. The microengine is the primary actuation mechanism that is being used to drive mirrors out of plane and rotate 1600-micrometers diameter gears. Also discussed is our most advanced micromechanical system to date, a complex proof-of-concept batch-fabricated assembly that, upon transmitting the proper electrical code to a mechanical lock, permits the operation of a micro-optical shutter.
The treatment for multilevel noncontiguous spinal fractures
Lian, Xiao Feng; Hou, Tie Sheng; Yuan, Jian Dong; Jin, Gen Yang; Li, Zhong Hai
2006-01-01
We report the outcome of 30 patients with multilevel noncontiguous spinal fractures treated between 2000 and 2005. Ten cases were treated conservatively (group A), eight cases were operated on at only one level (group B), and 12 cases were treated surgically at both levels (group C). All cases were followed up for 14–60 months (mean 32 months). Initial mobilisation with a wheelchair or crutches in group A was 9.2±1.1 weeks, which was significantly longer than groups B and C with 6.8±0.7 weeks and 3.1±0.4 weeks, respectively. Operative time and blood loss in group C were significantly more than group B. The neurological deficit improved in six cases in group A (60%), six in group B (75%) and eight in group C (80%). Correction of kyphotic deformity was significantly superior in groups C and B at the operated level, and increasing deformity occurred in groups A and B at the non-operated level. From the results we believe that three treatment strategies were suitable for multilevel noncontiguous spinal fractures, and individualised treatment should be used in these patients. In the patients treated surgically, the clinical and radiographic outcomes are much better. PMID:17043863
An introduction to multilevel modeling for anesthesiologists.
Glaser, Dale; Hastings, Randolph H
2011-10-01
In population-based research, subjects are frequently in clusters with shared features or demographic characteristics, such as age range, neighborhood, who they have for a physician, and common comorbidities. Classification into clusters also applies at broader levels. Physicians are classified by physician group or by practice site; hospitals can be characterized by size, location, or demographics. Hierarchical, nested structures pose unique challenges in the conduct of research. Data from nested structures may be interdependent because of similarities among subjects in a cluster, while nesting at multiple levels makes it difficult to know whether findings should be applied to the individual or to the larger group. Statistical tools, known variously as hierarchical linear modeling, multilevel modeling, mixed linear modeling, and other terms, have been developed in the education and social science fields to deal effectively with these issues. Our goal in this article is to review the implications of hierarchical, nested data organization and to provide a step-by-step tutorial of how multilevel modeling could be applied to a problem in anesthesia research using current, commercially available software.
Henry, Kimberly L.; Muthén, Bengt
2010-01-01
Latent Class Analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical and/or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this paper, a new methodology, multilevel latent class analysis (MLCA), is described and an applied example is presented. Latent classes of cigarette smoking among 10,772 European American females in 9th grade who live in one of 206 rural communities across the U.S. are considered. A parametric and non-parametric approach for estimating a MLCA are presented and both individual and contextual predictors of the smoking typologies are assessed. Both latent class and indicator-specific random effects models are explored. The best model was comprised of three Level 1 latent smoking classes (heavy smokers, moderate smokers, non-smokers), two random effects to account for variation in the probability of Level 1 latent class membership across communities, and a random factor for the indicator-specific Level 2 variances. Several covariates at the individual and contextual level were useful in predicting latent classes of cigarette smoking as well as the individual indicators of the latent class model. This paper will assist researchers in estimating similar models with their own data. PMID:21057651
NASA Astrophysics Data System (ADS)
Cheng, Chaojun; Zhou, Bingchang; Gao, Xiao; McDonnell, Mark D.
2017-08-01
We investigate multilevel threshold systems with signal-dependent noise that transmit a common random input signal. We demonstrate the occurrence of M-ary suprathreshold stochastic resonance caused by the signal-dependent noise, and quantify the information enhancement that results relative to the absence of noise. We also find that in the case of M-ary threshold systems, the values of mutual information and signal-to-quantization-noise ratio are larger than the corresponding values in the case of binary threshold systems. These results are potentially useful for understanding the encoding mechanism of inner-ear hair cells and other biological sensory systems.
Individual relocation decisions after tornadoes: a multi-level analysis.
Cong, Zhen; Nejat, Ali; Liang, Daan; Pei, Yaolin; Javid, Roxana J
2017-08-02
This study examines how multi-level factors affected individuals' relocation decisions after EF4 and EF5 (Enhanced Fujita Tornado Intensity Scale) tornadoes struck the United States in 2013. A telephone survey was conducted with 536 respondents, including oversampled older adults, one year after these two disaster events. Respondents' addresses were used to associate individual information with block group-level variables recorded by the American Community Survey. Logistic regression revealed that residential damage and homeownership are important predictors of relocation. There was also significant interaction between these two variables, indicating less difference between homeowners and renters at higher damage levels. Homeownership diminished the likelihood of relocation among younger respondents. Random effects logistic regression found that the percentage of homeownership and of higher income households in the community buffered the effect of damage on relocation; the percentage of older adults reduced the likelihood of this group relocating. The findings are assessed from the standpoint of age difference, policy implications, and social capital and vulnerability. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.
Discrete gauge symmetries in discrete MSSM-like orientifolds
NASA Astrophysics Data System (ADS)
Ibáñez, L. E.; Schellekens, A. N.; Uranga, A. M.
2012-12-01
Motivated by the necessity of discrete ZN symmetries in the MSSM to insure baryon stability, we study the origin of discrete gauge symmetries from open string sector U(1)'s in orientifolds based on rational conformal field theory. By means of an explicit construction, we find an integral basis for the couplings of axions and U(1) factors for all simple current MIPFs and orientifolds of all 168 Gepner models, a total of 32 990 distinct cases. We discuss how the presence of discrete symmetries surviving as a subgroup of broken U(1)'s can be derived using this basis. We apply this procedure to models with MSSM chiral spectrum, concretely to all known U(3)×U(2)×U(1)×U(1) and U(3)×Sp(2)×U(1)×U(1) configurations with chiral bi-fundamentals, but no chiral tensors, as well as some SU(5) GUT models. We find examples of models with Z2 (R-parity) and Z3 symmetries that forbid certain B and/or L violating MSSM couplings. Their presence is however relatively rare, at the level of a few percent of all cases.
NASA Astrophysics Data System (ADS)
Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.
2017-03-01
Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.
Truncated Gaussian simulation of discrete-valued, ordinal coregionalized variables
NASA Astrophysics Data System (ADS)
Emery, Xavier; Cornejo, Javier
2010-10-01
This paper deals with the modeling and cosimulation of ordinal coregionalized variables, such as indicators, counts or continuous-valued variables discretized into a limited number of classes. The proposed model relies on truncations of a set of cross-correlated stationary Gaussian random fields. We provide guidelines and algorithms for inferring and validating the structural model (direct and cross variograms of the underlying Gaussian random fields) and constructing realizations conditioned to data. The algorithms are implemented in a set of computer programs and are illustrated with applications to datasets in pest management and mineral resources evaluation.
Discrete tomography by Bayesian labeling with its efficient algorithm
NASA Astrophysics Data System (ADS)
Cheng, Yuan; Dewey, C. Forbes
2000-10-01
these class values. The paper also discusses a Markov random field (MRF) model for non-stationary a priori probability, encouraging the local regularity and smoothness in the reconstruction. The experimental results demonstrate that discrete tomography using the proposed method improves the reconstruction quality greatly, especially when fewer projections are given.
Spatial data discretization methods for geocomputation
NASA Astrophysics Data System (ADS)
Cao, Feng; Ge, Yong; Wang, Jinfeng
2014-02-01
Geocomputation provides solutions to complex geographic problems. Continuous and discrete spatial data are involved in the geocomputational process; however, geocomputational methods for discrete spatial data cannot be directly applied to continuous or mixed spatial data. Therefore, discretization methods for continuous or mixed spatial data are involved in the process. Since spatial data has spatial features, such as association, heterogeneity and spatial structure, these features cannot be handled by traditional discretization methods. Therefore, this work develops feature-based spatial data discretization methods that achieve optimal discretization results for spatial data using spatial information implicit in those features. Two discretization methods considering the features of spatial data are presented. One is an unsupervised method considering autocorrelation of spatial data and the other is a supervised method considering spatial heterogeneity. Discretization processes of the two methods are exemplified using neural tube defects (NTD) for Heshun County in Shanxi Province, China. Effectiveness is also assessed.
Systoles in discrete dynamical systems
NASA Astrophysics Data System (ADS)
Fernandes, Sara; Grácio, Clara; Ramos, Carlos Correia
2013-01-01
The fruitful relationship between Geometry and Graph Theory has been explored by several authors benefiting also the Theory of discrete dynamical systems seen as Markov chains in graphs. In this work we will further explore the relation between these areas, giving a geometrical interpretation of notions from dynamical systems. In particular, we relate the topological entropy with the systole, here defined in the context of discrete dynamical systems. We show that for continuous interval maps the systole is trivial; however, for the class of interval maps with one discontinuity point the systole acquires relevance from the point of view of the dynamical behavior. Moreover, we define the geodesic length spectrum associated to a Markov interval map and we compute the referred spectrum in several examples.
Dark energy from discrete spacetime.
Trout, Aaron D
2013-01-01
Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT) model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, [Formula: see text] in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies.
Dark Energy from Discrete Spacetime
Trout, Aaron D.
2013-01-01
Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT) model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies. PMID:24312502
Observability of discretized partial differential equations
NASA Technical Reports Server (NTRS)
Cohn, Stephen E.; Dee, Dick P.
1988-01-01
It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.
[Applying multilevel models in evaluation of bioequivalence (I)].
Liu, Qiao-lan; Shen, Zhuo-zhi; Chen, Feng; Li, Xiao-song; Yang, Min
2009-12-01
This study aims to explore the application value of multilevel models for bioequivalence evaluation. Using a real example of 2 x 4 cross-over experimental design in evaluating bioequivalence of antihypertensive drug, this paper explores complex variance components corresponding to criteria statistics in existing methods recommended by FDA but obtained in multilevel models analysis. Results are compared with those from FDA standard Method of Moments, specifically on the feasibility and applicability of multilevel models in directly assessing the bioequivalence (ABE), the population bioequivalence (PBE) and the individual bioequivalence (IBE). When measuring ln (AUC), results from all variance components of the test and reference groups such as total variance (sigma(TT)(2) and sigma(TR)(2)), between-subject variance (sigma(BT)(2) and sigma(BR)(2)) and within-subject variance (sigma(WT)(2) and sigma(WR)(2)) estimated by simple 2-level models are very close to those that using the FDA Method of Moments. In practice, bioequivalence evaluation can be carried out directly by multilevel models, or by FDA criteria, based on variance components estimated from multilevel models. Both approaches produce consistent results. Multilevel models can be used to evaluate bioequivalence in cross-over test design. Compared to FDA methods, this one is more flexible in decomposing total variance into sub components in order to evaluate the ABE, PBE and IBE. Multilevel model provides a new way into the practice of bioequivalence evaluation.
Interference in discrete Wigner functions
Cormick, Cecilia; Paz, Juan Pablo
2006-12-15
We analyze some features of the class of discrete Wigner functions that was recently introduced by Gibbons et al. [Phys. Rev. A 70, 062101 (2004)] to represent quantum states of systems with power-of-prime dimensional Hilbert spaces. We consider ''cat'' states obtained as coherent superpositions of states with positive Wigner function; for such states we show that the oscillations of the discrete Wigner function typically spread over the entire discrete phase space (including the regions where the two interfering states are localized). This is a generic property, which is in sharp contrast with the usual attributes of Wigner functions that make them useful candidates to display the existence of quantum coherence through oscillations. However, it is possible to find subsets of cat states with a natural phase-space representation, in which the oscillatory regions remain localized. We show that this can be done for interesting families of stabilizer states used in quantum error-correcting codes, and illustrate this by analyzing the phase-space representation of the five-qubit error-correcting code.
Umbral Deformations on Discrete SPACE TIME
NASA Astrophysics Data System (ADS)
Zachos, Cosmas K.
Given a minimum measurable length underlying spacetime, the latter may be effectively regarded as discrete, at scales of order the Planck length. A systematic discretization of continuum physics may be effected most efficiently through the umbral deformation. General functionals yielding such deformations at the level of solutions are furnished and illustrated, and broad features of discrete oscillations and wave propagation are outlined.
Discrete Optimization in Chemical Space Reference Manual
2012-10-01
Discrete Optimization in Chemical Space Reference Manual by B. C. Rinderspacher ARL-TR-6202 October 2012...2012 Discrete Optimization in Chemical Space Reference Manual B. C. Rinderspacher Weapons and Materials Research Directorate, ARL...2011 4. TITLE AND SUBTITLE Discrete Optimization in Chemical Space Reference Manual 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT
Multi-level coupled cluster theory
Myhre, Rolf H.; Koch, Henrik; Sánchez de Merás, Alfredo M. J.
2014-12-14
We present a general formalism where different levels of coupled cluster theory can be applied to different parts of the molecular system. The system is partitioned into subsystems by Cholesky decomposition of the one-electron Hartree-Fock density matrix. In this way the system can be divided across chemical bonds without discontinuities arising. The coupled cluster wave function is defined in terms of cluster operators for each part and these are determined from a set of coupled equations. The total wave function fulfills the Pauli-principle across all borders and levels of electron correlation. We develop the associated response theory for this multi-level coupled cluster theory and present proof of principle applications. The formalism is an essential tool in order to obtain size-intensive complexity in the calculation of local molecular properties.
Multilevel architectures for electronic document retrieval
Rome, J.A.; Tolliver, J.S.
1997-04-01
Traditionally, most classified computer systems run at the highest level of any of the data on the system, and all users must be cleared to this security level. This architecture precludes the use of low-level (pay and clearance) personnel for such tasks as data entry, and makes sharing data with other entities difficult. The government is trying to solve this problem by the introduction of multilevel-secure (MLS) computer systems. In addition, wherever possible, there is pressure to use commercial off-the-shelf software (COTS) to improve reliability, and to reduce purchase and maintenance costs. This paper presents two architectures for an MLS electronic document retrieval system using COTS products. Although the authors believe that the resulting systems represent a real advance in usability, scaleability, and scope, the disconnect between existing security rules and regulations and the rapidly-changing state of technology will make accreditation of such systems a challenge.
Structural optimization by generalized, multilevel decomposition
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.; James, B. B.; Riley, M. F.
1985-01-01
The developments toward a general multilevel optimization capability and results for a three-level structural optimization are described. The method partitions a structure into a number of substructuring levels where each substructure corresponds to a subsystem in the general case of an engineering system. The method is illustrated by a portal framework that decomposes into individual beams. Each beam is a box that can be further decomposed into stiffened plates. Substructuring for this example spans three different levels: (1) the bottom level of finite elements representing the plates; (2) an intermediate level of beams treated as substructures; and (3) the top level for the assembled structure. The three-level case is now considered to be qualitatively complete.
Earning potential in multilevel marketing enterprises
NASA Astrophysics Data System (ADS)
Legara, Erika Fille; Monterola, Christopher; Juanico, Dranreb Earl; Litong-Palima, Marisciel; Saloma, Caesar
2008-08-01
Government regulators and other concerned citizens warily view multilevel marketing enterprises (MLM) because of their close operational resemblance to exploitative pyramid schemes. We analyze two types of MLM network architectures - the unilevel and binary, in terms of growth behavior and earning potential among members. We show that network growth decelerates after reaching a size threshold, contrary to claims of unrestricted growth by MLM recruiters. We have also found that the earning potential in binary MLM’s obey the Pareto “80-20” rule, implying an earning opportunity that is strongly biased against the most recent members. On the other hand, unilevel MLM’s do not exhibit the Pareto earning distribution and earning potential is independent of member position in the network. Our analytical results agree well with field data taken from real-world MLM’s in the Philippines. Our analysis is generally valid and can be applied to other MLM architectures.
Multilevel wireless capsule endoscopy video segmentation
NASA Astrophysics Data System (ADS)
Hwang, Sae; Celebi, M. Emre
2010-03-01
Wireless Capsule Endoscopy (WCE) is a relatively new technology (FDA approved in 2002) allowing doctors to view most of the small intestine. WCE transmits more than 50,000 video frames per examination and the visual inspection of the resulting video is a highly time-consuming task even for the experienced gastroenterologist. Typically, a medical clinician spends one or two hours to analyze a WCE video. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs and shots each of which consists of the same or similar shots. In this paper a multi-level WCE video segmentation methodology is presented to reduce the examination time.
Multilevel domain decomposition for electronic structure calculations
Barrault, M. . E-mail: maxime.barrault@edf.fr; Cances, E. . E-mail: cances@cermics.enpc.fr; Hager, W.W. . E-mail: hager@math.ufl.edu; Le Bris, C. . E-mail: lebris@cermics.enpc.fr
2007-03-01
We introduce a new multilevel domain decomposition method (MDD) for electronic structure calculations within semi-empirical and density functional theory (DFT) frameworks. This method iterates between local fine solvers and global coarse solvers, in the spirit of domain decomposition methods. Using this approach, calculations have been successfully performed on several linear polymer chains containing up to 40,000 atoms and 200,000 atomic orbitals. Both the computational cost and the memory requirement scale linearly with the number of atoms. Additional speed-up can easily be obtained by parallelization. We show that this domain decomposition method outperforms the density matrix minimization (DMM) method for poor initial guesses. Our method provides an efficient preconditioner for DMM and other linear scaling methods, variational in nature, such as the orbital minimization (OM) procedure.
Cantilevered multilevel LIGA devices and methods
Morales, Alfredo Martin; Domeier, Linda A.
2002-01-01
In the formation of multilevel LIGA microstructures, a preformed sheet of photoresist material, such as polymethylmethacrylate (PMMA) is patterned by exposure through a mask to radiation, such as X-rays, and developed using a developer to remove the exposed photoresist material. A first microstructure is then formed by electroplating metal into the areas from which the photoresist has been removed. Additional levels of microstructure are added to the initial microstructure by covering the first microstructure with a conductive polymer, machining the conductive polymer layer to reveal the surface of the first microstructure, sealing the conductive polymer and surface of the first microstructure with a metal layer, and then forming the second level of structure on top of the first level structure. In such a manner, multiple layers of microstructure can be built up to allow complex cantilevered microstructures to be formed.
Multilevel library instruction for emerging nursing roles.
Francis, B W; Fisher, C C
1995-10-01
As new nursing roles emerge that involve greater decision making than in the past, added responsibility for outcomes and cost control, and increased emphasis on primary care, the information-seeking skills needed by nurses change. A search of library and nursing literature indicates that there is little comprehensive library instruction covering all levels of nursing programs: undergraduate, returning registered nurses, and graduate students. The University of Florida is one of the few places that has such a multilevel, course-integrated curriculum in place for all entrants into the nursing program. Objectives have been developed for each stage of learning. The courses include instruction in the use of the online public access catalog, printed resources, and electronic databases. A library classroom equipped with the latest technology enables student interaction with electronic databases. This paper discusses the program and several methods used to evaluate it.
Towards the development of multilevel-multiagent diagnostic aids
Stratton, R.C.; Jarrell, D.B.
1991-10-01
Presented here is our methodology for developing automated aids for diagnosing faults in complex systems. We have designed these aids as multilevel-multiagent diagnostic aids based on principles that should be generally applicable to any complex system. In this methodology, multilevel'' refers to information models described at successful levels of abstraction that are tied together in such a way that reasoning is directed to the appropriate level as determined by the problem solving requirements. The concept of multiagent'' refers to the method of information processing within the multilevel model network; each model in the network is an independent information processor, i.e., an intelligent agent. 19 refs., 15 figs., 9 tabs.
A New Dual Floating Gate Flash Cell for Multilevel Operation
NASA Astrophysics Data System (ADS)
Lin, Hongchin; Chen, Jack Tai-Yuan; Wong, Shyh-Chyi
2001-04-01
A new dual floating gate flash memory cell using constant bias voltages for multilevel operation is proposed to increase memory density. Channel hot electrons (CHE) and drain avalanche hot electrons (DAHE) are used to store different amounts of charge in different floating gates. To erase the data, channel fowler-nordheim (FN) tunneling is applied first, and then substrate hot electron (SHE) injection is utilized to prevent from over erase and tighten the threshold voltage spread. The simulation results indicate that the multilevel flash memory cell with slight modifications of triple well technology is a promising device for future multilevel operation devices.
Multilevel surgery in adults with cerebral palsy.
Putz, C; Döderlein, L; Mertens, E M; Wolf, S I; Gantz, S; Braatz, F; Dreher, T
2016-02-01
Single-event multilevel surgery (SEMLS) has been used as an effective intervention in children with bilateral spastic cerebral palsy (BSCP) for 30 years. To date there is no evidence for SEMLS in adults with BSCP and the intervention remains focus of debate. This study analysed the short-term outcome (mean 1.7 years, standard deviation 0.9) of 97 ambulatory adults with BSCP who performed three-dimensional gait analysis before and after SEMLS at one institution. Two objective gait variables were calculated pre- and post-operatively; the Gillette Gait Index (GGI) and the Gait Profile Score (GPS). The results were analysed in three groups according to their childhood surgical history (group 1 = no surgery, group 2 = surgery other than SEMLS, group 3 = SEMLS). Improvements in gait were shown by a significant decrease of GPS (p = 0.001). Similar results were obtained for both legs (GGI right side and left side p = 0.01). Furthermore, significant improvements were found in all subgroups although this was less marked in group 3, where patients had undergone previous SEMLS. SEMLS is an effective and safe procedure to improve gait in adults with cerebral palsy. However, a longer rehabilitation period is to be expected than found in children. SEMLS is still effective in adult patients who have undergone previous SEMLS in childhood. Single-event multilevel surgery is a safe and effective procedure to improve gait disorders in adults with bilateral spastic cerebral palsy. ©2016 The British Editorial Society of Bone & Joint Surgery.
Evolutionary biosemiotics and multilevel construction networks.
Sharov, Alexei A
2016-12-01
In contrast to the traditional relational semiotics, biosemiotics decisively deviates towards dynamical aspects of signs at the evolutionary and developmental time scales. The analysis of sign dynamics requires constructivism (in a broad sense) to explain how new components such as subagents, sensors, effectors, and interpretation networks are produced by developing and evolving organisms. Semiotic networks that include signs, tools, and subagents are multilevel, and this feature supports the plasticity, robustness, and evolvability of organisms. The origin of life is described here as the emergence of simple self-constructing semiotic networks that progressively increased the diversity of their components and relations. Primitive organisms have no capacity to classify and track objects; thus, we need to admit the existence of proto-signs that directly regulate activities of agents without being associated with objects. However, object recognition and handling became possible in eukaryotic species with the development of extensive rewritable epigenetic memory as well as sensorial and effector capacities. Semiotic networks are based on sequential and recursive construction, where each step produces components (i.e., agents, scaffolds, signs, and resources) that are needed for the following steps of construction. Construction is not limited to repair and reproduction of what already exists or is unambiguously encoded, it also includes production of new components and behaviors via learning and evolution. A special case is the emergence of new levels of organization known as metasystem transition. Multilevel semiotic networks reshape the phenotype of organisms by combining a mosaic of features developed via learning and evolution of cooperating and/or conflicting subagents.
On equivalence of discrete-discrete and continuum-discrete design sensitivity analysis
NASA Technical Reports Server (NTRS)
Choi, Kyung K.; Twu, Sung-Ling
1989-01-01
Developments in design sensitivity analysis (DSA) method have been made using two fundamentally different approaches as shown. In the first approach, a discretized structural finite element model is used to carry out DSA. There are three different methods in the discrete DSA approach: finite difference, semi-analytical, and analytical methods. The finite difference method is a popular one due to its simplicity, but a serious shortcoming of the method is the uncertainty in the choice of a perturbation step size of design variables. In the semi-analytical method, the derivatives of stiffness matrix is computed by finite differences, whereas in the analytical method, the derivatives are obtained analytically. For the shape design variable, computation of analytical derivative of stiffness matrix is quite costly. Because of this, the semi-analytical method is a popular choice in discrete shape DSA approach. However, recently, Barthelemy and Haftka presented that the semi-analytical method can have serious accuracy problems for shape design variables in structures modeled by beam, plate, truss, frame, and solid elements. They found that accuracy problems occur even for a simple cantilever beam. In the second approach, a continuum model of the structure is used to carry out DSA.
Mills, Melinda; Begall, Katia
2010-03-01
Comparative research on the preferred sex of children in Western societies has generally focused on women only and ignored the role of gender equity and the need for children's economic support in old age. A multilevel analysis extends existing research by examining, for both men and women and across 24 European countries, the effect of the preferred sex-composition of offspring on whether parents have or intend to have a third child. Using the European Social Survey (2004/5), a multilevel (random coefficient) ordered logit regression of that intention (N = 3,323) and a binary logistic multilevel model of the transition to a third child (N = 6,502) demonstrate the presence of a mixed-sex preference. In countries with a high risk of poverty in old age, a preference for sons is found, particularly for men. In societies where there is lower gender equity, both men and women have a significant preference for boys.
Analysis of Multilevel Pressure Transient Data at the Illinois Basin - Decatur Project
NASA Astrophysics Data System (ADS)
Strandli, Christin W.; Mehnert, Edward; Benson, Sally M.
2014-05-01
Based on numerical studies in TOUH2/ECO2N and analyses of multilevel (depth-discrete) pressure transient data at the Illinois Basin - Decatur Project (IBDP), this study demonstrates methods for using multilevel pressure transient data as a means to further characterize the storage formation and for monitoring carbon dioxide (CO2) and displaced brine migration. By incorporating multilevel pressure monitoring into the monitoring program, additional information is available that can be used to minimize and manage potential risk associated with CO2 and displaced brine migration to shallower depths. Previously, we used simulated pressure data from numerical studies in TOUGH2/ECO2N to identify diagnostics for reservoir structure (layering and anisotropy) and CO2 plume migration. In particular, we found that important insights can be obtained by: 1) normalizing the pressure buildups to the pressure buildup at the depth of injection, and 2) calculating vertical pressure gradients normalized to the initial hydrostatic pressure gradient. Soon after the start of injection, pressure buildups normalized to the pressure buildup at the depth of injection and vertical pressure gradients normalized to the initial hydrostatic pressure gradient are diagnostic of reservoir structure, and over time provide information on the height of the CO2 plume. In this study, the identified diagnostics are applied to the pressure transient data at the IBDP, where the Westbay* multilevel groundwater characterization and monitoring system was installed in a deep in-zone verification well (2,000 m) to measure the pressure buildup at multiple depths within the Mt. Simon storage reservoir and above the Eau Claire Formation (primary seal) during CO2 injection. Using the diagnostic tools, we are able to correctly identify the height of the CO2 plume. Specifically, the multilevel pressure transient data alone indicate that the CO2 plume remains largely confined to the 23-24 m interval into which it is
Bayesian estimation of the discrete coefficient of determination.
Chen, Ting; Braga-Neto, Ulisses M
2016-12-01
The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.
Multilevel Atomic Coherent States and Atomic Holomorphic Representation
NASA Technical Reports Server (NTRS)
Cao, Chang-Qi; Haake, Fritz
1996-01-01
The notion of atomic coherent states is extended to the case of multilevel atom collective. Based on atomic coherent states, a holomorphic representation for atom collective states and operators is defined. An example is given to illustrate its application.
OSNR sensitivity of multi-level modulation formats
NASA Astrophysics Data System (ADS)
Eiselt, M.; Dochhan, A.; Rosenkranz, W.
2010-12-01
A simple analytical method to estimate the OSNR sensitivity of multi-level amplitude, phase and combined modulation formats is shown. The results are compared to numerical simulations with coherent and direct detection technique using RZ and NRZ pulse shape.
Novel multilevel inverter carrier-based PWM method
Tolbert, L.M.; Habetler, T.G.
1999-10-01
The advent of the transformerless multilevel inverter topology has brought forth various pulsewidth modulation (PWM) schemes as a means to control the switching of the active devices in each of the multiple voltage levels in the inverter. An analysis of how existing multilevel carrier-based PWM affects switch utilization for the different levels of a diode-clamped inverter is conducted. Two novel carrier-based multilevel PWM schemes are presented which help to optimize or balance the switch utilization in multilevel inverters. A 10-kW prototype six-level diode-clamped inverter has been built and controlled with the novel PWM strategies proposed in this paper to act as a voltage-source inverter for a motor drive.
Discrete Boltzmann equation for microfluidics.
Li, Baoming; Kwok, Daniel Y
2003-03-28
We propose a discrete Boltzmann model for microfluidics based on the Boltzmann equation with external forces using a single relaxation time collision model. Considering the electrostatic interactions in microfluidics systems, we introduce an equilibrium distribution function that differs from the Maxwell-Boltzmann distribution by an exponential factor to represent the action of an external force field. A statistical mechanical approach is applied to derive the equivalent external acceleration force exerting on the lattice particles based on a mean-field approximation, resulting from the electro-static potential energy and intermolecular potential energy between fluid-fluid and fluid-substrate interactions.
Invariants of broken discrete symmetries.
Kalozoumis, P A; Morfonios, C; Diakonos, F K; Schmelcher, P
2014-08-01
The parity and Bloch theorems are generalized to the case of broken global symmetry. Local inversion or translation symmetries in one dimension are shown to yield invariant currents that characterize wave propagation. These currents map the wave function from an arbitrary spatial domain to any symmetry-related domain. Our approach addresses any combination of local symmetries, thus applying, in particular, to acoustic, optical, and matter waves. Nonvanishing values of the invariant currents provide a systematic pathway to the breaking of discrete global symmetries.
Invariants of Broken Discrete Symmetries
NASA Astrophysics Data System (ADS)
Kalozoumis, P. A.; Morfonios, C.; Diakonos, F. K.; Schmelcher, P.
2014-08-01
The parity and Bloch theorems are generalized to the case of broken global symmetry. Local inversion or translation symmetries in one dimension are shown to yield invariant currents that characterize wave propagation. These currents map the wave function from an arbitrary spatial domain to any symmetry-related domain. Our approach addresses any combination of local symmetries, thus applying, in particular, to acoustic, optical, and matter waves. Nonvanishing values of the invariant currents provide a systematic pathway to the breaking of discrete global symmetries.
Berhane, Kiros; Molitor, Nuoo-Ting
2008-10-01
Flexible multilevel models are proposed to allow for cluster-specific smooth estimation of growth curves in a mixed-effects modeling format that includes subject-specific random effects on the growth parameters. Attention is then focused on models that examine between-cluster comparisons of the effects of an ecologic covariate of interest (e.g. air pollution) on nonlinear functionals of growth curves (e.g. maximum rate of growth). A Gibbs sampling approach is used to get posterior mean estimates of nonlinear functionals along with their uncertainty estimates. A second-stage ecologic random-effects model is used to examine the association between a covariate of interest (e.g. air pollution) and the nonlinear functionals. A unified estimation procedure is presented along with its computational and theoretical details. The models are motivated by, and illustrated with, lung function and air pollution data from the Southern California Children's Health Study.
Multi-level bandwidth efficient block modulation codes
NASA Technical Reports Server (NTRS)
Lin, Shu
1989-01-01
The multilevel technique is investigated for combining block coding and modulation. There are four parts. In the first part, a formulation is presented for signal sets on which modulation codes are to be constructed. Distance measures on a signal set are defined and their properties are developed. In the second part, a general formulation is presented for multilevel modulation codes in terms of component codes with appropriate Euclidean distances. The distance properties, Euclidean weight distribution and linear structure of multilevel modulation codes are investigated. In the third part, several specific methods for constructing multilevel block modulation codes with interdependency among component codes are proposed. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C which has the same rate as C, a minimum squared Euclidean distance not less than that of code C, a trellis diagram with the same number of states as that of C and a smaller number of nearest neighbor codewords than that of C. In the last part, error performance of block modulation codes is analyzed for an AWGN channel based on soft-decision maximum likelihood decoding. Error probabilities of some specific codes are evaluated based on their Euclidean weight distributions and simulation results.
Jasra, Ajay; Law, Kody J. H.; Zhou, Yan
2016-01-01
Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are used for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.
Cuadrado, Esther; Tabernero, Carmen
2015-01-01
Little research has focused on how individual- and team-level characteristics jointly influence, via interaction, how prosocially individuals behave in teams and few studies have considered the potential influence of team context on prosocial behavior. Using a multilevel perspective, we examined the relationships between individual (affective balance) and group (team prosocial efficacy and team trust) level variables and prosocial behavior towards team members. The participants were 123 students nested in 45 small teams. A series of multilevel random models was estimated using hierarchical linear and nonlinear modeling. Individuals were more likely to behave prosocially towards in-group members when they were feeling good. Furthermore, the relationship between positive affective balance and prosocial behavior was stronger in teams with higher team prosocial efficacy levels as well as in teams with higher team trust levels. Finally, the relevance of team trust had a stronger influence on behavior than team prosocial efficacy.
Cuadrado, Esther; Tabernero, Carmen
2015-01-01
Little research has focused on how individual- and team-level characteristics jointly influence, via interaction, how prosocially individuals behave in teams and few studies have considered the potential influence of team context on prosocial behavior. Using a multilevel perspective, we examined the relationships between individual (affective balance) and group (team prosocial efficacy and team trust) level variables and prosocial behavior towards team members. The participants were 123 students nested in 45 small teams. A series of multilevel random models was estimated using hierarchical linear and nonlinear modeling. Individuals were more likely to behave prosocially towards in-group members when they were feeling good. Furthermore, the relationship between positive affective balance and prosocial behavior was stronger in teams with higher team prosocial efficacy levels as well as in teams with higher team trust levels. Finally, the relevance of team trust had a stronger influence on behavior than team prosocial efficacy. PMID:26317608
Portoghese, Igor; Galletta, Maura; Burdorf, Alex; Cocco, Pierluigi; D'Aloja, Ernesto; Campagna, Marcello
2017-08-02
The aim of the study was to examine the relationship between role stress, emotional exhaustion, and a supportive coworker climate among health care workers, by adopting a multilevel perspective. Aggregated data of 738 health care workers nested within 67 teams of three Italian hospitals were collected. Multilevel regression analysis with a random intercept model was used. Hierarchical linear modeling showed that a lack of role clarity was significantly linked to emotional exhaustion at the individual level. At the unit level, the cross-level interaction revealed that a supportive coworker climate moderated the relationship between lack of role clarity and emotional exhaustion. This study supports previous results of single-level burnout studies, extending the existing literature with evidence on the multidimensional and cross-level interaction associations of a supportive coworker climate as a key aspect of job resources on burnout.
Entwinement in discretely gauged theories
NASA Astrophysics Data System (ADS)
Balasubramanian, V.; Bernamonti, A.; Craps, B.; De Jonckheere, T.; Galli, F.
2016-12-01
We develop the notion of "entwinement" to characterize the amount of quantum entanglement between internal, discretely gauged degrees of freedom in a quantum field theory. This concept originated in the program of reconstructing spacetime from entanglement in holographic duality. We define entwinement formally in terms of a novel replica method which uses twist operators charged in a representation of the discrete gauge group. In terms of these twist operators we define a non-local, gauge-invariant object whose expectation value computes entwinement in a standard replica limit. We apply our method to the computation of entwinement in symmetric orbifold conformal field theories in 1+1 dimensions, which have an S N gauging. Such a theory appears in the weak coupling limit of the D1-D5 string theory which is dual to AdS3 at strong coupling. In this context, we show how certain kinds of entwinement measure the lengths, in units of the AdS scale, of non-minimal geodesics present in certain excited states of the system which are gravitationally described as conical defects and the M = 0 BTZ black hole. The possible types of entwinement that can be computed define a very large new class of quantities characterizing the fine structure of quantum wavefunctions.
Supervised Discrete Hashing With Relaxation.
Gui, Jie; Liu, Tongliang; Sun, Zhenan; Tao, Dacheng; Tan, Tieniu
2016-12-29
Data-dependent hashing has recently attracted attention due to being able to support efficient retrieval and storage of high-dimensional data, such as documents, images, and videos. In this paper, we propose a novel learning-based hashing method called ''supervised discrete hashing with relaxation'' (SDHR) based on ''supervised discrete hashing'' (SDH). SDH uses ordinary least squares regression and traditional zero-one matrix encoding of class label information as the regression target (code words), thus fixing the regression target. In SDHR, the regression target is instead optimized. The optimized regression target matrix satisfies a large margin constraint for correct classification of each example. Compared with SDH, which uses the traditional zero-one matrix, SDHR utilizes the learned regression target matrix and, therefore, more accurately measures the classification error of the regression model and is more flexible. As expected, SDHR generally outperforms SDH. Experimental results on two large-scale image data sets (CIFAR-10 and MNIST) and a large-scale and challenging face data set (FRGC) demonstrate the effectiveness and efficiency of SDHR.
Discreteness effects in population dynamics
NASA Astrophysics Data System (ADS)
Guevara Hidalgo, Esteban; Lecomte, Vivien
2016-05-01
We analyse numerically the effects of small population size in the initial transient regime of a simple example population dynamics. These effects play an important role for the numerical determination of large deviation functions of additive observables for stochastic processes. A method commonly used in order to determine such functions is the so-called cloning algorithm which in its non-constant population version essentially reduces to the determination of the growth rate of a population, averaged over many realizations of the dynamics. However, the averaging of populations is highly dependent not only on the number of realizations of the population dynamics, and on the initial population size but also on the cut-off time (or population) considered to stop their numerical evolution. This may result in an over-influence of discreteness effects at initial times, caused by small population size. We overcome these effects by introducing a (realization-dependent) time delay in the evolution of populations, additional to the discarding of the initial transient regime of the population growth where these discreteness effects are strong. We show that the improvement in the estimation of the large deviation function comes precisely from these two main contributions.
Statistics of primordial density perturbations from discrete seed masses
NASA Technical Reports Server (NTRS)
Scherrer, Robert J.; Bertschinger, Edmund
1991-01-01
The statistics of density perturbations for general distributions of seed masses with arbitrary matter accretion is examined. Formal expressions for the power spectrum, the N-point correlation functions, and the density distribution function are derived. These results are applied to the case of uncorrelated seed masses, and power spectra are derived for accretion of both hot and cold dark matter plus baryons. The reduced moments (cumulants) of the density distribution are computed and used to obtain a series expansion for the density distribution function. Analytic results are obtained for the density distribution function in the case of a distribution of seed masses with a spherical top-hat accretion pattern. More generally, the formalism makes it possible to give a complete characterization of the statistical properties of any random field generated from a discrete linear superposition of kernels. In particular, the results can be applied to density fields derived by smoothing a discrete set of points with a window function.
Statistics of primordial density perturbations from discrete seed masses
NASA Technical Reports Server (NTRS)
Scherrer, Robert J.; Bertschinger, Edmund
1991-01-01
The statistics of density perturbations for general distributions of seed masses with arbitrary matter accretion is examined. Formal expressions for the power spectrum, the N-point correlation functions, and the density distribution function are derived. These results are applied to the case of uncorrelated seed masses, and power spectra are derived for accretion of both hot and cold dark matter plus baryons. The reduced moments (cumulants) of the density distribution are computed and used to obtain a series expansion for the density distribution function. Analytic results are obtained for the density distribution function in the case of a distribution of seed masses with a spherical top-hat accretion pattern. More generally, the formalism makes it possible to give a complete characterization of the statistical properties of any random field generated from a discrete linear superposition of kernels. In particular, the results can be applied to density fields derived by smoothing a discrete set of points with a window function.
Women's status and depressive symptoms: a multilevel analysis.
Chen, Ying-Yeh; Subramanian, S V; Acevedo-Garcia, Doloros; Kawachi, Ichiro
2005-01-01
The effects of state-level women's status and autonomy on individual-level women's depressive symptoms were examined. We conducted a multi-level analysis of the 1991 longitudinal follow up of the 1988 National Maternal Infant Health Survey (NMIHS), with 7789 women nested within the fifty American states. State-level women's status was assessed by four composite indices measuring women's political participation, economic autonomy, employment & earnings, and reproductive rights. The main outcome measure was symptoms of depression (Center for Epidemiologic Studies Depression Scale, CES-D). The participants were a nationally representative stratified random sample of women in the USA aged between 17 and 40 years old who gave birth to live babies in 1988, were successfully contacted again in 1991 and provided complete information on depressive symptoms. Women who were younger, non-white, not currently married, less educated or had lower household income tended to report higher levels of depressive symptoms. Compared with states ranking low on the employment & earnings index, women residing in states that were high on the same index scored 0.85 points lower on the CES-D (p<0.01). Women who lived in states that were high on the economic autonomy index scored 0.83 points lower in depressive symptoms (p<0.01), compared with women who lived in states low on the same index. Finally, women who resided in states with high reproductive rights scored 0.62 points lower on the CES-D (p<0.05) compared with women who lived in states with lower reproductive rights. Gender inequality appears to contribute to depressive symptoms in women.
Poverty and fever vulnerability in Nigeria: a multilevel analysis.
Yusuf, Oyindamola B; Adeoye, Babatunde W; Oladepo, Oladimeji O; Peters, David H; Bishai, David
2010-08-19
Malaria remains a major public health problem in Sub Saharan Africa, where widespread poverty also contribute to the burden of the disease. This study was designed to investigate the relationship between the prevalence of childhood fever and socioeconomic factors including poverty in Nigeria, and to examine these effects at the regional levels. Determinants of fever in the last two weeks among children under five years were examined from the 25004 children records extracted from the Nigeria Demographic and Health Survey 2008 data set. A two-level random effects logistic model was fitted. About 16% of children reported having fever in the two weeks preceding the survey. The prevalence of fever was highest among children from the poorest households (17%), compared to 15.8% among the middle households and lowest among the wealthiest (13%) (p<0.0001). Of the 3,110 respondents who had bed nets in their households, 506(16.3%) children had fever, while 2,604(83.7%) did not. (p=0.082). In a multilevel model adjusting for demographic variables, fever was associated with rural place of residence (OR=1.27, p<0.0001, 95% CI: 1.16, 1.41), sex of child: female (OR=0.92, p=0.022, 95% CI: 0.859, 0.988) and all age categories (>6 months), whereas the effect of wealth no longer reached statistical significance. While, overall bednet possession was low, less fever was reported in households that possessed bednets. Malaria control strategies and interventions should be designed that will target the poor and make an impact on poverty. The mechanism through which wealth may affect malaria occurrence needs further investigation.
Improving prediction of surgical site infection risk with multilevel modeling.
Saunders, Lauren; Perennec-Olivier, Marion; Jarno, Pascal; L'Hériteau, François; Venier, Anne-Gaëlle; Simon, Loïc; Giard, Marine; Thiolet, Jean-Michel; Viel, Jean-François
2014-01-01
Surgical site infection (SSI) surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule). To improve the predictive performance of an individual-based SSI risk model by considering a multilevel hierarchical structure. Data were collected anonymously by the French SSI active surveillance system in 2011. An SSI diagnosis was made by the surgical teams and infection control practitioners following standardized criteria. A random 20% sample comprising 151 hospitals, 502 wards and 62280 patients was used. Three-level (patient, ward, hospital) hierarchical logistic regression models were initially performed. Parameters were estimated using the simulation-based Markov Chain Monte Carlo procedure. A total of 623 SSI were diagnosed (1%). The hospital level was discarded from the analysis as it did not contribute to variability of SSI occurrence (p = 0.32). Established individual risk factors (patient history, surgical procedure and hospitalization characteristics) were identified. A significant heterogeneity in SSI occurrence between wards was found (median odds ratio [MOR] 3.59, 95% credibility interval [CI] 3.03 to 4.33) after adjusting for patient-level variables. The effects of the follow-up duration varied between wards (p<10-9), with an increased heterogeneity when follow-up was <15 days (MOR 6.92, 95% CI 5.31 to 9.07]). The final two-level model significantly improved the discriminative accuracy compared to the single level reference model (p<10-9), with an area under the ROC curve of 0.84. This study sheds new light on the respective contribution of patient-, ward- and hospital-levels to SSI occurrence and demonstrates the significant impact of the ward level over and above risk factors present at patient level (i.e., independently from patient case-mix).
Phase computations and phase models for discrete molecular oscillators
2012-01-01
Background Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. Results In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. Conclusions The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations. PMID:22687330
Two-dimensional discrete Coulomb alloy
NASA Astrophysics Data System (ADS)
Xiao, Yuqing; Thorpe, M. F.; Parkinson, J. B.
1999-01-01
We study an A1-xBx alloy on a two-dimensional triangular lattice. The ions A and B have different charges, with a background charge to ensure neutrality, and are constrained to lie at the discrete sites defined by a fixed triangular lattice. We study the various structures formed at different compositions x by doing computer simulations to find the lowest energy, using an energy minimization scheme, together with simulated annealing. Like ions try to avoid each other because of charge repulsion, which leads to structures, which are very different from those in a random alloy. At low concentrations, a triangular Wigner lattice is formed, which evolves continuously up to a concentration of x=1/3. For higher concentrations, 1/3<=x<=1/2 there are long polymer chains, with occasional branches. We show that there is a symmetry about x=1/2, which is the percolation point for nearest neighbors on the triangular lattice. At certain special stoichiometries, regular superlattices are formed, which usually have a slightly lower energy than a disordered configuration. The powder-diffraction patterns are calculated. The magnetic properties of this structure are also studied, and it is shown that the high-temperature susceptibility could be a useful diagnostic tool, in that it is very sensitive to the number of nearest-neighbor magnetic pairs. This work contributes to a better understanding of layered double hydroxides like Ni1-xAlx(OH)2(CO3)x/2.yH2O.
NASA Astrophysics Data System (ADS)
Nishihara, Masato; Kai, Yutaka; Tanaka, Toshiki; Takahara, Tomoo; Li, Lei; Yan, Weizhen; Liu, Bo; Tao, Zhenning; Rasmussen, Jens C.
2013-12-01
Advanced multi-level modulation is an attractive modulation technique for beyond 100 Gbps short reach optical transmission system. Above all, discrete multi-tone (DMT) technique and pulse amplitude modulation (PAM) technique are the strong candidates. We compared the 100 Gbps transmission characteristics of DMT and PAM by simulation and experiment. The comparison was done by using same devices and only the digital signal processing was changed. We studied the transmission distance dependence for 0.5 to 40 km and the impact of the frequency responses of the optical devices. Finally we discuss the features of the both modulation techniques.
Learning Stable Multilevel Dictionaries for Sparse Representations.
Thiagarajan, Jayaraman J; Ramamurthy, Karthikeyan Natesan; Spanias, Andreas
2015-09-01
Sparse representations using learned dictionaries are being increasingly used with success in several data processing and machine learning applications. The increasing need for learning sparse models in large-scale applications motivates the development of efficient, robust, and provably good dictionary learning algorithms. Algorithmic stability and generalizability are desirable characteristics for dictionary learning algorithms that aim to build global dictionaries, which can efficiently model any test data similar to the training samples. In this paper, we propose an algorithm to learn dictionaries for sparse representations from large scale data, and prove that the proposed learning algorithm is stable and generalizable asymptotically. The algorithm employs a 1-D subspace clustering procedure, the K-hyperline clustering, to learn a hierarchical dictionary with multiple levels. We also propose an information-theoretic scheme to estimate the number of atoms needed in each level of learning and develop an ensemble approach to learn robust dictionaries. Using the proposed dictionaries, the sparse code for novel test data can be computed using a low-complexity pursuit procedure. We demonstrate the stability and generalization characteristics of the proposed algorithm using simulations. We also evaluate the utility of the multilevel dictionaries in compressed recovery and subspace learning applications.
Processing multilevel secure test and evaluation information
NASA Astrophysics Data System (ADS)
Hurlburt, George; Hildreth, Bradley; Acevedo, Teresa
1994-07-01
The Test and Evaluation Community Network (TECNET) is building a Multilevel Secure (MLS) system. This system features simultaneous access to classified and unclassified information and easy access through widely available communications channels. It provides the necessary separation of classification levels, assured through the use of trusted system design techniques, security assessments and evaluations. This system enables cleared T&E users to view and manipulate classified and unclassified information resources either using a single terminal interface or multiple windows in a graphical user interface. TECNET is in direct partnership with the National Security Agency (NSA) to develop and field the MLS TECNET capability in the near term. The centerpiece of this partnership is a state-of-the-art Concurrent Systems Security Engineering (CSSE) process. In developing the MLS TECNET capability, TECNET and NSA are providing members, with various expertise and diverse backgrounds, to participate in the CSSE process. The CSSE process is founded on the concepts of both Systems Engineering and Concurrent Engineering. Systems Engineering is an interdisciplinary approach to evolve and verify an integrated and life cycle balanced set of system product and process solutions that satisfy customer needs (ASD/ENS-MIL STD 499B 1992). Concurrent Engineering is design and development using the simultaneous, applied talents of a diverse group of people with the appropriate skills. Harnessing diverse talents to support CSSE requires active participation by team members in an environment that both respects and encourages diversity.
The genetical theory of multilevel selection
Gardner, A
2015-01-01
The theory of multilevel selection (MLS) is beset with conceptual difficulties. Although it is widely agreed that covariance between group trait and group fitness may arise in the natural world and drive a response to ‘group selection’, ambiguity exists over the precise meaning of group trait and group fitness and as to whether group selection should be defined according to changes in frequencies of different types of individual or different types of group. Moreover, the theory of MLS has failed to properly engage with the problem of class structure, which greatly limits its empirical application to, for example, social insects whose colonies are structured into separate age, sex, caste and ploidy classes. Here, I develop a genetical theory of MLS, to address these problems. I show that taking a genetical approach facilitates a decomposition of group-level traits – including reproductive success – into the separate contributions made by each constituent individual, even in the context of so-called emergence. However, I uncover a novel problem with the group-oriented approach: in many scenarios, it may not be possible to express a meaningful covariance between trait and fitness at the level of the social group, because the group's constituents belong to separate, irreconcilable classes. PMID:25475922
Multilevel Radiative Transfer with Partial Frequency Redistribution
NASA Astrophysics Data System (ADS)
Uitenbroek, H.
2001-08-01
A multilevel accelerated lambda iteration (MALI) method for radiative transfer calculations with partial frequency redistribution (PRD) is presented. The method, which is based on Rybicki & Hummer's complete frequency redistribution (CRD) formalism with full preconditioning, consistently accounts for overlapping radiative transitions. Its extension to PRD is implemented in a very natural way through the use of the Ψ operator operating on the emissivity rather than the commonly used Λ operator, which operates on the source function. Apart from requiring an additional inner computational loop to evaluate the PRD emission-line profiles with fixed population numbers, implementation of the presented method requires only a trivial addition of computer code. Since the presented method employs a diagonal operator, it is easily extended to different geometries. Currently, it has been implemented for one-, two-, and three-dimensional Cartesian grids and spherical symmetry. In all cases, the speed of convergence with PRD is very similar to that in CRD, with the former sometimes even surpassing the latter. Sample calculations exhibiting the favorable convergence behavior of the PRD code are presented in the case of the Ca II H and K lines, the Mg II h and k lines, and the hydrogen Lyα and Lyβ lines in a one-dimensional solar model and the Ca II resonance lines in a two-dimensional flux-sheet model.
Visual attention as a multilevel selection process.
Kastner, Sabine; Pinsk, Mark A
2004-12-01
Natural visual scenes are cluttered and contain many different objects that cannot all be processed simultaneously. Therefore, attentional mechanisms are needed to select relevant and to filter out irrelevant information. Evidence from functional brain imaging reveals that attention operates at various processing levels within the visual system and beyond. First, the lateral geniculate nucleus appears to be the first stage in the processing of visual information that is modulated by attention, consistent with the idea that it may play an important role as an early gatekeeper in controlling neural gain. Second, areas at intermediate cortical-processing levels, such as V4 and TEO, appear to be important sites at which attention filters out unwanted information by means of receptive field mechanisms. Third, the attention mechanisms that operate in the visual system appear to be controlled by a distributed network of higher order areas in the frontal and parietal cortex, which generate top-down signals that are transmitted via feedback connections to the visual system. And fourth, the pulvinar of the thalamus may operate by integrating and coordinating attentional functions in concert with the fronto-parietal network, although much needs to be learned about its functional properties. The overall view that emerges from the studies reviewed in this article is that neural mechanisms of selective attention operate at multiple stages in the visual system and beyond and are determined by the visual processing capabilities of each stage. In this respect, attention can be considered in terms of a multilevel selection process.
Experiments in encoding multilevel images as quadtrees
NASA Technical Reports Server (NTRS)
Lansing, Donald L.
1987-01-01
Image storage requirements for several encoding methods are investigated and the use of quadtrees with multigray level or multicolor images are explored. The results of encoding a variety of images having up to 256 gray levels using three schemes (full raster, runlength and quadtree) are presented. Although there is considerable literature on the use of quadtrees to store and manipulate binary images, their application to multilevel images is relatively undeveloped. The potential advantage of quadtree encoding is that an entire area with a uniform gray level may be encoded as a unit. A pointerless quadtree encoding scheme is described. Data are presented on the size of the quadtree required to encode selected images and on the relative storage requirements of the three encoding schemes. A segmentation scheme based on the statistical variation of gray levels within a quadtree quadrant is described. This parametric scheme may be used to control the storage required by an encoded image and to preprocess a scene for feature identification. Several sets of black and white and pseudocolor images obtained by varying the segmentation parameter are shown.
Ideal shrinking and expansion of discrete sequences
NASA Technical Reports Server (NTRS)
Watson, Andrew B.
1986-01-01
Ideal methods are described for shrinking or expanding a discrete sequence, image, or image sequence. The methods are ideal in the sense that they preserve the frequency spectrum of the input up to the Nyquist limit of the input or output, whichever is smaller. Fast implementations that make use of the discrete Fourier transform or the discrete Hartley transform are described. The techniques lead to a new multiresolution image pyramid.
Discrete modelling of drapery systems
NASA Astrophysics Data System (ADS)
Thoeni, Klaus; Giacomini, Anna
2016-04-01
Drapery systems are an efficient and cost-effective measure in preventing and controlling rockfall hazards on rock slopes. The simplest form consists of a row of ground anchors along the top of the slope connected to a horizontal support cable from which a wire mesh is suspended down the face of the slope. Such systems are generally referred to as simple or unsecured draperies (Badger and Duffy 2012). Variations such as secured draperies, where a pattern of ground anchors is incorporated within the field of the mesh, and hybrid systems, where the upper part of an unsecured drapery is elevated to intercept rockfalls originating upslope of the installation, are becoming more and more popular. This work presents a discrete element framework for simulation of unsecured drapery systems and its variations. The numerical model is based on the classical discrete element method (DEM) and implemented into the open-source framework YADE (Šmilauer et al., 2010). The model takes all relevant interactions between block, drapery and slope into account (Thoeni et al., 2014) and was calibrated and validated based on full-scale experiments (Giacomini et al., 2012).The block is modelled as a rigid clump made of spherical particles which allows any shape to be approximated. The drapery is represented by a set of spherical particle with remote interactions. The behaviour of the remote interactions is governed by the constitutive behaviour of the wire and generally corresponds to a piecewise linear stress-strain relation (Thoeni et al., 2013). The same concept is used to model wire ropes. The rock slope is represented by rigid triangular elements where material properties (e.g., normal coefficient of restitution, friction angle) are assigned to each triangle. The capabilities of the developed model to simulate drapery systems and estimate the residual hazard involved with such systems is shown. References Badger, T.C., Duffy, J.D. (2012) Drapery systems. In: Turner, A.K., Schuster R
Discrete breathers in hydrogenated graphene
NASA Astrophysics Data System (ADS)
Liu, Bo; Baimova, Julia A.; Dmitriev, Sergey V.; Wang, Xu; Zhu, Hongwei; Zhou, Kun
2013-07-01
Discrete breathers (DBs) in graphane (fully hydrogenated graphene) are investigated using molecular dynamics simulations. It is found that the DB can be excited by applying an out-of-plane displacement on a single hydrogen atom of graphane. The vibration frequency of the DB lies either within the gap of the phonon spectrum of graphane or beyond its upper spectrum bound. Both soft and hard types of anharmonicity of the DB, which have not been found in the same system, are observed in graphane. The study shows that the DB is robust and its lifetime is affected by various factors including its anharmonicity type, its amplitude and frequency, and the force on the hydrogen atom that forms it, whose competition results in a complex mechanism for the lifetime determination. The investigation of the maximum kinetic energy of DBs reveals that they may function to activate or accelerate dehydrogenation of hydrogenated graphene at high temperatures.
Intermediate and advanced topics in multilevel logistic regression analysis.
Austin, Peter C; Merlo, Juan
2017-09-10
Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R(2) measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Scalar discrete nonlinear multipoint boundary value problems
NASA Astrophysics Data System (ADS)
Rodriguez, Jesus; Taylor, Padraic
2007-06-01
In this paper we provide sufficient conditions for the existence of solutions to scalar discrete nonlinear multipoint boundary value problems. By allowing more general boundary conditions and by imposing less restrictions on the nonlinearities, we obtain results that extend previous work in the area of discrete boundary value problems [Debra L. Etheridge, Jesus Rodriguez, Periodic solutions of nonlinear discrete-time systems, Appl. Anal. 62 (1996) 119-137; Debra L. Etheridge, Jesus Rodriguez, Scalar discrete nonlinear two-point boundary value problems, J. Difference Equ. Appl. 4 (1998) 127-144].
A discrete event method for wave simulation
Nutaro, James J
2006-01-01
This article describes a discrete event interpretation of the finite difference time domain (FDTD) and digital wave guide network (DWN) wave simulation schemes. The discrete event method is formalized using the discrete event system specification (DEVS). The scheme is shown to have errors that are proportional to the resolution of the spatial grid. A numerical example demonstrates the relative efficiency of the scheme with respect to FDTD and DWN schemes. The potential for the discrete event scheme to reduce numerical dispersion and attenuation errors is discussed.
Discrete gauge symmetry in continuum theories
Krauss, L.M.; Wilczek, F.
1989-03-13
We point out that local symmetries can masquerade as discrete global symmetries to an observer equipped with only low-energy probes. The existence of the underlying local gauge invariance can, however, result in observable Aharonov-Bohm-type effects. Black holes can therefore carry discrete gauge charges: a form of nonclassical ''hair.'' Neither black-hole evaporation, wormholes, nor anything else can violate discrete gauge symmetries. In supersymmetric unified theories such discrete symmetries can forbid proton-decay amplitudes that might otherwise be catastrophic.
ERIC Educational Resources Information Center
Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael
2014-01-01
Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…
ERIC Educational Resources Information Center
Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael
2014-01-01
Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…
Modeling biological tissue growth: discrete to continuum representations.
Hywood, Jack D; Hackett-Jones, Emily J; Landman, Kerry A
2013-09-01
There is much interest in building deterministic continuum models from discrete agent-based models governed by local stochastic rules where an agent represents a biological cell. In developmental biology, cells are able to move and undergo cell division on and within growing tissues. A growing tissue is itself made up of cells which undergo cell division, thereby providing a significant transport mechanism for other cells within it. We develop a discrete agent-based model where domain agents represent tissue cells. Each agent has the ability to undergo a proliferation event whereby an additional domain agent is incorporated into the lattice. If a probability distribution describes the waiting times between proliferation events for an individual agent, then the total length of the domain is a random variable. The average behavior of these stochastically proliferating agents defining the growing lattice is determined in terms of a Fokker-Planck equation, with an advection and diffusion term. The diffusion term differs from the one obtained Landman and Binder [J. Theor. Biol. 259, 541 (2009)] when the rate of growth of the domain is specified, but the choice of agents is random. This discrepancy is reconciled by determining a discrete-time master equation for this process and an associated asymmetric nonexclusion random walk, together with consideration of synchronous and asynchronous updating schemes. All theoretical results are confirmed with numerical simulations. This study furthers our understanding of the relationship between agent-based rules, their implementation, and their associated partial differential equations. Since tissue growth is a significant cellular transport mechanism during embryonic growth, it is important to use the correct partial differential equation description when combining with other cellular functions.
Some Tests of Randomness with Applications
1981-02-01
relative efficiencies of distriLution-free tests of randomness against normal alternatives. J. Am. Statist. Assoc. 49, 147-57. Wald . A. and Wolfowitz , J...assumption of randomness in data analysis. There may be possibilities of grave errors in assuming the randomness of a given set of data while it i may...Equidistribution test. This can be performed by using Kolmogorov-Smirnov statistic to test uniformity of the real valued sequence so generated. The discrete form of
Convergence time towards periodic orbits in discrete dynamical systems.
San Martín, Jesús; Porter, Mason A
2014-01-01
We investigate the convergence towards periodic orbits in discrete dynamical systems. We examine the probability that a randomly chosen point converges to a particular neighborhood of a periodic orbit in a fixed number of iterations, and we use linearized equations to examine the evolution near that neighborhood. The underlying idea is that points of stable periodic orbit are associated with intervals. We state and prove a theorem that details what regions of phase space are mapped into these intervals (once they are known) and how many iterations are required to get there. We also construct algorithms that allow our theoretical results to be implemented successfully in practice.